Spatially Refined Time-Varying Reproduction Numbers of COVID-19 by Health District in Georgia, USA, March–December 2020

Abstract

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, <i>R_t</i> 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 <i>R_t</i> fluctuations as state and countywide policies are implemented. Policy changes are associated with increases or decreases at different time points. <i>R_t</i> 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, <i>p</i> = 0.04) and October 15 (slope = -0.05, <i>p</i> = 0.03), but not on August 15 (slope = -0.04, <i>p</i> = 0.09), nor December 15 (slope = -0.02, <i>p</i> = 0.41). We found extensive community transmission of SARS-CoV-2 across all 18 health districts in Georgia with median 7-day-sliding window <i>R_t</i> estimates between 1 and 1.4 after March 2020.