A systematic review of the prevalence of anxiety symptoms during coronavirus epidemics

Abstract

Coronavirus pandemics causes systemic and mainly pulmonary changes. We assessed the prevalence of generalized anxiety disorder (GAD) in pandemic survivors and the general population. Papers indexed by MEDLINE/PubMed, The Cochrane, Embase, Lilacs, Scielo, Psycoinfo, and Pepsic databases were searched to April 2020, using GAD and Coronavirus (CoV) infection as keywords. Sixteen studies with 25,779 participants in eight countries were included. A 46% pooled prevalence of anxiety symptoms (95% CI 33.9–58.2%) was found with significant evidence of between-study heterogeneity (Q = 154953, I2 = 99.99%, p < 0.001). Age and sex were not found to be significant moderators for anxiety symptoms. Intervention programs for anxiety symptoms are highly recommended.

Keywords

anxiety betacoronavirus coronavirus nervousness psychological stress

Introduction

Understanding the anxiety and psychological changes in periods of outbreaks of respiratory infections is important for the adoption of measures related to behavioral variations such as those that occurred during the pandemic period of the coronavirus Severe Acute Respiratory Syndrome (SARS-CoV) in 2009 (Liao et al., 2014) and now during the new Coronavirus (2019-nCoV) (Rastegar et al., 2020).

The new Coronavirus (2019-nCOV), initially identified in December 2019 in China, in the city of Wuhan, province of Hubei (Holshue et al., 2020), spread rapidly across all countries, becoming an emergency of international concern on January 30, 2020 (Rehman et al., 2020) by causing systemic and, mainly, pulmonary changes with characteristics of severe respiratory failure. The continuous spread of the epidemic together with the isolation measures imposed by the governments and the sanitary conditions, aggravated the health condition of the populations (Bao et al., 2020). The Coronavirus Disease (COVID-19) pandemic has not only affected the physical health of infected patients but also the psychosocial health of the uninfected world population, increasing depression, stress, and anxiety (Xiao et al., 2020).

Anxiety occurs from the moment that sensations and changes on homeostasis are perceived, including those related, in some situations, to diseases of infectious origin. Generally, these perceptions occur correctly in individuals, however, in some situations, these perceptions become excessive and the possibility of severe complications to the individual arises. This experience has become constant in recent times, especially in the events imposed by the presence of COVID-19 (Asmundson, 2020).

In confinement situations, self-protection and family protection mechanisms are common, which can lead to an individual’s frustration, accompanied by fear, anxiety and anguish, factors that can affect the individual’s homeostasis (Matias et al., 2020)

Public health management is an important point related to the installation of anxiety, seen as capturing decisions such as risk communications, vaccines, hygiene practices, social isolation can trigger symptoms in society can lead to success or failure of the measures taken by government officials (Adalja et al., 2020). Accurate information and available sources have importance for the global resolution of the epidemic, mismatched information with fear and anxiety (Corbett et al., 2020).

Exposure to and repeated surveillance of social media is one of the factors that can increase levels of anxiety and psychosocial problems during the outbreak of COVID-19, especially with conflicting and incorrect information. Governments should be alert to minimize anxiety in the population. China’s government, for example, has provided communication channels for mental health services (Gao et al., 2020; Wang and Di et al., 2020). Therefore, governments should be concerned about disseminating effective methods of awareness of the disease, regarding prevention, dissemination and clinical characteristics, to provide financial subsidies for the present and the future of the population, so that the impact on anxiety during COVID-19 (Wang and Di et al., 2020).

Anxiety during pandemic situations can confuse common symptoms, such as muscle pain, cough, and fever, with symptoms presented by those who were infected, resulting in increased levels of anxiety and stress, especially in vulnerable populations, such as pregnant women (Corbett et al., 2020), students (Cao et al., 2020) and in some professions as teachers (Liu, 2020). There are two possible explanations for this situation: some people tend to be isolated and for fear of being infected go to the doctor’s office; others, in any type of sign, seek medical attention outside social isolation and become exposed to infection (Adalja et al., 2020).

High levels of stress can generate behavioral changes that can be characterized by excessive hand washing, social withdrawal, and panic, which can result in negative consequences for the person and society such as excessive and inadequate use of the families’ financial budget and the scarcity of resources (Asmundson, 2020; Corbett et al., 2020).

On the other hand, the low level of anxiety can also compromise the safety of the population, the same occurrence during H1N1 epidemic in 2009 when, due to the low risk of infection, people minimized the importance of handwashing and governments did not concerned about vaccination campaigns, a fact that may have contributed to viral spread (Wheaton et al., 2012).

The high levels of anxiety can impair the support of the health teams in face of COVID-19 because by being on the “frontlines” in the “fight” against the virus on order to reestablish the health of the population, many health professionals are getting sick, so the fear of being infected and transmitting this disease to other co-workers and to the family itself has increased the level of anxiety in this population. As many teams were removed due to contamination, young professionals without adequate experience were included in the “fight” against COVID-19, many of them affected by psychosocial changes and anxiety (Lu et al., 2020; Moghadasi, 2020; Zhang et al., 2020), thus, the objective of this systematic review and meta-analysis is to assess the prevalence of global anxiety related to COVID-19 in survivors and population in general.

Methods

Search strategy

We conducted a systematic review and meta-analysis in compliance with the recommendations and criteria described in the preferred reporting items for systematic reviews and meta-analyses (PRISMA).

Sources of data

Potential published studies were identified via a comprehensive strategy. The systematic review was performed in the following databases: MEDLINE/PubMed; EMBASE; The Cochrane; Pepsic; PsycInfo; Lilacs; and Scielo. The search strategy involved the crosschecking of keywords selected based on the Medical Subjects Headings (Mesh) and Descritores em Ciências da Saúde (Decs). There was no language restriction.

The following keywords were used for (i) Population studied: (“coronavirus”[All Fields] OR “coronavirus”[All Fields] OR “coronavirus infections”[All Fields] OR “betacoronavirus”[All Fields] OR “betacoronavirus”[All Fields] OR “betacoronavirus”[All Fields] OR “betacoronavirus”[All Fields] OR “coronavirus”[All Fields] OR “coronavirus”[All Fields] OR “coronaviruses”[All Fields] OR “Coronavirus Infection”[All Fields] OR “COVID-19”[All Fields] OR “2019 Novel Coronavirus Infection”[All Fields] OR “2019-nCoV Infection”[All Fields] OR “2019 nCoV Infection”[All Fields] OR “2019-nCoV Infections”[All Fields] OR “Novel Coronavirus Pneumonia”[All Fields] OR “2019 novel coronavirus”[All Fields] OR nCoV[All Fields] OR covid[All Fields] OR “SARS-CoV-2”[All Fields] OR “SARS2”[All Fields] OR “Wuhan coronavirus”[All Fields]); AND (ii) outcomes:((“anxiety”[MeSH Terms] OR “anxiety”[All Fields] OR “anxiety”[MeSH Terms] OR “anxiety”[All Fields] OR “hyper-vigilance”[All Fields] OR “anxiety”[MeSH Terms] OR “anxiety”[All Fields] OR “nervous-ness”[All Fields] OR “anxiety”[MeSH Terms] OR “anxiety”[All Fields] OR “social”[All Fields] OR “anxiety”[All Fields]) OR “social anxiety”[All Fields] OR “anxiety”[MeSH Terms] OR “anxiety”[All Fields] OR “social”[All Fields] OR “anxieties”[All Fields] OR “social anxieties”[All Fields]) OR “panic”[MeSH Terms] OR “panic”[All Fields] OR “panic”[MeSH Terms] OR “panic”[All Fields] OR “panics”[All Fields] OR “Life Stress” [All Fields] OR “Psychologic Stress” [All Fields] OR “Psychological Stressor” OR “Psychological Stressors”.

All relevant studies were selected, the full-text versions were analyzed for methodological quality by two researchers (ML and RS) independently and disagreement between reviewers (KCC) was resolved by discussion or arbitration by the other researcher. Gray literature and preprints were not considered.

Types of studies and participants

The following criteria were adopted for the selection of the studies: Cross-sectional studies; anxiety condition related to the COVID outbreaks, in survivors and the general population. Editorial, letter to the editor, viewpoint, case presentation, gray literature, or brief communication was excluded as it did not contain data on anxiety related to COVID.

Data extraction

Initially, the studies were exported to a Mendeley® file and reported on the PRISMA diagram (Figure 1). The first two screenings (selection by title and abstract) were performed by two independent researchers (ML and RS), whose selection of articles would potentially be included in the final compilation. In cases where there were disagreements, a fourth independent researcher (KCC) resolved the discrepancies. Regarding data extraction, the three independent researchers (CR, JR, and ML) used a form which was intended to record: study data (authors, journal name, country and study scenario, year of publication), methodological information (objective of the study, design, size of the total sample, aspect or variable of quality of life, exercise practice and instruments used to evaluate them).

Figure 1.

Study flow diagram.

Quality assessment

We used the Newcastle–Ottawa scale to assess the quality of the included studies. Relevant organizational websites including the Joanna Briggs Institute publish a Reviewers’ Manual, which is designed to support individuals who are undertaking systematic reviews following JBI methodologies and methods (Munn et al., 2015). This checklist contains 9 questions, which we divided into 3 domains: participants (questions 1, 2, 4, and 9), outcome measurement (6 and 7), and statistics (3, 5, and 8). A study was rated as having high quality when the methods were appropriate in all 3 domains. Quality assessment was also performed by two independent reviewers and any uncertainties were resolved by consulting a third reviewer.

Data analysis

For the prevalence estimates of the included observational studies, a random-effects meta-analysis model was used according to DerSimonian and Laird (2015), assuming that the effect of interest is the same in all studies and that the differences observed between them are only due to sampling errors (variability within studies). The heterogeneity of the estimates of the sample size effect throughout these studies was quantified by the I² statistic. The heterogeneity between the studies was assessed by Cochran’s Q test and I² statistics. Based on the possibility of varying the estimates of the prevalence of anxiety according to the types of populations involved, as professionals of the medical team, patients with SARS-CoV and the population in general, subgroup analyzes were used to assess whether the anxiety in each of the populations influenced the joint estimation. The results are presented in a forest plot with 95% confidence intervals (95% CI) or scattered plots with point estimates and 95% CI. Sensitivity analysis was performed to determine A leave-one-out sensitivity analysis was performed by iteratively removing one study at a time to confirm that our findings were not driven by any single study (R Core Team, 2018). Meta-regression technique was applied to analyze covariates of anxiety; we have used two covariates, mean age and proportion of male sex. Subgroup analysis was applied to analyze the factorial population of the study (Balduzzi et al., 2019; Barendregt et al., 2013).

Results

Selection and evaluation of studies

The initial search identified 1087 studies with a generalized anxiety disorder (GAD) related COVID-19 outbreak. Seventeen duplicate studies were removed yielding a total of 1070 studies. After title and abstract analysis, we excluded 1037 studies which were ineligible based on inclusion criteria, the present systematic included a total of 16 studies (Figure 1).

Characteristics of the included studies

16 studies were included, 10 from China, one from the USA, one from India, two from Hong Kong, one from the Kingdom of Saudi Arabia, and one from Korea. The total population corresponded to 25779 participants, with 7027 medical health jobs, 16203 general population, and 1887 patients with SARS-CoC. All respondents were under 18 and approximately 7789 were male (some studies were unclear).

Prevalence of anxiety symptoms

Meta-analytical pooling of the point estimates of anxiety symptoms were 46% (95% CI 33.9% – 58.2%), with statistically significant evidence of between-study heterogeneity (Q = 154953, I² = 99.99%, p < 0.001) shown in Figure 2. Sensitivity analysis indicated that no study influenced the pooled prevalence results by more than 2%. The subgroup analysis of the study population revealed that 52,6% of the general population (95% CI 42.0–63.2%) had a higher prevalence of anxiety symptoms, followed by medical health workers corresponding to 49.9% (95% CI 15.4–84.4%) and, finally, infected patients with 8.0% (95% CI −4.0–20.0%), shown in Figure 3. Meta-regression covariate analyses were conducted for age and gender. The results indicated that neither age (β = −0.027, p = 0.060) nor sex (β = 0.406, p = 0.562) were significant moderators of the prevalence of anxiety symptoms.

Figure 2.

Overall prevalence of anxiety symptoms.

Figure 3.

Prevalence of anxiety symptoms according to the type of population investigated.

The methodological quality of the selected studies

The quality of the studies was analyzed by the Newcastle-Ottawa Scale. The Newcastle-Ottawa Scale is graduated by a system with stars graduation that goes from 0 to 9 delimited in three domains: selection, comparability, and outcome. Higher grades represent better quality.

The studies considered to be of excellent quality were those with high scores in all three domains. In Table 1 the studies by Wang and Zhao et al. (2020), Alnajjar et al. (2016), Mo et al. (2020), Wang C et al. (2020), Cao et al. (2020), Zhang et al. (2020), Jeong et al. (2020) e Lai et al. (2020) obtained excellent methodological quality when submitted to Newcastle-Ottawa Scale evaluation.

Table 1.

Study bias risk included according to JNI critical appraisal checklist for analytical cross sectional studies.

Author	Year	Were the criteria for inclusion in the sample clearly defined?	Were the study subjects and the setting described in detail?	Was the exposure measured in a valid and reliable way?	Were objective, standard criteria used for measurement of the condition?	Were confounding factors identified?	Were strategies to deal with confounding factors stated?	Were the outcomes measured in a valid and reliable way?	Was appropriate statistical analysis used?
Wang and Zhao et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Roy et al.,	2020	Yes	Yes	No	Yes	Yes	No	No	No
Alnajjar et al.,	2016	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Mo et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
C. Wang et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Lee et al.,	2020	Yes	Yes	No	Yes	No	No	No	No
Yuan et al.,	2020	Yes	No		Yes	No	No	Yes	Yes
Xiao et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Cao et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Zhang et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Gao et al.,	2020	Yes	Yes	Yes	Yes	No	No	Yes	Yes
Jeong et al.,	2016	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Lai et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Wong, Gao, Tam	2007	Yes	Yes	No	Yes	No	No	No	No
Lu et al.,	2020	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes
Wu, Chan, Ma	2005	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes

The study bias risk was analyzed by the Critical Appraisal Checklist for Analytical Cross-Sectional Studies, the scale consists of 7 questions: 1. Where the criteria for inclusion in the sample clearly defined? 2. Were the study subjects and the setting described in detail? 3. Was the exposure measured validly and reliably? 4. Were objective, standard criteria used for measurement of the condition? 5. Were confounding factors identified? 6. Were strategies to deal with confounding factors stated? 7. Were the outcomes measured validly and reliably? 8. Was an appropriate statistical analysis used? The answers by analytical cross-sectional studies Critical Appraisal Tool Answers were: Yes, No, Unclear, or Not/Applicable (Table 1).

According to a risk analysis by the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies, all studies describe a description of the inclusion criteria, however, the studies by Roy et al. (2020) and Yuan et al. (2020) does not describe in detail, for example, the resources of the sample, in addition to not using validated measures to analyze the variables related to anxiety. All studies have defined standards for measuring anxiety. The studies by Lee et al. (2014), Yuan et al. (2020), Gao et al. (2020), and Wong et al. (2020) did not identify the confounding factors and none of the studies used strategies to deal with confounding factors. As for the statistical analysis of the studies by Roy et al. (2020), Lee et al. (2014) and Wong et al. (2020) did not use adequate statistical analysis methods but were kept in the study by the relevance of the same.

Discussion

The main findings of the study report that the pandemic caused by the new Coronavirus and previously by other viral infections brought anxiety to the population, whether related to social isolation or the lockdown determined by governments; for fear caused by the severity of the disease, risk of crisis, the economic and financial impact on families or even fear about life. Our findings confirm that a significant proportion of the population are vulnerable to mental health problems yet, in the vast majority of cases, individuals in social isolation have no access to mental healthcare (Matias et al., 2020). The only resource is people themselves using self-help, self-medication and self-care. During prolonged COVID-19 isolation, an in-built system of homeostasis helps rebalance activity, thought and feeling.

In this systematic review with meta-analysis, we found 16 studies that analyzed anxiety during COVID epidemics. We divided the articles evaluating the anxiety of health workers, including 6 studies; the general population, including 8 studies; and patients with COVID including 2 studies.

In this review, we identified that 46% of the entire population, including survivors and the general population, suffers from the perception of increased anxiety, either due to the fear of being infected and not having a hospital bed available for treatment or the fear of infecting other people, such as experienced by health professionals who are increasingly isolated and end up adopting measures that can compromise health and interpersonal relationships, on the other hand, people infected with Coronavirus have lower levels of anxiety.

Several factors can increase anxiety rates, including personality and genetics, past traumas and substance abuse that can be identified in several ways such excessive worry, sleep disorders, muscle pain, indigestion (McAlonan et al., 2007), these signs could be confused with COVID-19, these signs can identify anxiety (Aggarwal et al., 2020).

It is important to emphasize that anxiety disorder, in addition to its high prevalence, is characterized by excessive anxiety and worries, in combination with psychological and somatic disorders such as autonomic changes, agitation, fatigue, concentration problems, irritability and sleep problems (Borza et al., 2017), as identified in our systematic review.

In some cases, panic disorder can also be found, characterized by anxiety attacks that result in fear or worry negatively impacting life in society. Anxiety disorders are considered less serious psychiatric disorders because patients do not lose their sense of reality. However, the symptoms can be associated with social and functional deficiencies and contribute independently to the reduction of quality of life and to a longer duration of absence, a fact than can compromise the structures of the work teams, especially in the healthcare area that are overload (Lee et al., 2014).

Several scales were used to investigate different levels of anxiety, some of them valid and used before the new Coronavirus pandemic such as Generalized Anxiety Disorder (DAD), Clinical Anxiety Scale (CAS), BECK Anxiety Scale and others with variations elaborated and proposed for the current context on the new Coronavirus (Hahad et al., 2020). In this meta-analysis, it was possible to observe that18% of the articles used not validated scales, a fact that can reduce the quality and increase the bias of the studies, however, these studies were maintained due to the relevance of them and because everyone explained in detail how they would use the assessment tools.

A study by Huang and Zhao (2020), in a population of 7236, investigated anxiety and depression and identified that the younger population has a higher risk of triggering events related to anxiety when compared to the elderly, just as the health professionals can present events related to sleep disorders. Our findings demonstrate that the articles generally portray anxiety conditions in different populations, especially health professionals and the elderly population, but make little reference to youth populations.

The social isolation triggered in pandemic situations contributes significantly to the appearance of anxiety symptoms that, in general, can be confused with symptoms related to diseases such as COVID-19. Eminent risk of death and fear of hospitalization are conditions that can further worsen the mental health of the isolated population. The limitations of our systematic review and meta-analysis involve the lack of studies in more regions of the planet, most studies are concentrated in China and part of Europe since in some places the peak of the disease has not yet been reached and studies have not yet been carried out, which may limit the generalization of results and this limitation can be revealed because COVID-19 has been occurring for approximately 6 months and in some parts of the world the peak of the disease has not yet been reached, allowing the accomplishment of few studies so far. Studies with anxiety scales that have not yet been validated were included, although they are detailed in the studies, a fact that may generate a risk of bias in these studies. Another limitation is due to the presence of different types of population, such health professionals, survivors, and populations in general, and when dividing into subgroups, a small number of specific studies were found for the populations studied.

The implications of this review are large for public mental health, the main implication is that with the anticipated elevated rates of stress or anxiety; efforts for screening and intervention are needed. In this journal, Matias et al. (2020) have pointed out that a significant proportion of the population live alone and are vulnerable to mental health problems yet, in the vast majority of cases, individuals in social isolation have no access to mental healthcare. The only resource is people themselves using self-help, self-medication and self-care.

As new measures and impacts are introduced during the pandemic different approaches need to be taken. Co-occurring psychological problems also needed to be levels of loneliness, depression, harmful alcohol and drug use, and self-harm or suicidal behaviours are also anticipated to rise, this calling for global wide action plans.

In countries and populations already heavily affected by the pandemic, issues of service access and continuity for people with developing or existing mental health conditions are also now a major concern, along with the mental health and well-being of “frontline” workers.

Conclusion

The findings of this systematic review and meta-analysis demonstrate that during pandemics the prevalence of anxiety symptoms affects approximately half of the population. Future studies using improved methods are needed to identify, prevent, and treat mental health problems during pandemics. In most cases, the only resource is people themselves using self-help, self-medication and self-care. An in-built system of homeostasis can help rebalance activity, thought and feeling.

Supplemental Material

Supplementary_material_9 – Supplemental material for A systematic review of the prevalence of anxiety symptoms during coronavirus epidemics

Supplemental material, Supplementary_material_9 for A systematic review of the prevalence of anxiety symptoms during coronavirus epidemics by Marianne Lucena da Silva, Rodrigo Santiago Barbosa Rocha, Mohamed Buheji, Haitham Jahrami and Katiane da Costa Cunha in Journal of Health Psychology

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Rodrigo Santiago Barbosa Rocha

References

Adalja

Toner

Inglesby

(2020) Priorities for the US health community responding to COVID-19. JAMA 323(14): 1343–1344.

Aggarwal

Garcia-Telles

Aggarwal

, et al. (2020) Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States. Diagnosis (Berl) 7(2): 91–96.

AlNajjar

Attar

Farahat

, et al. (2016) Psycho-behavioural responses to the 2014 Middle East respiratory syndrome-novel coronavirus (MERS CoV) among adults in two shopping malls in Jeddah, western Saudi Arabia. Eastern Mediterranean Health Journal 22(11): 817–823.

Asmundson

(2020) How health anxiety influences responses to viral outbreaks like COVID-19: What all decision-makers, health authorities, and health care professionals need to know. Journal of Anxiety Disorders 71(102211).

Balduzzi

Rücker

Schwarzer

(2019) How to perform a meta-analysis with R: a practical tutorial. Evidence-Based Mental Health 22(4): 153–160.

Bao

Sun

Meng

, et al. (2020) 2019-nCoV epidemic: address mental health care to empower society. Lancet 395(10224):e37–e38.

Barendregt

Doi

Lee

, et al. (2013) Meta-analysis of prevalence. Journal of Epidemiology& Community Health 67(11): 974–978.

Borza

(2017) Cognitive-behavioral therapy for generalized anxiety. Dialogues in Clinical Neuroscience 19(2): 203–207.

Cao

Fang

Hou

, et al. (2020) The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research 287: 112934.

10.

Corbett

Milne

Hehir

, et al. (2020) Health anxiety and behavioural changes of pregnant women during the COVID-19 pandemic. European Journal of Obstetrics & Gynecology and Reproductive Biology 249: 96–97.

11.

DerSimonian

Laird

(2015) Meta-analysis in clinical trials revisited. Comtemporary Clinical Trials 45: 139–145.

12.

Gao

Zheng

Jia

, et al. (2020) Mental health problems and social media exposure during COVID-19 outbreak. PLoS One 15(4): e0231924.

13.

Hahad

Gilan

Daiber

, et al. (2020) Public mental health as one of the key factors in dealing with COVID-19. Gesundheitswesen 82(5): 389–391.

14.

Holshue

DeBolt

Lindquist

, et al. (2020) First case of 2019 Novel Coronavirus in the United States. New England Journal of Medicine 382: 929–936.

15.

Huang

Zhao

(2020) Chinese mental health burden during the COVID-19 pandemic. Asian Journal of Psychiatry 51: 102052.

16.

Jeong

Yim

Song

, et al. (2016) Mental health status of people isolated due to Middle East Respiratory Syndrome. Epidemiology and Health 38: e2016048.

17.

Lai

Wang

, et al., (2020) Factors associated with mental health outcomes among health care workers exposed to Coronavirus disease 2019. JAMA Network Open 3(3): e203976.

18.

Lee

Kim

Chae

, et al. (2014) Impairment of work productivity in panic disorder patients. Journal of Affective Disorders 157: 60–65.

19.

Liao

Cowling

Lam

, et al. (2014) Anxiety, worry and cognitive risk estimate in relation to protective behaviors during the 2009 influenza A/H1N1 pandemic in Hong Kong: Ten cross-sectional surveys. BMC Infectious Disease. 14: 169.

20.

Liu

(2020) How I faced my coronavirus anxiety. Science 367(6484): 1398.

21.

Wang

Lin

, et al. (2020) Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study. Psychiatry Research 288: 112936.

22.

Matias

Dominski

Marks

(2020) Human needs in COVID-19 isolation. Journal of Health Psychology 25(7): 871–882.

23.

McAlonan

Lee

Cheung

, et al. (2007) Immediate and sustained psychological impact of an emerging infectious disease outbreak on health care workers. The Canadian Journal of Psychiatry 52: 241–247.

24.

Deng

Zhang

, et al. (2020) Work stress among Chinese nurses to support Wuhan in fighting against COVID-19 epidemic. Journal of Nursing Management 28: 1002–1009.

25.

Moghadasi

(2020) Evaluation of the level of anxiety among Iranian multiple sclerosis fellowships during the outbreak of COVID-19. Archives of Iranian Medicine 23(4): 283.

26.

Munn

Moola

Lisy

, et al. (2015) Methodo-logical guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. International Journal of Evidence-Based Healthcare 13(3): 147–53.

27.

R Core Team (2018) A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at: https://www.R-project.org/ (accessed 15 May 2020).

28.

Rastegar

Amini

Tabari

, et al. (2020) Peer mentoring for medical students during COVID-19 pandemic via a social media platform. Medical Education 54(8): 762–763.

29.

Rehman

Shafique

Ihsan

, et al. (2020) Evolutionary trajectory for the emergence of Novel Coronavirus SARS-CoV-2. Pathogens 9(3): E240.

30.

Roy

Tripathy

Kar

, et al. (2020) Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic. Asian Journal of Psychiatry 51: 102083.

31.

Wang

Zhao

Feng

, et al. (2020) Psychological assistance during the coronavirus disease 2019 outbreak in China. Journal of Health Psychology 25(6): 733–737.

32.

Wang

Pan

Wan

, et al. (2020) A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain, Behavior and Immunity 87: 40–48.

33.

Wang

, et al. (2020) Study on the public psychological states and its related factors during the outbreak of coronavirus disease 2019 (COVID-19) in some regions of China. Psychology, Health and Medicine 1–10.

34.

Wheaton

Abramowitz

Berman

, et al. (2012) Psychological predictors of anxiety in response to the H1N1 (Swine Flu) pandemic. Cognitive, Therapy and Research 36: 210–218.

35.

Wong

Gao

Tam

(2007) Anxiety among university students during the SARS epidemic in Hong Kong. Stress and Health 23(1): 31–35.

36.

Chan

(2005) Posttraumatic stress, anxiety, and depression in survivors of severe acute respiratory syndrome (SARS). Journal of Traumatic Stress 18(1): 39–42.

37.

Xiao

Zhang

Kong

, et al. (2020) Social capital and sleep quality in individuals who self-isolated for 14 days during the Coronavirus Disease 2019 (COVID-19) outbreak in January 2020 in China. Medicine Science Monitor 26: e923921.

38.

Yuan

Liao

Huang

, et al. (2020) Comparison of the indicators of psychological stress in the population of Hubei province and non-endemic provinces in China during two weeks during the coronavirus disease 2019 (COVID-19) outbreak in February 2020. Medicine Science Monitor 26: e923767.

39.

Zhang

Wang

Yin

, et al. (2020) Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China. Psychotherapy and Psychosomatics 9: 1–9.

Supplementary Material

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