Sociodemographic and Policy Factors Associated with the Transmission of COVID-19: Analyzing Longitudinal Contact Tracing Data from a Northern Chinese City

Abstract

To examine how sociodemographic characteristics and non-pharmaceutical interventions affect the transmission of COVID-19, we analyze patient profiles and contact tracing data from almost all cases in an outbreak in Shijiazhuang, China, from January to February 2021. Because of universal testing and digital tracing, the data are of high quality. Results from negative binomial models indicate that the counts of close contacts and secondary infections vary with the cases’ age and occupation. Notably, cases under age 18 are causing an increased infection rate among their close contacts and leading to more within-neighborhood secondary infections than adults aged 18–49. Also, county-wide interventions and lockdown are found to be effective at containing the spread of COVID-19. These measures can reduce the number of close contacts that each case has and largely restrict the remaining infections to the case’s neighborhood. These results suggest that transmission risks of COVID-19 are associated with the case’s sociodemographic characteristics and can be reduced with interventions at the county level. Implications on mitigation measures and reopening plans are discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s11524-022-00639-1.

COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China

“…We were motivated by the recent contributions mentioned above to establish an age-group model in this study, we assumed that G1 meant age group who were under 60 years old, G2 meant age group who were 60 years old and over. Together with the recent contributions regarding epidemiological characteristics of Shijiazhuang epidemic in ( Guo et al., 2021 ; Liu et al., 2022 ; Lu et al., 2021 ; Sun et al., 2021 ; Zhu et al., 2021 ), we further assumed that the local population was separated into five compartments: the susceptible ( S ), the exposed ( E ), the infected ( I ), the recovered ( R ) and the vaccinated ( V ) when COVID-19 outbroke. The exposed meant the individuals who were infectious with low virus load, they were supposed to spread virus to other individuals hardly.…”

Spatial Transmission Network Analysis of the COVID-19 Outbreak in a Megacity: A Study Based on 2994 Affected Locations in Xi'an in 2021

“…Migration and tourism, especially in the case of male return travelers, have signi cantly contributed to the worldwide dissemination of the epidemic [9,10]. The social attributes of COVID-19 lead to varying exposure risks among different socioeconomic groups [11], with vulnerable populations at a higher risk of infection due to frequent grocery shopping and increased mobility [2].…”