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Title: Spatio-temporal Bayesian modeling of county level Covid-19 in South Carolina Authors:  Andrew Lawson - Medical University of South Carolina (United States) [presenting]
Joanne Kim - Medical University of South Carolina (United States)
Abstract: Covid-19 has spread around the world and has become a pandemic in 2020. Locally within the US, the spread of the disease had been highly variable and considerable spatial heterogeneity has been apparent. In addition, data quality issues abound. We outline a spatially-referenced susceptible-infected-removed (SIR) model that can be used to describe the dynamics of symptomatic transmission. We also treat asymptomatic cases as latent variables. Deaths are also modeled. The modeling is at county level in South Carolina, although other spatial scales could be examined using these tools. Prediction of outbreaks and general future events is also discussed.