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

In terms of model fitting, we state several observations. The SIR-Pre model represents a "worst case" scenario, as if the disease were allowed to run its course. Hence, early in a pandemic like this, it serves a useful purpose to help leaders understand the consequences of taking no action, or delayed action on implementing public health interventions. Beyond that, a basic SIR model, especially one that is used after being fit only to early pandemic data, imparts no further value for informing pandemic response planning, and indeed may provide errant forecasts. This diminished value also holds true when a basic SIR model is fit to contemporary data, yet ignores the effect of a public health intervention, as demonstrated by . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.