Prevalence and related factors of depression, anxiety, and insomnia among medical staff during COVID-19 pandemic

[Background] The epidemic of coronavirus disease 2019 (COVID-19) seriously affects the psychological status of medical staff who directly face the risk of the disease. [Objective] This study investigates the prevalence and related factors of depression, anxiety, and insomnia among medical staff during the COVID-19 pandemic. [Methods] From February 13 to March 1, 2020, a network questionnaire survey was conducted among 482 medical staff selected by convenience sampling. A self-designed questionnaire was used to investigate the basic demographic information and COVID-19-related questions. The Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Insomnia Severity Index (ISI) were used to estimate the prevalence of depression, anxiety, and insomnia among the medical staff. Stepwise multiple linear regression analysis was performed with PHQ-9 score, GAD-7 score, and ISI score as dependent variables. Multivariate logistic regression analysis (forward-conditional method) on depression, anxiety, and insomnia as dependent variables was performed with basic demographic information and COVID-19-related questions as independent variables. [Results] Among the surveyed medical staff, the prevalence rates of depression, anxiety, and insomnia were 14.3%, 11.2%, and 23.2%, respectively. There were no significant differences in the prevalence rates among different age, gender, local risk level, and occupation groups and those aiding Hubei Province or not. The medical staff who directly contacted fever or diagnosed patients had more serious depression (b=1.73, 95%CI: 0.79-2.66) and insomnia (b=2.43, 95%CI: 1.48-3.39) and a higher risk of insomnia (OR=1.89, 95%CI: 1.21-2.96). The medical staff whose current protective measures cannot prevent infection had more serious depression (b=1.72, 95% CI: 0.65-2.80), anxiety (b=1.75, 95% CI: 0.76-2.75), and insomnia (b=1.73, 95% CI: 0.63-2.82), and had a higher risk of depression (OR=1.97, 95% CI: 1.11-3.49), anxiety (OR=3.00, 95%CI: 1.64-5.46), and insomnia (OR=1.79, 95%CI: 1.08-2.96). [Conclusion] During the COVID-19 epidemic, the risks of depression, anxiety, and insomnia among selected medical staff are increased compared with the non-epidemic period. Occupational exposure to high-risk groups and protective measures would significantly affect mental health of medical staff.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Can government subsidies and public mechanisms alleviate the physical and mental health vulnerability of China's urban and rural residents?

BACKGROUND: Poverty vulnerability has been defined as the likelihood of a family falling into poverty in the upcoming months. Inequality is a major cause of poverty vulnerability in developing countries. There is evidence that establishing effective government subsidies and public service mechanisms significantly reduces health poverty vulnerability. One of the ways to study poverty vulnerability is by using empirical data such as income elasticity of demand to perform the analysis. Income elasticity refers to the extent to which changes in consumers' income affect changes in demand for commodities or public goods. In this work, we assess health poverty vulnerability in rural and urban China. We provide two levels of evidence on the marginal effects of the design and implementation of government subsidies and public mechanisms in reducing health poverty vulnerability, before and after incorporating the income elasticity of demand for health. METHODS: Multidimensional physical and mental health poverty indexes, according to the Oxford Poverty & Human Development Initiative and the Andersen model, were implemented to measure health poverty vulnerability by using the 2018 China Family Panel Survey database (CFPS) as the data source for empirical analysis. The income elasticity of demand for health care was used as the key mediating variable of impact. Our assessment was conducted by a two-level multidimensional logistic regression using STATA16 software. RESULTS: The first level regression indicates that the marginal utility of public mechanism (PM) in reducing urban and rural vulnerability as expected poverty on physical and mental health (VEP-PH&MH) was insignificant. On the other hand, government subsidies (GS) policies had a positive suppression effect on VEP-PH&MH to a relatively low degree. The second level regression found that given the diversity of health needs across individual households, i.e., the income elasticity of demand (HE) for health care products, PM and GS policies have a significant effect in reducing VEP-PH&MH in rural and urban areas. Our analysis has verified the significant positive impact of enacting accurate GS and PM policies on effectively reducing VEP-PH&MH in rural as well as urban areas. CONCLUSIONS: This study shows that implementing government subsidies and public mechanisms has a positive marginal effect on reducing VEP-PH&MH. Meanwhile, there are individual variations in health demands, urban-rural disparities, and regional disparities in the effects of GS and PM on inhibiting VEP-PH&MH. Therefore, special consideration needs to be given to the differences in the degree of health needs of individual residents among urban and rural areas and regions with varying economic development. Furthermore, considerations of this approach in the current worldwide scenario are analyzed.

Analysis on occurrence and risk factors of drug-induced liver injury in patients with novel coronavirus pneumonia.

Objective: To analyze the occurrence and risk factors of drug-induced liver injury (DILI) in patients with novel coronavirus pneumonia (COVID-19). Method(s): The medical records of patients with COVID-19 who were discharged from the First Hospital of Changsha from January 15 to March 7, 2020 were collected and the patients were divided into the DILI group and the non-DILI group based on DILI diagnostic criteria. Basic information of patients in the 2 groups including gender, age, underlying diseases, classification of COVID-19, liver function test results on admission and after medication, drug use, time to DILI onset after medication, and treatments and outcomes of DILI were recorded and compared. The incidence of DILI in patients with COVID-19 was calculated, and the factors whose P<0.05 in inter-group comparison were included in the multivariate logistic regression analysis to calculate the odds ratio (OR) and95% confidence interval (CI). Result(s): A total of 203 discharged patients with COVID-19 met the inclusion criteria. Of them, 36 patients developed DILI, the incidence was 17.73%. Between the DILI group and the non-DILI group (167 patients), the differences were statistically significant in gender distribution, proportion of patients with underlying diseases such as hypertension, fatty liver, and cholelithiasis, clinical classification of COVID-19, and the kinds of drug use (P<0.05 for all), but not statistically significant in levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin (TBil) on admission (P>0.05 for all). The levels of ALT and AST in patients in the DILI group after medication were higher than those before medication, and the differences were statistically significant (P<0.001 for all). The median time for time to DILI onset after medication was 8 (6, 11) days and none of the patients had obvious clinical signs and symptoms. After the occurrence of DILI, 16 patients stopped the suspicious drugs and received liver-protective treatments, 6 patients only stopped the suspicious drug without additional treatments, and 14 patients received liver-protective treatments without drug withdrawal. Among the 36 patients in the DILI group, liver function were improved in 34 patients but did not returned to normal in 2 patients when they were discharged from the hospital. Multivariate logistic regression analysis showed that male (OR=3.939, 95%CI: 1.426-10.883, P=0.008), being severe and critical in clinical classification (OR=6.433, 95%CI: 2.411-17.162, P<0.001), fatty liver (OR=3.815, 95%CI: 1.298-11.215, P=0.015), cholelithiasis (OR=16.347, 95%CI: 1.267-210.990, P=0.032), and the kinds of drug use >8 (OR=10.181, 95%CI: 3.606-28.744, P<0.001) were the independent risk factors of DILI in patients with COVID-19. Conclusion(s): The incidence of DILI in COVID-19 patients discharged from the First Hospital of Changsha is 17.73%. Male, being severe and critical in clinical classification of COVID-19, fatty liver, cholelithiasis, and the kinds of drug use >8 are the independent risk factors for DILI patients with COVID-19.Copyright © 2020 by the Chinese Medical Association.

C-reactive protein to lymphocyte ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 patients.

Objective: The aim of the present study is to assess the utility of C-reactive protein to Lymphocyte Ratio (CLR) in predicting short-term clinical outcomes of patients infected by SARS-CoV-2 BA.2.2. Methods: This retrospective study was performed on 1,219 patients with laboratory-confirmed SARS-CoV-2 BA.2.2 to determine the association of CLR with short-term clinical outcomes. Independent Chi square test, Rank sum test, and binary logistic regression analysis were performed to calculate mean differences and adjusted odds ratios (aORs) with their 95% CI, respectively. Results: Over 8% of patients admitted due to SARS-CoV-2 BA.2.2. were critically ill. The best cut-off value of CLR was 21.25 in the ROC with a sensitivity of 72.3% and a specificity of 86%. After adjusting age, gender, and comorbidities, binary logistic regression analysis showed that elevated CLR was an independent risk factor for poor short-term clinical outcomes of COVID-19 patients. Conclusion: C-reactive protein to Lymphocyte Ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 inflicted patients.

Delay in seeking health care from community residents during a time with low prevalence of COVID-19: A cross-sectional national survey in China.

Background: The pandemic of COVID-19 has significant implications on health resources allocation and health care delivery. Patients with non-COVID illness may have to change their care seeking behaviors to mitigate the risk of infections. The research aimed to investigate potential delay of community residents in seeking health care at a time with an overall low prevalence of COVID-19 in China. Methods: An online survey was conducted in March 2021 on a random sample drawn from the registered survey participants of the survey platform Wenjuanxing. The respondents who reported a need for health care over the past month (n = 1,317) were asked to report their health care experiences and concerns. Logistic regression models were established to identify predictors of the delay in seeking health care. The selection of independent variables was guided by the Andersen's service utilization model. All data analyses were performed using SPSS 23.0. A two-sided p value of <0.05 was considered as statistically significant. Key results: About 31.4% of respondents reported delay in seeking health care, with fear of infection (53.5%) as a top reason. Middle (31-59 years) age (AOR = 1.535; 95% CI, 1.132 to 2.246), lower levels of perceived controllability of COVID-19 (AOR = 1.591; 95% CI 1.187 to 2.131), living with chronic conditions (AOR = 2.008; 95% CI 1.544 to 2.611), pregnancy or co-habiting with a pregnant woman (AOR = 2.115; 95% CI 1.154 to 3.874), access to Internet-based medical care (AOR = 2.529; 95% CI 1.960 to 3.265), and higher risk level of the region (AOR = 1.736; 95% CI 1.307 to 2.334) were significant predictors of the delay in seeking health care after adjustment for variations of other variables. Medical consultations (38.7%), emergency treatment (18.2%), and obtainment of medicines (16.5%) were the top three types of delayed care, while eye, nose, and throat diseases (23.2%) and cardiovascular and cerebrovascular diseases (20.8%) were the top two conditions relating to the delayed care. Self-treatment at home was the most likely coping strategy (34.9%), followed by Internet-based medical care (29.2%) and family/friend help (24.0%). Conclusions: Delay in seeking health care remained at a relatively high level when the number of new COVID-19 cases was low, which may present a serious health risk to the patients, in particular those living with chronic conditions who need continuous medical care. Fear of infection is the top reason for the delay. The delay is also associated with access to Internet-based medical care, living in a high risk region, and perceived low controllability of COVID-19.

Comparison of clinical characteristics of COVID-19 in pregnant women between the Delta and Omicron variants of concern predominant periods

Background: Information regarding effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant strains on clinical manifestations and outcomes of coronavirus disease 2019 (COVID-19) in pregnant women is limited. Methods: A retrospective observational study was conducted using the data from the nationwide COVID-19 registry in Japan. We identified pregnant patients with symptomatic COVID-19 hospitalized during the study period. The Delta and Omicron variants of concern (VOC) predominant periods were defined as August 1 to December 31, 2021 and January 1 to May 31, 2022, respectively. Clinical characteristics were compared between the patients in the Delta and Omicron VOC periods. In addition, logistic regression analysis was performed to identify risk factors for developing moderate-to-severe COVID-19. Results: During the study period, 310 symptomatic COVID-19 cases of pregnant women were identified;111 and 199 patients were hospitalized during the Delta and Omicron VOC periods, respectively. Runny nose and sore throat were more common, and fatigue, dysgeusia, and olfactory dysfunction were less common manifestations observed in the Omicron VOC period. In the multivariable logistic regression analysis, onset during the later stage of pregnancy (OR: 2.08 [1.24–3.71]) and onset during the Delta VOC period (OR: 2.25 [1.08–4.90]) were independently associated with moderate-to-severe COVID-19, whereas two doses of SARS-CoV-2 vaccine were protective against developing moderate-to-severe COVID-19 (OR: 0.34 [0.13–0.84]). Conclusions: Clinical manifestations of COVID-19 in pregnant women differed between the Delta and Omicron VOC periods. SARS-CoV-2 vaccination was still effective in preventing severe COVID-19 throughout the Delta and Omicron VOC periods. © 2022 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases

Factors Affecting Access to Public Healthcare Facilities in the City of Tshwane, South Africa.

Access to healthcare services is largely determined by socioeconomic factors, with economically well-off individuals obtaining healthcare services more efficiently than those who are disadvantaged. This paper aims to assess the effects of socioeconomic and other related factors on access to healthcare facilities in the City of Tshwane, South Africa, during the COVID-19 pandemic. Data were sourced from the Gauteng City-Region Observatory (GCRO) quality of life survey (2020/2021). Multivariate logistic regression was applied. Results showed that 66.3% of the respondents reported that they had access to public healthcare facilities within their area. Furthermore, results showed that those who lived in informal houses were significantly (OR = 0.55, 95% CI [0.37-0.80], p < 0.01) less likely to report that they had access to public healthcare facilities in their area compared to those who lived in formal houses. More efforts need to be undertaken to ensure that all citizens have access to public healthcare facilities, especially among those who are disadvantaged, such as informal dwellers. In addition, future research should encompass locality in relation to the factors that affect access to public healthcare facilities, especially during pandemics such as the COVID-19 pandemic, in order to have geographically targeted interventions.

A Novel 3-Gene Signature for Identifying COVID-19 Patients Based on Bioinformatics and Machine Learning.

Although many biomarkers associated with coronavirus disease 2019 (COVID-19) were found, a novel signature relevant to immune cells has not been developed. In this work, the "CIBERSORT" algorithm was used to assess the fraction of immune infiltrating cells in GSE152641 and GSE171110. Key modules associated with important immune cells were selected by the "WGCNA" package. The "GO" enrichment analysis was used to reveal the biological function associated with COVID-19. The "Boruta" algorithm was used to screen candidate genes, and the "LASSO" algorithm was used for collinearity reduction. A novel gene signature was developed based on multivariate logistic regression analysis. Subsequently, M0 macrophages (PRAUC = 0.948 in GSE152641 and PRAUC = 0.981 in GSE171110) and neutrophils (PRAUC = 0.892 in GSE152641 and PRAUC = 0.960 in GSE171110) were considered as important immune cells. Forty-three intersected genes from two modules were selected, which mainly participated in some immune-related activities. Finally, a three-gene signature comprising CLEC4D, DUSP13, and UNC5A that can accurately distinguish COVID-19 patients and healthy controls in three datasets was constructed. The ROCAUC was 0.974 in the training set, 0.946 in the internal test set, and 0.709 in the external test set. In conclusion, we constructed a three-gene signature to identify COVID-19, and CLEC4D, DUSP13, and UNC5A may be potential biomarkers for COVID-19 patients.

Spatial and temporal patterns and factors influencing the spread of the COVID-19 pandemic in China

It is essential to unravel the spatial and temporal patterns of the spread of the epidemic in China during the backdrop of the global coronavirus disease 2019 (COVID-19) outbreak in 2020, as the underlying drivers are crucial for scientific formulation of epidemy-preventing strategies. A discriminant model for the spatio-temporal pattern of epidemic spread was developed for 317 prefecture-level cities using accumulated data on confirmed cases. The model was introduced for the real-time evolution of the outbreak starting from the rapid spread of COVID-19 on January 24, 2020, until the control on March 18, 2020. The model was used to analyze the basic characteristics of the spatio-temporal patterns of the epidemic spread by combining parameters such as peak position, full width at half maximum, kurtosis, and skewness. A multivariate logistic regression model was developed to unravel the key drivers of the spatio-temporal patterns based on traffic accessibility, urban connectivity, and population flow. The results of the study are as follows. (1) The straight-line distance of 588 km from Wuhan was used as the effective boundary to identify the four spatial patterns of epidemic spread, and 13 types of spatio-temporal patterns were obtained by combining the time-course categories of the same spatial pattern. (2) The spread of the epidemic was relatively severe in the leapfrogging model. Besides the short-distance leapfrogging model, significant differences emerged in the spatial patterns of the time course of epidemic spread. The peaks of the new confirmed cases in various spatio-temporal patterns were mostly observed on February 3, 2020. The average full widths at the half maximum of all ordinary cities were approximately 14 days, thus, resonating with the incubation period of the COVID-19 virus. (3) The degree of the population correlation with Wuhan city has mainly influenced the spreading and the short-distance leapfrogging spatial patterns. The existence of direct flight from Wuhan city exhibited a positive effect on the long-distance leapfrogging spatial pattern. The number of population outflows has significantly affected the leapfrogging spatial pattern. The integrated spatial pattern was influenced by both primary and secondary epidemic outbreak sites. Thus, cities should pay great attention to traffic control during the epidemic as analysis has shown that the spatio-temporal patterns of epidemic spread in the respective cities can curb the spread of the epidemic from key links. © 2022, Science Press. All right reserved.

Factors influencing the acquisition of COVID infection among high-risk contacts of COVID-19 patients in Madurai district-A case control study.

Introduction: COVID is a new disease; understanding the transmission dynamics and epidemiological characteristics may help in developing the effective control measures. The study is done 1. To determine the various factors influencing the acquisition of COVID-19 infection among high-risk contacts 2. To estimate the secondary attack rate among high-risk contacts 3. To determine the factors in COVID index cases influencing their secondary attack rate. Methodology: Unmatched case control study was conducted from March to August 2020 among 139 COVID index cases in Madurai district from March-May (Reference period) and their 50 COVID positive (cases), 551 COVID negative (controls) high-risk contacts. Case investigation form* and contact tracing Proforma*were used to collect data. Chi-square test and independent sample t test were used to find out the association. Univariate* and Multivariate logistic regression* were used to predict the risk of various factors in acquisition of COVID infection with the help of adjusted and unadjusted odds ratio. P value < 0.05 was considered statistically significant. Results: Male contacts (P = 0.005, OR = 2.520), overcrowding (P = 0.007, OR = 3.810), and duration of exposure to index case (for 4-7 days P = 0.014, OR = 2.902, for >7 days P = 0.001, OR = 6.748 and for > 12 hours/day P = 0.000, OR = 5.543) were significant factors predicted to be associated with acquisition of COVID infection among high-risk contacts. Reproductive number (R0)* estimated was 1.3. Secondary attack rate (SAR)* estimated among high-risk contacts was 8.32%. Index cases whose outcome was death (P = 0.026); symptomatic index cases (P = 0.000), cases with fever (P = 0.001); sorethroat (P = 0.019); breathlessness (P = 0.010); cough (P = 0.006) and running nose (P = 0.002) had significantly higher mean SAR than their counterparts. Conclusion: Contacts with above said risk factors who were found to be more prone to infection could be given special focus to prevent the transmission in them.

"Factors influencing the outcome of COVID-19 patients admitted in a tertiary care hospital, Madurai.- a cross-sectional study".

INTRODUCTION: COVID19* is a new disease with significant mortality risk. Because of the scarcity of the study on factors associated with the mortality in Tamil Nadu present study was done to determine the factors associated with the outcome of the COVID19 patients admitted in a tertiary care hospital, Madurai. METHODOLOGY: 4530 lab confirmed COVID19 patients admitted from March to August 31st, 2020; excluding the non-responders or who gave incomplete information were included in the study. Data retrieved from Case Investigation Forms *filled through telephonic interview. Chi -square test, Univariate and multivariate logistic regression were used to find out the association between the factors and risk of death(outcome). RESULTS: Out of 4530 COVID19 positive patients 381(8.4%) died and 4149(91.6%) were discharged. Using multivariate logistic regression* following were the factors predicted to be associated with mortality:Age group <17yrs(PR = 4.12),30-44yrs(PR = 2.28),45-59(PR = 3.12),60-69(PR = 4.26) and ≥ 70(PR = 7.05); male gender(PR = 1.26); breathlessness at the time of admission(PR = 7.05); with 1symptom (PR = 2.58), 2symptoms(PR = 3.16) and ≥ 3 symptoms(PR = 2.45); chronic kidney disease(PR = 3.07), malignancy(PR = 2.39); other chronic diseases(PR = 1.89); having only diabetes(PR = 1.58); diabetes with hypertension (PR = 1.70); diabetes with heart disease(PR = 1.94); Hypertension with heart disease(PR = 2.30); diabetes with hypertension and heart disease(PR = 1.58). Survival probability* was more than 90% when patient gets admitted within a week after symptom onset,<80% for between 7 and 10 days and declines thereafter. CONCLUSION: Early insights into factors associated with COVID-19 deaths have been generated in the context of a global health emergency *which may help the treating physician.

Analyses the effects of COVID-19 outbreak on human sexual behaviour using ordinary least-squares based multivariate logistic regression.

This study aimed to evaluate the impact of COVID-19 on sexual, mental and physical health. There were 262 respondents included in this study (38% female and 62% male) above 18 years of age from India. Statistical analysis was performed using Ordinary Least Squares (OLS) based on multivariate logistic regression analysis. The numerical tests were performed by using Python 3 engine and R-squared (coefficient of multiple determinations for multiple regressions) for prediction and P value > 0.5 is considered to be statistically significant. The study outcomes were obtained using a study-specific questionnaire to assess the quality of sex life, changes in sexual behavior and mental health. Frequency of sexual intercourse, frequency of watching porn, sexual hygiene, frequency of physical activity, depression, desire for parenthood in female respondents have more significant R 2 (0.903, 0.976, 0.973, 0.989, 0.985, 0.862) value respectively as compared to male respondents. Financial anxiety, Smoking and drinking habits in male respondents have more significant R 2 (0.917, 0.964) value respectively as compared to female respondents. The aim of this study is to understand quality of sex life, sexual behavior, reproductive planning, mental health, physical health and adult coping during the COVID-19 pandemic, as well as how past experiences have affected. Many respondents had a broad variety of problems concerning their sexual and reproductive well being. Measures should be set in order to safeguard the mental and sexual health of people during the pandemic.