Bertozzi, Andrea L.Franco, ElisaMohler, GeorgeShort, Martin B.Sledge, Daniel2020-07-092020-07-092020-07-02Bertozzi, A. L., Franco, E., Mohler, G., Short, M. B., & Sledge, D. (2020). The challenges of modeling and forecasting the spread of COVID-19. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.20065201171091-6490https://hdl.handle.net/1805/23207The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional-scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.en-USAttribution 4.0 InternationalCOVID-19Compartmental ModelsModelingForecastingArticle