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ABSTRACT Close contacts of those with COVID-19 (CC) may experience distress and long-lasting mental health effects. However, the mental health status and quality of life (QOL) in CC have not

been adequately examined. This study examined the mental health status and QOL in CC during the post-COVID-19 period. This cross-sectional study comprised 1169 CC and 1290 who were

non-close contacts (non-CC). Demographic data were collected; depression, fatigue, post-traumatic stress symptoms (PTSS) and QOL were assessed using the Patient Health Questionnaire - 9

items (PHQ-9), fatigue numeric rating scale, Post-Traumatic Stress Disorder Checklist - 17 items (PCL-17), and the World Health Organization Quality of Life Questionnaire - brief version

(WHOQOL-BREF), respectively. Analysis of covariance was used to compare depressive symptoms, QOL, fatigue, and PTSS between the CC and non-CC groups. Multiple logistic regression analyses

were performed to determine the independent correlates for depression, fatigue, PTSS, and QOL in the CC group. Compared to the non-CC group, the CC group reported significantly more severe

depression (_F_(1, 2458) = 5.58, _p_ = 0.018) and fatigue (_F_(1, 2458) = 9.22, _p_ = 0.002) in the post-COVID-19 period. No significant differences in PTSS and QOL between the CC and non-CC

groups were found (_F_(1, 2458) = 2.93, _p_ = 0.087 for PTSS; _F_(1, 2458) = 3.45, _p_ = 0.064 for QOL). In the CC group, younger age, financial loss due to COVID-19, and perception of poor

or fair health status were significantly associated with depression and fatigue, while frequent use of mass media was significantly associated with fatigue. In conclusion, close contacts of

COVID-19 patients experienced high levels of depression and fatigue in the post-COVID-19 period. Due to the negative effects of depression and fatigue on daily functioning, early detection

and timely interventions should be provided to this neglected population. SIMILAR CONTENT BEING VIEWED BY OTHERS LONG- COVID AND GENERAL HEALTH STATUS IN HOSPITALIZED COVID-19 SURVIVORS

Article Open access 19 May 2023 POST COVID-19 MENTAL HEALTH SYMPTOMS AND QUALITY OF LIFE AMONG COVID-19 FRONTLINE CLINICIANS: A COMPARATIVE STUDY USING PROPENSITY SCORE MATCHING APPROACH

Article Open access 09 September 2022 FEELINGS OF LONELINESS, COVID-19-SPECIFIC-HEALTH ANXIETY AND DEPRESSIVE SYMPTOMS DURING THE FIRST COVID-19 WAVE IN SWISS PERSONS WITH MULTIPLE SCLEROSIS

Article Open access 24 October 2022 INTRODUCTION At the end of 2019, coronavirus disease 2019 (COVID-19) was first reported in Wuhan, Hubei province of China and subsequently was also found

in other parts of the world [1, 2]. Due to its fast transmission rate, the World Health Organization (WHO) declared the COVID-19 outbreak a pandemic on March 11, 2020 [3]. By the middle of

March 2021, there were over 117 million COVID-19 cases globally with 2.6 million deaths. At the same time, over 66 million people have recovered from this disease [4]. Although research has

focused on patients with COVID-19 [5, 6], few studies have reported on the close contacts of COVID-19 patients (CC hereafter). Close contacts are at high risk of contracting COVID-19

infection [7,8,9,10]. Further, restrictions imposed on them, including mandatory quarantine in designated places or at home and frequent virus testing [11, 12], can also increase the risk of

physical and mental health problems. According to previous studies, CC usually refer to people who is within 6 feet (or 2 m) of an infected person for a total of ≥15 min, or who live in the

same household or shared accommodation with an infected person, or who travel in the same vehicle or an airplane with an infected person, or who have direct contact with body fluids or

secretions of an infected person (e.g., was coughed or sneezed on) [13,14,15,16,17,18,19]. The number of CC is difficult to estimate or track; previous studies found that one confirmed

COVID-19 case could have up to 44 close contacts on average [20,21,22,23,24,25]. Given the high number of CC and the adverse impact of the pandemic on them, it is important to examine their

mental health status and quality of life (QOL). In the past year, studies have found that CC had increased risk of mental health problems such as anxiety, depression, and psychological

distress during the COVID-19 pandemic [26,27,28]. In addition, QOL has gained increasing attention as an important health outcome in clinical practice and research during the pandemic [29].

An Italian study found that the frontline healthcare staff reported lower QOL than their non-frontline counterparts [30]. Furthermore, long-term negative mental health impact of biological

disasters (e.g., outbreak of infectious diseases) may occur in various populations even after the outbreak is controlled, with different clinical features compared to those during the

outbreak [31,32,33,34]. A longitudinal study on severe acute respiratory syndrome (SARS) found that healthcare workers who cared for infected patients had higher stress level at the 1-year

follow-up after the SARS outbreak compared to non-healthcare workers [31]. However, no studies have examined the mental health status and life quality in CC in the post COVID-19 period. For

76 days, the city of Wuhan, the epicenter of the COVID-19 outbreak in China, was under “lockdown,” with travel restrictions and other public health and administrative measures until the 8

April 2020 [35, 36]. The “post-COVID-19 era” in this study refers to the period after the lockdown policy and related public restrictions in Wuhan were lifted on April 8, 2020 after no new

cases were reported for 19 days in Wuhan [37, 38]. Additionally, during the 12-month period between April 8, 2020 and April 8, 2021, only 350 new cases were diagnosed in Hubei province [37],

indicating that there was no further serious outbreak after the lockdown policy was canceled. Wuhan is not only the first epicenter of the COVID-19 outbreak globally but also the first

major city where the outbreak was rapidly brought under control; therefore, Wuhan is one of the most suitable areas to conduct “post-COVID-19 era”-related research. This study examined the

mental health status, such as depression, fatigue, post-traumatic stress symptoms (PTSS), and QOL in CC during the post-COVID-19 period. Based on previous relevant findings [31,32,33,34], we

hypothesized that the CC group have higher levels of depression, fatigue, PTSS, and lower QOL than the non-CC group. METHODS STUDY SETTING AND PARTICIPANTS This was a cross-sectional,

comparative study conducted during the post-COVID-19 period between May 25, 2020 and June 18, 2020 in Wuhan, Hubei province, China. Following previous studies [39,40,41], to minimize the

risk of infection, participants were recruited and assessed online using the WeChat-based QuestionnaireStar program (Changsha Haoxing Information Technology Co., Ltd., Changsha, China) based

on snowball sampling. A QuestionnaireStar Quick Response (QR) code linked to the invitation and assessments was disseminated by study team members, their colleagues, and friends who worked

and lived in Wuhan via WeChat, which is the most popular social network application in China with around 1.2 billion monthly active users [42]. Persons who completed the assessments in this

study were encouraged to invite people around them to participate in this study. The QuestionnaireStar program has been widely used in observational studies during the COVID-19 pandemic. To

be eligible, participants needed to meet the following criteria: (1) age ≥18 years; (2) able to read Chinese and understand the purpose and contents of the assessments; (3) not infected with

COVID-19 during the pandemic; and (4) provided online electronic informed consent. Participants were divided into two groups: CC group and control group (non-CC hereinafter). Close contacts

were defined as individuals who had family members, colleagues, close friends, or neighbors infected with COVID-19; this practical definition was widely used in clinical practice [11]. The

study protocol was approved by the ethics committee of Beijing Anding Hospital, Capital Medical University. ASSESSMENT TOOLS An electronic data collection form was designed to collect

demographic and clinical data, including age, gender, education level, occupation, place of residence, living in urban or rural areas, living status (alone or with family members), frequency

of mass media use, financial loss due to the COVID-19 pandemic, and perception of financial and health status. They were asked whether they had family members, colleagues, close friends, or

neighbors infected with COVID-19 and whether they had previously been infected with COVID-19. Severity of depressive symptoms (depression hereafter) was assessed using the Chinese version

of the Patient Health Questionnaire - 9 items (PHQ-9), which consists of 9 items and each scored from 0 (not at all) to 3 (almost every day) [43, 44]. A higher score represents more severe

depression [45]. The psychometric properties of PHQ-9 Chinese version have been validated in Chinese populations [46, 47]. Participants were classified as “having depression” if their PHQ-9

total score was ≥5 [45]. Overall QOL was assessed with the first two items of the World Health Organization Quality of Life Questionnaire - brief version (WHOQOL-BREF) [48, 49], with a

higher score representing higher overall QOL [50]. Fatigue was assessed using the 11-point fatigue numeric rating scale, ranging from 0 (no fatigue) to 10 (the worst fatigue you can imagine)

[51,52,53]. Fatigue total score ≥4 was considered as “having clinically significant fatigue” (“having fatigue” hereinafter) [54]. PTSS was assessed using the Chinese version of the

Post-Traumatic Stress Disorder Checklist - 17 items (PCL-17) [55, 56]. Generally, Chinese people with psychiatric disorders tend to express their mental health problems in terms of physical

symptoms [57,58,59]. Therefore, fatigue is not only a physical symptom but also a very common somatic symptom of psychiatric disorders. The PCL-17 is a 5-point Likert scale, with each item

scoring from 1 (not at all) to 5 (extremely) in three domains: intrusion, avoidance/numbing, and hyperarousal. The Chinese version of the PCL-17 has been shown to have satisfactory

psychometric properties [56]. STATISTICAL ANALYSIS All the data analyses were conducted using Statistical Analysis System (SAS), University Edition (SAS Institute Inc., Cary, NC, USA). In

univariable analyses, the demographic and clinical characteristics between close contacts and non-close contacts were compared using independent two-sample _t_ tests, Wilcoxon rank-sum

tests, and chi-square tests as appropriate. Analysis of covariance (ANCOVA) was used to compare depressive symptoms, overall QOL, fatigue, and PTSS between the CC and the non-CC groups after

adjusting for variables that significantly differed in univariable analysis (confounders hereafter). Multiple logistic regression was applied to determine the independent demographic and

clinical correlates for depression, fatigue, PTSS, and QOL among CC if they were significantly different from non-CC. Two-sided _p_ values <0.05 were considered as statistically

significant. Around half of participants in the CC group were medical workers. As the high proportion of medical workers might bias the results, a post hoc sensitivity analysis was conducted

by excluding medical workers to examine whether this group could significantly affect the original results of logistic regression analyses. In the post hoc sensitivity analyses, similar

logistic regression conducted in the whole sample were repeated, and then the results were compared with the original ones in the whole sample. RESULTS In total, 2614 were invited to

participate in this study; 2459/2614 (94.1%) participants fulfilled the study entry criteria and completed the assessments, including 1169 CC and 1290 non-CC. Table 1 shows the basic

demographic data of the participants. There were significant differences between the CC and non-CC groups in terms of age, occupation, place of residence, living area (urban or rural),

frequency of mass media use, financial loss due to COVID-19, and perceived economic and health status (all _p_ values <0.05). After adjusting for confounders, close contacts still had

more severe depression (_F_(1, 2458) = 5.58, _p_ = 0.018) and fatigue (_F_(1, 2458) = 9.22, _p_ = 0.002), while no significant difference in PTSS and overall QOL between the two groups were

found (_F_(1, 2458) = 2.93, _p_ = 0.087) for PTSS; _F_(1, 2458) = 3.45, _p_ = 0.064 for QOL). In the CC group, 50.2% (95% confidence interval (CI): 47.3–53.1%) were classified as “having

depression,” while the corresponding figure was 43.9% (95% CI: 41.2–46.6%) among non-CC. The prevalence of fatigue was 63.8% (95% CI: 61.1–66.6%) and 54.3% (95% CI: 51.5–57.0%) in the CC and

non-CC groups, respectively. Multiple logistic regression analysis revealed that older age (odds ratio (OR) = 0.97, 95% CI: 0.96–0.98), significant financial loss during COVID-19 (OR = 2.0,

95% CI: 1.4–3.0), and perception of poor/fair health (OR = 3.9, 95% CI: 3.0–5.0) were significantly associated with depression in CC. In contrast, older age (OR = 0.97, 95% CI: 0.96–0.99),

frequent use of mass media (OR = 1.4, 95% CI: 1.02–1.97), financial loss (OR = 1.6, 95% CI: 1.2–2.2 for moderate financial loss; OR = 2.6, 95% CI: 1.7–3.9 for significant financial loss),

and perception of poor/fair health (OR = 3.3, 95% CI: 2.5–4.3) were significantly associated with fatigue in the CC group (Table 2). The results of post hoc sensitivity analysis

(Supplementary Table 1) were similar to the original results achieved in the CC group (Table 2), indicating that the high proportion of medical workers did not significantly affect the

results. DISCUSSION To the best of our knowledge, this was the first study that investigated the mental health status and QOL among CC in the post-COVID-19 period. Based on this study sample

recruited from the previous epicenter of COVID-19 and using validated assessment tools, we found that, after adjusting for potential confounders, CC experienced significantly higher rates

of depression and fatigue symptoms compared to non-CC. As no previous studies compared mental health status between the CC and non-CC groups in the post-COVID-19 period, direct comparisons

with other studies could not be made. However, other studies on mental health status of CC during the COVID-19 pandemic found that this population were more likely to report higher

prevalence of depression compared to community-dwelling residents and health professionals who were not close contacts [28, 60]. Several factors could contribute to more severe depression

and fatigue in the CC compared to the non-CC group. First, CC are likely to experience fear, anxiety, and frustration due to their increased risk of infection [61, 62]. Second, given that

their close ones were infected with COVID-19, and that physical and psychiatric comorbidities were common in COVID-19 survivors [63,64,65,66], CC are more likely to experience distress.

Third, due to the extended period (14–21 days) of mandatory quarantine [11, 12], CC are likely to face more financial burden and increased risk of mental health problems [67]. Finally,

stigma and discrimination associated with COVID-19, as well as social isolation, are risk factors for depression, anxiety, and fatigue [68,69,70,71]. All these factors could increase the

risk of depression, which could further contribute to fatigue and other somatic symptoms [72, 73]. Furthermore, the proportion of medical workers in the CC group (51.2%) was much higher than

that in the non-CC group (27.9%) in this study. Previous studies have found a high level of fatigue and burnout among healthcare workers during the COVID-19 outbreak [74,75,76,77,78,79],

which also contributed to the higher prevalence of fatigue in the CC group. The symptoms of depression and fatigue in the CC group were significantly associated with certain demographic and

clinical correlates. Previous studies found mental health problems such as depression, anxiety, and psychological distress were more common in younger people during the COVID-19 pandemic

[80,81,82,83,84,85]. Quarantine and other preventive measures during the pandemic may particularly affect the social and physical activities in younger people [86, 87]; in addition, younger

people may have reduced resilience and coping mechanisms [88]. Consequently, they may be more likely to have depressive and fatigue symptoms as we found in this study. Financial loss due to

COVID-19 was significantly associated with higher risk of depression and fatigue among close contacts, which confirms previous findings [89,90,91]. In this study, more frequent use of mass

media was an independent correlate of more severe fatigue (not depression) among close contacts. During the pandemic and quarantine period, close contacts facing quarantine and social

isolation usually spend more time on social media such as smartphone and the Internet. This could further reduce physical exercises and social communications with others, which could

increase the risk factors of chronic fatigue [92,93,94]. In this study, perception of poor/fair health was associated with higher risk of both depression and fatigue in CC. The relationship

between subjective health perception and depression/fatigue could be bidirectional. On the one hand, some studies found that perception of poor or moderate health was related to more severe

depression in nursing students, older people, and primary care patients [95,96,97,98] and was related to fatigue in the general population and students with school-year employment [99, 100].

On the other hand, poor perception of health could lead to health-related anxiety and hypochondria, which may further result in depression, headaches, insomnia, and even suicidal ideation

[101,102,103]. Another longitudinal study found that perception of good health was a predictor of less severe fatigue in worn-out employees [104]. One study found that fatigue played a

causal role in the subjective perception of health [105]. The strengths of this study included the large sample size and the focus on CC in the pandemic epicenter during the post-COVID-19

period. In addition, an online survey was used, which could ensure anonymity. However, there were several methodological limitations. First, due to the cross-sectional design, no causal

relationships between mental health status and other variables could be established. Second, due to logistical reasons, snowball, rather than random sampling, was used, which could lead to

selection bias. In addition, around half of participants in the CC group were medical workers. However, post hoc sensitivity analyses did not find that the high proportion of medical workers

significantly influence the original results. Third, certain important factors related to mental health of close contacts were not collected in this study, such as different types of close

contacts (e.g., household contacts, work contacts, and social contacts [106]), social supports, and quarantine history and quarantine duration of the close contacts. Fourth, information on

chronic or major diseases in medical records was not collected, although this could provide more precise information on participants’ physical health than their perception of health. Fifth,

the potential impact of death or post-COVID-19 disabilities of COVID-19 patients could have an important impact on the mental health status of CC, but the relevant information was not

collected in this study. In conclusion, close contacts experienced high levels of depression and fatigue in post-COVID-19 period, particularly in those who were younger, had experienced

financial loss due to COVID-19, and had perception of poor or fair health status. Considering the negative effects of depression and fatigue on QOL and daily functioning, early detection and

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Google Scholar  Download references FUNDING The study was supported by the National Science and Technology Major Project for investigational new drug (2018ZX09201-014), the Beijing Municipal

Science & Technology Commission (No. Z181100001518005), the University of Macau (MYRG2019-00066-FHS), Faculty-allocated funds for PIs (FAF), and the Fundamental Research Funds for the

Central Universities (2020YJ065). AUTHOR INFORMATION Author notes * These authors contributed equally: Yan-Jie Zhao, Shu-Fang Zhang, Wen Li, Ling Zhang. AUTHORS AND AFFILIATIONS * Unit of

Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China Yan-Jie

Zhao, Wen Li & Yu-Tao Xiang * Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China Yan-Jie Zhao, Wen Li & Yu-Tao Xiang * Institute of Advanced Studies in

Humanities and Social Sciences, University of Macau, Macao SAR, China Yan-Jie Zhao, Wen Li & Yu-Tao Xiang * Research Center for Psychological and Health Sciences, China University of

Geosciences, Wuhan, Hubei, China Shu-Fang Zhang * Department of Psychiatry, Wuhan Mental Health Center, Wuhan, Hubei Province, China Shu-Fang Zhang * The National Clinical Research Center

for Mental Disorders & Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University,

School of Mental Health, Beijing, China Ling Zhang * School of Nursing, Hong Kong Polytechnic University, Hong Kong SAR, China Teris Cheung * Department of Psychiatry and Behavioral

Sciences, Emory University, Atlanta, GA, USA Yi-Lang Tang * Mental Health Service Line, Atlanta VA Medical Center, Decatur, GA, USA Yi-Lang Tang * Department of Psychiatry, The Melbourne

Clinic and St Vincent’s Hospital, University of Melbourne, Richmond, VIC, Australia Chee H. Ng * School of Health Sciences, Wuhan University, Wuhan, Hubei, China Bing-Xiang Yang Authors *

Yan-Jie Zhao View author publications You can also search for this author inPubMed Google Scholar * Shu-Fang Zhang View author publications You can also search for this author inPubMed 

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inPubMed Google Scholar * Teris Cheung View author publications You can also search for this author inPubMed Google Scholar * Yi-Lang Tang View author publications You can also search for

this author inPubMed Google Scholar * Chee H. Ng View author publications You can also search for this author inPubMed Google Scholar * Bing-Xiang Yang View author publications You can also

search for this author inPubMed Google Scholar * Yu-Tao Xiang View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS Study design: S-FZ, B-XY,

Y-TX. Data collection, analysis, and interpretation: Y-JZ, WL, LZ, S-FZ, B-XY. Drafting of the manuscript: Y-JZ, TC, Y-TX. Critical revision of the manuscript: Y-LT. Approval of the final

version for publication: all co-authors. CORRESPONDING AUTHORS Correspondence to Bing-Xiang Yang or Yu-Tao Xiang. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing

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INFORMATION 41398_2021_1623_MOESM1_ESM.DOCX Supplementary Table 1. Post-hoc sensitivity analysis: independent correlates of depression and fatigue among close contacts after excluding

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CITE THIS ARTICLE Zhao, YJ., Zhang, SF., Li, W. _et al._ Mental health status and quality of life in close contacts of COVID-19 patients in the post-COVID-19 era: a comparative study.

_Transl Psychiatry_ 11, 505 (2021). https://doi.org/10.1038/s41398-021-01623-0 Download citation * Received: 16 March 2021 * Revised: 04 August 2021 * Accepted: 13 August 2021 * Published:

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