The effect of sociodemographic factors on COVID-19 incidence of 342 cities in China: a geographically weighted regression model analysis.

BACKGROUND: Since December 2019, the coronavirus disease 2019 (COVID-19) has spread quickly among the population and brought a severe global impact. However, considerable geographical disparities in the distribution of COVID-19 incidence existed among different cities. In this study, we aimed to explore the effect of sociodemographic factors on COVID-19 incidence of 342 cities in China from a geographic perspective. METHODS: Official surveillance data about the COVID-19 and sociodemographic information in China's 342 cities were collected. Local geographically weighted Poisson regression (GWPR) model and traditional generalized linear models (GLM) Poisson regression model were compared for optimal analysis. RESULTS: Compared to that of the GLM Poisson regression model, a significantly lower corrected Akaike Information Criteria (AICc) was reported in the GWPR model (61953.0 in GLM vs. 43218.9 in GWPR). Spatial auto-correlation of residuals was not found in the GWPR model (global Moran's I = - 0.005, p = 0.468), inferring the capture of the spatial auto-correlation by the GWPR model. Cities with a higher gross domestic product (GDP), limited health resources, and shorter distance to Wuhan, were at a higher risk for COVID-19. Furthermore, with the exception of some southeastern cities, as population density increased, the incidence of COVID-19 decreased. CONCLUSIONS: There are potential effects of the sociodemographic factors on the COVID-19 incidence. Moreover, our findings and methodology could guide other countries by helping them understand the local transmission of COVID-19 and developing a tailored country-specific intervention strategy.

Epidemic characteristics of close contacts of coronavirus disease 2019 in Xi'an

Objective To explore the epidemic characteristics of close contacts of corona virus disease 2019(COVID-19) in Xi'an so as to provide reference for further prevention and control of the epidemic. Methods Data of the close contacts of COVID-19 in Xi'an was collected. We analyzed the distribution of close contacts in the population and isolation measures of close contacts and confirmed cases among different exposure conditions. Results By 0: 00 February 28, the cumulative number of confirmed cases and close contacts in Xi'an had been 120 and 5 241, respectively.Medical workers accounted for 7.92% of the close contacts. Across different age groups, the proportion of the youth group was the highest (56%). Indifferent areas of Xi'an, Yanta District had the largest number of close contacts(913) while Huyi District had the lowest number (29). The main contact route was contact within the family (1 875). The majority of the confirmed cases were infected within the family (35), followed by shopping places (26). Conclusion By 0: 00 February 28, close contacts of COVID-19 in Xi'an had mostly been found in Yanta District. The young constituted the main group, and close contacts within the family had a high risk of infection. In view of the above characteristics, it is necessary to improve the screening of people having close contact with COVID-19 in key areas and populations.