I.C. Esobi^1,, M. K. Lasode², C. I Anyanwu², M.O Flores Barriguete³, M. A. Okorie⁴, D.O Lasode⁵

Apart from clinical and epidemiological factors, a multitude of demographic, social, and economic factors also influence the extent of the coronavirus disease prevalence within a population. Consequently, there is ongoing discourse regarding the socio-economic predictors of COVID-19. This study explores the influence of several demographic and socio-economic variables on COVID-19 cases in all 46 counties of South Carolina, USA as of October 18, 2020. To understand the level of association between the demographic and socio-economic variables with the coronavirus disease outcome, we employed a spatial mapping technique in a geographic information system (GIS) to assess social vulnerabilities of populations dependent on public assistance income and spatially compared the distribution with COVID-19 cases across the 46 counties in South Carolina, USA. We find that dependence on food stamps showed a positive but weak correlation to COVID-19. For individual variables, Age and poverty were strongly associated with dependence on public assistance and were determined to be major predictors of COVID-19. Social vulnerability assessment showed an interesting spatial pattern of counties with high prevalence of COVID-19 cases also having high social vulnerabilities. The results complement knowledge about the COVID-19 pandemic beyond clinical and biological risk factors by assessing socio-economic perspectives and determinants. Findings from this study can inform policy decisions on poverty alleviation, public assistance, and food security programs.

food insecurity, COVID-19, social vulnerability, SNAP