Impact of the COVID-19 Pandemic on the Incidence of Notifiable Infectious Diseases in China Based on SARIMA Models Between 2013 and 2021.

BACKGROUND: During the COVID-19 pandemic, the Chinese government implemented nationwide public health interventions to control its spread. However, the impact of these measures on other infectious diseases remains unclear. METHODS: The incidence of three types of notifiable infectious diseases in China were analyzed between 2013 and 2021. The seasonal Mann-Kendall test and Mann-Kendall mutation test were employed to examine trends and mutations in the time series. Based on the counterfactual inference, historical incidence rates were employed to construct SARIMA models and predict incidence between January 2020 and December 2021. Differences between reported and predicted incidences during the pandemic were compared using the Mann-Whitney U test. RESULTS: Between 2013 and 2019, the incidence rate of three types of notifiable infectious diseases fluctuated between 494.05/100,000 and 550.62/100,000. No discernible trend was observed for types A and B infectious diseases (Z = -1.344, P = 0.18). A significant upward trend was observed for type C infectious diseases (Z = 2.56, P = 0.01). In 2020, the overall incidence rate of three types of notifiable infectious diseases decreased to 367.08/100,000. Compared to predicted values, the reported incidence of three types of infectious diseases was, on average, 30.05% lower in 2020 and 16.58% lower in 2021. CONCLUSION: The public health interventions implemented during the pandemic had a positive consequence on the prevention and control of other infectious diseases, with a particularly notable effect on type C infectious diseases. Among the diseases with different transmission routes, respiratory diseases and gastrointestinal or enteroviral diseases decreased significantly.

Factors associated with the enrollment of commercial medical insurance in China: Results from China General Social Survey.

BACKGROUND: The Chinese government has been promoting commercial medical insurance (CMI) in recent decades as it plays an increasingly important role in addressing disease burden, health inequities, and other healthcare challenges. However, compared with developed countries, the CMI is still less fledged with low coverage. OBJECTIVE: This study aims to explore the factors associated with enrollment in CMI, with regards to explicit characteristics (including sociodemographic characteristics and family economic status), latent characteristics (including social security status), and the global incentive compatibility index (including health status), to inform the design of CMI to improve its coverage in China. METHODS: Based on the principal-agent model, we summarized and classified the factors associated with the enrollment in CMI, and then analyzed the data generated from the Chinese General Social Survey in 2015,2018 and 2021 respectively. A comparison of factors regarding sociodemographic characteristics, family economic status, social security status, and health status was conducted between individuals enrolled and unenrolled in CMI using Mann-Whitney U test and Chi-square test. Binary logistic regression analysis was used to explore factors influencing the enrollment status of CMI. RESULTS: Of all individuals, the proportion of enrolled individuals shows an increasing trend year by year, with 8.7%,11.8% and 14.1% enrolled in CMI in 2015,2018 and 2021, respectively. The binary regression analysis further suggested that the factors associated with the enrollment in CMI were consistent in 2015,2018 and 2021.We found that individuals divorced, obese, who had a higher level of education, had non-agricultural household registration, perceived themselves as the upper social status, conducted daily exercise, had more family houses, had a car, had investment activities, or did not have basic health insurance were more likely to be enrolled in CMI. CONCLUSIONS: We identified multidimensional factors associated with the enrollment of CMI, which help inform the government and insurance industry to improve the coverage of CMI.

Analysis of factors associated with depressive symptoms in stroke patients based on a national cross-sectional study.

Post-stroke depression is commonly experienced by stroke survivors and has a significant negative impact on the physical, cognitive, and social functioning of those affected. This study aims to investigate the prevalence of depressive symptoms and their associated factors in Chinese stroke patients. Research samples were selected from the China Health and Retirement Longitudinal Study 2018 survey. Depression was evaluated using the 10-item Center for Epidemiological Studies Depression Scale, with a score ≥ 10 defined as depression. Univariate and multivariable analyses were performed to examine the associations of depressive symptoms with demographics, family relationships, health status, and lifestyle. A total of 963 stroke patients were included and 57.8% of them had depressive symptoms. Depressive symptoms were significantly associated with female sex (OR 1.762, 95% CI 1.235-2.514), lower education level (non-formal education: OR 2.148, 95% CI 1.235-3.737, primary to secondary school education: OR 1.964, 95% CI 1.272-3.033), dissatisfaction with spouse (OR 1.912, 95% CI 1.075-3.401), dissatisfaction with life (OR 1.779, 95% CI 1.080-2.931), dissatisfaction with health (OR 1.592, 95% CI 1.138-2.226), pain (OR 1.392, 95% CI 1.005-1.928) and abnormal sleep (OR 1.557, 95% CI 1.126-2.152). The findings suggest the need for regular depression screening and evaluation after a stroke, and that a well-functioning support system, effective health management, and lifestyle modifications could potentially improve the mental state of stroke patients.