Journal Pre-proof

Prevalence of Symptoms of Depression, Anxiety, Insomnia,

Posttraumatic Stress Disorder, and Psychological Distress among
Populations Affected by the COVID-19 Pandemic: A Systematic
Review and Meta-Analysis

Jude Mary Cénat , Camille Blais-Rochette ,

Cyrille Kossigan Kokou-Kpolou , Pari-Gole Noorishad ,
Joana N. Mukunzi , Sara-Emilie McIntee , Rose Darly Dalexis ,
Marc-André Goulet , Patrick Labelle

PII: S0165-1781(20)33260-1
DOI: https://doi.org/10.1016/j.psychres.2020.113599
Reference: PSY 113599

To appear in: Psychiatry Research

Received date: 19 June 2020

Accepted date: 23 November 2020

Please cite this article as: Jude Mary Cénat , Camille Blais-Rochette ,
Cyrille Kossigan Kokou-Kpolou , Pari-Gole Noorishad , Joana N. Mukunzi , Sara-Emilie McIntee ,
Rose Darly Dalexis , Marc-André Goulet , Patrick Labelle , Prevalence of Symptoms of Depression,
Anxiety, Insomnia, Posttraumatic Stress Disorder, and Psychological Distress among Populations
Affected by the COVID-19 Pandemic: A Systematic Review and Meta-Analysis, Psychiatry Research
(2020), doi: https://doi.org/10.1016/j.psychres.2020.113599

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 Covid-19 and Mental Health Problems 1

Running Head: COVID-19 AND MENTAL HEALTH PROBLEMS

Prevalence of Symptoms of Depression, Anxiety, Insomnia, Posttraumatic Stress Disorder, and

Psychological Distress among Populations Affected by the COVID-19 Pandemic: A Systematic
Review and Meta-Analysis

Jude Mary Cénat1*, Camille Blais-Rochette1, Cyrille Kossigan Kokou-Kpolou2, Pari-Gole Noorishad1,
Joana N. Mukunzi1, Sara-Emilie McIntee1, Rose Darly Dalexis3, Marc-André Goulet1, Patrick Labelle1
1
School of psychology, University of Ottawa, Ontario, Canada
2
Department of Psychology University Picardie Jules Verne, Amiens, France
3
School of Industrial Relations, Université de Montréal, Québec, Canada
Word count: 3 826

*Corresponding author:
Jude Mary Cénat
School of Psychology (Clinical) - University of Ottawa
136 Jean-Jacques-Lussier, 4017, Vanier Hall
Ottawa, Ontario, K1N 6N5
Phone: (613) 562-5800
Email: jcenat@uottawa.ca
Highlights

- Infectious disease outbreaks are associated with mental health symptoms and disorders
- Pooled prevalence of depression, anxiety, insomnia, PTSD, and psychological distress were
15.97%, 15.15%, 23,87%, 21.94%, and 13.29%, respectively
- No significant differences were observed for gender, geographical regions, and healthcare
workers (except for insomnia, which was more prevalent among healthcare workers)
- This study provides findings that will guide research and the development of better mental health
programs during and after the pandemic
 Covid-19 and Mental Health Problems 2

Abstract

Objective. We conducted a systematic review and meta-analysis to estimate the pooled

prevalence of depression, anxiety, insomnia, PTSD, and Psychological distress (PD) related to
COVID-19 among affected populations.

Methods. We searched articles in Medline, Embase, APA PsycInfo, CINAHL, Scopus, and Web
of Science. Random-effects meta-analyses on the proportions of individuals with symptoms of
depression, anxiety, insomnia, PTSD, and PD were generated and between-group differences for
gender, healthcare workers (HCWs), and regions where studies were conducted.

Results. A total of 2189 articles were screened, 136 full-text articles were assessed for
eligibility. Fifty-five peer-reviewed studies met inclusion criteria for the meta-analysis
(N=189,159). The prevalence of depression (k=46) was 15.97% (95%CI, 13.24-19.13). The
prevalence of anxiety (k=54) was 15.15% (95%CI, 12.29-18.54). The prevalence of insomnia
(k=14) was 23.87% (95%CI, 15.74-34.48). The prevalence of PTSD (k=13) was 21.94%
(95%CI, 9.37-43.31). Finally, the prevalence of psychological distress (k=19) was 13.29%
(95%CI, 8.80-19.57). Between-group differences were only found in HCWs (z=2.69, p < .05)
who had a higher prevalence of insomnia than others.

Conclusions. Findings suggest that the short-term mental health consequences of COVID-19 are
equally high across affected countries, and across gender. However, reports of insomnia are
significantly higher among HCWs than the general population.

Keywords: COVID-19; Depression; Anxiety; Insomnia; Posttraumatic Stress Disorder;

Psychological Distress; Systematic review with meta-analysis
 Covid-19 and Mental Health Problems 3

1. Introduction

On March 11, 2020, the World Health Organization (WHO) officially declared the
Coronavirus disease 2019 (COVID-19, also known as SARS-CoV-2) outbreak as a pandemic
(World Health Organization, 2020). This pandemic provoked unprecedented public health
measures aimed at preventing the spread of the virus: confinement of more than half of the
world’s population, closure of schools and universities, social and physical distancing, and the
declaration of health emergency in many countries (Jernigan, 2020; Prem et al., 2020; Qiu et al.,
2020). On November 14, 2020, more than 53,78 million confirmed cases of COVID-19 were
identified worldwide, causing more than 1,3 million deaths (John Hopkins University, 2020).

Previous studies have shown that infectious disease outbreaks are associated with mental
health symptoms and disorders (e.g., depression, anxiety, posttraumatic stress disorder,
insomnia) in survivors, family members, healthcare workers (HCW), and members of affected
communities (Cénat et al., 2020b, 2020d; Keita et al., 2017; Lehmann et al., 2015; Mohammed et
 Covid-19 and Mental Health Problems 4

al., 2015). A meta-analysis has shown the major consequences of Ebola disease on mental health
(Cénat et al., 2020b). Although having a lower fatality case rate than Ebola, this pandemic is
associated with considerable deaths worldwide and studies conducted among affected
populations have shown major risk factors for the mental health of affected populations (Cénat et
al., 2021; Lai et al., 2020; Lee et al., 2020; Lei et al., 2020; Guo Li et al., 2020; Xingxing Li et
al., 2020; Yuchen Li et al., 2020; Yun Li et al., 2020; N. Liu et al., 2020; Lu et al., 2020; Mazza
et al., 2020; Moccia et al., 2020a; Moghanibashi-Mansourieh, 2020; Nguyen et al., 2020). These
factors include anxiety and stress associated with the risk of being infected, death of loved ones,
infection of loved ones, containment measures, social isolation and loneliness, physical and
emotional fatigue of HCW, massive job loss, financial insecurity and poverty, excessive
consumption of information from the media, and the vulnerability of certain groups in high-
income countries (HICs) and low- and middle-income countries (LMICs) (Ahmed et al., 2020;
Al-Rabiaah et al., 2020; Bo et al., 2020; Cai et al., 2020; Cao et al., 2020; Cénat, 2020a; Cénat et
al., 2021; Chen et al., 2020; Chew et al., 2020; Du et al., 2020; Gao et al., 2020; F. Hao et al.,
2020; X. Hao et al., 2020; Huang and Zhao, 2020; Lai et al., 2020; Lee et al., 2020; Lei et al.,
2020; Moccia et al., 2020a; Moghanibashi-Mansourieh, 2020; Nguyen et al., 2020; Pappa et al.,
2020a; Rogers et al., 2020). These studies and others also revealed that all these elements
constitute risk factors can contribute to mental health problems such as anxiety, depression,
insomnia, somatization, social phobia, PTSD, OCD, self-harm, and suicidal ideations and
behaviors (Cao et al., 2020; Cénat, 2020a; Cénat et al., 2021; Du et al., 2020; Gao et al., 2020; F.
Hao et al., 2020; X. Hao et al., 2020; Huang and Zhao, 2020; Lai et al., 2020; Lee et al., 2020;
 Covid-19 and Mental Health Problems 5

Lei et al., 2020; Moghanibashi-Mansourieh, 2020; Nguyen et al., 2020; Pappa et al., 2020a;
Rogers et al., 2020).

A systematic review and meta-analysis on different coronaviruses (SARS, MERS, and

SARS-Cov2) showed that 14 to 61% of infected individuals face serious psychiatric and
neuropsychiatric problems (such as depression, impaired memory, insomnia and sleep disorders,
anxiety, and PTSD, etc.) during the illness, and 14.8 to 76.9% afterwards (Rogers et al., 2020).
On May 8, 2020, a meta-analytic review conducted on COVID-19 HCW in Asian countries
examined anxiety, depression, and insomnia (Pappa et al., 2020a). Estimates of the pooled
prevalence was 23.20% for anxiety, 22.8% for depression, and 34.32% for insomnia. These
results can be explained by the stressors and anxieties faced by HCW in their work environment,
including the fear of being infected and of infecting their loved ones or colleagues, the rapid
deaths of patients, as well as emotional and physical fatigue. It also showed the need for
systematic reviews on the general population to develop and implement both prevention and
intervention mental health programs based on initial evidence. Another systematic review
showed that relative high rate of anxiety, depression, posttraumatic stress disorder and
psychological distress symptoms among population affected by COVID-19 in multiple countries
(Xiong et al., 2020).

Conducted in a global mental health perspective, the main objective of this systematic
review and meta-analysis is to analyze the impacts of the COVID-19 pandemic on the mental
health of affected populations to help develop and implement mental health programs based on
initial evidence. Specifically, it aims to (1) analyze the pooled prevalence of depression, anxiety,
insomnia, PTSD, and psychological distress (PD) in the general population; (2) examine
 Covid-19 and Mental Health Problems 6

differences in the pooled prevalence of these problems among HCW compared to the general
population; (3) analyze gender-based differences in the pooled prevalence of investigated mental
health problems; and (4) as the pandemic has disproportionately affected different parts of the
world, this systematic review also aims to analyze differences in mental health problems
according to the geographical regions in which the studies were conducted.

2. Methods

This meta-analysis follows methods described in the Cochrane Handbook for Systematic
Reviews of Interventions (Higgins et al., 2019) as well as guidelines presented in the Preferred
Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Moher et al.,
2009).

2.1. Protocol and Registration

We registered this meta-analysis with PROSPERO (#BLINDED FOR REVIEW) to avoid

unnecessary replication.

2.2. Identification and Selection of Studies

This meta-analysis focuses on mental health consequences of the COVID-19 pandemic.

Scholarly journal articles that reported prevalence for mental health disorders or symptoms were
selected. A social sciences research librarian with experience in planning systematic reviews
assisted in drafting, developing, and implementing a search strategy to find pertinent published
articles in APA PsycInfo (Ovid), Medline (Ovid), Embase (Ovid), CINAHL (Ebsco), Scopus,
and Web of Science. The search strategy itself was designed, in part, by examining reviews
 Covid-19 and Mental Health Problems 7

related to COVID-19 (Lalonde, 2020; Nussbaumer-Streit et al., 2020) and reviews focused on
psychological distress (Thekkumpurath et al., 2008; Wade et al., 2016), by consulting COVID-
19 search strategies used by other information professionals and compiled by the Medical
Library Association (Nussbaumer-Streit et al., 2020), and through discussions with members of
the research team. The final search strategy includes pertinent keywords and was executed on
May 12, 2020. No limits or restrictions were used in any of the database searches (the complete
search strategy is available as supplementary material). Some authors were contacted by email to
obtain clarifications or additional information on their article.

2.3. Inclusion and Exclusion Criteria

Published peer-reviewed journal articles were included if they met the following criteria:
(1) were published in either French or English, (2) had empirical data on the prevalence of
mental health symptoms or disorders collected during the COVID-19 pandemic. There were no
restrictions in terms of age or the type of population studied (e.g., HCW, patients, non-patients).

2.4. Steps for Selection

A total of 4572 references were identified across all six databases and were imported into
CovidenceTM. Pairs of coders (CKKK, PGN, JNM, RDD, SEM, JMC) were involved in all
selection steps (e.g., sorting of articles, data extraction, assessment of quality). Each pair of
coders was responsible for half of the articles at each step of the process. Disagreements in
screening and coding within a team were resolved by discussion between the two coders. Once
duplicates were removed after importing references in CovidenceTM, the titles and abstracts of
2189 references were screened. Of these 2189, 130 full-text references were screened. Following
 Covid-19 and Mental Health Problems 8

this step, a total of 60 articles were included and 46 articles passed the quality evaluation step.
Four additional articles that were published after the initial search were added to the final pool of
articles. Five articles were found in the reference list of a previous meta-analysis on COVID-19
(Pappa et al., 2020b). The present meta-analysis is based on a total of 55 articles. From these, 68
independent samples or sub-samples were kept for the meta-analysis. The screening process is
recorded in the PRISMA chart (Figure 1).

2.5. Data Extraction and Management

Sample characteristics of the 68 independent samples included in the meta-analysis are

summarized in Table 1 and were the following: author names, month of publication (all articles
were submitted or published in 2020, except for the samples that were sent by email to the team),
gender, country, type of sample (general population or HCW), assessment tools used for
depression, anxiety, insomnia, psychological distress, and PTSD.

2.6. Quality Assessment

We used the Joanna Briggs Institute (JBI) checklist for prevalence studies (Martin, 2017)
to evaluate the quality of the 68 retained independent samples. The evaluation criteria were: (1)
appropriateness of the sample frame; (2) recruitment procedure; (3) adequacy of the sample size;
(4) description of subjects and setting; (5) coverage of the identified sample; (6) validity of the
methods used to identify the mental health symptoms or disorders; (7) reliability of the methods
used to identify mental health symptoms or disorders; (8) adequacy of statistical analyses; and
(9) response rate. Articles were assigned one point per criterion met, for a maximum of 9 points.
Articles were excluded if their total score was less than 5 points (no included articles received a
 Covid-19 and Mental Health Problems 9

rating lower than 5). There were 55 articles remaining after this step and 14 articles were
removed because they had less than 5 out of 9 on the JBI checklist.

2.7. Meta-analysis

Random effects meta-analyses were generated based on the proportions of individuals

with symptoms or disorders (depression, anxiety, insomnia, psychological distress, and PTSD)
among samples of people affected by the COVID-19 pandemic using the “9etaphor” package in
R Version 4 (Viechtbauer, 2010). Random effects account for the heterogeneity among the studies.
Logit transformed proportions were used and transformed back for ease of interpretation into a
forest plot. The binomial-normal model was indicated as it gives unbiased estimates and a good
coverage of confidence intervals for meta-analyses with proportions (Hamza et al., 2008; Stijnen et
al., 2010).

3. Results

The prevalence of mental health symptoms/disorders (depression, anxiety, insomnia,

PTSD, psychological distress) were analyzed in 68 independent samples (N=189,159). Most
studies were conducted in China (k= 45) and on the general population (k=41), the rest of the
studies were on other countries and on HCW respectively. The data allowed for comparisons
between the general population and HCW for all the mental health symptoms and for
comparisons between male and female genders and geographical regions (China and other
countries) for depression and anxiety.
 Covid-19 and Mental Health Problems 10

3.1. Depression

Figure 2A shows a forest plot of the pooled prevalence of depression in people during the
COVID-19 pandemic (k=46, N=105,468). The pooled prevalence of depression among
participants is 15.97% CI 95% [13.24%;19.13%]. The Kendall’s tau rank order correlation is not
significant (rτ= -.01, p>.05), indicating an absence of asymmetry in the funnel plot. This result
provides evidence that there is no publication bias in the present meta-analysis. There is
heterogeneity in the results (I2 = 99.44) (Higgins et al., 2003). Figure 2A shows that there are no
differences in the prevalence of depression between citizens (k=28, 17.05, 95% CI
[13.03;22.01]) and HCW (k=18,13.75, 95% CI [11.04;16.96]), (z = -1.24, p > .05). Figure 2B
shows that there is no difference in the prevalence of depression in studies conducted in China
(k=34, 16.23, 95% CI [13.02;20.04]) compared to studies conducted in other countries (k=12,
16.92, 95% CI [11.78;23.70]), (z = .20, p > .05). Figure 2C indicates that there are no differences
in the prevalence of depression between males (k=9,19.05, 95% CI [11.17;30.57]) and females
(k=9, 22.93, 95% CI [15.16;33.14]), (z = -0.57, p > .05).

3.2. Anxiety

Figure 3A shows a forest plot of the pooled prevalence of anxiety in people during the
COVID-19 pandemic (k=54, N= 121,373). The pooled prevalence of anxiety among participants
is 15.15% CI 95% [12.29%;18.54%]. The Kendall’s tau rank order correlation is not significant
(rτ= -.20, p<.05), indicating the presence of asymmetry in the funnel plot. This result provides
evidence of publication bias in the present meta-analysis. There is heterogeneity in the results (I2
= 99.58) (Higgins et al., 2003). Figure 3A indicates that there are no differences in the prevalence
 Covid-19 and Mental Health Problems 11

of anxiety between citizens (k=31, 14.62, 95% CI [10.69;19.69]) and HCW (k=23, 15.86, 95%
CI [12.22;20.33]), (z = 0.40, p > .05). Figure 3B shows that there is no difference in the
prevalence of anxiety in studies conducted in China (k=33, 13.49, 95% CI [9.90;18.11])
compared to studies conducted in other countries (k=18, 19.02, 95% CI [15.01;23.80]), (z = 1.78,
p > .05). However, we might lack statistical power to detect a difference between the two groups.
Figure 3C shows that there are no differences in the prevalence of anxiety between males (k=6,
14.19, 95% CI [7.14;26.23]) and females (k=6, 17.87, 95% CI [9.64;30.73]), (z = -0.51, p > .05).

3.3. Insomnia

Figure 4A shows a forest plot of the pooled prevalence of insomnia in people during the
COVID-19 pandemic (k=14, N= 42,169). The pooled prevalence of insomnia among participants
is 23.87% CI 95% [15.74%;34.48%]. The Kendall’s tau rank order correlation is not significant
(rτ= -.12, p>.05), which indicates that there is no asymmetry in the funnel plot. This result
provides evidence that there is no publication bias in the present meta-analysis. There is
heterogeneity in the results (I2 = 99.73) (Higgins et al., 2003). Figure 4A indicates a difference in
the prevalence of insomnia between citizens (k=8, 16.45, 95% CI [8.39;29.74]) and HCW (k=6,
36.52, 95% CI [32.99;40.20]), (z = 2.69, p < .05). HCW have a higher prevalence of insomnia
than citizens.

3.4. Posttraumatic stress disorder (PTSD)

Figure 4B shows a forest plot of the pooled prevalence of PTSD in people during the
COVID-19 pandemic (k=13, N=30,449). The pooled prevalence of PTSD among participants is
21.94% CI 95% [9.37%;43.31%]. The Kendall’s tau rank order correlation is not significant (rτ=
 Covid-19 and Mental Health Problems 12

-.08, p>.05), which indicates that there is no asymmetry in the funnel plot. This result provides
evidence that there is no publication bias in the present meta-analysis. There is heterogeneity in
the results (I2 = 99.85) (Higgins et al., 2003). Figure 4B shows no difference in the prevalence of
PTSD between citizens (k=9, 22.43, 95% CI [7.62;50.32]) and HCW (k=4, 20.91, 95% CI
[5.01;57.00]), (z = -.09, p > .05).

3.5. Psychological Distress

Figure 4C shows a forest plot of the pooled prevalence of psychological distress in people
during the COVID-19 pandemic (k=19, N=68,155). The pooled prevalence of psychological
distress among participants is 13.29% CI 95% [8.80%;19.57%]. The Kendall’s tau rank order
correlation is not significant (rτ= -.08, p>.05), indicating an absence of asymmetry in the funnel
plot. This result provides evidence that there is no publication bias in the present meta-analysis.
There is heterogeneity in the results (I2 = 99.60) (Higgins et al., 2003). Figure 4C indicates no
difference in the prevalence of psychological distress between citizens (k=10, 10.19, 95% CI
[4.63;20.96]) and HCW (k=9, 16.88, 95% CI [13.02;21.61]), (z = 1.27, p > .05).

4. Discussion
Conducted with a global mental health perspective, the objective of this systematic
review and meta-analysis was to analyze the impacts of COVID-19 on the mental health of
affected populations to help implement programs based on initial evidence. The results showed
that the most studied mental health problems during COVID-19 are depression, anxiety,
insomnia, PTSD, and PD. We conducted meta-analyses on the prevalence of these five mental
 Covid-19 and Mental Health Problems 13

health problems. This meta-analysis includes 68 independent samples and sub-samples that
indicate that pandemic-affected populations have significantly higher prevalence of depression,
anxiety, insomnia, PTSD, and PD compared to the general population under normal
circumstances. First, compared to what was observed in the latest WHO study on common
mental health disorders, prevalence of depression in populations affected by COVID-19 is more
than three times higher (15.97%) than in the general population (4.4%); while it is four times
higher for anxiety (15.15% vs. 3.6%); and five times higher for PTSD (21.94% vs. 4%) (Kessler
et al., 2017; Liu et al., 2017; World Health Organization, 2017). These prevalence rates are also
higher than those usually observed in the general population (Atwoli et al., 2015; Dorrington et
al., 2014; Grove et al., 2011; Guo et al., 2016; Kessler et al., 2017; Liu et al., 2017; Slade et al.,
2011; Stein et al., 2017; Vilagut et al., 2016; Weinberger et al., 2018; World Health
Organization, 2017). Results also showed significantly higher prevalence of insomnia and PD in
populations affected by COVID-19 compared to the general population (Cao et al., 2017; Ford et
al., 2015; Jiang et al., 2015; Mojtabai and Jorm, 2015; Nishi et al., 2018; Slade et al., 2011).
These high prevalence rates can be explained by the fear associated with the pandemic,
containment measures, high numbers of people infected, and deaths (Moghanibashi-Mansourieh,
2020; Ohayon, 2002; Rogers et al., 2020). Additionally, the pandemic is associated with a lack of
control among infected people, job losses, wage losses, and uncertainty about the future (Nicola
et al., 2020).
The second objective of this study was to compare mental health problems between
HCW and other populations affected by COVID-19. Results showed that there were no
significant differences in depression, anxiety, PTSD, and PD. These results are consistent with
 Covid-19 and Mental Health Problems 14

previous studies that have shown that during epidemics and crises (e.g., SARS, Ebola), HCW
generally have the same level or fewer mental health problems than community members (Cénat
et al., 2020b, 2020d, 2020c; Lancee et al., 2008; Lehmann et al., 2015; Pappa et al., 2020b).
However, longitudinal studies need to be conducted to determine whether this non-differentiation
between HCW and the general population is related to temporary coping strategies associated
with being on the front lines. After the pandemic ends, HCW may develop more severe mental
health problems. For example, the prevalence of insomnia that is more than two times higher
among HCW is a predictor of depression and suicidal ideation (Cukrowicz et al., 2006).
The third objective of this study was to test for gender differences in the prevalence of
mental health problems. The data allowed comparisons for depression and anxiety. While a
higher prevalence of anxiety and depression was expected in females, surprisingly, there were no
gender differences. Available data have not always allowed for the evaluation of gender
differences during past epidemics (Cénat et al., 2020d). Studies conducted during this pandemic
have shown that males and females experience stressors in similar ways (Cao et al., 2020).
Studies conducted in China, both with very large and small samples, have also found no gender
differences (Cao et al., 2020; Chen et al., 2020; Huang and Zhao, 2020). However, studies in the
Middle East and the West have shown that women are at greater risk of developing mental health
problems during COVID-19 (Mazza et al., 2020; Moccia et al., 2020b; Moghanibashi-
Mansourieh, 2020). These observations should be investigated longitudinally because
confirmation of this pattern could lead to questions about the association between cultural gender
roles and the development of mental health problems.
 Covid-19 and Mental Health Problems 15

As the pandemic has disproportionately affected different parts of the world, the final
objective of this study was to analyze differences in mental health problems according to the
regions in which the studies were conducted. We wanted to compare studies from Asia, Europe,
and North America. Since most of the studies were from China, we were only able to analyze
differences between China and other countries as a whole, and only for depression and anxiety.
The global nature of this pandemic offers the possibility of analyzing the phenomenology of
psychopathology between countries.

5. Limitations
While this study provides findings that will guide research and the development of
better mental health programs during and after the pandemic, it has some limitations. The first is
that the pandemic is still ongoing. Articles are written quickly and do not always document
essential aspects that would allow us to analyze differences between groups. In addition, new
publications are published daily, but this study was necessary to allow mental health programs to
be developed based on early evidence. The second limitation of this study is that most of the
published research comes from China. This is because China is the first country to have faced the
pandemic. Also, although we only retained studies with high cut-off scores and valid measures, a
large heterogeneity was found in the results. A recent meta-analysis on mental health problems
in populations affected by Ebola disease and others on HCW during the COVID-19 pandemic
had a similar finding (Cénat et al., 2020b; Pappa et al., 2020b; Xiong et al., 2020). The
disproportionate spread of COVID-19, associated consequences, and differences between scales
used to measure mental health problems are all factors that may explain this heterogeneity.
 Covid-19 and Mental Health Problems 16

Moreover, very few studies have been conducted among survivors of COVID-19, especially
those who developed severe symptoms. These studies could have allowed for an analysis of
probable differences within groups affected by COVID-19. Finally, the lack of studies in low-
and middle-income countries prevents a more global perspective in this study.

6. Future Directions
The greatest strength of this study is that it identifies a range of avenues for future
research. First, this article shows the need for longitudinal studies to better understand the
impacts of COVID-19 on survivors, gender, geographical regions, etc. Second, these studies
should also analyze socio-demographic characteristics to highlight the differences that may exist
between groups, and identify those most at risk to facilitate the development of programs based
on their specific needs. Also, studies should explore mental health problems specifically among
HCW on a longitudinal basis, while comparing with the rest of the population. This will allow us
to observe whether being in the heat of the moment acts as a protective factor in the short term
and in the long term, HCW present more health problems than the rest of the population. Future
studies should also pay special attention to survivors, especially those who have developed
severe symptoms or who have been on artificial ventilators. Finally, studies should also analyze
whether differences exist depending on the measures used to assess mental health problems. This
will help identify the best tools to accurately measure mental health problems.

7. Conclusions
 Covid-19 and Mental Health Problems 17

This study shows that regardless of gender, group or region, the current pandemic is
impacting the mental health of affected populations. Indeed, all groups have a high prevalence of
depression, anxiety, insomnia, PTSD, and PD. Thus, this study provides initial evidence for the
implementation of mental health prevention and intervention programs that provide holistic care
to affected individuals. Special attention must be paid to infected individuals and those who have
developed severe symptoms to make healthcare as minimally traumatic as possible for them and
their families, while respecting measures to prevent the spread of the virus. Also, programs must
be developed quickly for HCW to address the mental health problems associated with the
pandemic and to prevent them in the long term.
Finally, research is necessary to identify and document all aspects of the pandemic that
impact mental health including social inequalities, the vulnerability of children and adolescents,
the resilience of LMICs, confinement, traumatic characteristics of COVID-19-related deaths
(Bhopal, 2020; Cénat, 2020a, 2020b; Cénat et al., 2020a; Cénat and Dalexis, 2020; Dalexis and
Cénat, 2020; Holmes et al., 2020; Kokou-Kpolou et al., 2020; Zhenyu Li et al., 2020; Xiong et
al., 2020). Research must help build more resilient populations and healthcare systems in the
face of epidemics by providing sufficient evidence to develop both surveillance, prevention and
intervention programs during and after this worldwide crisis (Cénat, 2020c; Collin-Vézina et al.,
2020; Holmes et al., 2020; S. Liu et al., 2020).
Declaration of interest

No conflict of interest for any author.

Funding
 Covid-19 and Mental Health Problems 18

None

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Authors Mont Tot Gen Coun Samp Depres Anxiety Insom PTSD Psychol Qualit
h of al der try le sion Assess nia Assess ogical y
Public Sa Assess ment Asses ment Distres Evalua
ation mpl ment sment s tion
e Assess
Size ment

Ahmed April 107 46.8 Chin Gene Beck Beck 9

et al. 4 % a ral Depres Anxiety
Popul sion Invent
ation Invento ory
ry (BDI) (BAI)
 Covid-19 and Mental Health Problems 33

Al- Januar 174 53.2 Chin Gene Genera 8

Rabiaa y % a ral l
h et al. Popul Anxiety
ation Disord
er 7-
item
(GAD-
7)

Bo et March 714 50.9 Chin Gene PTSD 6

al. % a ral Checkli
Popul st–
ation Civilian
Versio
n (PCL-
C)

Cai et April 152 75.5 Chin HCW Sympto 8

al. 1 % a m
Check-
List 90
(SCL-
90)

Cao et March 714 69.6 Chin Gene Genera 9

al. 3 5% a ral l
Popul Anxiety
ation Disord
er 7-
item
(GAD-
7)
 Covid-19 and Mental Health Problems 34

Casagra May 229 74.6 Italy Gene Genera Pittsb PTSD Psychol 9
nde et 1 % ral lized urgh Checkli ogical
al. Popul Anxiety Sleep st for Genera
ation Disord Qualit DSM-5; l Well-
er y PCL-5 Being
scale Index questio
(GAD- (PSQI) nnaire
7) (PGWB
)

Chen et March 105 90.5 Chin HCW Self- Self- 7

al. % a Rating Rating
Depres Anxiety
sion Scale
Scale (SAS)
(SDS)

Chew April 906 64.3 India HCW Depres Depres Impact 9

et al. % & sion sion of
Sing Anxiety Anxiety Events
apor Stress Stress Scale-
e Scales Scales Revise
(DASS- (DASS- d (IES-
21) 21) R)

Du et March 134 60.5 Chin HCW Beck Beck 7

al. (a) % a Depres Anxiety
sion Invent
Invento ory
ry (BDI) (BAI)

Du et April 134 60.5 Chin HCW Beck Beck 8

al. (b) % a Depres Anxiety
 Covid-19 and Mental Health Problems 35

sion Invent
Invento ory
ry-II (BAI)
(BDI-II)

Gao et April 487 67.7 Chin Gene WHO- Genera 9

al. 2 % a ral Five l
Popul Well- Anxiety
ation Being Disord
Index er 7-
(WHO- item
5) (GAD-
7)

Guo et March 111 74.8 Chin HCW Self- Self- 9

al. 18 % a Rating Rating
Depres Anxiety
sion Scale
Scale (SAS)
(SDS)

Hao, J. Febru 504 52.4 Chin Gene Kessler 7

et al. ary % a ral 6-Item
Popul (K-6)
ation Psychol
ogical
Distres
s Scale

Hao, F. April 185 64.3 Chin HCW Depres Depres Insom Impact 9
et al. % a sion, sion, nia of
Anxiety Anxiety Severi Event
and and ty Scale-
 Covid-19 and Mental Health Problems 36

Stress Stress Index Revise

Scale Scale (ISI) d (IES-
(DASS- (DASS- R)
21) 21)

Huang March 723 54.6 Chin Gene Pittsb 9

& Zhao 6 % a ral urgh
Popul Sleep
ation Qualit
y
Index
(PSQI)

Kokou- May 556 75.5 Fran Gene Insom 9

Kpolou % ce ral nia
et al. Popul Severi
ation ty
Index

Lai et March 125 76.7 Chin Gene 9-item Genera 7- Impact 9

al. 7 % a ral Patient l item of
Popul Health Anxiety Insom Event
ation Questio Disord nia Scale-
nnaire er 7- Severi Revise
(PHQ-9) item ty d (IES-
(GAD- Index R)
7)

Lee, April 123 45.1 Unit Gene 9-item Genera 8

Jobe, & 7 % ed- ral Patient l
Mathis Wo State Popul Health Anxiety
men s ation Questio Disord
, nnaire er 7-
 Covid-19 and Mental Health Problems 37

0.3 (PHQ-9) item

% (GAD-
Oth 7)
er

Lei et April 159 61.3 Chin Gene Self- Self- 9

al. 3 % a ral Rating Rating
Popul Depres Depres
ation sion sion
Scale Scale
(SDS) (SDS)

Li, G. et May 436 100 Chin HCW 9-item Genera 9

al. 9 % a Patient l
Health Anxiety
Questio Disord
nnaire er 7-
(PHQ-9) item
(GAD-
7)

Li, X. et May 948 76.8 Chin HCW Athen 9

al. % a s
Insom
nia
Scale
(AIS)

Li, May 144 N/A Chin Gene Kessler 9

Yuchen 2 a ral 6-Item
et al. Popul (K-6)
ation Psychol
ogical
 Covid-19 and Mental Health Problems 38

Distres
s Scale

Li, Yun May 363 63% Chin Gene 9-item Genera Insom 9
et al. 7 a ral Patient l nia
Popul Health Anxiety Severi
ation Questio Disord ty
nnaire er 7- Index
(PHQ-9) item (ISI)
(GAD-
7)

Liu, N. March 285 54.4 Chin Gene PTSD 9

et al. % a ral Checkli
Popul st for
ation DSM-5
(PCL-5)

Liu, C. March 512 84.6 Chin HCW Zung 9

et al. % a Self-
rating
Anxiety
Scale
(SAS)

Liu, Z. May 467 82.3 Chin HCW Zung WHO 9

et al. 9 % a Self- 20-
rating item
Depres Self-
sion Reporti
Scale ng
(SDS) Questi
onnair
 Covid-19 and Mental Health Problems 39

e (SRQ-
20)

Lu et al. April 204 77.9 Chin HCW Hamilto Hamilt 7

(A) 2 % a n on
Depres Anxiety
sion Scale
Scale

Lu et al. April 257 75.5 Chin HCW Hamilto Hamilt 7

(B) % a n on
Depres Anxiety
sion Scale
Scale

Mazza May 276 71.6 Italy Gene Depres Depres 8

et al. 6 % ral sion, sion,
Popul Anxiety Anxiety
ation and and
Stress Stress
Scale- Scale-
21 21
(DASS-
21)

Moccia April 500 59.6 Italy Gene Kessler 7

et al. % ral 10-
Popul item
ation Psychol
ogical
Distres
s Scale
(K-10)
 Covid-19 and Mental Health Problems 40

Mogha April 107 65.8 Iran Gene Depres 8

nibashi- 54 % ral sion,
Manso Popul Anxiety
urieh ation and
Stress
Scale-
21

Nguyen March 394 55.7 Vietn Gene Patient 9

et al. 7 % am ral Health
Popul Questio
ation nnaire
9-item
(PHQ-9)

Ni et al. May 214 68.8 Chin HCW Patient Genera 8

(A) % a Health l
Questio Anxiety
nnaire Disord
2-item er 2-
(PHQ-2) item
(GAD-
2)

Ni et al. May 157 60.8 Chin Gene Patient Genera 8

(B) 7 % a ral Health l
Popul Questio Anxiety
ation nnaire Disord
2-item er 2-
(PHQ-2) item
(GAD-
2)
 Covid-19 and Mental Health Problems 41

Ozamiz April 976 81.1 Spai Gene Depres 8

- % n ral sion,
Etxebar Popul Anxiety
ria ation and
Stress
Scale-
21
(DASS-
21)

Ozdin May 343 49.2 Turk Gene Hospita Hospit 8

et al. % ey ral l al
Popul Anxiety Anxiety
ation and and
Depres Depres
sion sion
Scale Scale
(HADS) (HADS)

Qi et al. March 130 80.4 Chin HCW Athen 9

6 % a s
Insom
nia
Scale
(AIS)

Qiu et March 527 64.7 Chin Gene COVID- 7

al. 30 3% a ral 19
Popul Pertitra
ation umatic
Distres
s Index
 Covid-19 and Mental Health Problems 42

(CPDI)

Rossi et May 181 79.6 Italy Gene 9-item Genera 7- Global 9

al. 47 % ral Patient l item Psycho
Popul Health Anxiety Insom trauma
ation Questio Disord nia Screen,
nnaire er 7- Severi post-
(PHQ-9) item ty trauma
(GAD- Index tic
7) (ISI) stress
sympto
ms
subscal
e (GPS-
PTSS)

Shacha April 338 58.6 Israe HCW Kessler 6

m et al. % l 6-item
Psychol
ogical
Distres
s Scale
(K-6)

Tan et April 470 68.3 Sing HCW Depres Depres Impact 8

al. (a) % apor sion, sion, of
e Anxiety Anxiety Events
and and Scale-
Stress Stress Revise
Scale- Scale- d (IES-
21 21 R)
(DASS- (DASS-
 Covid-19 and Mental Health Problems 43

21) 21)

Tan et April 673 25.6 Chin Gene Depres Depres Insom Impact 8
al. (b) % a ral sion, sion, nia of
Popul Anxiety Anxiety Severi Events
ation and and ty Scale-
Stress Stress Index Revise
Scale- Scale- (ISI) d (IES-
21 21 R)
(DASS- (DASS-
21) 21)

Tang et May 248 61.4 Chin Gene Patient PTSD 8

al. 5 % a ral Health Checkli
Popul Questio st
ation nnaire Civilian
9-item (PCL-C)
(PHQ-9)

Wang, March 600 55.5 Chin Gene Self- 9

Y. et al. % a ral rating
Popul anxiety
ation scale
(SAS)

Wang, April 130 67.3 Chin Gene Depres Depres 8

C. et al. 4 % a ral sion, sion,
(a) Popul Anxiety Anxiety
ation and and
Stress Stress
Scale Scale
(DASS- (DASS-
21) 21)
 Covid-19 and Mental Health Problems 44

Wang, March 121 67.3 Chin Gene Depres Depres Impact 7

C. et al. 0 % a ral sion, sion, of
(b) Popul Anxiety Anxiety Events
ation and and Scale-
Stress Stress Revise
Scale- Scale- d (IES-
21 21 R)
(DASS- (DASS-
21) 21)

Wang, May 123 90% Chin HCW Self- Pittsb 9

S. et al. a rating urgh
anxiety sleep
scale qualit
(SAS) y
index
(PSQI)

Xie et April 178 43.3 Chin Gene Screen 9

al. 4 % a ral for
Popul Child
ation Anxiety
Relate
d
Emotio
nal
Disord
ers

Zhang, Unpu 240 Boliv HCW Genera Unpu

S. blishe ia l blishe
(Bolivia d Anxiety d
sampl Disord sampl
 Covid-19 and Mental Health Problems 45

) e sent er 7- e sent
by item by
autho (GAD- autho
r 7) r

Zhang, Unpu 252 Ecua HCW Genera Unpu

S. blishe dor l blishe
(Ecuad d Anxiety d
or) sampl Disord sampl
e sent er 7- e sent
by item by
autho (GAD- autho
r 7) r

Zhang, Unpu 521 Iran Gene Patient Genera Unpu

S. (Iran) blishe ral Health l blishe
d Popul Questio Anxiety d
sampl ation nnaire Disord sampl
e sent 9-item er 7- e sent
by (PHQ-9) item by
autho (GAD- autho
r 7) r

Zhang, Unpu 304 Iran HCW Patient Genera Unpu

S. blishe Health l blishe
(Iran2) d Questio Anxiety d
sampl nnaire Disord sampl
e sent 9-item er 7- e sent
by (PHQ-9) item by
autho (GAD- autho
r 7) r

Zhang, Unpu 139 Iran Gene Patient Genera Unpu

 Covid-19 and Mental Health Problems 46

S. blishe ral Health l blishe

(Iran3) d Popul Questio Anxiety d
sampl ation nnaire Disord sampl
e sent 9-item er 7- e sent
by (PHQ-9) item by
autho (GAD- autho
r 7) r

Zhang , Unpu 655 Mala Gene Genera Unpu

S.(Mala blishe ysia ral l blishe
ysia) d Popul Anxiety d
sampl ation Disord sampl
e sent er 7- e sent
by item by
autho (GAD- autho
r 7) r

Zhang, Unpu 474 Mult Gene Patient Genera 0 Unpu

S. blishe i- ral Health l blishe
(middle d coun Popul Questio Anxiety d
) sampl tries ation nnaire Disord sampl
e sent 9-item er 7- e sent
by (PHQ-9) item by
autho (GAD- autho
r 7) r

Zhang, Unpu 629 Pakis HCW Genera 0 Unpu

S. blishe tan l blishe
(Pakista d Anxiety d
n) sampl Disord sampl
e sent er 7- e sent
by item by
autho (GAD- autho
 Covid-19 and Mental Health Problems 47

r 7) r

Zhang, Unpu 220 Peru HCW Genera 0 Unpu

S. blishe l blishe
(Peru) d Anxiety d
sampl Disord sampl
e sent er 7- e sent
by item by
autho (GAD- autho
r 7) r

Zhang, Unpu 182 Mult Gene Patient Genera 0 Unpu

S. blishe i- ral Health l blishe
(senior) d coun Popul Questio Anxiety d
sampl tries ation nnaire Disord sampl
e sent 9-item er 7- e sent
by (PHQ-9) item by
autho (GAD- autho
r 7) r

Zhang, May 304 58.6 Iran HCW Patient Patient Kessler 6

S. et al. % Health Health 6-item
(a) Questio Questi Psychol
nnaire onnair ogical
4-item e 4- Distres
(PHQ-4) item s Scale
(PHQ- (K-6)
4)

Zhang, March 263 59.7 Chin Gene Impact 7

Y. et al. % a ral of
Popul Events
ation Scale-
 Covid-19 and Mental Health Problems 48

Revise
d (IES-
R)

Zhang, April 218 64.2 Chin HCW Patient Insom 8

W.-R. 2 % a Health nia
et al. Questi Severi
onnair ty
e 4- Index
item (ISI)
(PHQ-
4)

Zhang, April 156 82.7 Chin HCW Genera Insom Impact 9

C. et al. 3 3% a l nia of
Anxiety Severi Events
Disord ty Scale-
er 2- Index Revise
item (ISI) d (IES-
(GAD- R)
2)

Zhang, April 205 56.1 Chin Gene Patient Genera 6

J. et al. % a ral Health lized
Popul Questio Anxiety
ation nnaire Disord
9-item er
(PHQ-9) scale
(GAD-
7)

Zhang, May 369 45% Chin Gene Kessler 7

S. et al. a ral 6-item
 Covid-19 and Mental Health Problems 49

(b) Popul Psychol

ation ogical
Distres
s Scale
(K-6)

Zhou, J. April 206 N/A Chin Gene Genera Insom 6

et al. 5 a ral lized nia
Popul Anxiety Severi
ation Disord ty
er Index
scale (ISI)
(GAD-
7)

Zhou, April 807 53.5 Chin Gene Genera 9

S.-J. et 9 % a ral lized
al. Popul Anxiety
ation Disord
er
scale
(GAD-
7)

Zhu, S. April 227 59.7 Chin Gene Genera 9

et al. 9 % a ral lized
Popul Anxiety
ation Disord
er
scale
(GAD-
7)
 Covid-19 and Mental Health Problems 50

Zhu, Z. Febru 506 85% Chin HCW Patient Genera 6

et al. ary 2 a Health lized
Questio Anxiety
nnaire- Disord
9 (PHQ- er
9) Scale
(GAD-
7)

Note. All articles were published or submitted in 2020, except for the unpublished data.

Figure 1. PRISMA chart for the meta-analysis search process

Identificatio

Records identified through

database searching
(n = 4572)

Records after duplicates removed

Records ex
(n = 2189)
(n = 20
Screening

Full-text article
Records screened with rea
n = 2189 (n = 8
23 Prevalence n
14 Less than 5 o
Full-text articles
11 Articles in an
Eligibility

assessed for eligibility