key: cord-329561-4cz2jtt7 authors: Ismael, F.; Bizario, J. C. S.; Battagin, T.; Zaramella, B.; Leal, F. E.; Torales, J.; Ventriglio, A.; Marziali, M. E.; Martins, S. S.; Castaldelli-Maia, J. M. title: Post-infection depression, anxiety and PTSD: a retrospective cohort study with mild COVID-19 patients date: 2020-08-31 journal: nan DOI: 10.1101/2020.08.25.20182113 sha: doc_id: 329561 cord_uid: 4cz2jtt7 Background: It remains unclear whether COVID-19 is associated with psychiatric symptoms during or after the acute illness phase. Being affected by the disease exposes the individual to an uncertain prognosis and a state of quarantine. These factors can predispose individuals to the development of mental symptoms during or after the acute phase of the disease. There is a need for prospective studies assessing mental health symptoms in COVID-19 patients in the post-infection period. Methods: In this retrospective cohort study, nasopharyngeal swabs for COVID-19 tests were collected at patients homes under the supervision of trained healthcare personnel. Patients who tested positive for COVID-19 and were classified as mild cases (N=895) at treatment intake were further assessed for the presence of mental health disorders (on average, 56.6 days after the intake). We investigated the association between the number of COVID-19 symptoms at intake and depression, anxiety and PTSD, adjusting for previous mental health status, time between baseline and outcome, and other confounders. Multivariate logistic regression and generalized linear models were employed for categorical and continuous outcomes, respectively. Findings: Depression, anxiety and PTSD were reported by 26.2% (N=235), 22.4% (N=201), and 17.3% (N=155) of the sample. Reporting an increased number of COVID-related symptoms was associated with depression (aOR=1.059;95%CI=1.002-1.119), anxiety (aOR=1.072;95%CI=1.012-1.134), and PTSD (aOR=1.092;95%CI=1.024-1.166). Sensitivity analyses supported findings for both continuous and categorical measures. Interpretation: Exposure to an increased number of COVID-19 symptoms may predispose individuals to depression, anxiety and PTSD after the acute phase of the disease. These patients should be monitored for the development of mental health disorders after COVID-19 treatment discharge. Early interventions, such as brief interventions of psychoeducation on coping strategies, could benefit these individuals. The COVID-19 pandemic has affected more than 8 million individuals worldwide (Kim et al., 2020) . Despite the efforts to limit viral spread, cases are increasing worldwide and deaths are continually occurring (Aljabali et al., 2020) . This pandemic is generating further mental issues such as insomnia, anxiety, depression, stress, anger, and fear (Torales et al., 2020) . Those directly or indirectly affected by the virus could be more disturbed by these symptoms (Torales et al., 2020; Vindegaard & Benros, 2020) . Word cloud studies indicate that uncertainties about lack of COVID-19 tests and medical supplies are common (Lwin et al., 2020) . There is still much uncertainty about the best treatment to be administered to individuals affected by the disease (Lwin et al., 2020) . Though highly transmissible, most cases present with mild symptoms (Aljabali et al., 2020) . However, having been affected by the disease exposes the individual to an uncertain prognosis and a need to quarantine to mitigate viral spread (Fernández et al., 2020) . These factors can predispose individuals to the development of mental symptoms during or after the acute phase of the disease. It is unclear whether COVID-19 can produce psychiatric symptoms during or after the acute illness phase (Vindegaard & Benros, 2020; Sinanović et al., 2020) . In general, survivors of critical illnesses have a high level of mental symptoms after the condition improves. Depression, anxiety and post-traumatic stress disorder (PTSD) are among the most reported events in patients with these conditions (Sparks, 2018) . Patients infected with SARS-CoV-1 had a high rate of depressive symptoms during follow-up after the acute phase of the disease (Cheng et al., 2004; Wu et al., 2005; Lee et al., 2007) . These symptoms lasted for an extended period, being reported up to a year after the improvement in SARS-CoV-1 symptoms (Lee et al., 2007) . Anxiety symptoms were also reported during the post-SARS-CoV-1 follow-up (Cheng et al., 2004; Wu et al., 2005) . Some studies in Asia investigated depression and/or anxiety in patients admitted in hospitals due to COVID-19 (Guo et al., 2020; Hu et al., 2020; Nguyen et al., 2020 , Zhang et al., 2020 . In a case-control design, Guo et al. (2020) investigated the mental status and inflammatory markers of 103 COVID-19 hospitalized mild patients, matching them with controls that were COVID-19 negative. Hu et al. (2020) carried out a cross-sectional survey with COVID-19 inpatients in two isolation wards of a COVID-19 designated hospital. Zhang et al. (2020) evaluated the prevalence and severity of depression and anxiety within patients recently recovered from COVID-19 infection, who were under quarantine. In Vietnam, Nguyen et al. (2020) carried out a cross-sectional study with individuals infected by COVID-19 attending outpatient departments of nine hospitals and health centers across the country. All these studies found increased levels of both anxiety and depression (6.8-21.0% and 7.4-31.5%, respectively). There was no follow-up study to investigate prospective symptoms of depression and anxiety in COVID-19 patients. The ongoing COVID-19 pandemic has disrupted the lives of many across the globe, resulting in an increased burden of physical and mental health consequences. Through this analysis, we investigated the association between COVID-19 symptoms and post-infection depression, anxiety and post-traumatic stress disorder (PTSD) among a sample of patients diagnosed with mild COVID-19 in Brazil. There is a need for prospective studies assessing mental health symptoms in COVID-19 patients, evaluating the post-infection period in other regions of the world. The present study was approved by the local ethics committee (Comissão de Ética para Análise de Projeto de Pesquisa -CAPPesq, protocol No. 32293020.9 .0000.5510, approved on July 13 th , 2020). This was a retrospective cohort study. All people who tested positive for COVID-19 and classified as mild cases at treatment intake (baseline: April 6 th to July 15 th ) were considered for the presence of mental health disorders in a follow-up assessment (outcome: July 20 th to early August 7 th ). We investigated the association between the number of COVID-19 symptoms at intake and depression, anxiety and PTSD in the follow-up assessment, adjusting for previous mental health status, and the time between the baseline and outcome, among other possible confounders. Sensitivity analyses were carried out where we excluded: (i) individuals with a short time between baseline and outcome assessment (≧ 14 days), because these individuals could be in the late active phase of the COVID-19 disease, and (ii) those who progressed to a more severe case of COVID-19. Residents of the municipality ≥ 18 years of age with suspected COVID-19 symptoms were encouraged to contact the dedicated Corona São Caetano platform via the website (access at https://coronasaocaetano.org/) or by phone (baseline: April 6 th to July 15 th ). They were invited to complete an initial screening questionnaire that included socio-demographic data; information on symptoms type, onset and duration; and recent contacts. People meeting the suspected COVID-19 case definition (i.e., having at least two of the following symptoms: fever, cough, sore throat, coryza, or change in/loss of smell (anosmia); or one of these symptoms plus at least two other symptoms consistent with COVID-19) were further evaluated, whilst people not meeting these criteria were reassured, advised to stay at home and contact the service again if they were to develop new symptoms or the worsening of current ones. Patients were then asked by a medical student to complete a risk assessment. There were no refusals. All pregnant women, and patients meeting pre-defined triage criteria for severe disease, were advised to attend a hospital service -either an emergency department or outpatient service, depending on availability. All other patients were offered a home visit for self-collection of a nasopharyngeal swab (NPS -both nostrils and throat), which were collected at the patients' homes under the supervision of trained healthcare personnel. More details can be found in Leal et al. (2020) . Due to shortages of some reagents, two RT-PCR platforms were used at different times during the study: ALTONA RealStar® SARS-CoV-2 RT-PCR Kit 1.0 (Hamburg, Germany) and the Mico BioMed RT-qPCR kit (Seongnam, South Korea) . For serology, we tested 10μL of serum or plasma (equivalent in performance) using a qualitative rapid chromatographic immunoassay (Wondfo Biotech Co., Guangzhou, China), that jointly detects anti-SARS172 CoV-2 IgG/IgM. The assay has been found to have a sensitivity of 81.5% and specificity of 99.1% in a U.S. study. In our local validation, after two weeks of symptoms, the sensitivity in RT-PCR confirmed cases (N=59) was 94.9%, and specificity in biobank samples (N=106) from 2019 was 100%. Patients testing RT-PCR negative were followed up by the primary health care program of their residential area. They were advised to contact the platform for additional consultation if they developed new symptoms. All patients testing SARS-CoV-2 RT-PCR positive (N=1,757) were invited to participate in the retrospective cohort study (N = 895), in which we assessed depression and anxiety (outcome: July 20 th to early August 7 th ). We had a response rate of 50.9%. Table S1 presents differences a comparison between those that agreed to participate (N=895) and those that did not (N=862). People that agreed to participate in the study were younger and reported more headaches, anosmia and dysgeusia, and less tachypnea and joint pain than those that refused to be part of the study. More importantly, no significant difference was found regarding the total number of COVID-19 symptoms, which was our main exposure measure. Patients testing positive for SARS-CoV-2 via RT-PCR were followed up to 14 days (a maximum of 7 phone calls) from completion of their initial questionnaire. They were contacted every 48 hours by a medical student (supervised by a medical doctor) who completed another risk assessment and recorded any ongoing or new symptoms. Following the COVID-19 clinical assessment protocol of São Caetano do Sul (Leal et al., 2020), the following COVID-19 symptoms were assessed during these contacts: dyspnea; tachypnea; persistent fever (≥ 72 hours); mental health disturbance (e.g., changes in consciousness, thought, perception); fever (at any timepoint); cough; sore throat; nasal congestion; coryza; headache; fatigue; asthenia; lack of appetite; myalgia; joint pain; diarrhea; nausea; vomit; anosmia; and dysgeusia. The total number of symptoms during the treatment was the primary exposure investigated in the present study. The GAD-7 scale is an instrument for assessing, diagnosing and monitoring anxiety. It was created by Spitzer et al. (2006) . It was validated by Kroenke et al. (2007) , according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders -Fourth Edition (DSM-IV), for the assessment of signs and symptoms of anxiety disorder, and also to classify severity levels. This study uses the Brazilian Portuguese validated version (Moreno et al., 2017) . GAD-7 consists of seven items, on a four-point scale: 0 (not at all), 1 (several days), 2 (more than half the days), and 3 (nearly every day). The total score ranges from 0 to 21, assessing the frequency of signs and symptoms of anxiety over a two-week period. No missingness was observed in any of the question items. A cutoff ≥ 10 was used for the categorical diagnosis of anxiety (Muñoz-Navarro et al., 2017) . In our sample, we found a Cronbach's alpha of 0.92 (Table S1 ). The PHQ-9 scale is an adaptation of the PRIME-MD (Sptizer et al., 1994) . It is a brief instrument for assessing, diagnosing and monitoring depression. It was validated by Spitzer et al. (1999) and by Kroenke et al. (2001) . The present study uses a version which has been translated and validated to Brazilian Portuguese (de Lima Osório et al., 2009 ). PHQ-9 was created based on the DSV-IV criteria for Major Depressive Disorder, for the assessment of its signs and symptoms, and also to classify severity levels. It consists of nine items, arranged on a frequency four-point scale: 0 (not at all), 1 (several days), 2 (more than half the days), and 3 (nearly every day). Its score ranges from 0 to 21, assessing the frequency of signs and symptoms of anxiety over two weeks. No missingness was observed in any of the question items. A cutoff ≥ 10 was used for the categorical diagnosis of depression (Levis et al., 2019) . In our sample, we found a Cronbach's alpha of 0.90 (Table S1) . Weathers et al. (1993) developed the PCL-C scale, which was translated, adapted and validated to Brazilian Portuguese (Berger et al., 2004; Lima et al., 2012) to assess the consequences of different types of traumatic experiences. It is based on the DSM-III diagnostic criteria for PTSD. The patient must report the levels of last-month disturbance by 17 items, using a severity scale ranging from 1 (not at all), 2 (a little bit), 3 (moderately, 4 (quite a bit), and 5 (extremely). No missingness was observed in any of the question items. A cutoff ≥ 44 for the categorical diagnosis of PTSD (Archer et al., 2016) . In our sample, we found a Cronbach's alpha of 0.94 (Table S1 ). Lifetime diagnosis of psychiatric disorder (yes vs. no), current psychiatric treatment (yes vs. no), age (continuous: 18-88 years), gender (male vs. female), education (up to high school vs. more than high school), civil status (married vs. single, which included previously married), income level (as defined by the Brazilian Institute of Geography and Statistics: up to three times the typical salary for a minimum wage job vs. more), current health treatment for any acute or chronic medical condition (yes vs. no) and time between the treatment intake and mental assessment (continuous: 6-116 days), were assessed as potential confounders. STATA software version 16.2 was used to run the analysis. Initially, we performed a comparison between those who attended the mental health follow-up assessment and were included in the present study (N= 895) and those who did not, using logistic regression models. This comparison was performed to identify any potential baseline difference between the groups, which could generate bias to our outcome analysis (e.g., higher number of COVID-19-related symptoms among those not included). Our final analytical sample included 895 participants. We first conducted a descriptive analysis of the COVID-19 treatment intake profile, sociodemographic measures, and the health profile of included patients. Secondly, we described the mean and prevalences of anxiety, depression and PTSD in these patients. We then created scatterplot figures for continuous outcomes across time. Multivariate logistic regression models for categorical outcomes (binarized scales) were carried out. These models were adjusted for all aforementioned confounders listed in section 2.4.3. Two distinct models were carried out, one which included lifetime psychiatric diagnosis, and the other included current psychiatric treatment, due to significant correlation between these two variables determined via pairwise testing (p<0.05). We subsequently ran sensitivity analyses, where we excluded: (i) individuals with a short time between baseline and outcome assessment, as individuals could be in the late active phase of the COVID-19 disease (≧ 14 days), (ii) those who progressed to a more severe COVID-19 case, and (iii) those with a previous psychiatric diagnosis. In a final sensitivity analysis, we ran multivariate generalized linear models (GLM) for the continuous outcomes. Based on a previous study (Gustavsson et al., 2014) , gamma-family GLM with log link were the models of choice, because of a log-normal distribution of the continuous outcomes of depression, anxiety and PTSD in our sample (Figures S1, S2, and S3). Table 1 shows descriptive analysis of our sample (N=895). The majority were female (60.4%), married (51.4%), and had up to high-school education (60.4%) and three minimum salaries per month of income (58.9%). Around one in every five individuals have had a psychiatric disorder during lifetime (20.1%). Only about half of these individuals have been undergoing psychiatric treatment (10.5%). Current health treatment was reported by 43.1% of the sample. Regarding COVID-19 symptomatic profile, patients had a mean of 4.2 COVID-19-related symptoms. The most common symptoms were anosmia (51.9%), dysgeusia (49.6%), cough (43.1%), headache (41.3%), and fatigue (36.9%), being reported by more than 35% of the sample. Table 2 presents depressive, anxiety and post-traumatic stress symptoms and disorders in the sample. Depression, anxiety and PTSD were reported by 26.2% (N = 235), 22.4% (N = 201), and 17.3% (N = 155) of the sample. Among these patients, 39.2% (N = 92), 37.8% (N = 76), and 50.3% (N = 78), had a previous psychiatric diagnosis during lifetime. On average, we assessed patient mental health almost two months after the treatment intake (mean = 56.6 days, 95%CI = 54.7-58.5), with the vast being assessed after the acute phase of the disease (78.7%, N = 840). Few patients (6.7%, N = 61) were referred for in-person consultation. Figures 1A, 1B, and 1C present scatterplots of mean scores of depression, anxiety, and PTSD (y-axis) by the time of the mental health assessment (x-axis). There were wide ranges of scores for all disorders, more concentrated in the lower severity levels during the entire period (from 1 week to almost four months). For all disorders, a similar pattern of distribution was found through the time of the mental health assessment. Table 3 presents the results of the logistic regression models of the exposure (previous total number of symptoms of COVID-19) for the outcomes (categorical diagnosis of depression, anxiety disorder and PTSD). The exposure was significantly associated with all the outcomes, after adjustment for all confounders. In the sensitivity analysis (Table 4) , these results remained significant after the exclusion of (i) individuals with a short time between baseline and outcome assessment (≥ 14 days), as individuals could be in the late active phase of the COVID-19 disease, (ii) those who progressed to a more severe COVID-19 case, and (iii) those with a previous psychiatric diagnosis. In the final sensitivity analysis (GLM for continuous outcomes), we found a significant relationship between number of COVID-19 symptoms and all the outcomes, with the exception of PTSD when adjusting for lifetime psychiatric disorder (p = 0.053). The present study aimed to investigate the post-infection levels of mental health disorders among individuals with mild COVID-19 disease. We aimed to investigate whether COVID-19 infection symptomatology could be associated with mental health disorders. We found that an increased number of COVID-related symptoms were associated with depression, anxiety, and PTSD. Sensitivity analyses supported those findings for the categorical clinical diagnosis of such disorders. More importantly, our findings adjusted for confounders that could increase the vulnerability of mental health disorders. These results shed light on a significant subpopulation at risk for mental disorders. This has been the largest study . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . evaluating mental health symptoms in patients who had COVID-19 disease to date, and the only study assessing mental health status of patients with prior COVID-19 infections. Four studies in Asia investigated depression and/or anxiety in COVID-19 patients using the same scales used in the present study (Guo et al., 2020; Hu et al., 2020; Nguyen et al., 2020 , Zhang et al., 2020 . Prevalence of depression and anxiety varied between 7.4-31.5%.and 6.8-21.0%, respectively (Guo et al., 2020; Hu et al., 2020; Nguyen et al., 2020 , Zhang et al., 2020 . All of these studies were conducted in Asia (three in China and one in Vietnam). The prevalence of depression in our study (26.2%) is included within this interval, but anxiety prevalence was greater (22.4%) than previously reported values (6.8-21.0%). Our results were more similar to those found by Zhang et al. (2020), who sampled home-quarantined COVID-19 patients. The lowest depression and anxiety prevalences were found in the Guo et al. (2020) (Lin et al., 2007) . Previous estimates of PTSD levels within Brazil were 8.5% (de Castro Longo et al., 2020) demonstrating that the prevalence of PTSD within individuals presenting with mild COVID-19 is increased in comparison to past estimates. Our results support the hypothesis that the prevalence of depression, anxiety and PTSD were elevated in people with increased number of COVID-19 symptoms at baseline. These findings echo warnings from the previous SARS outbreak, wherein survivors of SARS infections experienced increased psychological distress, persisting one year or more subsequent to the outbreak (Lee et al., 2007) . Similar findings were observed following the occurrence of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2015, indicating that survivors experienced mental health consequences following the outbreak (Park et al., 2020) . Mental health supports should be strengthened, and healthcare systems must prepare for an influx of individuals experiencing psychological distress as a result of the COVID-19 pandemic. Following the PTSD model, these individuals should be referred to early interventions. Brief interventions of psychoeducation on coping strategies have been effective in promoting mental health among individuals who experienced traumatic life events (Oosterbaan et al., 2019) . Internet-based psychological intervention for acute COVID-19 patients has also been described, and could be an interesting early-intervention tool for those who experience psychological distress during this phase (Wei et al., 2020) . It is unclear whether COVID-19 can produce psychiatric symptoms during or after the acute illness phase (Vindegaard & Benros, 2020) . Neuropsychiatric issues, such as: headaches, paresthesia, myalgia, impaired consciousness, confusion or delirium, and cerebrovascular diseases have been reported among individuals with COVID-19 (Sinanović et al., 2020) . However, the symptoms assessed in the present study (i.e., depressive, anxiety and PTSD) are substantially different from neuropsychiatric symptoms observed among some individuals . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . in the acute phase of COVID-19. In addition, we found no differences of level of mental health symptomatology depending on the time of assessment after the acute phase of the disease. Thus, it seems improbable that depressive, anxiety and PTSD symptoms could be a direct effect of the SARS-CoV-2. Rather, it is likely that the increased prevalence of mental health disorders post-COVID-19 is resultant from the psychosocial context of the pandemic (Dubey et al., 2020). People who have been infected with COVID-19 have likely experienced long periods of quarantine, and some have reported fear of transmitting the virus to members of their social and familial networks (Iglesia-Sanchez et al., 2020) . This, in combination with uncertainties surrounding treatment and clinical course (Guo et al.,2020) , could be working synergistically to worsen mental health symptoms. Future studies should explore neurobiological effects of SARS-Coronavirus-2 and mental health impacts. Assessing people for depression, anxiety, and PTSD at different timepoints should be noted as an important limitation of the present study. However, we adjusted all the logistic regression and GLM models to the time of assessment and also conducted sensitivity analyses, excluding those who could potentially be assessed during the acute phase of COVID-19 and testing whether the continuous or categorical version. We were also not able to assess other important behavioral disorders (i.e., substance use and sleep disorders). However, we were able to assess the most prevalent disorders following traumatic experiences in almost a thousand COVID-19 patients, with an acceptable response rate. The patients included in the present study were slightly different from those who did not attend the invitation. Despite being the latter being older, no significant difference was found for the total number of COVID-19 symptoms, which was our exposure measure. Exposure to increased levels of COVID-19 symptomatology may predispose individuals to depression, anxiety and PTSD after the acute phase of the disease, independently of previous psychiatric diagnosis. These patients should be monitored for the development of mental health disorders after COVID-19 treatment discharge. Early mental health intervention such as psychotherapy and supportive groups could play an important role in preventing incident mental health problems in these people. It is probable that the increased prevalence of mental health disorders post-COVID-19 is due to the social and psychological context of the disease. However, further studies should investigate the possible neurobiological mechanisms linking COVID-19 and mental health conditions. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. -19 pandemic. Brain, behavior, and immunity, 87, 49-50. https://doi.org/10.1016/j.bbi.2020.04.031 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . D e s c r i p t i v e a n a l y s i s o f 8 9 5 p a t i e n t s c l a s s i f i e d a s h a v i n g m i l d C O V I D -1 9 a t t r e a t m e n t i n t a k e , S ã o C a e t a n o d . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . https://doi.org/10.1101/2020.08.25.20182113 doi: medRxiv preprint T a b l e 2 . D e p r e s s i v e , a n x i e t y a n d p o s t -t r a u m a t i c s t r e s s s y m p t o m s a n d d i s o r d e r s a m o n g 8 9 5 p a t i e n t s w h o h a d p r e v i o u s l y m i l d C O V I D -1 9 , S ã o C a e t a n o d o S u l , 2 0 2 0 . M e a n 9 5 % C I C u t t o f f n % D e p r e s s i v e S y m p t o m s / D e p r e s s i o n ( P H Q . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . Figures 1A-1B-1C . Scatterplots of mean scores of depression, anxiety, and PTSD (y-axis) by the time of the mental health assessment (x-axis). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020 . . https://doi.org/10.1101 T a b l e 3 . R e s u l t s o f t h e m u l t i v a r i a t e l o g i s t i c r e g r e s s i o n m o d e l s a m o n g 8 9 5 p a t i e n t s w h o h a d p r e v i o u s l y m i l d C O V I D -1 9 , S ã o C a e t a n o d o S u l , 2 0 2 0 . E x p o s u r e : T o t a l n u m b e r o f C O V I D -1 9 s y m p t o m s C a t e g o r i c a . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted August 31, 2020. . T a b l e 4 . R e s u l t s o f t h e s e n s i t i v i t y a n a l y s i s a m o n g 8 9 5 p a t i e n t s w h o h a d p r e v i o u s l y m i l d C O V I D -1 9 , S ã o C a e t a n o d o S u l , 2 0 2 0 . E x p o s u r e : T o t a l n u m b e r o f C O V I D -1 9 s y m p t o m s C a t e g o r i c a . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 31, 2020. . Figures S1-S2-S3 . Distribution of the continuous outcomes of depression, anxiety and PTSD in our sample. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 31, 2020. . https://doi.org/10.1101/2020.08.25.20182113 doi: medRxiv preprint T a b l e S 2 . L o g i s t i c r e g r e s s i o n m o d e l s f o r f o l l o w -u p v e r s u s m i s s i n g a m o n g t h o s e c l a s s i f i e d a s h a v i n g m i l d C O V I D -1 9 p a t i e n t s a t t r e a t m e n t i n t a k e , S ã o C a e t a n o d o S u l , 2 0 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 31, 2020. . https://doi.org/10. 1101 Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends. 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