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Temporal Geospatial Analysis Of Covid-19 Pre-Infection Determinants Of Risk In South Carolina, Tianchu Lyu, Nicole L. Hair, Nicholas Yell, Zhenlong Li, Shan Qiao, Chen Liang, Xiaoming Li

Faculty Publications

Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal–geospatial associations between PIDRs and COVID-19 infection at the county level in South Carolina. We used the spatial error model (SEM), spatial lag model (SLM), and conditional autoregressive model (CAR) as global models and the geographically weighted regression model (GWR) as a local model. The data were retrieved from multiple sources including …

Spatial-Temporal Relationship Between Population Mobility And Covid-19 Outbreaks In South Carolina: Time Series Forecasting Analysis, Chengbo Zeng, Jiajia Zhang Ph.D., Zhenlong Li Ph.D., Xiaowen Sun, Bankole Olatosi Ph.D., Sharon Weissman, Xiaoming Li Ph.D.

Faculty Publications

Background: Population mobility is closely associated with COVID-19 transmission, and it could be used as a proximal indicator to predict future outbreaks, which could inform proactive nonpharmaceutical interventions for disease control. South Carolina is one of the US states that reopened early, following which it experienced a sharp increase in COVID-19 cases.

Objective: The aims of this study are to examine the spatial-temporal relationship between population mobility and COVID-19 outbreaks and use population mobility data to predict daily new cases at both the state and county level in South Carolina.

Methods: This longitudinal study used disease surveillance …