Association between work stress and mental health in Chinese public health workers during the COVID-19 epidemic: mediating role of social support and self-efficacy.

Background: Little is known about the mediating mechanisms underlying the association between work stress and mental health, especially among primary public health workers (PHWs). We aimed to evaluated the association between work stress and mental health among PHWs, and explore the mediating roles of social support and self-efficacy. Methods: A large-scale cross-sectional survey was conducted among 3,809 PHWs from all 249 community health centers in 16 administrative districts throughout Shanghai, China. Pearson correlation and hierarchical linear regression were used to explore the associations among work stress, social support, self-efficacy and mental health. Structural equation modeling (SEM) was conducted to examine the mediation effects. Results: The prevalence of depression and anxiety symptoms among primary PHWs was 67.3 and 55.5%, respectively. There is a significant positive direct effect of work stress on mental health (ß = 0.325, p < 0.001). Social support and self-efficacy partially mediated the relationship between work stress and mental health, respectively. Meanwhile, the chained mediating effects of social support and self-efficacy also buffered the predictive effects of work stress on anxiety and depression symptoms (ß = 0.372, p < 0.001). Conclusion: Work stress has significant direct and indirect effects on mental health among primary PHWs. Enhancing social support and self-efficacy may be effective psychological interventions to mitigate the effects of work-related stress on mental health. These findings highlight the severity of mental health problems among primary public health workers and provide new evidence for early prevention and effective intervention strategies.

Gender-Specific and U-Shaped Relationship Between Serum Uric Acid and All-Cause Mortality Among Chinese Older Adults: A National Population-Based Longitudinal Study.

Objectives: This study aimed to prospectively investigate gender-specific relationship between hyperuricemia and all-cause mortality among Chinese older adults. Methods: The study was based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) 2008-2018, a prospective nationwide cohort of older adults in China. Multivariate Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs for all-cause mortality. Restricted cubic splines (RCS) were conducted to explore the dose-response relationship between SUA levels and all-cause mortality. Results: For older women, compared to the participants in the third quartile of SUA level, those in the highest quartile of SUA was associated with significantly higher risk of all-cause mortality in the fully adjusted model (HR: 1.41, 95% CI: 1.03-1.92). No significant associations between SUA levels and all-cause mortality were observed in older men. The present study further found a U-shaped non-linear relationship between SUA levels and all-cause mortality in both sexes of older population (P for non-linear <0.05). Conclusions: This study provided prospective epidemiological evidence for the predictive role of SUA on all-cause mortality among the Chinese aging population over 10 years of follow-up, while revealing considerable gender-related differences.

TNF-α derived from arsenite-induced microglia activation mediated neuronal necroptosis.

Arsenic, an identified environmental toxicant, poses threats to the health of human beings through contaminated water and food. Recently, increasing reports focused on arsenic-induced nerve damage, however, the underlying mechanism remains elusive. Microglia are important immune cells in the nervous system, which produce a large number of inflammatory factors including TNF-α when activated. Recent reports indicated that TNF-α is involved in the process of necroptosis, a new type of programmed cell death discovered recently. Although there were evidences suggested that arsenic could induce both microglia activation and TNF-α production in the nervous system, the mechanism of arsenic-induced neurotoxicity due to microglia activation is rarely studied. In addition, the role of microglia-derived TNF-α in response to arsenic exposure in necroptosis has not been documented before. In this study, we found that arsenite induced microglial activation through p38 MAPK signaling pathway, leading to the production of TNF-α. Microglia-derived TNF-α further induced necroptosis in the neuronal cells. Our findings suggested that necroptosis induced by microglia-derived TNF-α upon arsenite exposure partially played a role in arsenic-induced cell death which underlie the fundamental event of arsenic-related neurotoxicity.

Prediction Model for the Risk of HIV Infection among MSM in China: Validation and Stability.

The impact of psychosocial factors on increasing the risk of HIV infection among men who have sex with men (MSM) has attracted increasing attention. We aimed to develop and validate an integrated prediction model, especially incorporating emerging psychosocial variables, for predicting the risk of HIV infection among MSM. We surveyed and collected sociodemographic, psychosocial, and behavioral information from 547 MSM in China. The participants were split into a training set and a testing set in a 3:1 theoretical ratio. The prediction model was constructed by introducing the important variables selected with the least absolute shrinkage and selection operator (LASSO) regression, applying multivariate logistic regression, and visually assessing the risk of HIV infection through the nomogram. Receiver operating characteristic curves (ROC), Kolmogorov-Smirnov test, calibration plots, Hosmer-Lemeshow test and population stability index (PSI) were performed to test validity and stability of the model. Four of the 15 selected variables-unprotected anal intercourse, multiple sexual partners, involuntary subordination and drug use before sex-were included in the prediction model. The results indicated that the comprehensive prediction model we developed had relatively good predictive performance and stability in identifying MSM at high-risk for HIV infection, thus providing targeted interventions for high-risk MSM.

Microglia-derived IL-1ß promoted neuronal apoptosis through ER stress-mediated signaling pathway PERK/eIF2α/ATF4/CHOP upon arsenic exposure.

Arsenic is the leading toxicant of hazardous environmental chemicals, which is linked with neurotoxicity including cognitive dysfunction, neurodevelopmental alterations and neurodegenerative disorders. It has been suggested that sustained pro-inflammatory response is one of the triggering factors of arsenic-induced neurotoxicity. Microglia, the immune cells in the central nervous system, response to physiological and pathological stress, and release a large array of pro-inflammatory cytokines if activated excessively. Several studies indicated that arsenic was capable of inducing microglia activation, however, the role of the subsequently released pro-inflammatory cytokines in arsenic-induced neurotoxicity remains to be elucidated. Our findings demonstrated that arsenic-induced cognitive dysfunction, microglia activation, up-regulation and release of IL-1ß and ER stress-mediated apoptosis could be attenuated by minocycline, a recognized inhibitor of microglia activation. In addition, the IL-1 receptor antagonist IL-1ra diminished arsenic-induced activation of ER stress-mediated apoptotic pathway PERK/eIF2α/ATF4/CHOP and neuronal apoptosis. Our findings provided evidences that arsenic-induced microglia activation also contributed to neuronal apoptosis through pro-inflammatory cytokine. Microglia-derived IL-1ß promoted hippocampal neuronal apoptosis through ER stress-mediated PERK/eIF2α/ATF4/CHOP apoptotic pathway. Neuronal apoptosis induced by prolonged activation of microglia was partially involved in the arsenic-induced cognitive dysfunction.

Effective mitigation strategy in early stage of COVID-19 pandemic in China.

In the past five months, success in control the national epidemic of coronavirus disease 2019 (COVID-19) has been witnessed in China. The implementation of public health measures accounts for the success which include different interventions in the early or later stages of the outbreak. It is clear that although not all measures were universally effective worldwide, their achievements have been significant. More solidarity is needed to deal with this global pandemic with more learning and understanding. Understanding which of the public health interventions implemented in China were effective may provide ideas for international epidemic control.

Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios.

The coronavirus disease 2019 (COVID-19) has become a life-threatening pandemic. The epidemic trends in different countries vary considerably due to different policy-making and resources mobilization. We calculated basic reproduction number (R0) and the time-varying estimate of the effective reproductive number (Rt) of COVID-19 by using the maximum likelihood method and the sequential Bayesian method, respectively. European and North American countries possessed higher R0 and unsteady Rt fluctuations, whereas some heavily affected Asian countries showed relatively low R0 and declining Rt now. The numbers of patients in Africa and Latin America are still low, but the potential risk of huge outbreaks cannot be ignored. Three scenarios were then simulated, generating distinct outcomes by using SEIR (susceptible, exposed, infectious, and removed) model. First, evidence-based prompt responses yield lower transmission rate followed by decreasing Rt. Second, implementation of effective control policies at a relatively late stage, in spite of huge casualties at early phase, can still achieve containment and mitigation. Third, wisely taking advantage of the time-window for developing countries in Africa and Latin America to adopt adequate measures can save more people's life. Our mathematical modeling provides evidence for international communities to develop sound design of containment and mitigation policies for COVID-19.

Impact of temperature on the dynamics of the COVID-19 outbreak in China.

A COVID-19 outbreak emerged in Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. The effects of temperature on the dynamics of the COVID-19 epidemic in China are unknown. Data on COVID-19 daily confirmed cases and daily mean temperatures were collected from 31 provincial-level regions in mainland China between Jan. 20 and Feb. 29, 2020. Locally weighted regression and smoothing scatterplot (LOESS), distributed lag nonlinear models (DLNMs), and random-effects meta-analysis were used to examine the relationship between daily confirmed cases rate of COVID-19 and temperature conditions. The daily number of new cases peaked on Feb. 12, and then decreased. The daily confirmed cases rate of COVID-19 had a biphasic relationship with temperature (with a peak at 10 °C), and the daily incidence of COVID-19 decreased at values below and above these values. The overall epidemic intensity of COVID-19 reduced slightly following days with higher temperatures with a relative risk (RR) was 0.96 (95% CI: 0.93, 0.99). A random-effect meta-analysis including 28 provinces in mainland China, we confirmed the statistically significant association between temperature and RR during the study period (Coefficient = -0.0100, 95% CI: -0.0125, -0.0074). The DLNMs in Hubei Province (outside of Wuhan) and Wuhan showed similar patterns of temperature. Additionally, a modified susceptible-exposed-infectious-recovered (M-SEIR) model, with adjustment for climatic factors, was used to provide a complete characterization of the impact of climate on the dynamics of the COVID-19 epidemic.

Phase- and epidemic region-adjusted estimation of the number of coronavirus disease 2019 cases in China.

The outbreak of the coronavirus disease 2019 was first reported in Wuhan in December 2019 and gradually spread to other areas in China. After implementation of prevention and control measures, the estimation of the epidemic trend is needed. A phase- and region-adjusted SEIR model was applied for modeling and predicting the number of cases in Wuhan, Hubei Province and regions outside Hubei Province in China. The estimated number of infections could reach its peak in late February 2020 in Wuhan and Hubei Province, which is 55 303-84 520 and 83 944-129 312, respectively, while the epidemic peaks in regions outside Hubei Province in China could appear on February 13, 2020 with the estimated 13 035-19 108 cases. According to the estimation, the outbreak would abate in March and April all over China. Current estimation provided evidence for planned work resumption under stringent prevention and control in China to further support the fight against the epidemic. Nevertheless, there is still possibility of the second outbreak brought by the work resumption and population migration, especially from Hubei Province and high intensity cities outside Hubei Province. Strict prevention and control measures still need to be considered in the regions with high intensity of epidemic and densely-populated cities.

Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China.

An outbreak of clusters of viral pneumonia due to a novel coronavirus (2019-nCoV/SARS-CoV-2) happened in Wuhan, Hubei Province in China in December 2019. Since the outbreak, several groups reported estimated R0 of Coronavirus Disease 2019 (COVID-19) and generated valuable prediction for the early phase of this outbreak. After implementation of strict prevention and control measures in China, new estimation is needed. An infectious disease dynamics SEIR (Susceptible, Exposed, Infectious, and Removed) model was applied to estimate the epidemic trend in Wuhan, China under two assumptions of Rt . In the first assumption, Rt was assumed to maintain over 1. The estimated number of infections would continue to increase throughout February without any indication of dropping with Rt = 1.9, 2.6, or 3.1. The number of infections would reach 11,044, 70,258, and 227,989, respectively, by 29 February 2020. In the second assumption, Rt was assumed to gradually decrease at different phases from high level of transmission (Rt = 3.1, 2.6, and 1.9) to below 1 (Rt = 0.9 or 0.5) owing to increasingly implemented public health intervention. Several phases were divided by the dates when various levels of prevention and control measures were taken in effect in Wuhan. The estimated number of infections would reach the peak in late February, which is 58,077-84,520 or 55,869-81,393. Whether or not the peak of the number of infections would occur in February 2020 may be an important index for evaluating the sufficiency of the current measures taken in China. Regardless of the occurrence of the peak, the currently strict measures in Wuhan should be continuously implemented and necessary strict public health measures should be applied in other locations in China with high number of COVID-19 cases, in order to reduce Rt to an ideal level and control the infection.

COVID-19 containment: China provides important lessons for global response.

The world must act fast to contain wider international spread of the epidemic of COVID-19 now. The unprecedented public health efforts in China have contained the spread of this new virus. Measures taken in China are currently proven to reduce human-to-human transmission successfully. We summarized the effective intervention and prevention measures in the fields of public health response, clinical management, and research development in China, which may provide vital lessons for the global response. It is really important to take collaborative actions now to save more lives from the pandemic of COVID-19.