Epidemiological study on severe acute respiratory syndrome coronavirus 2 virus transmission network in northeast China

Abstract

In this study, corona virus disease 2019 (COVID-19) transmission networks were built to analyze the epidemic situation of COVID-19 in Liaoning and Jilin provinces in early 2020. We explore the characteristics of the spread of COVID-19, and put forward effective recommendations for epidemic prevention and control. We collected demographic characteristics, exposure history, and course of action of COVID-19 cases. We described the demographic and case characteristics of these cases to show the basic characteristics of COVID-19 cases in both provinces. Combined with the spatial analysis of confirmed cases, the distribution law of the number of confirmed cases in different regions was analyzed. We exhibit the relationship among COVID-19 cases with a transmission network. The transmission characteristics of COVID-19 were analyzed through the transmission network. Mainly cases in Liaoning and Jilin provinces were imported cases from other provinces and the vast majority of these cases were related to Hubei province. The number of confirmed cases in different regions was positively correlated with their GDP and population. The main clinical symptoms of the cases were fever. Judge from the transmission network relationship between the 2 provinces, the transmission chain in Liaoning province contains fewer cases than that in Jilin province. The main transmission routes of the local cases in the 2 provinces were the family members, and the infection of the imported cases were mainly occurred in public places. It was estimated that the unidentified asymptomatic infected cases in the 2 provinces account for approximately 7.3% of the total number of infected cases. The length of the transmission chain suggests that the spread of COVID-19 can be effectively controlled with effective prevention measures.

Spatiotemporal analysis of the morbidity of global Omicron from November 2021 to February 2022

“…Positive correlations were observed between Omicron morbidity and income support, workplace closures, and containment index. Feng et al 21 found that the number of confirmed cases was positively correlated with gross domestic product in LiaoNing and Jilin, China. Marcos César Ferreira also found that the population most vulnerable to COVID‐19 were those living in the districts with lower salaries and slum areas in the São Paulo municipality, Brazil 19 .…”

“…Feng et al 21 found that the number of confirmed cases was positively correlated with gross domestic product in LiaoNing and Jilin, China.…”