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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.

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.

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.

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].

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