Spatially Refined Time-Varying Reproduction Numbers of COVID-19 by Health District in Georgia, USA, March–December 2020
Chigozie A. Ogwara,
Arshpreet Kaur Mallhi,
Xinyi Hua,
Kamalich Muniz-Rodriguez,
Jessica S. Schwind,
Xiaolu Zhou,
Jeffery A. Jones,
Joanne Chopak-Foss,
Gerardo Chowell,
Isaac Chun-Hai Fung
Affiliations
Chigozie A. Ogwara
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Arshpreet Kaur Mallhi
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Xinyi Hua
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Kamalich Muniz-Rodriguez
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Jessica S. Schwind
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Xiaolu Zhou
Department of Geography, AddRan College of Liberal Arts, Texas Christian University, Fort Worth, TX 76109, USA
Jeffery A. Jones
Department of Health Policy and Community Health, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Joanne Chopak-Foss
Department of Health Policy and Community Health, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
Gerardo Chowell
Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA 30302, USA
Isaac Chun-Hai Fung
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA 30460, USA
This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, Rt of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package ‘EpiEstim’ to the time series of historical daily incidence of confirmed cases, 2 March–15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log10-transformed per capita cumulative case count and log10-transformed population size. We observe Rt fluctuations as state and countywide policies are implemented. Policy changes are associated with increases or decreases at different time points. Rt increases, following the reopening of schools for in-person instruction in August. Evidence suggests that counties with lower population size had a higher per capita cumulative case count on June 15 (slope = −0.10, p = 0.04) and October 15 (slope = −0.05, p = 0.03), but not on August 15 (slope = −0.04, p = 0.09), nor December 15 (slope = −0.02, p = 0.41). We found extensive community transmission of SARS-CoV-2 across all 18 health districts in Georgia with median 7-day-sliding window Rt estimates between 1 and 1.4 after March 2020.
