a thesis on covid 19

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http://orcid.org/0000-0003-1512-4471 Emily Long 1 ,
Susan Patterson 1 ,
Karen Maxwell 1 ,
Carolyn Blake 1 ,
http://orcid.org/0000-0001-7342-4566 Raquel Bosó Pérez 1 ,
Ruth Lewis 1 ,
Mark McCann 1 ,
Julie Riddell 1 ,
Kathryn Skivington 1 ,
Rachel Wilson-Lowe 1 ,
http://orcid.org/0000-0002-4409-6601 Kirstin R Mitchell 2
1 MRC/CSO Social and Public Health Sciences Unit , University of Glasgow , Glasgow , UK
2 MRC/CSO Social and Public Health Sciences Unit, Institute of Health & Wellbeing , University of Glasgow , Glasgow , UK
Correspondence to Dr Emily Long, MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow G3 7HR, UK; emily.long{at}glasgow.ac.uk

This essay examines key aspects of social relationships that were disrupted by the COVID-19 pandemic. It focuses explicitly on relational mechanisms of health and brings together theory and emerging evidence on the effects of the COVID-19 pandemic to make recommendations for future public health policy and recovery. We first provide an overview of the pandemic in the UK context, outlining the nature of the public health response. We then introduce four distinct domains of social relationships: social networks, social support, social interaction and intimacy, highlighting the mechanisms through which the pandemic and associated public health response drastically altered social interactions in each domain. Throughout the essay, the lens of health inequalities, and perspective of relationships as interconnecting elements in a broader system, is used to explore the varying impact of these disruptions. The essay concludes by providing recommendations for longer term recovery ensuring that the social relational cost of COVID-19 is adequately considered in efforts to rebuild.

inequalities

Data availability statement

Data sharing not applicable as no data sets generated and/or analysed for this study. Data sharing not applicable as no data sets generated or analysed for this essay.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/jech-2021-216690

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Introduction

Infectious disease pandemics, including SARS and COVID-19, demand intrapersonal behaviour change and present highly complex challenges for public health. 1 A pandemic of an airborne infection, spread easily through social contact, assails human relationships by drastically altering the ways through which humans interact. In this essay, we draw on theories of social relationships to examine specific ways in which relational mechanisms key to health and well-being were disrupted by the COVID-19 pandemic. Relational mechanisms refer to the processes between people that lead to change in health outcomes.

At the time of writing, the future surrounding COVID-19 was uncertain. Vaccine programmes were being rolled out in countries that could afford them, but new and more contagious variants of the virus were also being discovered. The recovery journey looked long, with continued disruption to social relationships. The social cost of COVID-19 was only just beginning to emerge, but the mental health impact was already considerable, 2 3 and the inequality of the health burden stark. 4 Knowledge of the epidemiology of COVID-19 accrued rapidly, but evidence of the most effective policy responses remained uncertain.

The initial response to COVID-19 in the UK was reactive and aimed at reducing mortality, with little time to consider the social implications, including for interpersonal and community relationships. The terminology of ‘social distancing’ quickly became entrenched both in public and policy discourse. This equation of physical distance with social distance was regrettable, since only physical proximity causes viral transmission, whereas many forms of social proximity (eg, conversations while walking outdoors) are minimal risk, and are crucial to maintaining relationships supportive of health and well-being.

The aim of this essay is to explore four key relational mechanisms that were impacted by the pandemic and associated restrictions: social networks, social support, social interaction and intimacy. We use relational theories and emerging research on the effects of the COVID-19 pandemic response to make three key recommendations: one regarding public health responses; and two regarding social recovery. Our understanding of these mechanisms stems from a ‘systems’ perspective which casts social relationships as interdependent elements within a connected whole. 5

Social networks

Social networks characterise the individuals and social connections that compose a system (such as a workplace, community or society). Social relationships range from spouses and partners, to coworkers, friends and acquaintances. They vary across many dimensions, including, for example, frequency of contact and emotional closeness. Social networks can be understood both in terms of the individuals and relationships that compose the network, as well as the overall network structure (eg, how many of your friends know each other).

Social networks show a tendency towards homophily, or a phenomenon of associating with individuals who are similar to self. 6 This is particularly true for ‘core’ network ties (eg, close friends), while more distant, sometimes called ‘weak’ ties tend to show more diversity. During the height of COVID-19 restrictions, face-to-face interactions were often reduced to core network members, such as partners, family members or, potentially, live-in roommates; some ‘weak’ ties were lost, and interactions became more limited to those closest. Given that peripheral, weaker social ties provide a diversity of resources, opinions and support, 7 COVID-19 likely resulted in networks that were smaller and more homogenous.

Such changes were not inevitable nor necessarily enduring, since social networks are also adaptive and responsive to change, in that a disruption to usual ways of interacting can be replaced by new ways of engaging (eg, Zoom). Yet, important inequalities exist, wherein networks and individual relationships within networks are not equally able to adapt to such changes. For example, individuals with a large number of newly established relationships (eg, university students) may have struggled to transfer these relationships online, resulting in lost contacts and a heightened risk of social isolation. This is consistent with research suggesting that young adults were the most likely to report a worsening of relationships during COVID-19, whereas older adults were the least likely to report a change. 8

Lastly, social connections give rise to emergent properties of social systems, 9 where a community-level phenomenon develops that cannot be attributed to any one member or portion of the network. For example, local area-based networks emerged due to geographic restrictions (eg, stay-at-home orders), resulting in increases in neighbourly support and local volunteering. 10 In fact, research suggests that relationships with neighbours displayed the largest net gain in ratings of relationship quality compared with a range of relationship types (eg, partner, colleague, friend). 8 Much of this was built from spontaneous individual interactions within local communities, which together contributed to the ‘community spirit’ that many experienced. 11 COVID-19 restrictions thus impacted the personal social networks and the structure of the larger networks within the society.

Social support

Social support, referring to the psychological and material resources provided through social interaction, is a critical mechanism through which social relationships benefit health. In fact, social support has been shown to be one of the most important resilience factors in the aftermath of stressful events. 12 In the context of COVID-19, the usual ways in which individuals interact and obtain social support have been severely disrupted.

One such disruption has been to opportunities for spontaneous social interactions. For example, conversations with colleagues in a break room offer an opportunity for socialising beyond one’s core social network, and these peripheral conversations can provide a form of social support. 13 14 A chance conversation may lead to advice helpful to coping with situations or seeking formal help. Thus, the absence of these spontaneous interactions may mean the reduction of indirect support-seeking opportunities. While direct support-seeking behaviour is more effective at eliciting support, it also requires significantly more effort and may be perceived as forceful and burdensome. 15 The shift to homeworking and closure of community venues reduced the number of opportunities for these spontaneous interactions to occur, and has, second, focused them locally. Consequently, individuals whose core networks are located elsewhere, or who live in communities where spontaneous interaction is less likely, have less opportunity to benefit from spontaneous in-person supportive interactions.

However, alongside this disruption, new opportunities to interact and obtain social support have arisen. The surge in community social support during the initial lockdown mirrored that often seen in response to adverse events (eg, natural disasters 16 ). COVID-19 restrictions that confined individuals to their local area also compelled them to focus their in-person efforts locally. Commentators on the initial lockdown in the UK remarked on extraordinary acts of generosity between individuals who belonged to the same community but were unknown to each other. However, research on adverse events also tells us that such community support is not necessarily maintained in the longer term. 16

Meanwhile, online forms of social support are not bound by geography, thus enabling interactions and social support to be received from a wider network of people. Formal online social support spaces (eg, support groups) existed well before COVID-19, but have vastly increased since. While online interactions can increase perceived social support, it is unclear whether remote communication technologies provide an effective substitute from in-person interaction during periods of social distancing. 17 18 It makes intuitive sense that the usefulness of online social support will vary by the type of support offered, degree of social interaction and ‘online communication skills’ of those taking part. Youth workers, for instance, have struggled to keep vulnerable youth engaged in online youth clubs, 19 despite others finding a positive association between amount of digital technology used by individuals during lockdown and perceived social support. 20 Other research has found that more frequent face-to-face contact and phone/video contact both related to lower levels of depression during the time period of March to August 2020, but the negative effect of a lack of contact was greater for those with higher levels of usual sociability. 21 Relatedly, important inequalities in social support exist, such that individuals who occupy more socially disadvantaged positions in society (eg, low socioeconomic status, older people) tend to have less access to social support, 22 potentially exacerbated by COVID-19.

Social and interactional norms

Interactional norms are key relational mechanisms which build trust, belonging and identity within and across groups in a system. Individuals in groups and societies apply meaning by ‘approving, arranging and redefining’ symbols of interaction. 23 A handshake, for instance, is a powerful symbol of trust and equality. Depending on context, not shaking hands may symbolise a failure to extend friendship, or a failure to reach agreement. The norms governing these symbols represent shared values and identity; and mutual understanding of these symbols enables individuals to achieve orderly interactions, establish supportive relationship accountability and connect socially. 24 25

Physical distancing measures to contain the spread of COVID-19 radically altered these norms of interaction, particularly those used to convey trust, affinity, empathy and respect (eg, hugging, physical comforting). 26 As epidemic waves rose and fell, the work to negotiate these norms required intense cognitive effort; previously taken-for-granted interactions were re-examined, factoring in current restriction levels, own and (assumed) others’ vulnerability and tolerance of risk. This created awkwardness, and uncertainty, for example, around how to bring closure to an in-person interaction or convey warmth. The instability in scripted ways of interacting created particular strain for individuals who already struggled to encode and decode interactions with others (eg, those who are deaf or have autism spectrum disorder); difficulties often intensified by mask wearing. 27

Large social gatherings—for example, weddings, school assemblies, sporting events—also present key opportunities for affirming and assimilating interactional norms, building cohesion and shared identity and facilitating cooperation across social groups. 28 Online ‘equivalents’ do not easily support ‘social-bonding’ activities such as singing and dancing, and rarely enable chance/spontaneous one-on-one conversations with peripheral/weaker network ties (see the Social networks section) which can help strengthen bonds across a larger network. The loss of large gatherings to celebrate rites of passage (eg, bar mitzvah, weddings) has additional relational costs since these events are performed by and for communities to reinforce belonging, and to assist in transitioning to new phases of life. 29 The loss of interaction with diverse others via community and large group gatherings also reduces intergroup contact, which may then tend towards more prejudiced outgroup attitudes. While online interaction can go some way to mimicking these interaction norms, there are key differences. A sense of anonymity, and lack of in-person emotional cues, tends to support norms of polarisation and aggression in expressing differences of opinion online. And while online platforms have potential to provide intergroup contact, the tendency of much social media to form homogeneous ‘echo chambers’ can serve to further reduce intergroup contact. 30 31

Intimacy relates to the feeling of emotional connection and closeness with other human beings. Emotional connection, through romantic, friendship or familial relationships, fulfils a basic human need 32 and strongly benefits health, including reduced stress levels, improved mental health, lowered blood pressure and reduced risk of heart disease. 32 33 Intimacy can be fostered through familiarity, feeling understood and feeling accepted by close others. 34

Intimacy via companionship and closeness is fundamental to mental well-being. Positively, the COVID-19 pandemic has offered opportunities for individuals to (re)connect and (re)strengthen close relationships within their household via quality time together, following closure of many usual external social activities. Research suggests that the first full UK lockdown period led to a net gain in the quality of steady relationships at a population level, 35 but amplified existing inequalities in relationship quality. 35 36 For some in single-person households, the absence of a companion became more conspicuous, leading to feelings of loneliness and lower mental well-being. 37 38 Additional pandemic-related relational strain 39 40 resulted, for some, in the initiation or intensification of domestic abuse. 41 42

Physical touch is another key aspect of intimacy, a fundamental human need crucial in maintaining and developing intimacy within close relationships. 34 Restrictions on social interactions severely restricted the number and range of people with whom physical affection was possible. The reduction in opportunity to give and receive affectionate physical touch was not experienced equally. Many of those living alone found themselves completely without physical contact for extended periods. The deprivation of physical touch is evidenced to take a heavy emotional toll. 43 Even in future, once physical expressions of affection can resume, new levels of anxiety over germs may introduce hesitancy into previously fluent blending of physical and verbal intimate social connections. 44

The pandemic also led to shifts in practices and norms around sexual relationship building and maintenance, as individuals adapted and sought alternative ways of enacting sexual intimacy. This too is important, given that intimate sexual activity has known benefits for health. 45 46 Given that social restrictions hinged on reducing household mixing, possibilities for partnered sexual activity were primarily guided by living arrangements. While those in cohabiting relationships could potentially continue as before, those who were single or in non-cohabiting relationships generally had restricted opportunities to maintain their sexual relationships. Pornography consumption and digital partners were reported to increase since lockdown. 47 However, online interactions are qualitatively different from in-person interactions and do not provide the same opportunities for physical intimacy.

Recommendations and conclusions

In the sections above we have outlined the ways in which COVID-19 has impacted social relationships, showing how relational mechanisms key to health have been undermined. While some of the damage might well self-repair after the pandemic, there are opportunities inherent in deliberative efforts to build back in ways that facilitate greater resilience in social and community relationships. We conclude by making three recommendations: one regarding public health responses to the pandemic; and two regarding social recovery.

Recommendation 1: explicitly count the relational cost of public health policies to control the pandemic

Effective handling of a pandemic recognises that social, economic and health concerns are intricately interwoven. It is clear that future research and policy attention must focus on the social consequences. As described above, policies which restrict physical mixing across households carry heavy and unequal relational costs. These include for individuals (eg, loss of intimate touch), dyads (eg, loss of warmth, comfort), networks (eg, restricted access to support) and communities (eg, loss of cohesion and identity). Such costs—and their unequal impact—should not be ignored in short-term efforts to control an epidemic. Some public health responses—restrictions on international holiday travel and highly efficient test and trace systems—have relatively small relational costs and should be prioritised. At a national level, an earlier move to proportionate restrictions, and investment in effective test and trace systems, may help prevent escalation of spread to the point where a national lockdown or tight restrictions became an inevitability. Where policies with relational costs are unavoidable, close attention should be paid to the unequal relational impact for those whose personal circumstances differ from normative assumptions of two adult families. This includes consideration of whether expectations are fair (eg, for those who live alone), whether restrictions on social events are equitable across age group, religious/ethnic groupings and social class, and also to ensure that the language promoted by such policies (eg, households; families) is not exclusionary. 48 49 Forethought to unequal impacts on social relationships should thus be integral to the work of epidemic preparedness teams.

Recommendation 2: intelligently balance online and offline ways of relating

A key ingredient for well-being is ‘getting together’ in a physical sense. This is fundamental to a human need for intimate touch, physical comfort, reinforcing interactional norms and providing practical support. Emerging evidence suggests that online ways of relating cannot simply replace physical interactions. But online interaction has many benefits and for some it offers connections that did not exist previously. In particular, online platforms provide new forms of support for those unable to access offline services because of mobility issues (eg, older people) or because they are geographically isolated from their support community (eg, lesbian, gay, bisexual, transgender and queer (LGBTQ) youth). Ultimately, multiple forms of online and offline social interactions are required to meet the needs of varying groups of people (eg, LGBTQ, older people). Future research and practice should aim to establish ways of using offline and online support in complementary and even synergistic ways, rather than veering between them as social restrictions expand and contract. Intelligent balancing of online and offline ways of relating also pertains to future policies on home and flexible working. A decision to switch to wholesale or obligatory homeworking should consider the risk to relational ‘group properties’ of the workplace community and their impact on employees’ well-being, focusing in particular on unequal impacts (eg, new vs established employees). Intelligent blending of online and in-person working is required to achieve flexibility while also nurturing supportive networks at work. Intelligent balance also implies strategies to build digital literacy and minimise digital exclusion, as well as coproducing solutions with intended beneficiaries.

Recommendation 3: build stronger and sustainable localised communities

In balancing offline and online ways of interacting, there is opportunity to capitalise on the potential for more localised, coherent communities due to scaled-down travel, homeworking and local focus that will ideally continue after restrictions end. There are potential economic benefits after the pandemic, such as increased trade as home workers use local resources (eg, coffee shops), but also relational benefits from stronger relationships around the orbit of the home and neighbourhood. Experience from previous crises shows that community volunteer efforts generated early on will wane over time in the absence of deliberate work to maintain them. Adequately funded partnerships between local government, third sector and community groups are required to sustain community assets that began as a direct response to the pandemic. Such partnerships could work to secure green spaces and indoor (non-commercial) meeting spaces that promote community interaction. Green spaces in particular provide a triple benefit in encouraging physical activity and mental health, as well as facilitating social bonding. 50 In building local communities, small community networks—that allow for diversity and break down ingroup/outgroup views—may be more helpful than the concept of ‘support bubbles’, which are exclusionary and less sustainable in the longer term. Rigorously designed intervention and evaluation—taking a systems approach—will be crucial in ensuring scale-up and sustainability.

The dramatic change to social interaction necessitated by efforts to control the spread of COVID-19 created stark challenges but also opportunities. Our essay highlights opportunities for learning, both to ensure the equity and humanity of physical restrictions, and to sustain the salutogenic effects of social relationships going forward. The starting point for capitalising on this learning is recognition of the disruption to relational mechanisms as a key part of the socioeconomic and health impact of the pandemic. In recovery planning, a general rule is that what is good for decreasing health inequalities (such as expanding social protection and public services and pursuing green inclusive growth strategies) 4 will also benefit relationships and safeguard relational mechanisms for future generations. Putting this into action will require political will.

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Twitter @karenmaxSPHSU, @Mark_McCann, @Rwilsonlowe, @KMitchinGlasgow

Contributors EL and KM led on the manuscript conceptualisation, review and editing. SP, KM, CB, RBP, RL, MM, JR, KS and RW-L contributed to drafting and revising the article. All authors assisted in revising the final draft.

Funding The research reported in this publication was supported by the Medical Research Council (MC_UU_00022/1, MC_UU_00022/3) and the Chief Scientist Office (SPHSU11, SPHSU14). EL is also supported by MRC Skills Development Fellowship Award (MR/S015078/1). KS and MM are also supported by a Medical Research Council Strategic Award (MC_PC_13027).

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

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Coronavirus disease 2019 (COVID-19): A literature review

Affiliations.

1 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
2 Division of Infectious Diseases, AichiCancer Center Hospital, Chikusa-ku Nagoya, Japan. Electronic address: [email protected].
3 Department of Family Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
4 Department of Pulmonology and Respiratory Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
5 School of Medicine, The University of Western Australia, Perth, Australia. Electronic address: [email protected].
6 Siem Reap Provincial Health Department, Ministry of Health, Siem Reap, Cambodia. Electronic address: [email protected].
7 Department of Microbiology and Parasitology, Faculty of Medicine and Health Sciences, Warmadewa University, Denpasar, Indonesia; Department of Medical Microbiology and Immunology, University of California, Davis, CA, USA. Electronic address: [email protected].
8 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Clinical Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
9 Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, MI 48109, USA. Electronic address: [email protected].
10 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
PMID: 32340833
PMCID: PMC7142680
DOI: 10.1016/j.jiph.2020.03.019

In early December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. On January 30, 2020 the World Health Organization declared the outbreak as a Public Health Emergency of International Concern. As of February 14, 2020, 49,053 laboratory-confirmed and 1,381 deaths have been reported globally. Perceived risk of acquiring disease has led many governments to institute a variety of control measures. We conducted a literature review of publicly available information to summarize knowledge about the pathogen and the current epidemic. In this literature review, the causative agent, pathogenesis and immune responses, epidemiology, diagnosis, treatment and management of the disease, control and preventions strategies are all reviewed.

Keywords: 2019-nCoV; COVID-19; Novel coronavirus; Outbreak; SARS-CoV-2.

PubMed Disclaimer

COVID-19 pandemic and Internal Medicine Units in Italy: a precious effort on the front line. Montagnani A, Pieralli F, Gnerre P, Vertulli C, Manfellotto D; FADOI COVID-19 Observatory Group. Montagnani A, et al. Intern Emerg Med. 2020 Nov;15(8):1595-1597. doi: 10.1007/s11739-020-02454-5. Epub 2020 Jul 31. Intern Emerg Med. 2020. PMID: 32737837 Free PMC article. No abstract available.

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Research article
Open access
Published: 04 June 2021

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews

Israel Júnior Borges do Nascimento 1 , 2 ,
Dónal P. O’Mathúna 3 , 4 ,
Thilo Caspar von Groote 5 ,
Hebatullah Mohamed Abdulazeem 6 ,
Ishanka Weerasekara 7 , 8 ,
Ana Marusic 9 ,
Livia Puljak ORCID: orcid.org/0000-0002-8467-6061 10 ,
Vinicius Tassoni Civile 11 ,
Irena Zakarija-Grkovic 9 ,
Tina Poklepovic Pericic 9 ,
Alvaro Nagib Atallah 11 ,
Santino Filoso 12 ,
Nicola Luigi Bragazzi 13 &
Milena Soriano Marcolino 1

On behalf of the International Network of Coronavirus Disease 2019 (InterNetCOVID-19)

BMC Infectious Diseases volume 21 , Article number: 525 ( 2021 ) Cite this article

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Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO’s Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes.

Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as “critically low”. Identified symptoms of COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%) and gastrointestinal complaints (5–9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%.

Conclusions

In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Peer Review reports

The spread of the “Severe Acute Respiratory Coronavirus 2” (SARS-CoV-2), the causal agent of COVID-19, was characterized as a pandemic by the World Health Organization (WHO) in March 2020 and has triggered an international public health emergency [ 1 ]. The numbers of confirmed cases and deaths due to COVID-19 are rapidly escalating, counting in millions [ 2 ], causing massive economic strain, and escalating healthcare and public health expenses [ 3 , 4 ].

The research community has responded by publishing an impressive number of scientific reports related to COVID-19. The world was alerted to the new disease at the beginning of 2020 [ 1 ], and by mid-March 2020, more than 2000 articles had been published on COVID-19 in scholarly journals, with 25% of them containing original data [ 5 ]. The living map of COVID-19 evidence, curated by the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), contained more than 40,000 records by February 2021 [ 6 ]. More than 100,000 records on PubMed were labeled as “SARS-CoV-2 literature, sequence, and clinical content” by February 2021 [ 7 ].

Due to publication speed, the research community has voiced concerns regarding the quality and reproducibility of evidence produced during the COVID-19 pandemic, warning of the potential damaging approach of “publish first, retract later” [ 8 ]. It appears that these concerns are not unfounded, as it has been reported that COVID-19 articles were overrepresented in the pool of retracted articles in 2020 [ 9 ]. These concerns about inadequate evidence are of major importance because they can lead to poor clinical practice and inappropriate policies [ 10 ].

Systematic reviews are a cornerstone of today’s evidence-informed decision-making. By synthesizing all relevant evidence regarding a particular topic, systematic reviews reflect the current scientific knowledge. Systematic reviews are considered to be at the highest level in the hierarchy of evidence and should be used to make informed decisions. However, with high numbers of systematic reviews of different scope and methodological quality being published, overviews of multiple systematic reviews that assess their methodological quality are essential [ 11 , 12 , 13 ]. An overview of systematic reviews helps identify and organize the literature and highlights areas of priority in decision-making.

In this overview of systematic reviews, we aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Methodology

Research question.

This overview’s primary objective was to summarize and critically appraise systematic reviews that assessed any type of primary clinical data from patients infected with SARS-CoV-2. Our research question was purposefully broad because we wanted to analyze as many systematic reviews as possible that were available early following the COVID-19 outbreak.

Study design

We conducted an overview of systematic reviews. The idea for this overview originated in a protocol for a systematic review submitted to PROSPERO (CRD42020170623), which indicated a plan to conduct an overview.

Overviews of systematic reviews use explicit and systematic methods for searching and identifying multiple systematic reviews addressing related research questions in the same field to extract and analyze evidence across important outcomes. Overviews of systematic reviews are in principle similar to systematic reviews of interventions, but the unit of analysis is a systematic review [ 14 , 15 , 16 ].

We used the overview methodology instead of other evidence synthesis methods to allow us to collate and appraise multiple systematic reviews on this topic, and to extract and analyze their results across relevant topics [ 17 ]. The overview and meta-analysis of systematic reviews allowed us to investigate the methodological quality of included studies, summarize results, and identify specific areas of available or limited evidence, thereby strengthening the current understanding of this novel disease and guiding future research [ 13 ].

A reporting guideline for overviews of reviews is currently under development, i.e., Preferred Reporting Items for Overviews of Reviews (PRIOR) [ 18 ]. As the PRIOR checklist is still not published, this study was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 statement [ 19 ]. The methodology used in this review was adapted from the Cochrane Handbook for Systematic Reviews of Interventions and also followed established methodological considerations for analyzing existing systematic reviews [ 14 ].

Approval of a research ethics committee was not necessary as the study analyzed only publicly available articles.

Eligibility criteria

Systematic reviews were included if they analyzed primary data from patients infected with SARS-CoV-2 as confirmed by RT-PCR or another pre-specified diagnostic technique. Eligible reviews covered all topics related to COVID-19 including, but not limited to, those that reported clinical symptoms, diagnostic methods, therapeutic interventions, laboratory findings, or radiological results. Both full manuscripts and abbreviated versions, such as letters, were eligible.

No restrictions were imposed on the design of the primary studies included within the systematic reviews, the last search date, whether the review included meta-analyses or language. Reviews related to SARS-CoV-2 and other coronaviruses were eligible, but from those reviews, we analyzed only data related to SARS-CoV-2.

No consensus definition exists for a systematic review [ 20 ], and debates continue about the defining characteristics of a systematic review [ 21 ]. Cochrane’s guidance for overviews of reviews recommends setting pre-established criteria for making decisions around inclusion [ 14 ]. That is supported by a recent scoping review about guidance for overviews of systematic reviews [ 22 ].

Thus, for this study, we defined a systematic review as a research report which searched for primary research studies on a specific topic using an explicit search strategy, had a detailed description of the methods with explicit inclusion criteria provided, and provided a summary of the included studies either in narrative or quantitative format (such as a meta-analysis). Cochrane and non-Cochrane systematic reviews were considered eligible for inclusion, with or without meta-analysis, and regardless of the study design, language restriction and methodology of the included primary studies. To be eligible for inclusion, reviews had to be clearly analyzing data related to SARS-CoV-2 (associated or not with other viruses). We excluded narrative reviews without those characteristics as these are less likely to be replicable and are more prone to bias.

Scoping reviews and rapid reviews were eligible for inclusion in this overview if they met our pre-defined inclusion criteria noted above. We included reviews that addressed SARS-CoV-2 and other coronaviruses if they reported separate data regarding SARS-CoV-2.

Information sources

Nine databases were searched for eligible records published between December 1, 2019, and March 24, 2020: Cochrane Database of Systematic Reviews via Cochrane Library, PubMed, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Sciences, LILACS (Latin American and Caribbean Health Sciences Literature), PDQ-Evidence, WHO’s Global Research on Coronavirus Disease (COVID-19), and Epistemonikos.

The comprehensive search strategy for each database is provided in Additional file 1 and was designed and conducted in collaboration with an information specialist. All retrieved records were primarily processed in EndNote, where duplicates were removed, and records were then imported into the Covidence platform [ 23 ]. In addition to database searches, we screened reference lists of reviews included after screening records retrieved via databases.

Study selection

All searches, screening of titles and abstracts, and record selection, were performed independently by two investigators using the Covidence platform [ 23 ]. Articles deemed potentially eligible were retrieved for full-text screening carried out independently by two investigators. Discrepancies at all stages were resolved by consensus. During the screening, records published in languages other than English were translated by a native/fluent speaker.

Data collection process

We custom designed a data extraction table for this study, which was piloted by two authors independently. Data extraction was performed independently by two authors. Conflicts were resolved by consensus or by consulting a third researcher.

We extracted the following data: article identification data (authors’ name and journal of publication), search period, number of databases searched, population or settings considered, main results and outcomes observed, and number of participants. From Web of Science (Clarivate Analytics, Philadelphia, PA, USA), we extracted journal rank (quartile) and Journal Impact Factor (JIF).

We categorized the following as primary outcomes: all-cause mortality, need for and length of mechanical ventilation, length of hospitalization (in days), admission to intensive care unit (yes/no), and length of stay in the intensive care unit.

The following outcomes were categorized as exploratory: diagnostic methods used for detection of the virus, male to female ratio, clinical symptoms, pharmacological and non-pharmacological interventions, laboratory findings (full blood count, liver enzymes, C-reactive protein, d-dimer, albumin, lipid profile, serum electrolytes, blood vitamin levels, glucose levels, and any other important biomarkers), and radiological findings (using radiography, computed tomography, magnetic resonance imaging or ultrasound).

We also collected data on reporting guidelines and requirements for the publication of systematic reviews and meta-analyses from journal websites where included reviews were published.

Quality assessment in individual reviews

Two researchers independently assessed the reviews’ quality using the “A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR 2)”. We acknowledge that the AMSTAR 2 was created as “a critical appraisal tool for systematic reviews that include randomized or non-randomized studies of healthcare interventions, or both” [ 24 ]. However, since AMSTAR 2 was designed for systematic reviews of intervention trials, and we included additional types of systematic reviews, we adjusted some AMSTAR 2 ratings and reported these in Additional file 2 .

Adherence to each item was rated as follows: yes, partial yes, no, or not applicable (such as when a meta-analysis was not conducted). The overall confidence in the results of the review is rated as “critically low”, “low”, “moderate” or “high”, according to the AMSTAR 2 guidance based on seven critical domains, which are items 2, 4, 7, 9, 11, 13, 15 as defined by AMSTAR 2 authors [ 24 ]. We reported our adherence ratings for transparency of our decision with accompanying explanations, for each item, in each included review.

One of the included systematic reviews was conducted by some members of this author team [ 25 ]. This review was initially assessed independently by two authors who were not co-authors of that review to prevent the risk of bias in assessing this study.

Synthesis of results

For data synthesis, we prepared a table summarizing each systematic review. Graphs illustrating the mortality rate and clinical symptoms were created. We then prepared a narrative summary of the methods, findings, study strengths, and limitations.

For analysis of the prevalence of clinical outcomes, we extracted data on the number of events and the total number of patients to perform proportional meta-analysis using RStudio© software, with the “meta” package (version 4.9–6), using the “metaprop” function for reviews that did not perform a meta-analysis, excluding case studies because of the absence of variance. For reviews that did not perform a meta-analysis, we presented pooled results of proportions with their respective confidence intervals (95%) by the inverse variance method with a random-effects model, using the DerSimonian-Laird estimator for τ 2 . We adjusted data using Freeman-Tukey double arcosen transformation. Confidence intervals were calculated using the Clopper-Pearson method for individual studies. We created forest plots using the RStudio© software, with the “metafor” package (version 2.1–0) and “forest” function.

Managing overlapping systematic reviews

Some of the included systematic reviews that address the same or similar research questions may include the same primary studies in overviews. Including such overlapping reviews may introduce bias when outcome data from the same primary study are included in the analyses of an overview multiple times. Thus, in summaries of evidence, multiple-counting of the same outcome data will give data from some primary studies too much influence [ 14 ]. In this overview, we did not exclude overlapping systematic reviews because, according to Cochrane’s guidance, it may be appropriate to include all relevant reviews’ results if the purpose of the overview is to present and describe the current body of evidence on a topic [ 14 ]. To avoid any bias in summary estimates associated with overlapping reviews, we generated forest plots showing data from individual systematic reviews, but the results were not pooled because some primary studies were included in multiple reviews.

Our search retrieved 1063 publications, of which 175 were duplicates. Most publications were excluded after the title and abstract analysis ( n = 860). Among the 28 studies selected for full-text screening, 10 were excluded for the reasons described in Additional file 3 , and 18 were included in the final analysis (Fig. 1 ) [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Reference list screening did not retrieve any additional systematic reviews.

PRISMA flow diagram

Characteristics of included reviews

Summary features of 18 systematic reviews are presented in Table 1 . They were published in 14 different journals. Only four of these journals had specific requirements for systematic reviews (with or without meta-analysis): European Journal of Internal Medicine, Journal of Clinical Medicine, Ultrasound in Obstetrics and Gynecology, and Clinical Research in Cardiology . Two journals reported that they published only invited reviews ( Journal of Medical Virology and Clinica Chimica Acta ). Three systematic reviews in our study were published as letters; one was labeled as a scoping review and another as a rapid review (Table 2 ).

All reviews were published in English, in first quartile (Q1) journals, with JIF ranging from 1.692 to 6.062. One review was empty, meaning that its search did not identify any relevant studies; i.e., no primary studies were included [ 36 ]. The remaining 17 reviews included 269 unique studies; the majority ( N = 211; 78%) were included in only a single review included in our study (range: 1 to 12). Primary studies included in the reviews were published between December 2019 and March 18, 2020, and comprised case reports, case series, cohorts, and other observational studies. We found only one review that included randomized clinical trials [ 38 ]. In the included reviews, systematic literature searches were performed from 2019 (entire year) up to March 9, 2020. Ten systematic reviews included meta-analyses. The list of primary studies found in the included systematic reviews is shown in Additional file 4 , as well as the number of reviews in which each primary study was included.

Population and study designs

Most of the reviews analyzed data from patients with COVID-19 who developed pneumonia, acute respiratory distress syndrome (ARDS), or any other correlated complication. One review aimed to evaluate the effectiveness of using surgical masks on preventing transmission of the virus [ 36 ], one review was focused on pediatric patients [ 34 ], and one review investigated COVID-19 in pregnant women [ 37 ]. Most reviews assessed clinical symptoms, laboratory findings, or radiological results.

Systematic review findings

The summary of findings from individual reviews is shown in Table 2 . Overall, all-cause mortality ranged from 0.3 to 13.9% (Fig. 2 ).

A meta-analysis of the prevalence of mortality

Clinical symptoms

Seven reviews described the main clinical manifestations of COVID-19 [ 26 , 28 , 29 , 34 , 35 , 39 , 41 ]. Three of them provided only a narrative discussion of symptoms [ 26 , 34 , 35 ]. In the reviews that performed a statistical analysis of the incidence of different clinical symptoms, symptoms in patients with COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%), gastrointestinal disorders, such as diarrhea, nausea or vomiting (5.0–9.0%), and others (including, in one study only: dizziness 12.1%) (Figs. 3 , 4 , 5 , 6 , 7 , 8 and 9 ). Three reviews assessed cough with and without sputum together; only one review assessed sputum production itself (28.5%).

A meta-analysis of the prevalence of fever

A meta-analysis of the prevalence of cough

A meta-analysis of the prevalence of dyspnea

A meta-analysis of the prevalence of fatigue or myalgia

A meta-analysis of the prevalence of headache

A meta-analysis of the prevalence of gastrointestinal disorders

A meta-analysis of the prevalence of sore throat

Diagnostic aspects

Three reviews described methodologies, protocols, and tools used for establishing the diagnosis of COVID-19 [ 26 , 34 , 38 ]. The use of respiratory swabs (nasal or pharyngeal) or blood specimens to assess the presence of SARS-CoV-2 nucleic acid using RT-PCR assays was the most commonly used diagnostic method mentioned in the included studies. These diagnostic tests have been widely used, but their precise sensitivity and specificity remain unknown. One review included a Chinese study with clinical diagnosis with no confirmation of SARS-CoV-2 infection (patients were diagnosed with COVID-19 if they presented with at least two symptoms suggestive of COVID-19, together with laboratory and chest radiography abnormalities) [ 34 ].

Therapeutic possibilities

Pharmacological and non-pharmacological interventions (supportive therapies) used in treating patients with COVID-19 were reported in five reviews [ 25 , 27 , 34 , 35 , 38 ]. Antivirals used empirically for COVID-19 treatment were reported in seven reviews [ 25 , 27 , 34 , 35 , 37 , 38 , 41 ]; most commonly used were protease inhibitors (lopinavir, ritonavir, darunavir), nucleoside reverse transcriptase inhibitor (tenofovir), nucleotide analogs (remdesivir, galidesivir, ganciclovir), and neuraminidase inhibitors (oseltamivir). Umifenovir, a membrane fusion inhibitor, was investigated in two studies [ 25 , 35 ]. Possible supportive interventions analyzed were different types of oxygen supplementation and breathing support (invasive or non-invasive ventilation) [ 25 ]. The use of antibiotics, both empirically and to treat secondary pneumonia, was reported in six studies [ 25 , 26 , 27 , 34 , 35 , 38 ]. One review specifically assessed evidence on the efficacy and safety of the anti-malaria drug chloroquine [ 27 ]. It identified 23 ongoing trials investigating the potential of chloroquine as a therapeutic option for COVID-19, but no verifiable clinical outcomes data. The use of mesenchymal stem cells, antifungals, and glucocorticoids were described in four reviews [ 25 , 34 , 35 , 38 ].

Laboratory and radiological findings

Of the 18 reviews included in this overview, eight analyzed laboratory parameters in patients with COVID-19 [ 25 , 29 , 30 , 32 , 33 , 34 , 35 , 39 ]; elevated C-reactive protein levels, associated with lymphocytopenia, elevated lactate dehydrogenase, as well as slightly elevated aspartate and alanine aminotransferase (AST, ALT) were commonly described in those eight reviews. Lippi et al. assessed cardiac troponin I (cTnI) [ 25 ], procalcitonin [ 32 ], and platelet count [ 33 ] in COVID-19 patients. Elevated levels of procalcitonin [ 32 ] and cTnI [ 30 ] were more likely to be associated with a severe disease course (requiring intensive care unit admission and intubation). Furthermore, thrombocytopenia was frequently observed in patients with complicated COVID-19 infections [ 33 ].

Chest imaging (chest radiography and/or computed tomography) features were assessed in six reviews, all of which described a frequent pattern of local or bilateral multilobar ground-glass opacity [ 25 , 34 , 35 , 39 , 40 , 41 ]. Those six reviews showed that septal thickening, bronchiectasis, pleural and cardiac effusions, halo signs, and pneumothorax were observed in patients suffering from COVID-19.

Quality of evidence in individual systematic reviews

Table 3 shows the detailed results of the quality assessment of 18 systematic reviews, including the assessment of individual items and summary assessment. A detailed explanation for each decision in each review is available in Additional file 5 .

Using AMSTAR 2 criteria, confidence in the results of all 18 reviews was rated as “critically low” (Table 3 ). Common methodological drawbacks were: omission of prospective protocol submission or publication; use of inappropriate search strategy: lack of independent and dual literature screening and data-extraction (or methodology unclear); absence of an explanation for heterogeneity among the studies included; lack of reasons for study exclusion (or rationale unclear).

Risk of bias assessment, based on a reported methodological tool, and quality of evidence appraisal, in line with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method, were reported only in one review [ 25 ]. Five reviews presented a table summarizing bias, using various risk of bias tools [ 25 , 29 , 39 , 40 , 41 ]. One review analyzed “study quality” [ 37 ]. One review mentioned the risk of bias assessment in the methodology but did not provide any related analysis [ 28 ].

This overview of systematic reviews analyzed the first 18 systematic reviews published after the onset of the COVID-19 pandemic, up to March 24, 2020, with primary studies involving more than 60,000 patients. Using AMSTAR-2, we judged that our confidence in all those reviews was “critically low”. Ten reviews included meta-analyses. The reviews presented data on clinical manifestations, laboratory and radiological findings, and interventions. We found no systematic reviews on the utility of diagnostic tests.

Symptoms were reported in seven reviews; most of the patients had a fever, cough, dyspnea, myalgia or muscle fatigue, and gastrointestinal disorders such as diarrhea, nausea, or vomiting. Olfactory dysfunction (anosmia or dysosmia) has been described in patients infected with COVID-19 [ 43 ]; however, this was not reported in any of the reviews included in this overview. During the SARS outbreak in 2002, there were reports of impairment of the sense of smell associated with the disease [ 44 , 45 ].

The reported mortality rates ranged from 0.3 to 14% in the included reviews. Mortality estimates are influenced by the transmissibility rate (basic reproduction number), availability of diagnostic tools, notification policies, asymptomatic presentations of the disease, resources for disease prevention and control, and treatment facilities; variability in the mortality rate fits the pattern of emerging infectious diseases [ 46 ]. Furthermore, the reported cases did not consider asymptomatic cases, mild cases where individuals have not sought medical treatment, and the fact that many countries had limited access to diagnostic tests or have implemented testing policies later than the others. Considering the lack of reviews assessing diagnostic testing (sensitivity, specificity, and predictive values of RT-PCT or immunoglobulin tests), and the preponderance of studies that assessed only symptomatic individuals, considerable imprecision around the calculated mortality rates existed in the early stage of the COVID-19 pandemic.

Few reviews included treatment data. Those reviews described studies considered to be at a very low level of evidence: usually small, retrospective studies with very heterogeneous populations. Seven reviews analyzed laboratory parameters; those reviews could have been useful for clinicians who attend patients suspected of COVID-19 in emergency services worldwide, such as assessing which patients need to be reassessed more frequently.

All systematic reviews scored poorly on the AMSTAR 2 critical appraisal tool for systematic reviews. Most of the original studies included in the reviews were case series and case reports, impacting the quality of evidence. Such evidence has major implications for clinical practice and the use of these reviews in evidence-based practice and policy. Clinicians, patients, and policymakers can only have the highest confidence in systematic review findings if high-quality systematic review methodologies are employed. The urgent need for information during a pandemic does not justify poor quality reporting.

We acknowledge that there are numerous challenges associated with analyzing COVID-19 data during a pandemic [ 47 ]. High-quality evidence syntheses are needed for decision-making, but each type of evidence syntheses is associated with its inherent challenges.

The creation of classic systematic reviews requires considerable time and effort; with massive research output, they quickly become outdated, and preparing updated versions also requires considerable time. A recent study showed that updates of non-Cochrane systematic reviews are published a median of 5 years after the publication of the previous version [ 48 ].

Authors may register a review and then abandon it [ 49 ], but the existence of a public record that is not updated may lead other authors to believe that the review is still ongoing. A quarter of Cochrane review protocols remains unpublished as completed systematic reviews 8 years after protocol publication [ 50 ].

Rapid reviews can be used to summarize the evidence, but they involve methodological sacrifices and simplifications to produce information promptly, with inconsistent methodological approaches [ 51 ]. However, rapid reviews are justified in times of public health emergencies, and even Cochrane has resorted to publishing rapid reviews in response to the COVID-19 crisis [ 52 ]. Rapid reviews were eligible for inclusion in this overview, but only one of the 18 reviews included in this study was labeled as a rapid review.

Ideally, COVID-19 evidence would be continually summarized in a series of high-quality living systematic reviews, types of evidence synthesis defined as “ a systematic review which is continually updated, incorporating relevant new evidence as it becomes available ” [ 53 ]. However, conducting living systematic reviews requires considerable resources, calling into question the sustainability of such evidence synthesis over long periods [ 54 ].

Research reports about COVID-19 will contribute to research waste if they are poorly designed, poorly reported, or simply not necessary. In principle, systematic reviews should help reduce research waste as they usually provide recommendations for further research that is needed or may advise that sufficient evidence exists on a particular topic [ 55 ]. However, systematic reviews can also contribute to growing research waste when they are not needed, or poorly conducted and reported. Our present study clearly shows that most of the systematic reviews that were published early on in the COVID-19 pandemic could be categorized as research waste, as our confidence in their results is critically low.

Our study has some limitations. One is that for AMSTAR 2 assessment we relied on information available in publications; we did not attempt to contact study authors for clarifications or additional data. In three reviews, the methodological quality appraisal was challenging because they were published as letters, or labeled as rapid communications. As a result, various details about their review process were not included, leading to AMSTAR 2 questions being answered as “not reported”, resulting in low confidence scores. Full manuscripts might have provided additional information that could have led to higher confidence in the results. In other words, low scores could reflect incomplete reporting, not necessarily low-quality review methods. To make their review available more rapidly and more concisely, the authors may have omitted methodological details. A general issue during a crisis is that speed and completeness must be balanced. However, maintaining high standards requires proper resourcing and commitment to ensure that the users of systematic reviews can have high confidence in the results.

Furthermore, we used adjusted AMSTAR 2 scoring, as the tool was designed for critical appraisal of reviews of interventions. Some reviews may have received lower scores than actually warranted in spite of these adjustments.

Another limitation of our study may be the inclusion of multiple overlapping reviews, as some included reviews included the same primary studies. According to the Cochrane Handbook, including overlapping reviews may be appropriate when the review’s aim is “ to present and describe the current body of systematic review evidence on a topic ” [ 12 ], which was our aim. To avoid bias with summarizing evidence from overlapping reviews, we presented the forest plots without summary estimates. The forest plots serve to inform readers about the effect sizes for outcomes that were reported in each review.

Several authors from this study have contributed to one of the reviews identified [ 25 ]. To reduce the risk of any bias, two authors who did not co-author the review in question initially assessed its quality and limitations.

Finally, we note that the systematic reviews included in our overview may have had issues that our analysis did not identify because we did not analyze their primary studies to verify the accuracy of the data and information they presented. We give two examples to substantiate this possibility. Lovato et al. wrote a commentary on the review of Sun et al. [ 41 ], in which they criticized the authors’ conclusion that sore throat is rare in COVID-19 patients [ 56 ]. Lovato et al. highlighted that multiple studies included in Sun et al. did not accurately describe participants’ clinical presentations, warning that only three studies clearly reported data on sore throat [ 56 ].

In another example, Leung [ 57 ] warned about the review of Li, L.Q. et al. [ 29 ]: “ it is possible that this statistic was computed using overlapped samples, therefore some patients were double counted ”. Li et al. responded to Leung that it is uncertain whether the data overlapped, as they used data from published articles and did not have access to the original data; they also reported that they requested original data and that they plan to re-do their analyses once they receive them; they also urged readers to treat the data with caution [ 58 ]. This points to the evolving nature of evidence during a crisis.

Our study’s strength is that this overview adds to the current knowledge by providing a comprehensive summary of all the evidence synthesis about COVID-19 available early after the onset of the pandemic. This overview followed strict methodological criteria, including a comprehensive and sensitive search strategy and a standard tool for methodological appraisal of systematic reviews.

In conclusion, in this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all the reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic could be categorized as research waste. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards to provide patients, clinicians, and decision-makers trustworthy evidence.

Availability of data and materials

All data collected and analyzed within this study are available from the corresponding author on reasonable request.

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Acknowledgments

We thank Catherine Henderson DPhil from Swanscoe Communications for pro bono medical writing and editing support. We acknowledge support from the Covidence Team, specifically Anneliese Arno. We thank the whole International Network of Coronavirus Disease 2019 (InterNetCOVID-19) for their commitment and involvement. Members of the InterNetCOVID-19 are listed in Additional file 6 . We thank Pavel Cerny and Roger Crosthwaite for guiding the team supervisor (IJBN) on human resources management.

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IJBN conceived the research idea and worked as a project coordinator. DPOM, TCVG, HMA, IW, AM, LP, VTC, IZG, TPP, ANA, SF, NLB and MSM were involved in data curation, formal analysis, investigation, methodology, and initial draft writing. All authors revised the manuscript critically for the content. The author(s) read and approved the final manuscript.

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Supplementary Information

Additional file 1: appendix 1..

Search strategies used in the study.

Additional file 2: Appendix 2.

Adjusted scoring of AMSTAR 2 used in this study for systematic reviews of studies that did not analyze interventions.

Additional file 3: Appendix 3.

List of excluded studies, with reasons.

Additional file 4: Appendix 4.

Table of overlapping studies, containing the list of primary studies included, their visual overlap in individual systematic reviews, and the number in how many reviews each primary study was included.

Additional file 5: Appendix 5.

A detailed explanation of AMSTAR scoring for each item in each review.

Additional file 6: Appendix 6.

List of members and affiliates of International Network of Coronavirus Disease 2019 (InterNetCOVID-19).

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Borges do Nascimento, I.J., O’Mathúna, D.P., von Groote, T.C. et al. Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews. BMC Infect Dis 21 , 525 (2021). https://doi.org/10.1186/s12879-021-06214-4

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Research Article

The impact of COVID-19 pandemic on physical and mental health of Asians: A study of seven middle-income countries in Asia

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Institute of Cognitive Neuroscience, Faculty of Education, Huaibei Normal University, Huaibei, China

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation College of Medicine, University of the Philippines, Manila, Philippines

Roles Conceptualization, Supervision, Visualization

Affiliation University Malaysia Sarawak (UNIMAS), Sarawak, Malaysia

Roles Conceptualization, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Psychology, Zahedan Branch, Islamic Azad University, Zahedan, Iran

Roles Conceptualization, Investigation, Methodology, Supervision, Visualization

Affiliation College of Public Health Sciences, Chulalongkorn University, a member of Thailand One Health University Network (THOHUN), Bangkok, Thailand

Roles Conceptualization, Investigation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

Affiliation Institute of Clinical Psychology, University of Karachi, Karachi, Pakistan

Affiliations Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America

Roles Formal analysis, Investigation, Methodology, Supervision, Validation

Affiliation DHQ Hospital Jhelum, Jhelum, Pakistan

Roles Formal analysis, Investigation, Methodology, Supervision

Affiliation Institute for Global Health Innovations, Duy Tan University, Da Nang, Vietnam

Roles Investigation, Methodology, Project administration, Supervision, Validation

Affiliation Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam

Roles Data curation, Investigation, Methodology, Project administration, Supervision, Validation

Roles Investigation, Methodology, Supervision, Validation

Affiliation Faculty of Medicine, Duy Tan University, Da Nang, Vietnam

Roles Data curation, Investigation, Methodology, Supervision, Validation

Affiliation Department of Psychology, University of Sistan and Baluchestan, Zahedan, Iran

Affiliation Center of Excellence in Evidence-based Medicine, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

Roles Data curation, Project administration, Validation

Affiliation Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

Roles Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Mood Disorders Psychopharmacology Unit, University Health Network, University of Toronto, Toronto, Canada

Roles Formal analysis, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Psychological Medicine, National University Health System, Singapore, Singapore

Roles Conceptualization, Formal analysis, Funding acquisition, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Institute for Health Innovation and Technology (iHealthtech), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

[ ... ],

Roles Conceptualization, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation Southeast Asia One Health University Network (SEAOHUN), Chiang Mai, Thailand

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Cuiyan Wang,
Michael Tee,
Ashley Edward Roy,
Mohammad A. Fardin,
Wandee Srichokchatchawan,
Hina A. Habib,
Bach X. Tran,
Shahzad Hussain,
Men T. Hoang,

Published: February 11, 2021
https://doi.org/10.1371/journal.pone.0246824
Reader Comments

The coronavirus disease (COVID-19) pandemic has impacted the economy, livelihood, and physical and mental well-being of people worldwide. This study aimed to compare the mental health status during the pandemic in the general population of seven middle income countries (MICs) in Asia (China, Iran, Malaysia, Pakistan, Philippines, Thailand, and Vietnam). All the countries used the Impact of Event Scale–Revised (IES-R) and Depression, Anxiety and Stress Scale (DASS-21) to measure mental health. There were 4479 Asians completed the questionnaire with demographic characteristics, physical symptoms and health service utilization, contact history, knowledge and concern, precautionary measure, and rated their mental health with the IES-R and DASS-21. Descriptive statistics, One-Way analysis of variance (ANOVA), and linear regression were used to identify protective and risk factors associated with mental health parameters. There were significant differences in IES-R and DASS-21 scores between 7 MICs (p<0.05). Thailand had all the highest scores of IES-R, DASS-21 stress, anxiety, and depression scores whereas Vietnam had all the lowest scores. The risk factors for adverse mental health during the COVID-19 pandemic include age <30 years, high education background, single and separated status, discrimination by other countries and contact with people with COVID-19 (p<0.05). The protective factors for mental health include male gender, staying with children or more than 6 people in the same household, employment, confidence in doctors, high perceived likelihood of survival, and spending less time on health information (p<0.05). This comparative study among 7 MICs enhanced the understanding of metal health in the general population during the COVID-19 pandemic.

Citation: Wang C, Tee M, Roy AE, Fardin MA, Srichokchatchawan W, Habib HA, et al. (2021) The impact of COVID-19 pandemic on physical and mental health of Asians: A study of seven middle-income countries in Asia. PLoS ONE 16(2): e0246824. https://doi.org/10.1371/journal.pone.0246824

Editor: Tauqeer Hussain Mallhi, Jouf University, Kingdom of Saudi Arabia, SAUDI ARABIA

Received: October 17, 2020; Accepted: January 27, 2021; Published: February 11, 2021

Copyright: © 2021 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This study has the following funding sources: 1. Author C.W, 1 grant, Huaibei Normal University, China. 2. Author R.H, 1 grant, National University of Singapore iHealthtech Other Operating Expenses (R-722-000-004-731) 3. Author B.X.T, 1 grant, Vingroup Innovation Foundation (VINIF) COVID research grant (VINIF.2020.Covid19.DA07) in Vietnam

Competing interests: The authors have declared that no competing interests exist.

Introduction

Emerging psychiatric conditions and mental well-being were identified as the tenth most frequent research topic during the COVID-19 pandemic [ 1 ]. A recent systematic review found that relatively high rates of symptoms of anxiety, depression, post-traumatic stress disorder and stress were reported in the general population and health care professionals during the COVID-19 pandemic globally [ 2 , 3 ]. Asia has a number of middle income countries (MICs) that face tremendous economic challenges and limited medical resources to maintain physical and mental well-being during the pandemic [ 4 ]. This extended to North America as well, with the sudden change in economic security during COVID-19 projected to increase suicide rates [ 5 ]. During the pandemic, the Asia Pacific Disaster Mental Health Network recommended to establish a mental health agenda for Asia [ 6 ]. It is therefore important to conduct research to assess psychiatric status of Asians living in MICs to develop capacity of various health systems to respond to COVID-19. Previous studies mainly focused on mental health of individual Asian countries during the pandemic without cross comparison [ 7 – 9 ].

With no prior comparative study found on physical and mental health of Asians living in MICs during the COVID-19 pandemic, this study aimed to investigate the impact of the pandemic on physical and mental health in 7 Asian MICs (China, Iran, Malaysia, Pakistan, Philippines, Thailand and Vietnam), identify differences among countries, understand their concerns and precautions toward COVID-19, as well as to identify protective and risk factors associated with mental health outcomes.

Methodology

Study design and study population.

This was a cross-sectional study that involved seven countries. The recruitment was conducted after COVID-19 became an epidemic in each country. To minimize risks of COVID-19 infection, a respondent-driven sampling strategy on recruiting the general public was utilized where new participants were electronically invited by existing study respondents rather than face-to-face interaction. The respondents completed the questionnaires through an online survey platform (‘SurveyStar’, Changsha Ranxing Science and Technology in China, SurveyMonkey in Philippines, and Google Forms in other countries).

Ethics approval

The study was approved by the Institutional Review Boards from each MIC, China (Huaibei Normal University of China, HBU-IRB-2020-001/002), Iran (Islamic Azad University, Protocol Number: IRB-2020-001), Malaysia (Universiti Malaysia Sarawak, UNIMAS/NC-21.02/03-02 Jld.4 (85)), Pakistan (University of Karachi Protocol Number: ICP-1 (101) 2698), Philippines (University of Philippines Manila Research Ethics Board, UPMREB 2020-198-01), Thailand (Chulalongkorn University, COA No. 147/2563), and Vietnam (Hanoi Medical University, QD 75/QD-YHDP&YHDP). All IRBs allowed participants aged 12 years to 17 years to participate in this study and provide their own consent because the online survey did not pose any risk to research participants. All respondents provided informed consent. Confidentiality was maintained because no personally identifiable information was collected.

Measures and instruments

The COVID-19 online questionnaire designed by the National University of Singapore [ 10 ] had five sections: demographic, physical symptoms related to COVID-19 in the past 14 days, knowledge and concerns about COVID-19, precautionary measures against COVID, and views of health information required. Psychometric properties of the questionnaire were established in the initial phase and peak of the COVID-19 epidemic [ 8 , 9 ].

The psychological impact of COVID-19 was measured using the well-validated Impact of Event Scale-Revised (IES-R) in the Asians for determining the extent of psychological impact after exposure to a traumatic event (i.e., the COVID-19 pandemic) within one week of exposure [ 11 – 14 ]. In this study, the Cronbach’s alpha for different versions of IES-R is very high in all countries and ranges from 0.912–0.950. Cronbach’s alpha of 0.70 or higher in measuring the internal consistency is considered “acceptable” in most social science research [ 15 ].

The mental health status of respondents was measured using the Depression, Anxiety and Stress Scale (DASS-21) [ 16 ], which has been used to assess mental health in Asians [ 17 , 18 ]. Furthermore, DASS-21 assessed three domains (i.e. anxiety, depression and stress) and its psychometric properties was validated across clinical and non-clinical samples in different cultures and languages during the COVID-19 pandemic [ 19 ]. In this study, the Cronbach’s alpha (internal consistency) for different versions of DASS-21 is as follows: stress scale ranges from 0.839–0.934, anxiety scale ranges from 0.784–0.914, and depression scale ranges from 0.878–0.943. The IES-R and DASS-21 scales were previously used in research related to the COVID-19 epidemic [ 8 , 12 , 20 , 21 ]. The DASS and IES-R questionnaires are available in the public domain, and so permission is not required to use these two questionnaires [ 22 , 23 ].

Statistical analysis

Descriptive statistics were calculated to compare demographic characteristics, physical symptoms and health service utilization, contact history, knowledge and concern, precautionary measure and additional health information variables among 7 MICs. One-Way analysis of variance (ANOVA) was calculated to compare the mean IES-R and DASS-21 scores between 7 MICs in order to determine whether the associated population mean IES-R or DASS-21 scores were significantly different. If there were significant differences among 7 MICs, the Least Significant Difference (LSD) would calculate the smallest significant between mean scores of two countries with different combinations. Any difference larger than the LSD is considered a significant result. We used linear regressions to calculate the univariate associations between independent and dependent variables including the IES-S score and DASS-21 stress, anxiety and depression subscale scores for all respondents separately. All tests were two-tailed, with a significance level of p <0.05. Statistical analysis was performed on IBM SPSS Statistics version 21.0.

A total of 4479 participants from 7 MICs in Asia completed the survey. The distribution of the number of participants by country is listed as follows: China (27%), Philippines (19%), Malaysia (16.2%), Iran (12.3%), Thailand (11.6%), Pakistan (11.3%), and Vietnam (2.7%). Fig 1 compares the IES-R and DASS-21 scores amongst all 7 MICs in Asia.

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https://doi.org/10.1371/journal.pone.0246824.g001

The top three countries with highest IES-R scores were Thailand (mean 42.35, SD 13.39), China (mean 32.98, SD 15.42), and Iran (mean 30.42, SD 15.82). The top three countries with highest DASS-21 stress scores were Thailand (mean 21.94, SD 7.74), Pakistan (mean 14.02, SD 11.53) and Philippines (mean 10.60, SD 8.01). The top three countries with highest DASS-21 anxiety scores were Thailand (mean 18.66, SD 5.98), Pakistan (mean 8.23, SD 9.69) and Malaysia (mean 7.80, SD 10.95). The top three countries with highest DASS-21 depression scores were Thailand (mean 19.74, SD 6.99), Pakistan (mean 11.33, SD 11.28) and Philippines (mean 9.72, SD 8.99).

Differences in IES-R scores and DASS-21 stress, anxiety, depression scores amongst the 7 MICs were all statistically significant (IES-R: F(6, 4472) = 144.47, p<0.001, η2 = 0.16; Stress: F(6,4472) = 167.49 p<0.001, η2 = 0.18; Anxiety: F (6,4471) = 172.03, p<0.001, η2 = 0.19; Depression: F(6, 4472) = 137.11, p<0.001, η2 = 0.16). Vietnam had the lowest scores of IES-R (mean 17.39, SD 13.72), stress (mean 3.80, SD 5.81), anxiety (mean 2.10, SD 4.91) and depression (mean 2.28, SD 5.43). The LSD analysis revealed that the scores of Vietnam were significantly lower than the other countries (p<0.05).

S1 Table compares the demographics of 7 MICs. More than half of participants were women in all countries (Range: 52.6% in Pakistan to 76.8% in Thailand). More than half of Chinese, Filipino, Iranian and Pakistani participants were below age of 31 years. Majority of Chinese, Vietnamese and Malaysian respondents were married while majority of Filipino and Thai respondents were single. Majority of Filipino, Iranian, Pakistani, Malaysian and Thai respondents did not have children. More than half of participants stayed in a household with more than 3–5 people across all countries except Pakistan (49%). Majority of respondents from Philippines, Pakistan, Vietnam and Malaysia were employed when the study was conducted.

Table 1 shows the association between demographic characteristics of all participants and mental health parameters. Demographic characteristics associated with lower psychological impact were male gender whereas age younger than 30 years and students were associated with higher psychological impact. Participants who have children were associated with lower stress, anxiety and depression whereas participants with higher education, single and separated status were associated with higher stress, anxiety and depression. Staying with 6 or more people and those who were employed were associated with lower anxiety and depression.

https://doi.org/10.1371/journal.pone.0246824.t001

S2 Table shows the frequency of physical symptoms that resemble COVID-19 infection and there were significant differences among all countries. During the COVID-19 pandemic, the most common physical symptoms reported by general population in the 7 countries were headache (23.13%), cough (21.86%) and sore throat (19.29%). About 8.13% of respondents consulted General Practitioner (GP); 2.69% were hospitalized; 3.89% were tested positive for COVID-19 and 57.1% had a health insurance. Pakistani had the significantly highest proportion of respondents consulted GP (27.5%), hospitalized (16.4%), receiving COVID-19 test (17.2%) and being isolated (17.8%). Table 2 shows the association between physical symptoms and mental health outcomes. The physical symptoms that were significantly associated with higher scores in all mental health outcomes (IES-R and DASS-21 subscales) including rhinitis and persistent fever with cough or breathing difficulties. Chills or rigors, headache and nausea or vomiting were associated with higher DASS-21 stress and anxiety scores. Myalgia, cough, dizziness and sore throat were associated with higher score of IES-R. Usage of medical services such as seeing a doctor, hospitalization, recent COVID-19 testing, quarantine, poor rating of health status that were significantly associated with higher scores in all mental health outcomes (IES-R and DASS-21 subscales). History of chronic illness were significantly associated with higher DASS-21 subscale scores. Having medical insurance coverage was associated with higher IES-R scores.

https://doi.org/10.1371/journal.pone.0246824.t002

S3 Table shows the belief of route of transmission among participants in 7 MICs and there were significant differences among all countries. Out of all participants, there were a small number of participants who did not agree with transmission of COVID-19 being via droplets (10.34%) and contaminated objects (17.21%). It is interesting to note that China (60.5%) and Vietnam (59.8%) demonstrated significantly higher percentage of participants who believed in airborne transmission compared to .64.76% of participants from the other five countries who did not agree that COVID-19 was airborne transmitted.

Participants expressing confident and very confident in their doctors diagnosing COVID-19 were very high in Malaysia (93.8%) and China (92.9%); level of confidence was much lower in Iran (65.5%) and Pakistan (62.6%). About 50.26% of participants reported that they were likely and very likely to contract COVID-19, with Malaysian participants demonstrating the highest perceived risk of COVID-19 (72.8%) whilst the Filipino demonstrated the highest proportion of participants believing that they would not contract COVID-19 (53.2%). About 89.8% of Thai participants believed that they would survive if contracted with COVID-19 while the Pakistani had the highest proportion who believed that they would not survive COVID-19 (15.4%). About 78.43% of participants were satisfied with health information related to COVID-19; Vietnamese participants reported the highest proportion of satisfaction (97.5%). About 77.38% of participants were worried their family members contracting COVID-19. Pakistani participants reported the highest proportion of people who faced discrimination (42.7%). About 44.68% of participants spent more than 2 hours per day to view information on COVID-19 with Filipino participants having the highest proportion for spending more than 2 hours per day to view information (47.2%).

Table 3 shows the association between knowledge and concerns related to COVID-19 and mental health parameters. Agreement with airborne, contact with contaminated objects and droplet transmission was associated with higher DASS-21 in all subscales. Likelihood of contracting COVID-19, discrimination against by other countries and contact with people infected with COVID-19 were associated with higher IES-R or DASS-21 scores. Confidence in one’s own doctor diagnosing COVID-19, high likelihood of survival if infected with COVID-19 and spent less than two hours per day to monitor information relating to COVID-19 were associated with lower level of IES-R or DASS-21 scores.

https://doi.org/10.1371/journal.pone.0246824.t003

S4 Table shows the prevalence of precautionary measures and there were significant differences among 7 MICs (p<0.001). High percentages were reported by participants covering their mouth and nose after sneezing (98.0%), avoided sharing utensils (90.8%), practised hand hygiene (98.9%), washed hand after touching contaminated objects (96.2%), and wear face masks (93.5%). All Vietnamese participants (100%) responded wearing a face mask. About 68% of respondents felt that people were too worried about COVID-19 with Malaysia (90.5%), Thailand (90.5%) and Pakistan (86.6%) as the top three countries. Approximately 53% of respondents spent 20–24 hours per day at home; with China (84.7%), Iran (73.5%) and Philippines (55%) as the top three countries.

Table 4 shows the association between precautionary measures related to COVID-19 and mental health parameters. Avoidance of sharing cutlery dealing meals was associated with higher anxiety and depression. In contrast, hand hygiene practice was associated with lower IES-R and DASS-21 in all subscales. Wearing a face mask was associated with lower levels of stress and depression. Worries about COVID-19 was associated with significantly higher levels of DASS-21 in all subscales. Shorter duration of homestay was associated with higher levels of anxiety, depression and stress as compared to those who stayed at home for 20–24 hours per day.

https://doi.org/10.1371/journal.pone.0246824.t004

S5 Table compares the health information needs of participants from 7 MICs and there were significant differences among 7 MICs. The Chinese had the highest proportion who wanted to understand the symptoms of COVID-19 (91.6%), the prevention method (93.7%), effectiveness of drugs and vaccines (94.1%), number of infected cases and location (95.9%), travel advice (96.9%), mode of transmission (94.5%), required regular information update (92.7%) and personalized information (96.8%). The Iranians had the highest proportion who sought advices regarding treatment methods (90.4%) and Malaysians had the highest proportion who wanted to understand local outbreaks (94.2%).

Table 5 shows the association between health information needs about COVID-19 and mental health parameters. Most additional information including information on COVID-19 symptoms, prevention, treatment advice, needs for regular updates, knowledge on local transmission, effectiveness on drugs and vaccines, number of infected people based on geographical locations, travel advice and transmission mode of COVID were associated with higher IES-R scores. In contrast, the need for more personalized information, information on the effectiveness of drugs and vaccines, travel advices, transmission mode were associated with significantly lower level of depression.

https://doi.org/10.1371/journal.pone.0246824.t005

The main findings of this first multinational population-based study in MICs in Asia during the COVID-19 pandemic are summarized as follows. First, Thai respondents reported the highest levels of IES-R and DASS-21 scores. Second, Pakistani respondents reported the second highest levels of DASS-21 scores. Comparatively, Vietnamese respondents reported the lowest levels in DASS-21 scores. Third, Iranian respondents demonstrated the lowest confidence in their doctors whilst Pakistani respondents had the highest proportion who believed they would not survive COVID-19 and reported discrimination.

Assessing COVID-19’s association with respondents’ mental health, the three most common physical symptoms associated with adverse mental health were headache, cough and sore throat. Risk factors associated with adverse mental health during the COVID-19 pandemic include age <30 years old, high education background, single and separated status, discrimination by other countries, contact with people with COVID-19 and worries about COVID-19. Protective factors for mental health during the COVID-19 pandemic include male gender, staying with children, staying with 6 or more people, employment, confidence in own’s doctors diagnosing COVID-19, high perceived likelihood of surviving COVID-19, spending less time on health information, hand hygiene practice and wearing a face mask. Importantly, these findings will be significantly helpful for healthcare administrators in Asia at the national and local community levels [ 24 ] when preparing for the next wave of COVID-19 outbreak and future pandemics [ 25 ].

Iran had the highest total reported COVID cases (386,658) and number of COVID cases per 1 million people (4,593), as well as the highest number of deaths from COVID (22,293) and deaths per 1 million people (265) [ 26 ]. Pakistan had the second highest number of cases (298,509) and deaths (6,342) [ 26 ]. Of the 7 MICs, Vietnam had the lowest total numbers and rates across all seven countries, with 1,049 reported cases, 35 deaths and rates of just 11 cases and 0.4 deaths per 1 million [ 26 ]. As a result, Vietnamese respondents reported the lowest IES-R and DASS-21 scores. Vietnam has adopted several strategies to combat COVID-19 including development of the action plan and response strategies to optimize the utilization of human resources and equipment [ 24 ]; address the health information needs based on the diverse socioeconomic, demographic, and ethnic factors [ 27 ]; re-design communication activities for a more effective dissemination of information related to the epidemic [ 28 ]; safeguarding the health of workforce [ 29 ] to ensure minimal impact on economy and involvement of the grassroot system and village health collaborators to combat pandemics [ 30 , 31 ].

Thailand recorded the second lowest number of total cases (3,444) and deaths (58), and similarly the second lowest case rates (49) and death rates (0.8) per 1 million [ 26 ]. Surprisingly, we found that Thailand was the country with the highest IES-R and DASS-21 depression scores. This could be due to the impact of COVID-19 on the economy in Thailand. Among all MICs in Asia, the disruption on COVID-19 pandemic is the most severe on Thailand economy, due to its reliance on tourism as compared to other MICs. For 2020, the International Monetary Fund has predicted Thailand’s GDP to be reduced by 6.7 percent which is highest among Asian countries [ 32 ]. Pakistan ranked second in terms of DASS-21 scores and number of COVID cases and deaths. The congruence between psychological parameters and epidemiology of COVID-19 in Pakistan was due to poor sanitation, lack of basic preventive measures, lack of proper testing and medical facilities. Pakistani health professionals started protesting and threatened to quit work due to lack of Personal Protective Equipment (PPE) [ 33 ]. Currently, the vaccination coverage in rural Pakistan remains unsatisfactory amid various barriers including price, hesitancy, and low level of awareness [ 34 ]. Eid-ul-Adha is an annual religious festival that could not be cancelled due to religious obligations and led to a sharp spike in COVID-19 cases [ 35 ]. The unpreparedness and contradictory policies resulted in an alarming high rate of COVID-19 spread and worsening mental health and discrimination faced by Pakistani people. Iranian respondents demonstrated lowest confidence in their doctors. The economic sanctions that prevented medical supplies, equipment and drugs from arriving in Iran could lead to low confidence among Iranians [ 36 ].

This study highlighted unique protective factors for mental health in MICs of Asia. In this study, more than 90% of respondents agreed to wear masks to prevent COVID-19. During the initial stage of COVID-19 pandemic, medical and public health experts from the US and some European countries believed that there was no direct evidence of airborne transmission of COVID-19 [ 37 ]. In contrast, respiratory clinicians and public health experts from Asia argued that lack of evidence does not equate to evidence of ineffectiveness of face masks [ 38 ]. The use of face masks by Asians have played an important role in controlling the spread of COVID-19 [ 39 ]. This study showed the association between the use of face mask and lower DASS-21 anxiety and depression scores. This finding might support the postulation that wearing face mask could offer psychological benefits, such as feeling less vulnerable to infection via perceived control [ 37 ]. Staying with children and more than 6 people in the same household were protective factors due to the values of family support among Asians. Compared with western countries, family support has a greater influence on reducing the risk of adverse mental health in Asia [ 10 ].

The findings of this first multinational study have several implications for health and government policies. Firstly, the health authorities should offer psychological interventions to the general population who are at higher risk of developing adverse mental health including women, people younger than 30 years and single and separated status. High education background is a risk factor and online psychological interventions such as cognitive behaviour therapy (CBT) and mindfulness-based therapy could improve mental health for highly educated individual [ 40 ]. For countries with high IES-R scores (Thailand, China and Iran), online trauma-focused CBT that promotes trauma narration, problem solving related to problems associated with COVID-19 and home based relaxation could be helpful in reducing psychological impact [ 9 ]. Second, as physical symptoms resembling COVID-19 infection (e.g., rhinitis, persistent fever with cough, breathing difficulties) were associated with high IES-R and DASS-21 scores groups. There is an urgent need to develop accurate, rapid diagnostic tests in general practitioners’ clinics, community and rural settings [ 31 ]. A negative COVID-19 test result may alleviate anxiety, depression, stress and psychological impact. Enhancing the capacity of health system to combat COVID-19 may increase the confidence of public and improve mental health. Third, based on our findings, the WHO, governments and health authorities should provide regular updates on the effectiveness of vaccines and treatment methods. Mis-information related to the cause of COVID-19 [ 41 ], rumours [ 42 ] and inconsistent information [ 43 ] on COVID-19 symptoms, prevention, treatment and transmission mode were associated with negative psychological impact. Local governments, news agencies, professional and advocacy organisations should all provide health information and advices related to COVID-19 that are consistent with national guidelines and avoid mis-information [ 44 ]. It is important to identify group-specific demands would be helpful to provide proper information related to COVID-19 to fulfil the need of different population groups [ 27 ]. Various governments should offer relief packages to safeguard employment and economy to protect mental health. Additionally, the level of policy stringency in response to COVID-19 or pandemics, as measured by the Oxford Stringency Index, may influence mental health and should be moderated accordingly by respective governments [ 45 ].

This study has several limitations. First, the findings of this study were based on seven MICs in Asia and could not be generated to other countries. The study population had different sociodemographic characteristics as compared to the general population in the world due to sampling bias because only participants with Internet access could participate in this online survey. The respondent sampling method also compromised the representativeness of samples. The study population was female predominant (proportion of female in the study population: 67.76%; world population 49.58%) [ 46 ] and a high proportion of the study population possessed a university degree (85.6%). Thus, there is a potential risk of sampling bias because we could not reach out to potential respondents without Internet access. The second limitation was the cross-sectional nature of this study and inability to demonstrate cause and effect relationship. The third limitation was that we did not record demographic data regarding pre-existing mental illness of the study participants. The fourth limitation is that self-reported levels of psychological impact, anxiety, depression and stress may not always be aligned with objective assessment by mental health professionals. Nevertheless, psychological impact, anxiety, depression and stress are based on personal feelings, and self-reporting was paramount during the COVID-19 pandemic. The fifth limitation is that we did not study other aspects of the pandemic such as the potential threat of self-medication of hydroxychloroquine and cholorquine [ 47 ] and precautionary measures of walkthrough sanitization gates [ 48 ]. Lastly, we were unable to calculate the response rate. For potential respondents who were not keen to participate in the online survey, no response was recorded, and we could not collect any information from them.

Conclusions

In conclusion, this multi-national study across 7 MICs in Asia showed that Thai reported the highest mean IES-R and DASS-21 anxiety, depression and stress scores. In contrast, Vietnamese reported the lowest mean scores in IES-R and DASS-21 anxiety, depression and stress scales. The risk factors for adverse mental health include age < 30 years, high education background, single and separated status, discrimination by other countries, contact with people with COVID-19 and worries about COVID-19. The protective factors for mental health include male gender, staying with children, staying with 6 or more people, employment, confidence in own’s doctors diagnosing COVID-19, high perceived likelihood of surviving COVID-19, spending less time on health information, hand hygiene practice and wearing a face mask.

Supporting information

S1 table. comparison of demographics of the participants from seven countries..

https://doi.org/10.1371/journal.pone.0246824.s001

S2 Table. Physical symptoms resembling COVID-19 infection reported by the participants from seven countries.

https://doi.org/10.1371/journal.pone.0246824.s002

S3 Table. Comparison of knowledge related to COVID-19 in participants of the seven countries.

https://doi.org/10.1371/journal.pone.0246824.s003

S4 Table. Comparison of precautionary measures related to COVID-19 in the participants of the seven countries.

https://doi.org/10.1371/journal.pone.0246824.s004

S5 Table. Comparison of information needs about COVID-19 in the participants of the seven Asian countries.

https://doi.org/10.1371/journal.pone.0246824.s005

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Home > Honors College > Honors Theses > 1912

Honors Theses

An analysis of the effects of covid-19 on students at the university of mississippi: family, careers, mental health.

Hannah Newbold Follow

Date of Award

Spring 5-1-2021

Document Type

Undergraduate Thesis

Integrated Marketing Communication

First Advisor

Second advisor.

Cynthia Joyce

Third Advisor

Marquita Smith

Relational Format

Dissertation/Thesis

This study analyzes the effects of COVID-19 on students at the University of Mississippi. For students, COVID-19 changed the landscape of education, with classes and jobs going online. Students who graduated in May 2020 entered a poor job market and many ended up going to graduate school instead of finding a job. Access to medical and professional help was limited at the very beginning, with offices not taking patients or moving appointments to virtual only. This would require that each student needing help had to have access to quality internet service, which wasn’t always guaranteed, thus producing additional challenges.

These chapters, including a robust literature review of relevant sources, as well as a personal essay, consist further of interviews with students and mental health counselors conducted over the span of several months. These interviews were conducted and recorded over Zoom. The interviews were conducted with individuals who traveled in similar social circles as me. These previously existing relationships allowed the conversation to go deeper than before and allowed new levels of relationship. Emerging from these conversations were six overlapping themes: the importance of family, the need for health over career, the challenge of isolation, struggles with virtual education, assessing mental health, and facing the reality of a bright future not promised. Their revelations of deep academic challenges and fears about the future amid stories of devastating personal loss, produces a striking and complex picture of emerging strength.

Recommended Citation

Newbold, Hannah, "An Analysis Of The Effects Of COVID-19 On Students At The University of Mississippi: Family, Careers, Mental Health" (2021). Honors Theses . 1912. https://egrove.olemiss.edu/hon_thesis/1912

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Frontiers in Psychology
Personality and Social Psychology
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Coronavirus Disease (COVID-19): The Impact and Role of Mass Media During the Pandemic

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The outbreak of coronavirus disease 2019 (COVID-19) has created a global health crisis that has had a deep impact on the way we perceive our world and our everyday lives. Not only the rate of contagion and patterns of transmission threatens our sense of agency, but the safety measures put in place to contain ...

Keywords : COVID-19, coronavirus disease, mass media, health communication, prevention, intervention, social behavioral changes

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v.29(9); 2021 Sep 1

A comprehensive analysis of the efficacy and safety of COVID-19 vaccines

Changjing cai.

1 Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China

2 Key Laboratory for Molecular Radiation Oncology of Hunan Province, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China

Yinghui Peng

Edward shen.

3 Department of Life Science, McMaster University, Hamilton, ON L8S 4L8, Canada

Qiaoqiao Huang

Yihong chen, ziyang feng, xiangyang zhang.

5 Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA

4 National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, P.R. China

Associated Data

The numbers of cases and deaths from coronavirus disease 2019 (COVID-19) are continuously increasing. Many people are concerned about the efficacy and safety of the COVID-19 vaccines. We performed a comprehensive analysis of the published trials of COVID-19 vaccines and the real-world data from the Vaccine Adverse Event Reporting System. Globally, our research found that the efficacy of all vaccines exceeded 70%, and RNA-based vaccines had the highest efficacy of 94.29%; moreover, Black or African American people, young people, and males may experience greater vaccine efficacy. The spectrum of vaccine-related adverse drug reactions (ADRs) is extremely broad, and the most frequent ADRs are pain, fatigue, and headache. Most ADRs are tolerable and are mainly grade 1 or 2 in severity. Some severe ADRs have been identified (thromboembolic events, 21–75 cases per million doses; myocarditis/pericarditis, 2–3 cases per million doses). In summary, vaccines are a powerful tool that can be used to control the COVID-19 pandemic, with high efficacy and tolerable ADRs. In addition, the spectrum of ADRs associated with the vaccines is broad, and most of the reactions appear within a week, although some may be delayed. Therefore, ADRs after vaccination need to be identified and addressed in a timely manner.

Graphical abstract

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Object name is fx1.jpg

The numbers of cases and deaths from COVID-19 are continuously increasing. Cai et al. are the first to comprehensively analyze the efficacy of the existing COVID-19 vaccines and the incidence, spectrum, timing, and clinical features of adverse reactions associated with the COVID-19 vaccines, which can provide reference for general public.

Introduction

As of April 5, 2021, there were more than 131 million confirmed cases and more than 2.8 million deaths due to coronavirus disease 2019 (COVID-19) worldwide. 1 COVID-19 has posed a serious threat to public health worldwide. There is no cure for COVID-19, and only vaccines can stop the spread of the COVID-19 pandemic. According to the World Health Organization (WHO), as of April 5, 2021, 184 vaccines were being evaluated in the preclinical development stage, 85 were in the clinical evaluation stage, and some had partially passed through phase III clinical trials. 2 Vaccination against COVID-19 has now started in 161 locations, covering 91% of the global population. 3 However, the vaccination rates are still low; as of April 5, 2021, the highest rate of full vaccination was 56.2% in Israel, while those in other countries were all lower than 20%, and those in some countries were 0%. 4 A previous study pointed out that 53%–84% of the population needs to be vaccinated against COVID-19 to achieve herd immunity. 5 However, as various mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported, herd immunity is becoming more and more unrealistic, unless a vaccine to protect against different variants of SARS-CoV-2 can be developed. Other than protection, vaccination can reduce the severity of COVID-19 infection and be life saving. One of the key reasons for the low vaccination rate is that many people are concerned about the safety and efficacy of the COVID-19 vaccines.

However, no reports have addressed this issue satisfactorily. It is important to perform an analysis of the safety and efficacy of the COVID-19 vaccines. Therefore, we performed a comprehensive analysis to determine the incidence, spectrum, timing, and clinical features of adverse drug reactions (ADRs) and the efficacy of the COVID-19 vaccines.

First, we performed a meta-analysis of the published trials of the COVID-19 vaccines. Furthermore, we retrospectively obtained real-world data from the Vaccine Adverse Event Reporting System (VAERS), which is comanaged by the Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA) of the United States of America. 6 In our research, we provided a complete overview of the COVID-19 vaccines in terms of the incidence, spectrum, timing, and clinical features of ADRs and efficacy. We do hope this study will provide a guideline for clinicians managing ADRs associated with the COVID-19 vaccines and increase the confidence of the general public in the COVID-19 vaccines.

Efficacy of COVID-19 vaccines

To estimate the efficacy of the COVID-19 vaccines, we evaluated all the COVID-19 vaccine data that have been published from phase III clinical trials; a total of 194,015 cases were included. The overall efficacy was highly heterogeneous (>90%); therefore, we performed subgroup analyses with stratification by vaccine type, sex, and age, which effectively reduced the heterogeneity. The analysis of different types of vaccines showed that the efficacy of inactivated vaccines was 73.11% (95% confidence interval [CI], 34.23; 89.03), the efficacy of protein subunit vaccines was 89.33% (95% CI, 81.44; 93.10), and the efficacy of RNA-based vaccines was 94.29% (95% CI, 93.65; 95.40). The efficacy of the viral vector (non-replicating) vaccines was 79.56% (95% CI, 60.00; 89.92; Table1 ; Figure S2 ; Table S1 ).

The efficacy of COVID-19 vaccines

Group	The incidence of COVID-19 infection		Vaccine efficacy (95% CI)
Group	Vaccine group (95% CI)	Placebo group (95% CI)	VE = 100∗(1–RR) %


Inactivated vaccine (n = 5,705 versus 5,440)	0.0096 (0.0034– 0.0269)	0.0357 (0.0310– 0.0409)	73.11% (34.23–89.03)
Protein subunit (n = 7,500 versus 7,500)	0.0008 (0.0004– 0.0018)	0.0075 (0.0058– 0.0097)	89.33% (81.44–93.10)
RNA-based vaccine (n = 48,578 versus 48,732)	0.0006 (0.0004– 0.0008)	0.0105 (0.0087– 0.0126)	94.29% (93.65–95.40)
Viral vector (non-replicating; n = 40,285 versus 30,275)	0.0037 (0.0013– 0.0102)	0.0181 (0.0129– 0.0255)	79.56% (60.00–89.92)



Male (n = 36,245 versus 30,071)	0.0010 (0.0003– 0.0038)	0.0137 (0.0094- 0.0200)	92.70% (81.00–96.81)
Female (n = 29,774 versus 25,955)	0.0018 (0.0006– 0.0054)	0.0148 (0.0098– 0.0223)	87.84% (75.78–93.88)



16 to 55 years old (n = 47,958 versus 39,139)	0.0018 (0.0006– 0.0055)	0.0162 (0.0117– 0.0224)	88.89% (75.45–94.87)
Over 55 years old (n = 19,458 versus 18,390)	0.0013 (0.0005– 0.0038)	0.0105 (0.0067– 0.0164)	87.62% (76.83–92.54)



Black or African American (n = 9,952 versus 9,979)	0.0005 (0.0000– 0.0138)	0.0108 (0.0043– 0.0265)	95.37% (47.92–100.00)
White (n = 35,650 versus 35,719)	0.0016 (0.0004– 0.0063)	0.0157 (0.0104– 0.0234)	89.81% (73.08–96.15)

Since inactivated vaccines and protein subunit vaccines lacked subgroup data, including age and sex, only RNA-based vaccines and viral vector (non-replicating) vaccines were included in the subsequent subgroup analyses. Vaccine efficacy (VE) among male and female participants was 92.70% (95% CI, 81.00; 96.81) and 87.84% (95% CI, 75.78; 93.88), respectively. At the same time, the efficacy of vaccine among 16 to 55 years old recipients was 88.89% (95% CI, 75.45; 94.87) and that among those over 55 years old was 87.62% (95% CI, 76.83; 92.54). Only RNA-based vaccines and viral vector (non-replicating) vaccines provided the data of different races. In the subgroup analysis, VE among Black or African American and White participants was 95.37% (95% CI, 47.92; 100.00) and 89.81% (95% CI, 73.08; 96.15), respectively. We found that all vaccines achieved good efficacy, among which RNA-based vaccines had the highest, whereas inactivated vaccines had the lowest, although they were more than 70% effective. In addition, Black or African American people, males, and the 16- to-55-year-old subgroup experienced greater VE ( Table 1 ; Figure S2 ; Table S1 ).

Incidence of ADRs related to the COVID-19 vaccines

Safety is another important factor when considering vaccines. Therefore, we first performed a meta-analysis of the clinical trial data and then collected real-world data from the VAERS maintained by the CDC in the United States. In the clinical trials analysis, we evaluated a total of 6 phase III clinical trials and 6 phase I/II clinical trials and official reports of phase III results of COVID-19 vaccines, and 56,310 cases were included. Meanwhile, the data of 86,506,742 doses from 5 reports about the thromboembolic events were included, while 603,862,888 doses from 3 reports about the myocarditis/pericarditis events were included. In the real-world analysis, we included 11,936 participants. The results are as follows.

Incidence of ADRs in the meta-analysis of clinical trials

We observed 36 types of ADRs in the clinical trials, among which 8 were observed after vaccination with more than 50% of the vaccines ( Table S2 ), including pain, swelling, fever, fatigue, chills, muscle pain (myalgia), joint pain (arthralgia), and headache. We further conducted a meta-analysis of these 8 ADRs. Similarly, to minimize heterogeneity, we performed subgroup analyses stratified by dose, vaccine type, and age.

Since inactivated vaccines lacked ADRs data of dose 1, only RNA-based vaccines, viral vector (non-replicating) vaccines, and protein subunit vaccines were included in the analyses. The results showed that the most frequently reported ADR was pain (at the injection site) after dose 1 in protein subunit vaccines (38.46%) and RNA-based vaccines (80.97%). Pain was reported more frequently in younger vaccine recipients (16 to 55 years old) than in older vaccine recipients (over 55 years old; 80.00% versus 59.35%). Fatigue was the second most frequent ADR after dose 1 (30.77% of those receiving the protein subunit vaccines and 39.27% of those receiving the RNA-based vaccines). The incidence in the 16- to 55-year-old subgroup was significantly higher than that in the over 55-year-old subgroup (52.72% versus 33.73%). The incidences of other ADRs were below 50%. Headache ranked third, followed by muscle pain (myalgia), joint pain (arthralgia), chills, swelling, and fever. The incidence of ADRs after vaccination with RNA-based vaccines was high, and further analysis of age subgroups indicated that the results were generally consistent with those observed in the overall analysis. Meanwhile, unlike the two vaccines above, in viral vector (non-replicating) vaccines, the most frequently reported ADR was fatigue (56.25%). Headache ranked second, followed by pain, muscle pain (myalgia), joint pain (arthralgia), chills, fever, and swelling ( Table 2 ; Figures S3–S5 ; Table S2 ).

The incidence of ADRs associated with COVID-19 vaccines via meta-analysis

Group	Pain	Swelling	Fever	Fatigue	Chills	Muscle pain (myalgia)	Joint pain (arthralgia)	Headache


Protein subunit (n = 26)	0.3846 (0.2210–0.5793)	0.0000 (0.0000–1.0000)	0.0000 (0.0000–1.0000)	0.3077 (0.1620–0.5055)	0.0000 (0.0000–1.0000)	0.2308 (0.1075–0.4276)	0.0385 (0.0054–0.2279)	0.2308 (0.1075–0.4276)
RNA-based vaccine (n = 23,351)	0.8097 (0.7667–0.8463)	0.0624 (0.0594–0.0656)	0.0145 (0.0059–0.0350)	0.3927 (0.3630–0.4233)	0.0936 (0.0785–0.1112)	0.2029 (0.1726–0.2370)	0.1303 (0.0920–0.1813)	0.3366 (0.3218–0.3517)
Viral vector (non-replicating; n = 128)	0.4141 (0.3321–0.5011)	0.0156 (0.0039–0.0603)	0.0938 (0.0540–0.1578)	0.5625 (0.4755–0.6458)	0.1719 (0.1159–0.2473)	0.3594 (0.2811–0.4460)	0.2188 (0.1555–0.2986)	0.5234 (0.4371–0.6084)



16 to 55 years old (n = 16,177)	0.8000 (0.6778–0.8838)	0.0649 (0.0612–0.0688)	0.0458 (0.0094–0.1949)	0.5272 (0.3499–0.6979)	0.1615 (0.0842–0.2875)	0.2984 (0.1765–0.4578)	0.1733 (0.1043–0.2739)	0.4549 (0.3267–0.5892)
Over 55 years old (n = 7,302)	0.5935 (0.3553–0.7945)	0.0525 (0.0374–0.0731)	0.0049 (0.0019–0.0123)	0.3373 (0.3265–0.3482)	0.0568 (0.0518–0.0624)	0.1805 (0.1388–0.2313)	0.1275 (0.0897–0.1782)	0.2919 (0.2130–0.3857)



Protein subunit	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
(n = 26)	(0.0000– 1.0000)	(0.0000– 1.0000)	(0.0000– 1.0000)	(0.0000–1.0000)	(0.0000–1.0000)	(0.0000–1.0000)	(0.0000–1.0000)	(0.0000–1.0000)
RNA-based vaccine	0.0138	0.0065	0.0022	0.0104	0.0030	0.0064	0.0048	0.0142
(n = 23,351)	(0.0052– 0.0361)	(0.0049–0.0086)	(0.0007– 0.0063)	(0.0092– 0.0118)	(0.0012– 0.0074)	(0.0054–0.0075)	(0.0037–0.0062)	(0.0101–0.0199)
Viral vector (non-replicating)	0.0000	0.0000	0.0078	0.0313	0.0234	0.0156	0.0078	0.0156
(n = 128)	(0.0000– 1.0000)	(0.0000–1.0000)	(0.0011–0.0533)	(0.0118– 0.0803)	(0.0076–0.0701)	(0.0039–0.0603)	(0.0011–0.0533)	(0.0039–0.0603)



16 to 55 years old (n = 16,128)	0.8507 (0.8219–0.8755)	0.0647 (0.0596–0.0702)	0.0193 (0.0069–0.0528)	0.4263 (0.3682–0.4865)	0.1137 (0.0847–0.1510)	0.2239 (0.2060–0.2429)	0.1358 (0.1014–0.1796)	0.3857 (0.3406–0.4328)
Over 55 years old (n = 7,223)	0.7250 (0.704–0.7451)	0.0555 (0.0401–0.0765)	0.0053 (0.0021–0.0135)	0.3361 (0.3253–0.3471)	0.0568 (0.0517–0.0623)	0.1669 (0.1310–0.2103)	0.1224 (0.0796–0.1836)	0.2473 (0.2375–0.2573)



Inactivated vaccine (n = 6,286)	0.3175 (0.0781–0.7188)	0.0576 (0.0521–0.0636)	0.0060 (0.0007–0.0515)	0.0533 (0.0072–0.3041)	0.0161 (0.0008–0.2528)	0.0152 (0.0002–0.5744)	0.0156 (0.0006–0.2925)	0.0778 (0.0050–0.5877)
Protein subunit (n = 26)	0.5769 (0.3851–0.7480)	0.0385 (0.0054–0.2279)	0.0000 (0.0000–1.0000)	0.4615 (0.2839–0.6495)	0.0000 (0.0000–1.0000)	0.4615 (0.2839–0.6495)	0.2692 (0.1341–0.4671)	0.4615 (0.2839–0.6495)
RNA-based vaccine (n = 22,860)	0.8176 (0.6887–0.9009)	0.0890 (0.0565–0.1374)	0.1473 (0.1364–0.1590)	0.6057 (0.5369–0.6705)	0.3677 (0.2750–0.4713)	0.4553 (0.2945–0.6260)	0.3069 (0.1760–0.4785)	0.5260 (0.4418–0.6088)
Viral vector (non-replicating; n = 3,633)	0.4475 (0.3455–0.5540)	0.0534 (0.0465–0.0612)	0.1796 (0.0007–0.9846)	0.3922 (0.3765–0.4082)	0.0020 (0.0000–0.2194)	0.2622 (0.1949–0.3429)	0.0197 (0.0005–0.4453)	0.3473 (0.2742–0.4283)



16 to 55 years old (n = 17,988)	0.7240 (0.5312–0.8586)	0.0699 (0.0413–0.1158)	0.1160 (0.0499–0.2471)	0.5681 (0.4737–0.6577)	0.0440 (0.0008–0.7399)	0.4368 (0.3307–0.5490)	0.0295 (0.0006–0.6011)	0.4901 (0.3842–0.5969)
Over 55 years old (n = 8,356)	0.5106 (0.2473–0.7682)	0.0528 (0.0279–0.0975)	0.0478 (0.0167–0.1291)	0.4367 (0.3235–0.5569)	0.0291 (0.0010–0.4605)	0.2992 (0.2108–0.4055)	0.0396 (0.0014–0.5424)	0.3600 (0.2885–0.4384)



Inactivated virus	0.0000	0.0000	0.0000	0.0000	0.0001	0.0000	0.0001	0.0000
(n = 6,202)	(0.0000–1.0000)	(0.0000–1.0000)	(0.0000– 1.0000)	(0.0000–1.0000)	(0.0000– 0.0013)	(0.0000–1.0000)	(0.0000– 0.0013)	(0.0000– 1.0000)
Protein subunit	0.0000	0.0000	0.0000	0.0385	0.0189	0.0385	0.0385	0.0000
(n = 26)	(0.0000– 1.0000)	(0.0000–1.0000)	(0.0000–1.0000)	(0.0054– 0.2279)	(0.0012–0.2938)	(0.0054–0.2279)	(0.0056–0.2628)	(0.0000– 1.0000)
RNA-based vaccine	0.0212	0.0072	0.0135	0.0634	0.0164	0.0425	0.0245	0.0344
(n = 22,860)	(0.0083–0.0533)	(0.0021– 0.0248)	(0.0117– 0.0156)	(0.0343– 0.1145)	(0.0104–0.0258)	(0.0144– 0.1188)	(0.0055– 0.1097)	(0.0235– 0.0501)
Viral vector (non-replicating)	0.0031	0.0017	0.0023	0.0103	0.0024	0.0094	0.0024	0.0071
(n = 3,504)	(0.0017–0.0057)	(0.0008– 0.0038)	(0.0011–0.0046)	(0.0074– 0.0142)	(0.0001–0.0452)	(0.0067–0.0132)	(0.0001– 0.0452)	(0.0048– 0.0105)



16 to 55 years old (n = 15,707)	0.8488 (0.7482–0.9138)	0.0879 (0.0517–0.1454)	0.1681 (0.1588–0.1778)	0.6346 (0.5728–0.6922)	0.4168 (0.3259–0.5136)	0.4928 (0.3261–0.6611)	0.3267 (0.1863–0.5069)	0.5751 (0.4988–0.6480)
Over 55 years old (n = 7,153)	0.7557 (0.6183–0.8553)	0.0874 (0.0642–0.1179)	0.1050 (0.0981–0.1123)	0.5467 (0.4958–0.5967)	0.2678 (0.2166–0.3261)	0.3763 (0.2602–0.5087)	0.2622 (0.1667–0.3870)	0.4255 (0.3768–0.4757)



16 to 55 years old	0.5831	0.0299	0.0257	0.4419	0.0010	0.3906	0.0008	0.4445
(n = 2,281)	(0.5627–0.6032)	(0.0019–0.3302)	(0.0006– 0.5449)	(0.4216– 0.4624)	(0.0000– 0.9134)	(0.3708–0.4108)	(0.0000–0.6305)	(0.4243– 0.4650)
over 55 years old	0.2736	0.0266	0.0291	0.3009	0.0013	0.2377	0.0017	0.3026
(n = 1,203)	(0.1816– 0.3898)	(0.0189– 0.0374)	(0.0210– 0.0403)	(0.2756– 0.3274)	(0.0000– 0.3578)	(0.2145– 0.2626)	(0.0000– 0.8062)	(0.2773– 0.3291)

Among participants who received dose 2, the overall incidence of ADRs was higher than that after dose 1. As observed for dose 1, pain was the most frequent ADR. The incidences of pain in patients administered different types of vaccines were as follows: inactivated vaccines (31.75%), protein subunit vaccines (57.69%), RNA-based vaccines (81.76%), and viral vector (non-replicating) vaccines (44.75%). The incidences of pain in different age groups were as follows: 16 to 55 years old (72.40%) and over 55 years old (51.06%). The incidences of ADRs other than pain differed among the various types of vaccines. In particular, the incidence of ADRs was lowest for inactivated vaccines, with incidences of all ADRs less than 10%. In descending order of frequency, the ADRs were headache, swelling, fatigue, chills, joint pain (arthralgia), muscle pain (myalgia), and fever. The ADRs associated with the other three types of vaccines were similar to those after dose 1, with fatigue and headache ranking second and third, respectively. However, more than 50% of recipients experienced headache after dose 2, unlike after dose 1. Moreover, among the other ADRs with incidences less than 50%, chills ranked fifth after dose 2, while it had ranked sixth after dose 1, and the other ADRs in order were joint pain (arthralgia), swelling, and fever. For RNA-based vaccines and viral vector (non-replicating) vaccines, consistent results were obtained among subgroups stratified by age ( Table 2 ; Figures S7–S10 ; Table S2 ).

To assess the severity of vaccine-related ADRs, we calculated the proportions (the ADRs over grade 3/all ADRs) and conducted a meta-analysis according to severity grade. The results showed that the ADRs associated with the RNA-based vaccine (Moderna, BNT162b2) were the most severe, and instances of grade 3 reactions were reported for all 8 ADRs. Fortunately, the proportions were low, and even the largest was less than 20%. Grade 3 ADRs also occurred after vaccination with viral vector (non-replicating) vaccines (AZD1222, Sputnik V); however, the proportions were low (less than 10%). Most ADRs after vaccination with inactivated vaccines (BBIBP) and protein subunit vaccines (NVX-COV2373) were grades 1–2. Importantly, among the participants who received the first dose of an RNA-based vaccine, grade 4 fever was noted, but the proportion was less than 5%. Meanwhile, we also found that younger participants were more likely to report higher-grade ADRs than older participants. For the RNA-based vaccine (Moderna) and protein subunit vaccine (NVX-COV2373), the ADR grades were higher after the second dose than the first dose ( Figure 1 ; Table S2 ).

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The severity of vaccine-related ADRs in clinical trials

Stacked bar chart showing the percentage of four ADRs grade after dose 1 or dose 2 of COVID-19 vaccines. (A) pain, (B) swelling, (C) fever, (D) fatigue, (E) chills, (F) muscle pain (myalgia), (G) joint pain (arthralgia), and (H) headache. Grade 1 (dark blue), grade 2 (light blue), grade 3 (red), and grade 4 (brown).

In the analysis of ADRs over grade 3, the incidences were all less than 10%, among which the most frequently reported ADR was fatigue (6.34%) in RNA-based vaccines after dose 2. The ADR grades were higher after the second dose than the first dose in RNA-based vaccines, contrary to the viral vector (non-replicating) vaccines (AZD1222, Sputnik V). What’s more, the incidences of the ADRs over grade 3 in viral vector (non-replicating) vaccines were higher than those in RNA-based vaccines after dose 1 ( Table 2 ; Figures S6 and S11 ; Table S2 ).

The severe and rare ADRs of COVID-19 vaccines

Besides the ones that have been reported in the clinical trials, there are some severe and rare ADRs, such as thromboembolic events and myocarditis/pericarditis events, which may result in death. Our results showed that thromboembolic events were only found in viral vector (non-replicating) vaccines (Ad26.COV2.S and AZD1222), while myocarditis/pericarditis events were reported in both viral vector (non-replicating) vaccines (Ad26.COV2.S and AZD1222) and RNA-based vaccines (BNT162b2 and Moderna). The incidence of thromboembolic events in Ad26.COV2.S (75 cases per million doses) was higher than that in AZD1222 (21 cases per million doses; Figure 2 A; Table S3 ). The incidence of myocarditis/pericarditis events was similar in viral vector (non-replicating) vaccines and RNA-based vaccines (2 versus 3 cases per million doses; Figure 2 B; Table S3 ).

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Forest plot of the incidence of thromboembolic events and myocarditis/pericarditis events

Meta-analysis was performed using R statistical software. Event rates and their corresponding 95% confidence intervals were estimated using both a fixed-effects model and a random-effects model. (A) Thromboembolic events and (B) myocarditis/pericarditis events.

Incidence of ADRs associated with RNA-based vaccines in the real world (VAERS)

To evaluate the safety of the COVID-19 vaccines more comprehensively, we retrospectively obtained real-world data pertaining to ADRs associated with RNA-based vaccines from VAERS. A total of 11,936 participants were included in the study, among whom 4,990 were vaccinated with the Moderna vaccine and 6,946 were vaccinated with the Pfizer-BioNTech vaccine ( Table S4 ).

Our research revealed an unexpected phenomenon. The incidence of ADRs in the real world was far lower than that in clinical trials. The ADR with the highest incidence is headache (16.53%), but the spectrum of ADRs is significantly wider than that in clinical trials. We identified more than 700 ADRs, but the incidence of most ADRs (more than 90%) was lower than 1% ( Figure 3 D). To evaluate the tolerance of the vaccine in different populations, we conducted subgroup analyses stratified by age, sex, and vaccine manufacturer. All ADRs with incidences higher than 5% were included. After stratification by the vaccine manufacturer (Moderna and Pfizer-BioNTech), the results showed that there were no significant differences in the incidences of headache, pain, myalgia, and nausea, but the incidences of chills, pyrexia, injection site pain, injection site erythema, pain in the extremities, and injection site swelling were higher among patients vaccinated with the Moderna vaccine than among those vaccinated with the Pfizer-BioNTech vaccine. In contrast, fatigue, dizziness, and dyspnea occurred more frequently in patients vaccinated with the Pfizer-BioNTech vaccine ( Figure 4 ; Table S6 ). The details of the incidences of all ADRs associated with the different vaccines are shown in Table S6 . Headache was still the most frequent ADR after the subgroup analysis was performed with stratification by age. Meanwhile, among those vaccinated with the Moderna vaccine, all ADRs were reported more often in older participants than young participants. The result was the opposite for the Pfizer-BioNTech vaccine ( Figures 3 D and and4; 4 ; Tables S7 and S8 ). The details of the incidences of all ADRs in different age groups are shown in Tables S7 and S8 . In the analysis stratified by sex, we found that regardless of whether the Moderna or Pfizer-BioNTech vaccine was administered, pyrexia ranked first, which was different from the results of the other subgroup analyses. Other than pyrexia and chills, which were more common in males, the incidences of other ADRs were higher in females than in males ( Figures 3 D and and4; 4 ; Tables S9 and S10 ). The details of the incidences of all ADRs stratified by sex are shown in Tables S9 and S10 .

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The incidence of ADRs of RNA-based vaccine from real-world data (VAERS)

Log-rank test of ADRs onset time stratified by (A) vaccine type, (B) age, and (C) gender. (D) Heatmap showing the incidence of ADRs. (∗ADRs Spectrum: due to the limitation of figure size, the details are shown in Table S5 .)

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The subgroup analyses of ADRs in RNA-based vaccine from real-world data (VAERS)

To evaluate the tolerance of the vaccine in different populations, we conducted subgroup analyses stratified by age, sex, and vaccine manufacturer. All ADRs with incidences higher than 5% were included. (∗No application: the incidences of ADRs under 5% in the subgroups were defined as “no application,” which were not tested by χ 2 .)

We also further explored the timing of the onset of ADRs. Most participants developed symptoms within a week after vaccination, but the longest interval was 60 days. The median symptom onset time for the Moderna and Pfizer-BioNTech vaccines were 2 days and 1 day, respectively, but the difference was not statistically significant ( Figure 3 A, p = 0.07). Symptoms appeared earlier in young participants, and the median interval was 1 day, while in older people, it was 2 days ( Figure 3 B, p < 0.0001). Symptoms appeared earlier in females, with a median interval of 1 day, while in males it was 2 days ( Figure 3 C, p < 0.0001).

COVID-19 remains a global public health threat, although it has been more than a year since the first case was diagnosed. The number of cases and deaths from COVID-19 continues to increase. Undoubtedly, vaccines are the most promising means to control the COVID-19 pandemic. As of April 5, 2021, several vaccines had been approved for public use, including RNA-based vaccines (Moderna and Pfizer-BioNTech), inactivated vaccines (Sinopharm [BBIBP], CoronaVac, Covaxin, Sinopharm [WIBP], and CoviVac), viral vector vaccines (Oxford-AstraZeneca, Sputnik V, Johnson & Johnson, and Convidecia), and protein subunit vaccines (EpiVacCorona, RBD-Dimer). 3 Although vaccinations are continuing to be administered, the vaccinated population only accounts for a small proportion of the entire population, and safety and efficacy are the issues about which many people are concerned.

This is the first study on the efficacy and safety of COVID-19 vaccines using published clinical trial data and real-world data. We comprehensively analyzed the efficacy of the existing COVID-19 vaccines and their incidence, spectrum, timing, and clinical features of ADRs after vaccination. Our research indicated that the efficacy of all vaccines exceeded 70% and that RNA-based vaccines had the highest efficacy of 94.29%; moreover, young people, Black or African American people, and males may experience greater vaccine efficacy. The spectrum of vaccine-related ADRs is extremely broad, involving multiple systems. The most common ADRs are pain, fatigue, and headache. Most ADRs are tolerable and mainly in grade 1 or 2 in severity; only grade 4 fever has been observed. Some severe ADRs have been identified, though the incidences were low (thromboembolic events, 21–75 cases per million doses; myocarditis/pericarditis, 2–3 cases per million doses). Most symptoms appear soon after vaccination, and many people recover without any medication.

In terms of efficacy, RNA-based vaccines ranked first, reaching greater than 94%, due to their strong immunogenicity and effective presentation of SARS-CoV-2 antigens to the immune system. 7 Currently, mutant virus strains are also attracting attention. RNA-based vaccines may be more effective against these mutant strains owing to their use of the full immunogenicity of SARS-CoV-2. However, the incidence of ADRs is high after vaccination with RNA-based vaccines, reaching over 80% based on the clinical trial data, with the incidences of grade 3 or 4 ADRs accounting for a small proportion. Although the real-world incidence of ADRs was lower than that in the clinical trials, the spectrum was broader, and a large portion of types of ADRs were not observed in clinical trials, suggesting that attention should be given to the identification and treatment of rare ADRs. Meanwhile, myocarditis/pericarditis have been identified in RNA-based vaccines; fortunately, the incidence was low. Protein subunit vaccines had an efficacy of 89%, while the highest incidence of ADRs was only 57%, and highest incidence of the ADRs over grade 3 was 3.85%, significantly lower than that associated with RNA-based vaccines; therefore, it may be a promising candidate. However, because real-world data regarding protein subunit vaccines are lacking and the sample of published data is small, further analysis is needed. Moreover, viral vector (non-replicating) vaccines have an efficacy of 79%, while the highest incidence of ADRs is 40%. In addition, the incidence of ADRs above grade 3 is significantly lower than that associated with RNA-based vaccines. However, some thromboembolic events and myocarditis/pericarditis events have been reported after vaccination with viral vector (non-replicating) vaccines (Ad26.COV2.S and AZD1222), which are very severe. Fortunately, the incidences of thromboembolic events and myocarditis/pericarditis events were low. Inactivated vaccines, in particular, are very safe and easy to preserve and transport, although their efficacy is relatively lower.

In the subgroup analysis, the ADRs after dose 1 of viral vector (non-replicating) vaccine (AZD1222, Sputnik V) occurred more often than dose 2. In contrast, the incidence of ADRs was higher after dose 2 of the RNA-based vaccine produced by Moderna and the protein subunit vaccine called NVX-COV2373. The results suggest that there are differences among the vaccines, and the monitoring of ADRs cannot be taken lightly even if no adverse reaction occurs following dose 1, especially among those receiving RNA-based vaccines (e.g., Moderna) and protein subunit vaccines (e.g., NVX-COV2373). The second dose should not be avoided because of ADRs after dose 1. The process of building tolerance to viral vector (non-replicating) vaccines is gradual in vaccinated recipients. We also found that young people seem to be relatively more prone to higher grade ADRs. We speculate that the relatively stronger immune systems in young people lead to both a higher incidence of ADRs and greater vaccine efficacy. 8 This finding also reduces concerns about vaccinating elderly people. The higher incidence of ADRs among female participants than male participants is puzzling, because it suggests that a stronger immune response was elicited in females, but the efficacy is lower in females than in males. This is inconsistent with the results of previous studies on sex differences. 9 The specific reasons need to be explored further. Furthermore, in the analysis of the timing of the onset of ADRs, we found that young people and females developed symptoms earlier, which may be related to the higher incidence of ADRs and their stronger immune systems. 9 In addition, the interval between vaccination and the development of ADRs in some patients can be up to 60 days, suggesting that the vaccination history should be actively reported when symptoms develop after vaccination and clinicians should pay attention to the lag between vaccination and the development of ADRs.

In the ADR analysis, the real-world data from the VAERS and clinical trial data were compared. We found that there are differences in the spectrum of ADRs, with a wider spectrum of ADRs identified in the real-world data. One plausible explanation is that the data in VAERS are continuously and openly collected. However, only ADRs that occurred within 1 week were counted in most clinical trials, and those that appeared after 1 week were omitted. In addition, the VAERS system lacks a standardized description of symptoms, with multiple different descriptions referring to the same ADR, falsely increasing the spectrum of ADRs. Another surprising finding is that the incidence of ADRs in the real world is far lower than that in clinical trials. Real-world data are only available for RNA-based vaccines, and the sample size is not yet large enough. Additionally, the VAERS is a self-reporting system with reporting bias, 10 and a large number of participants who were vaccinated did not report their ADRs, resulting in a lower incidence rate than in clinical trials.

We also found that few cases of mortality were reported to VAERS, and there was not enough evidence to indicate that the death was related to vaccination after carefully assessing each case. Therefore, a large-scale real-world study is needed for further confirmation.

In addition to the possible bias in VAERS, our study also has other deficiencies. The heterogeneity of several subgroups was large in the meta-analysis. To minimize heterogeneity, we used a total of 5 transformation methods (PFT, PAS, PRAW, PLN, PLOGIT) and chose the method by which the lowest heterogeneity was achieved. 11

In addition, we also conducted sensitivity analyses and multiple subgroup analyses to minimize heterogeneity. Both fixed-effect model and random-effect model were performed. When I 2 was less than 50% and p > 0.1, the fixed-effect model was chosen; otherwise, the random-effect model was chosen. 12 , 13 , 14

The Begg’s and Egger’s tests were not used because there were not more than 10 subjects in each group. 15 Although some subgroups were heterogeneous, we determined that the heterogeneity was derived from the data itself after sufficient statistical correction and analysis, possibly due to factors such as the area in which the study was conducted, the risk of exposure to SARS-CoV-2, and other factors that were beyond our control. Therefore, our research comprehensively demonstrated the efficacy and safety of the COVID-19 vaccines to the greatest extent possible, providing a credible reference for clinical practice and the general public.

In summary, vaccines are a powerful tool against the COVID-19 pandemic, with high efficacy and tolerable adverse reactions. Each vaccine has its own advantages and shortcomings, and every citizen should choose to be vaccinated as soon as possible. In addition, the spectrum of ADRs associated with the vaccines is broad, and most of the reactions appear within a week, although a delay sometimes occurs. Some severe ADRs have been identified, though the incidences were low (thromboembolic events and myocarditis/pericarditis). Therefore, ADRs should be identified and addressed in a timely manner after vaccination. We hope that our research can eliminate fear of the vaccines among the general public and provide guidance regarding the management of vaccine-related side effects in a timely manner.

Materials and methods

Meta-analysis, part 1: the landscape of efficacy and safety of covid-19 vaccines, inclusion criteria.

The study was registered in PROSPERO (CRD42021234481). We identified records by searching PubMed, Medline, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) for “(COVID-19 OR 2019-nCoV OR SARS-CoV-2) AND vaccine” on March 7, 2021. English-language clinical trials were included.

Exclusion criteria

All 8,215 initially identified studies were screened; those that were clinical trials were included (n = 53), and those in which a vaccine against SARS-CoV-2 was not used were excluded (n = 29). Trials without adverse effect or efficacy data (n = 1) and those with only the clinical trial protocol (n = 1) were excluded.

The remaining trials (n = 22) included 17 phase I/phase II clinical trials of 12 vaccines, and 4 of these vaccines had published phase III clinical trial results (n = 5). We further searched for the remaining 8 vaccines on Google using the following keywords: “(candidate vaccine name or manufacturer) AND (COVID-19 OR 2019-nCoV OR SARS-CoV-2).” Phase I/phase II trials of vaccines that did not have official results from phase III clinical trials were excluded (n = 11).

The remaining trials (n = 11) included 8 different vaccines, phase III clinical trials were updated on June 17, 2021, and a new trial of Ad26.COV2.S vaccine was included (n = 1). Finally, 12 clinical trials were assessed individually, and a total of 194,015 cases were included. 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 The total number of patients treated, the number and type of adverse effects, the VE were compared, and the PRISMA diagram of articles selected for meta-analysis was shown in Figure S1 ( Figure S1 A; Table 3 ).

Clinical trials and the characteristics of COVID-19 vaccines

Vaccine name	Vaccine type	Developer	Participant age (years)	Dose schedule	Reference
BNT162b2	RNA-based vaccine	Pfizer/BioNTech; Fosun Pharma	16–55 >55	0 days: 30 μg 21 days: 30 μg	Polack et al.
mRNA-1273	RNA-based vaccine	Moderna; National Institute of Allergy and Infectious Diseases (NIAID)	18–65 >65	0 days, 100 μg 28 days, 100 μg	Baden et al.
AZD1222	viral vector (non-replicating)	AstraZeneca; University of Oxford	18–55 56–69 ≥70	0 days: low dose (2.2 × 10 virus particles)/standard dose (3.5–6.5 × 10 virus particles) 28 days: standard dose (3.5–6.5 × 10 virus particles)	Voysey et al. and Ramasamy et al.
Sputnik V	viral vector (non-replicating)	Gamaleya Research Institute; Health Ministry of the Russian Federation	18–30 31–40 41–50 51–60 >60	0 days: rAd26 10 viral particles 21 days: rAd5 10 viral particles	Logunov et al.
CoronaVac	inactivated virus	Sinovac Research and Development	18–59 ≥60	0 days: 3 μg 14 days: 3 μg	Bureau
NVX-CoV2373	protein subunit	Novavax	18–84	0 days: 5 μg, with Matrix-M1 adjuvant 21 days: 5 μg, with Matrix-M1 adjuvant	Keech et al. and Novavax I
BBIBP-CorV	inactivated virus	Sinopharm, China National Biotec Group, and Beijing Institute of Biological Products	18–80	0 days: 4 μg 21 days: 4 μg	Xia et al.
Ad5-nCoV	viral vector (non-replicating)	Cansino Biological/Beijing Institute of Biotechnology	≥18	5 × 10 virus particles, one dose	Zhu et al.
Ad26.COV2.S	viral vector (non-replicating)	Janssen/Johnson & Johnson	18–59 ≥60	single dose: 5 × 10 viral particles	Sadoff et al.

Part 2: The severe and rare ADRs of COVID-19 vaccines

We identified records by searching PubMed, Medline, EMBASE, Google, and the CENTRAL for “(Thromboembolic OR Myocarditis OR Pericarditis) AND COVID-19 vaccine” on June 17, 2021. English-language clinical trials and official reports were included.

All 2,910,000 results initially identified studies were screened; those that were clinical trials (n = 1), cohort study (n = 3), case reports (n = 12), and official reports (n = 8) were included. Those studies without the data of the exact total number and exact number of patients with thromboembolic or myocarditis or pericarditis were excluded (n = 14). Those official reports that were outdated or without the data of the exact vaccine type (n = 3) were excluded.

The remaining trial (n = 1), 27 cohort study (n = 1), 28 and official reports (n = 5) 29 , 30 , 31 , 32 , 33 were assessed individually, and a total of 86,506,742 doses with thromboembolic events and 603,862,888 doses with myocarditis/pericarditis events were included. The total number of doses, the number and type of adverse effects, and the vaccine types were compared, and the PRISMA diagram of articles selected for meta-analysis is shown in Figure S2 ( Figure S1 B; Table S3 ).

The study is based on data downloaded from the VAERS ( https://vaers.hhs.gov/data.html ). The VAERS is comanaged by the CDC and the FDA and has been used to detect possible safety problems in U.S.-licensed vaccines since 1990. Healthcare providers, vaccine manufacturers, and the public can submit reports to the system. 6

We accessed the VAERS on March 5, 2021 and downloaded data from 2020 and 2021. We included all entries in which the patient had been injected with the Moderna or Pfizer COVID-19 vaccine. Patients injected with COVID-19 vaccines manufactured by unknown developers or vaccines against other pathogens were excluded.

VE was calculated as 1-relative risk (RR): 34 , 35

The incidence of ADRs was extracted by “Engauge Digitizer” from histograms if the raw data were not displayed. 36 The incidences of ADRs were compared with χ2 tests. Other clinical variables of interest were evaluated descriptively. Statistical analyses were performed in GraphPad Prism (version 7, GraphPad Software); the meta-analysis was performed using R statistical software (packages metafor and meta, R Foundation). Event rates and their corresponding 95% confidence intervals were estimated using both a fixed-effects model and a random-effects model. Forest plots were constructed to summarize the data for each analytical group according to the incidence rate and to provide a visual analysis of fatal drug-related events.

Acknowledgments

This study was supported by grants from the National Key R&D Program of China (number 2018YFC1313300), National Natural Science Foundation of China (numbers 81070362, 81172470, 81372629, 81772627, 81874073, and 81974384), key projects from the Nature Science Foundation of Hunan Province (numbers 2015JC3021 and 2016JC2037), the projects from Beijing CSCO Clinical Oncology Research Foundation (numbers Y-HR2019-0182 and Y-2019Genecast-043), and the Fundamental Research Funds for the Central Universities of Central South University University (2020zzts273 and 2019zzts797). We want to show our appreciates to Zirconicusso/Freepik for providing the materials for making the Graphical Abstract.

Author contributions

C.C., Y.P., H.S., S.Z., and Y.H. designed the study. C.C., Y.P., E.S., Q.H., Y.C., P.L., C.G., Z.F., L.G., Y.L., and X.Z. collected the data and performed the major analysis. S.Z. and H.S. supervised the study. C.C. and Y.P. analyzed and interpreted the data. E.S. and Z.F. did the statistical analysis. C.C., Y.P., C.G., and Y.L. drafted the manuscript. All authors read and approved the final manuscript.

Declaration of interests

The authors declare no competing interests.

Supplemental information can be found online at https://doi.org/10.1016/j.ymthe.2021.08.001 .

Supplemental information

Assessing National Sentiment and Trends in COVID-19 Vaccine Hesitancy in the U.S.

Add to collection, downloadable content.

June 6, 2023
Affiliation: Eshelman School of Pharmacy
Considering the rapidly evolving state of the COVID-19 pandemic, it is necessary to identify trends in COVID-19 vaccine hesitancy. Little evidence exists on the intersection of themes of COVID-19 vaccine hesitancy and those demographic predictors as seen in national media coverage. This project aims to describe common trends in COVID-19 vaccine hesitancy as seen in the media and who is voicing those common concerns. This study collected articles from four ProQuest databases through search terms relating to Sars-CoV-2 and COVID-19, then developed a codebook to extract quotations from U.S. news media. Some concerns seen in high frequency among specific populations include mistrust in the government and pharmaceutical industry among doctors and the lack of perceived necessity among young adults. These intersections of COVID-19 vaccine hesitant trends and specific populations are important considerations when creating a nuanced public message to support the pandemic response an minimize the negative effects of a prolonged pandemic.
March 7, 2023
https://doi.org/10.17615/wj8k-4792
Honors Thesis
In Copyright
Other Affiliation: Higgins, Colleen
Doctor of Pharmacy

This work has no parents.

UNC-Chapel Hill Coronavirus Research

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Why the Pandemic Probably Started in a Lab, in 5 Key Points

By Alina Chan

Dr. Chan is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “Viral: The Search for the Origin of Covid-19.”

This article has been updated to reflect news developments.

On Monday, Dr. Anthony Fauci returned to the halls of Congress and testified before the House subcommittee investigating the Covid-19 pandemic. He was questioned about several topics related to the government’s handling of Covid-19, including how the National Institute of Allergy and Infectious Diseases, which he directed until retiring in 2022, supported risky virus work at a Chinese institute whose research may have caused the pandemic.

For more than four years, reflexive partisan politics have derailed the search for the truth about a catastrophe that has touched us all. It has been estimated that at least 25 million people around the world have died because of Covid-19, with over a million of those deaths in the United States.

Although how the pandemic started has been hotly debated, a growing volume of evidence — gleaned from public records released under the Freedom of Information Act, digital sleuthing through online databases, scientific papers analyzing the virus and its spread, and leaks from within the U.S. government — suggests that the pandemic most likely occurred because a virus escaped from a research lab in Wuhan, China. If so, it would be the most costly accident in the history of science.

Here’s what we now know:

1 The SARS-like virus that caused the pandemic emerged in Wuhan, the city where the world’s foremost research lab for SARS-like viruses is located.

At the Wuhan Institute of Virology, a team of scientists had been hunting for SARS-like viruses for over a decade, led by Shi Zhengli.
Their research showed that the viruses most similar to SARS‑CoV‑2, the virus that caused the pandemic, circulate in bats that live r oughly 1,000 miles away from Wuhan. Scientists from Dr. Shi’s team traveled repeatedly to Yunnan province to collect these viruses and had expanded their search to Southeast Asia. Bats in other parts of China have not been found to carry viruses that are as closely related to SARS-CoV-2.

The closest known relatives to SARS-CoV-2 were found in southwestern China and in Laos.

Large cities

Mine in Yunnan province

Cave in Laos

South China Sea

The closest known relatives to SARS-CoV-2

were found in southwestern China and in Laos.

philippines

The closest known relatives to SARS-CoV-2 were found

in southwestern China and Laos.

Sources: Sarah Temmam et al., Nature; SimpleMaps

Note: Cities shown have a population of at least 200,000.

There are hundreds of large cities in China and Southeast Asia.

There are hundreds of large cities in China

and Southeast Asia.

The pandemic started roughly 1,000 miles away, in Wuhan, home to the world’s foremost SARS-like virus research lab.

The pandemic started roughly 1,000 miles away,

in Wuhan, home to the world’s foremost SARS-like virus research lab.

The pandemic started roughly 1,000 miles away, in Wuhan,

home to the world’s foremost SARS-like virus research lab.

Even at hot spots where these viruses exist naturally near the cave bats of southwestern China and Southeast Asia, the scientists argued, as recently as 2019 , that bat coronavirus spillover into humans is rare .
When the Covid-19 outbreak was detected, Dr. Shi initially wondered if the novel coronavirus had come from her laboratory , saying she had never expected such an outbreak to occur in Wuhan.
The SARS‑CoV‑2 virus is exceptionally contagious and can jump from species to species like wildfire . Yet it left no known trace of infection at its source or anywhere along what would have been a thousand-mile journey before emerging in Wuhan.

2 The year before the outbreak, the Wuhan institute, working with U.S. partners, had proposed creating viruses with SARS‑CoV‑2’s defining feature.

Dr. Shi’s group was fascinated by how coronaviruses jump from species to species. To find viruses, they took samples from bats and other animals , as well as from sick people living near animals carrying these viruses or associated with the wildlife trade. Much of this work was conducted in partnership with the EcoHealth Alliance, a U.S.-based scientific organization that, since 2002, has been awarded over $80 million in federal funding to research the risks of emerging infectious diseases.
The laboratory pursued risky research that resulted in viruses becoming more infectious : Coronaviruses were grown from samples from infected animals and genetically reconstructed and recombined to create new viruses unknown in nature. These new viruses were passed through cells from bats, pigs, primates and humans and were used to infect civets and humanized mice (mice modified with human genes). In essence, this process forced these viruses to adapt to new host species, and the viruses with mutations that allowed them to thrive emerged as victors.
By 2019, Dr. Shi’s group had published a database describing more than 22,000 collected wildlife samples. But external access was shut off in the fall of 2019, and the database was not shared with American collaborators even after the pandemic started , when such a rich virus collection would have been most useful in tracking the origin of SARS‑CoV‑2. It remains unclear whether the Wuhan institute possessed a precursor of the pandemic virus.
In 2021, The Intercept published a leaked 2018 grant proposal for a research project named Defuse , which had been written as a collaboration between EcoHealth, the Wuhan institute and Ralph Baric at the University of North Carolina, who had been on the cutting edge of coronavirus research for years. The proposal described plans to create viruses strikingly similar to SARS‑CoV‑2.
Coronaviruses bear their name because their surface is studded with protein spikes, like a spiky crown, which they use to enter animal cells. T he Defuse project proposed to search for and create SARS-like viruses carrying spikes with a unique feature: a furin cleavage site — the same feature that enhances SARS‑CoV‑2’s infectiousness in humans, making it capable of causing a pandemic. Defuse was never funded by the United States . However, in his testimony on Monday, Dr. Fauci explained that the Wuhan institute would not need to rely on U.S. funding to pursue research independently.

The Wuhan lab ran risky experiments to learn about how SARS-like viruses might infect humans.

1. Collect SARS-like viruses from bats and other wild animals, as well as from people exposed to them.

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of human cells.

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of

human cells.

In Defuse, the scientists proposed to add a furin cleavage site to the spike protein.

3. Create new coronaviruses by inserting spike proteins or other features that could make the viruses more infectious in humans.

4. Infect human cells, civets and humanized mice with the new coronaviruses, to determine how dangerous they might be.

While it’s possible that the furin cleavage site could have evolved naturally (as seen in some distantly related coronaviruses), out of the hundreds of SARS-like viruses cataloged by scientists, SARS‑CoV‑2 is the only one known to possess a furin cleavage site in its spike. And the genetic data suggest that the virus had only recently gained the furin cleavage site before it started the pandemic.
Ultimately, a never-before-seen SARS-like virus with a newly introduced furin cleavage site, matching the description in the Wuhan institute’s Defuse proposal, caused an outbreak in Wuhan less than two years after the proposal was drafted.
When the Wuhan scientists published their seminal paper about Covid-19 as the pandemic roared to life in 2020, they did not mention the virus’s furin cleavage site — a feature they should have been on the lookout for, according to their own grant proposal, and a feature quickly recognized by other scientists.
Worse still, as the pandemic raged, their American collaborators failed to publicly reveal the existence of the Defuse proposal. The president of EcoHealth, Peter Daszak, recently admitted to Congress that he doesn’t know about virus samples collected by the Wuhan institute after 2015 and never asked the lab’s scientists if they had started the work described in Defuse. In May, citing failures in EcoHealth’s monitoring of risky experiments conducted at the Wuhan lab, the Biden administration suspended all federal funding for the organization and Dr. Daszak, and initiated proceedings to bar them from receiving future grants. In his testimony on Monday, Dr. Fauci said that he supported the decision to suspend and bar EcoHealth.
Separately, Dr. Baric described the competitive dynamic between his research group and the institute when he told Congress that the Wuhan scientists would probably not have shared their most interesting newly discovered viruses with him . Documents and email correspondence between the institute and Dr. Baric are still being withheld from the public while their release is fiercely contested in litigation.
In the end, American partners very likely knew of only a fraction of the research done in Wuhan. According to U.S. intelligence sources, some of the institute’s virus research was classified or conducted with or on behalf of the Chinese military . In the congressional hearing on Monday, Dr. Fauci repeatedly acknowledged the lack of visibility into experiments conducted at the Wuhan institute, saying, “None of us can know everything that’s going on in China, or in Wuhan, or what have you. And that’s the reason why — I say today, and I’ve said at the T.I.,” referring to his transcribed interview with the subcommittee, “I keep an open mind as to what the origin is.”

3 The Wuhan lab pursued this type of work under low biosafety conditions that could not have contained an airborne virus as infectious as SARS‑CoV‑2.

Labs working with live viruses generally operate at one of four biosafety levels (known in ascending order of stringency as BSL-1, 2, 3 and 4) that describe the work practices that are considered sufficiently safe depending on the characteristics of each pathogen. The Wuhan institute’s scientists worked with SARS-like viruses under inappropriately low biosafety conditions .

In the United States, virologists generally use stricter Biosafety Level 3 protocols when working with SARS-like viruses.

Biosafety cabinets prevent

viral particles from escaping.

Viral particles

Personal respirators provide

a second layer of defense against breathing in the virus.

DIRECT CONTACT

Gloves prevent skin contact.

Disposable wraparound

gowns cover much of the rest of the body.

Personal respirators provide a second layer of defense against breathing in the virus.

Disposable wraparound gowns

cover much of the rest of the body.

Note: Biosafety levels are not internationally standardized, and some countries use more permissive protocols than others.

The Wuhan lab had been regularly working with SARS-like viruses under Biosafety Level 2 conditions, which could not prevent a highly infectious virus like SARS-CoV-2 from escaping.

Some work is done in the open air, and masks are not required.

Less protective equipment provides more opportunities

for contamination.

Some work is done in the open air,

and masks are not required.

Less protective equipment provides more opportunities for contamination.

In one experiment, Dr. Shi’s group genetically engineered an unexpectedly deadly SARS-like virus (not closely related to SARS‑CoV‑2) that exhibited a 10,000-fold increase in the quantity of virus in the lungs and brains of humanized mice . Wuhan institute scientists handled these live viruses at low biosafet y levels , including BSL-2.
Even the much more stringent containment at BSL-3 cannot fully prevent SARS‑CoV‑2 from escaping . Two years into the pandemic, the virus infected a scientist in a BSL-3 laboratory in Taiwan, which was, at the time, a zero-Covid country. The scientist had been vaccinated and was tested only after losing the sense of smell. By then, more than 100 close contacts had been exposed. Human error is a source of exposure even at the highest biosafety levels , and the risks are much greater for scientists working with infectious pathogens at low biosafety.
An early draft of the Defuse proposal stated that the Wuhan lab would do their virus work at BSL-2 to make it “highly cost-effective.” Dr. Baric added a note to the draft highlighting the importance of using BSL-3 to contain SARS-like viruses that could infect human cells, writing that “U.S. researchers will likely freak out.” Years later, after SARS‑CoV‑2 had killed millions, Dr. Baric wrote to Dr. Daszak : “I have no doubt that they followed state determined rules and did the work under BSL-2. Yes China has the right to set their own policy. You believe this was appropriate containment if you want but don’t expect me to believe it. Moreover, don’t insult my intelligence by trying to feed me this load of BS.”
SARS‑CoV‑2 is a stealthy virus that transmits effectively through the air, causes a range of symptoms similar to those of other common respiratory diseases and can be spread by infected people before symptoms even appear. If the virus had escaped from a BSL-2 laboratory in 2019, the leak most likely would have gone undetected until too late.
One alarming detail — leaked to The Wall Street Journal and confirmed by current and former U.S. government officials — is that scientists on Dr. Shi’s team fell ill with Covid-like symptoms in the fall of 2019 . One of the scientists had been named in the Defuse proposal as the person in charge of virus discovery work. The scientists denied having been sick .

4 The hypothesis that Covid-19 came from an animal at the Huanan Seafood Market in Wuhan is not supported by strong evidence.

In December 2019, Chinese investigators assumed the outbreak had started at a centrally located market frequented by thousands of visitors daily. This bias in their search for early cases meant that cases unlinked to or located far away from the market would very likely have been missed. To make things worse, the Chinese authorities blocked the reporting of early cases not linked to the market and, claiming biosafety precautions, ordered the destruction of patient samples on January 3, 2020, making it nearly impossible to see the complete picture of the earliest Covid-19 cases. Information about dozens of early cases from November and December 2019 remains inaccessible.
A pair of papers published in Science in 2022 made the best case for SARS‑CoV‑2 having emerged naturally from human-animal contact at the Wuhan market by focusing on a map of the early cases and asserting that the virus had jumped from animals into humans twice at the market in 2019. More recently, the two papers have been countered by other virologists and scientists who convincingly demonstrate that the available market evidence does not distinguish between a human superspreader event and a natural spillover at the market.
Furthermore, the existing genetic and early case data show that all known Covid-19 cases probably stem from a single introduction of SARS‑CoV‑2 into people, and the outbreak at the Wuhan market probably happened after the virus had already been circulating in humans.

An analysis of SARS-CoV-2’s evolutionary tree shows how the virus evolved as it started to spread through humans.

SARS-COV-2 Viruses closest

to bat coronaviruses

more mutations

Source: Lv et al., Virus Evolution (2024) , as reproduced by Jesse Bloom

The viruses that infected people linked to the market were most likely not the earliest form of the virus that started the pandemic.

Not a single infected animal has ever been confirmed at the market or in its supply chain. Without good evidence that the pandemic started at the Huanan Seafood Market, the fact that the virus emerged in Wuhan points squarely at its unique SARS-like virus laboratory.

5 Key evidence that would be expected if the virus had emerged from the wildlife trade is still missing.

In previous outbreaks of coronaviruses, scientists were able to demonstrate natural origin by collecting multiple pieces of evidence linking infected humans to infected animals.

Infected animals

Earliest known

cases exposed to

live animals

Antibody evidence

of animals and

animal traders having

been infected

Ancestral variants

of the virus found in

Documented trade

of host animals

between the area

where bats carry

closely related viruses

and the outbreak site

Infected animals found

Earliest known cases exposed to live animals

Antibody evidence of animals and animal

traders having been infected

Ancestral variants of the virus found in animals

Documented trade of host animals

between the area where bats carry closely

related viruses and the outbreak site

For SARS-CoV-2, these same key pieces of evidence are still missing , more than four years after the virus emerged.

For SARS-CoV-2, these same key pieces of evidence are still missing ,

more than four years after the virus emerged.

Despite the intense search trained on the animal trade and people linked to the market, investigators have not reported finding any animals infected with SARS‑CoV‑2 that had not been infected by humans. Yet, infected animal sources and other connective pieces of evidence were found for the earlier SARS and MERS outbreaks as quickly as within a few days, despite the less advanced viral forensic technologies of two decades ago.
Even though Wuhan is the home base of virus hunters with world-leading expertise in tracking novel SARS-like viruses, investigators have either failed to collect or report key evidence that would be expected if Covid-19 emerged from the wildlife trade . For example, investigators have not determined that the earliest known cases had exposure to intermediate host animals before falling ill. No antibody evidence shows that animal traders in Wuhan are regularly exposed to SARS-like viruses, as would be expected in such situations.
With today’s technology, scientists can detect how respiratory viruses — including SARS, MERS and the flu — circulate in animals while making repeated attempts to jump across species . Thankfully, these variants usually fail to transmit well after crossing over to a new species and tend to die off after a small number of infections. In contrast, virologists and other scientists agree that SARS‑CoV‑2 required little to no adaptation to spread rapidly in humans and other animals . The virus appears to have succeeded in causing a pandemic upon its only detected jump into humans.

The pandemic could have been caused by any of hundreds of virus species, at any of tens of thousands of wildlife markets, in any of thousands of cities, and in any year. But it was a SARS-like coronavirus with a unique furin cleavage site that emerged in Wuhan, less than two years after scientists, sometimes working under inadequate biosafety conditions, proposed collecting and creating viruses of that same design.

While several natural spillover scenarios remain plausible, and we still don’t know enough about the full extent of virus research conducted at the Wuhan institute by Dr. Shi’s team and other researchers, a laboratory accident is the most parsimonious explanation of how the pandemic began.

Given what we now know, investigators should follow their strongest leads and subpoena all exchanges between the Wuhan scientists and their international partners, including unpublished research proposals, manuscripts, data and commercial orders. In particular, exchanges from 2018 and 2019 — the critical two years before the emergence of Covid-19 — are very likely to be illuminating (and require no cooperation from the Chinese government to acquire), yet they remain beyond the public’s view more than four years after the pandemic began.

Whether the pandemic started on a lab bench or in a market stall, it is undeniable that U.S. federal funding helped to build an unprecedented collection of SARS-like viruses at the Wuhan institute, as well as contributing to research that enhanced them . Advocates and funders of the institute’s research, including Dr. Fauci, should cooperate with the investigation to help identify and close the loopholes that allowed such dangerous work to occur. The world must not continue to bear the intolerable risks of research with the potential to cause pandemics .

A successful investigation of the pandemic’s root cause would have the power to break a decades-long scientific impasse on pathogen research safety, determining how governments will spend billions of dollars to prevent future pandemics. A credible investigation would also deter future acts of negligence and deceit by demonstrating that it is indeed possible to be held accountable for causing a viral pandemic. Last but not least, people of all nations need to see their leaders — and especially, their scientists — heading the charge to find out what caused this world-shaking event. Restoring public trust in science and government leadership requires it.

A thorough investigation by the U.S. government could unearth more evidence while spurring whistleblowers to find their courage and seek their moment of opportunity. It would also show the world that U.S. leaders and scientists are not afraid of what the truth behind the pandemic may be.

More on how the pandemic may have started

Where Did the Coronavirus Come From? What We Already Know Is Troubling.

Even if the coronavirus did not emerge from a lab, the groundwork for a potential disaster had been laid for years, and learning its lessons is essential to preventing others.

By Zeynep Tufekci

Why Does Bad Science on Covid’s Origin Get Hyped?

If the raccoon dog was a smoking gun, it fired blanks.

By David Wallace-Wells

A Plea for Making Virus Research Safer

A way forward for lab safety.

By Jesse Bloom

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

Follow the New York Times Opinion section on Facebook , Instagram , TikTok , WhatsApp , X and Threads .

Alina Chan ( @ayjchan ) is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “ Viral : The Search for the Origin of Covid-19.” She was a member of the Pathogens Project , which the Bulletin of the Atomic Scientists organized to generate new thinking on responsible, high-risk pathogen research.

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COVID-19 Thesis Impact Statement

The impact of the COVID-19 pandemic on all aspects of our lives is well known.

Victoria experienced six lockdowns between March 2020 and October 2021 that collectively totalled 262 days. Deakin University sought to mitigate this impact on the research by higher degree by research students in various ways, including providing priority access to laboratories and support to pivot research projects. Not all impact on research could be mitigated with direct and indirect effects of limited domestic and international travel, closed university campuses and restricted in-person access to human research participants.

Within this context, you have the option of describing the impact of COVID-19 on your research and how you modified your topic, methods and data collection due to COVID-19 restrictions. The COVID-19 Thesis Impact Statement aims to provide the examiners with a clearer understanding of how the research was affected and shaped due to COVID-19 disruptions.

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Honors Thesis Spotlight: The Effects of the COVID-19 Pandemic on Puerto Rico’s Tourism Industry

Published: September 13, 2022 | 2:01 pm

This content originally appeared on COSSPP’s Wicked Problems, Wicked Solutions Blog and is the work of the individual authors sharing their research, expertise, and experience and do not necessarily reflect the opinions or positions of the College of Social Sciences and Public Policy, Florida State University, or any other agency, institution, or entity.

Tourism is one of the primary businesses which attracts external investment to the island of Puerto Rico, while also furthering pro-business interests in place of those from the general public. It has set the bar for Puerto Rico’s urban economy today, especially that of its capital, San Juan, and has developed around the influx of over one million tourists annually. However, with the full force of the COVID-19 pandemic forcing the virtual shutdown of all travel, there has been a very noticeable drop in tourism. Monthly tourist entry into the island was reduced from almost 200,000 to just over 50,000, and the tourism industry labor force dropped to 46,900, (4).

Statistics like these are jarring for Puerto Rico since the tourism sector accounts for almost 30% of the gross domestic product. Tourism has particularly made SIDS (small island developing states) vulnerable to catastrophe. Instead of finding sustainable ways to rebuild their economy beyond tourism, many SIDS, including Puerto Rico, have found themselves instead accommodating to the pandemic. For example, there is a visible increase in testing kit prices, and “other accommodations to pandemic protocols have caused setbacks in economic recovery of SIDS across the world,” (4).

With this Puerto Rico example in mind, the researcher argues that an increasing dependence upon an outdated form of tourism has been and remains unsustainable. The researcher outlines their study in support of their thesis. It tracks the historical development of Puerto Rico’s tourism industry, and compares it with actual analysis and data on tourism during the COVID-19 pandemic from news sources, press releases, and interviews with visitors to Puerto Rico during the pandemic. In so doing, this study will outline the toxicities brought about by creating a critical economic sector which is dependent on the influx of external capital. It also briefly attempts to offer solutions from academics, journalists, and industry operatives regarding the future of tourism in 5 sustainability and renewability, with a particular focus on educative rather than exploitive tourism, (5).

The Puerto Rican government’s prolonged pro-business mindset has permitted the reopening of the tourism industry despite a raging pandemic. It is also perpetuated by the extant colonial relationship between the United States and Puerto Rico, (9). “By not being allowed to close its borders to entry from potentially viremic tourists, Puerto Rico was forced to play the game of capitalism,” (9).

The researcher advises these SIDS to decrease their focus on consumptive, capitalistic tourism so that regenerative forms of tourism can arise. Education must be the new purpose of tourism if it is to become a sustainable means of economy.

Carlos Rivera Fernandez is a graduate of the College of Social Sciences and Public Policy at Florida State University. This post was based on Carlos’s honors thesis, written by COSSPP Blog Intern, Jillian Kaplan.

School of Environment, Society & Sustainability

College of social & behavioral science, main navigation, envst 4800 internship/envst 5000 research/envst 4999 honors thesis requirement, fall 2024 course applications due august 12, by 5pm, spring 2025 course application due – december 30th by 5pm, summer 2025 course application due – may 5th by 5pm, late applications are not accepted.

If after reviewing this information you still have questions on how to count an Internship, Research or Honors Thesis towards the ENVST major, please contact Ally Marringa .

PREREQUISITES FOR ENROLLMENT:
ENVST 4800 Internship:
ENVST 5000 Research:
ENVST 4999 Honors Thesis:
FAQ's

Step 1 – ENVST Core Courses are required prerequisites in order to be approved and enroll in the ENVST Internship (ENVST 4800), Research (ENVST 5000) and Honors Thesis (ENVST 4999) courses. The ENVST core classes include: ENVST 2050, ENVST 2051, ENV 2100 (previously ENVST 2100), ENVST/GEOG 3210, ENVST 3364, ENVST 3365 and either POLS 3390 OR POLS 5322.

Step 2 – Find and secure an Internship, Research or Honors Thesis. The ENVST Program does not place students in opportunities, but see the relevant “ENVST 4800 Internship”, “ENVST 5000 Research”, and/or “ENVST 4999 Honors Thesis” tabs on this page for resources and criteria for approval.

Step 3 – Once you secure an Internship, Research, or Honors Thesis experience, you can Apply for ENVST Internship/Research/Thesis Credit . This application is required in order to get a permission code to register for the relevant course by the deadlines posted at the top of this page.

Step 4 – Once your ENVST Internship/Research/Thesis Credit Application is approved, you will be sent an add code and directions for enrollment.

For more information and resources on each option (ENVST 4800 Internship, ENVST 5000 Research and ENVST 4999 Honors Thesis), please select the appropriate tab. If you have additional questions after reviewing, please contact our ENVST Internship & Research Coordinator, Ally Marringa.

Credit Hours:

3 credits total of ENVST 4800, 5000 OR 4999 are required to fulfill the ENVST Major requirement. Below is a credit breakdown of how many hours you would be working at your internship or research experience per credit hour.

· 1 credit hour = 3 hours effort (45 total hours)

· 2 credit hours = 6 hours effort (90 total hours)

· 3 credit hours = 9 hours effort (135 total hours)

In order to enroll in this class, see the “Prerequisites for Enrollment” tab. The ENVST Internship/Research/Thesis Credit Application is required by the above posted deadlines.

Criteria for Internship Approval :

Your internship must be environmentally-focused (internships can be broad but must be focused on an environmental issue)
Whether paid or unpaid, your experience should provide you with the opportunity to apply theoretical and empirically based ideas from your coursework to a real-world setting
Internships should offer the opportunity to develop marketable, professional skills
Internships that primarily consist of physical labor, photocopying, filing, or similar work will not be considered

Resources for the Internship Search :

Start researching potential agencies and organizations at least two months prior to planned internship semester. Watch for posted internship announcements or contact agencies of interest directly.
The Hinckley Institute is another resource for finding an internship. They have their own deadlines and application process, but if you pursue this option and secure an environmentally-related internship through them, the same prerequisites, application and deadline applies for it to count for the ENVST major. Once secured, submit the ENVST Internship/Research/Thesis Credit Application. This is required and must be completed by the above posted deadline.
We also recommend connecting with the U Career Success for additional help with your application materials, interview skills and assistance with the search process. They also provide a program called the Step Up Fund , which is a great way to get paid for an internship.
Need more help getting started with application materials, support with the search and funding options? As a declared ENVST major, use the professional development tool pages in the Advising Canvas page!

Criteria for Approval:

Your research must be environmentally-focused (it does not need to be an ENVST professor, but does need to be a professor at the U whose project is environmentally-focused)
Draft a research proposal with the help of a faculty member. We suggest formatting your proposal based on the instructions given by the Undergraduate Research Opportunities Program (UROP) . Submission of a proposal to the UROP is not required.

Resources for the Research Search:

Find a faculty mentor to join an undergraduate research project. Consider professors you’ve had in class before, or talk with your advisor about research topics you are interested in. Write an introductory email to a faculty member conducting research in an area of interest including a brief (1-2 sentences each) description about why you are interested in conducting, background of relevant coursework, questions you hope to address and/or skills you hope to gain via research. Politely inquire if any opportunities exist.
View past examples of student research in ENVST
The Undergraduate Research Opportunities Program (UROP) . Submission of a proposal to the UROP is optional, and they hold different deadlines than ENVST
Apply for the travel and/or small grants funds through the Office of Undergraduate Research to support research efforts (as needed)
If applicable, apply for Undergraduate Research Scholar Designation (URSD) . This expectation applies only to students who have conducted two semesters of research
The Wilkes Center also offers funding support, awards and events centered on environmentally focused research

An Honors Thesis is required for all ENVST HBS OR HBA Honors Students, and not an option for students not admitted to the Honors College.

Your research must be environmentally-focused (it does not need to be an ENVST professor, but does need to be a professor at the U and your thesis topic must be focused on the environment and sustainability)

Resources for Developing an Honors Thesis:

Meet with the Faculty Honors Advisor in ENVST, Dr. Tim Collins , to discuss your thesis topic and potential thesis faculty advisor
Explore suggested timelines and see suggestions for developing your thesis on the Honors College Thesis Website
View Examples of Previous Honors Theses

Why is an Internship, Research or Thesis this required?

Since the ENVST major was established, this requirement has been part of the curriculum. Over and over again we have seen proof that these experiences help our students get jobs and connections in the field, help in building resumes, and allow students to apply their academics and interests to experience outside the classroom.

What is an internship vs research vs an honors thesis?

An Internship is a temporary experience where you can work with an organization in order to learn about how that organization works, and focus on a particular project or tasks in order to gain skills in the field.

Research can take many forms – you could be in a lab looking at samples, conducting interviews to collect data from individual perspectives, or helping analyzing numerical data from surveys. Research typically focuses on a particular question or problem that the investigators want to know more about. Students typically join a research project that a faculty member is already running, and will mentor and teach you skills on research techniques.

An Honors Thesis is required of students completing an Honors Degree. It is an in-depth independent study approved by your major’s department, where you work closely with a faculty mentor throughout the semester on research a particular topic. Thesis can range depending on your interest, so for examples we recommend visiting the “ENVST 4999 Honors Thesis” tab.

Can I do an internship or research before this requirement?

Of course! The more experience you have, the better – and we want you to maximize your experiences in college! However, you will not be able to do it for the major requirement until the relevant major perquisites are completed (see course prerequisites at the “Prerequisites for Enrollment” tab on this website). You can do an internship or research without registering for credit beforehand, but if you’d like academic credit, connect with your academic advisor for options.

Can I count an internship or research experience I did previously towards this requirement?

Unfortunately we cannot count a previous experience towards this requirement, as the ENVST course needs to be taken at the same time you’re doing your internship, research, or honors thesis. However, more experience is always helpful for a stronger resume!

Can my internship or research be paid?

We’d love if you found an opportunity that is paid!

Can I count one internship or research experience towards both of my majors?

No, the University does not allow 1 internship or research project to count for multiple academic programs in the same semester. It is also considered plagiarism to count the same internship hours for 2 different courses.

Can I use an internship or research course during Learning Abroad for this requirement?

The U of U needs supervision over this requirement and we need to ensure it meets our requirement for the major, so it is not a transfer course we will accept for the major.

Can I do more than 3 credits?

Yes, students can complete up to 6 credits total, though only 3 are needed for the major. The amount of hours is determined by how many hours you are working at your internship or research. See the Credit Hours Chart on the “Prerequisites for Enrollment tab”

I’m enrolling in a course, but is it actually a course?

ENVST 4800 does have required course assignments throughout the semester to ensure your experience is going well while completing your internship hours, and for professional development. The ENVST 5000 and ENVST 4999 course grades are determined by your faculty mentor.

Was one of your questions not answered? Contact Ally Marringa, the ENVST Internship & Research Coordinator for your specific questions and more details.

K.R. Shyam Sundar: Critical Essays on Labour Codes, Labour Institutions and Labour Market Governance in the Post-Covid-19 Times in India

Synergy Books India, New Delhi, ₹ 1,780

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Janardhan, V. K.R. Shyam Sundar: Critical Essays on Labour Codes, Labour Institutions and Labour Market Governance in the Post-Covid-19 Times in India. Ind. J. Labour Econ. (2024). https://doi.org/10.1007/s41027-024-00476-7

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Democrats grapple with virtual versus in-person formats at national convention

Published: June 05, 2024

Author: Tracy DeStazio

Geoffrey Layman

Department of Political Science

As the Democratic Party prepares for its 2024 Democratic National Convention, scheduled to take place Aug. 19-22 in Chicago, it faces an important question: Should the convention be a largely virtual event, similar to the one held in 2020 during the COVID-19 pandemic, or a largely in-person event like those held prior to 2020?

Some party leaders favor a virtual format to minimize the disruptive effects of protests likely to occur during the convention. The party has already decided to nominate President Joe Biden with a virtual roll call. But other leaders are skeptical of a virtual approach, favoring a traditional event where face-to-face interactions can foster unity among party activists.

A recent survey conducted by a political scientist at the University of Notre Dame provides important insight into this debate. The survey asked the delegates to the 2020 Democratic convention how they felt about the virtual format, which replaced the traditional coverage of in-person speeches to thousands of delegates with celebrity hosts, remote presentations and professionally produced video content.

The survey found that while most of the 2020 delegates considered the virtual convention a success, a large majority of them would prefer not to repeat it this year. Because many of these respondents are likely to be delegates again in 2024, their opinions suggest how well received and perhaps how successful another virtual convention would be.

Professor Layman has salt-and-pepper colored hair, mustache and beard, and wears a dark blue blazer and tie over a white shirt.

Geoff Layman , professor and chair of Notre Dame’s Department of Political Science , along with his collaborators, John Green of the University of Akron and John Jackson of Southern Illinois University, interviewed 554 respondents (21 percent of the 2,500 Democratic delegates whom they contacted) between July 2023 and March 2024.

In a report on their findings , they indicate that 56 percent of the 2020 delegates viewed the virtual experience in a positive light overall, with 27 percent providing a more negative assessment. For 2024, however, nearly 65 percent prefer a largely in-person event; 31 percent prefer to have a hybrid event with an even balance of virtual and in-person elements; and just 4 percent would be happy with a largely virtual event.

Democratic delegates’ views were mixed on specific facets of the 2020 virtual convention. For example, a clear majority of delegates had positive views on the technical innovations employed in conducting the convention, such as holding the roll call of state delegations from scenic locations in each state (69 percent thought the format was successful while 20 percent did not), and incorporating a greater use of celebrities presiding at convention events (53 percent approved of the tactic and 31 percent were not as impressed).

As far as meeting the traditional goals of national conventions, the majority of respondents said the virtual format was successful in persuading independent and swing voters and for conducting regular party business such as approving the platform and rules. The delegates believed the virtual format was less successful when it came to building a strong and cohesive organization to carry out the general election campaign and in generating enthusiasm and excitement among grassroots activists and key constituencies.

Layman believes that the limitations of a virtual convention for building party cohesion and grassroots excitement are the main reasons the 2020 delegates want an in-person 2024 convention. “These delegates are political activists and they like politics,” he said. “And while the 2020 convention was effective in terms of helping them achieve the ultimate goal — winning the election — it didn’t have the side benefits for them of the personal interactions and networking with other political activists.

“Discussing how best to mobilize voters, especially the ones sitting on the fence, and teaming up across counties, states or congressional districts to coordinate activities, training sessions and resources to help local party officials and activists campaign effectively — these are the types of in-person things that go on at the convention and that were missing in 2020.”

According to the report, displeasure with the 2020 virtual convention is concentrated among delegates who are younger than 40 years old and supporters of Sen. Bernie Sanders’ 2020 nomination campaign. Dissenters of 2020’s virtual format also report weaker levels of support for the Democratic Party organization and stronger support for issue and ideological groups.

Overall, the delegates reported giving top priority to six issues: protecting democracy from domestic extremists, reducing economic inequality, fighting climate change, and protecting abortion, minority and LGBTQ+ rights.

“I think our survey results should make Democratic Party officials who are thinking about moving to a virtual convention take pause, because while their activists were pleased with how it worked in 2020, they don’t want to go back to that. And you’ve got to keep them happy, enthusiastic, supportive and mobilized because the elections are going to be very close this year.”

A key reason for some Democratic leaders preferring to host the convention virtually is the potential for Israel-Palestine protests, which are reminiscent of the anti-Vietnam protests that took place during the 1968 Democratic National Convention — also held in Chicago.

But, according to Layman, this year represents a different time, a different war and vastly different local leadership. “The specter of the 1968 convention hangs over this a little bit since the last time we had these sorts of major campus protests against a sitting Democratic president and his foreign policy was in 1968,” Layman explained.

“But the context was completely different in 1968. We were many years into a very unpopular war with people in their 20s getting drafted into the military, and we had an old-style political machine running Chicago with a more aggressive police department confronting protesters. I think the probability of the Democrats having a repeat of 1968 is very low.”

If the convention moves to a hybrid production, the plan would incorporate in-person speeches from Biden and key Democrats as well as pre-recorded testimonials and videos taped from various parts of the country — with the intention of obtaining maximum television and internet coverage while minimizing contentious moments ripe for demonstrators to distract viewers and attendees.

Layman said the Democratic Party may choose to use more rehearsed and professionally produced content, which would give the party more opportunity to manage the narrative. “The more airtime you can control, the better it is for the party,” Layman said.

As the Democrats finalize plans for their 2024 convention format, Layman said these findings matter in the big picture. “I think our survey results should make Democratic Party officials who are thinking about moving to a virtual convention take pause, because while their activists were pleased with how it worked in 2020, they don’t want to go back to that,” he said.

“And you’ve got to keep them happy, enthusiastic, supportive and mobilized because the elections are going to be very close this year.”

Contact: Tracy DeStazio, associate director of media relations, 574-631-9958 or [email protected]

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Democrats grapple with virtual versus in-person formats at national
As the Democratic Party prepares for its 2024 Democratic National Convention, scheduled to take place Aug. 19-22 in Chicago, it faces an important question: Should the convention be a largely virtual event, similar to the one held in 2020 during the COVID-19 pandemic, or a largely in-person event like those held prior to 2020?

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The impact of COVID-19 pandemic on physical and mental health of Asians: A study of seven middle-income countries in Asia

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S2 Table. Physical symptoms resembling COVID-19 infection reported by the participants from seven countries.

S3 Table. Comparison of knowledge related to COVID-19 in participants of the seven countries.

S4 Table. Comparison of precautionary measures related to COVID-19 in the participants of the seven countries.

S5 Table. Comparison of information needs about COVID-19 in the participants of the seven Asian countries.

Honors Theses

Date of Award

Document Type

First Advisor

Third Advisor

Relational Format