Modeling COVID-19 latent prevalence to assess a public health intervention at a state and regional scale

Philip J. Turk; Shih-Hsiung Chou; Marc A. Kowalkowski; Pooja P. Palmer; Jennifer S. Priem; Melanie D. Spencer; Yhenneko J. Taylor; Andrew D. McWilliams

While the effects of the COVID-19 pandemic are experienced globally, many key health policy decisions designed to reduce transmissions are determined at national and regional levels. These critical policy decisions must be implemented quickly and evaluated continuously so they can be adapted to the local context, recognizing the clear effect that geography, community context, density and social determinants of health have on COVID-19 outcomes. In North Carolina (NC), the first COVID-19 case was reported on March 2, 2020, and cases increased to 3,963 total confirmed cases as of April 10 [12] . To slow the rapidly increasing transmission rate, within a few weeks after the 1st case was detected, NC state officials promoted social distancing strategies (i.e., deliberately increasing physical space), banned large social gatherings, and closed public schools and universities. Subsequently, a stay-at-home order, which only allows for essential travel outside the home, was issued in the southwestern part of the state by Mecklenburg County effective at 8 am March 26, lasting through April 16 (since extended to April 29) , while a statewide stay-at-home order was issued effective at 5 pm March 30, lasting to April 29.