An Application of the Partially Observed Markov Process in the Analysis of Transmission Dynamics of COVID-19 via Wastewater

Abstract

As the ongoing outbreak of Coronavirus Disease 2019 (COVID-19) is severely affecting all over the world, analysis of the transmission of COVID-19 is of more and more interest. We focus on the application of compartmental models in the analysis of transmission of COVID-19 based on the detected viral load in wastewater and the reported number of cases. The measurement of COVID-19 RNA concentrations in primary sludge gives us information about the virus prevalence on a population level. Since the transmission of COVID-19 is a partially observed Markov process including different states, we consider a likelihood-based approach to our statistical inference to understand the inner relationship between different states and how COVID-19 actually transmits. Understanding the transmission dynamics of COVID-19 could give suggestions on public policies.