Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 117, Issue 29, Pages 16732-16738Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2006520117
Keywords
COVID-19; pandemic; branching process; compartmental models
Categories
Funding
- NSF [DMS-2027438, DMS-1737770, SCC-1737585, ATD-1737996]
- Simons Foundation [510776]
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The 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 high-light the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.
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