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Proc. Natl. Acad. Sci. U.S.A. · Jul 2020
The challenges of modeling and forecasting the spread of COVID-19.
- Andrea L Bertozzi, Elisa Franco, George Mohler, Martin B Short, and Daniel Sledge.
- Department of Mathematics, University of California, Los Angeles, CA 90095; bertozzi@ucla.edu.
- Proc. Natl. Acad. Sci. U.S.A. 2020 Jul 21; 117 (29): 16732-16738.
AbstractThe 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.Copyright © 2020 the Author(s). Published by PNAS.
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