The challenges of modeling and forecasting the spread of COVID-19
Top Cited Papers
Open Access
- 2 July 2020
- journal article
- research article
- Published by Proceedings of the National Academy of Sciences in Proceedings of the National Academy of Sciences of the United States of America
- Vol. 117 (29), 16732-16738
- https://doi.org/10.1073/pnas.2006520117
Abstract
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 highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.Keywords
Funding Information
- National Science Foundation (2027438)
- National Science Foundation (1737770)
- National Science Foundation (1737585)
- National Science Foundation (1737996)
- Simons Foundation (510776)
This publication has 52 references indexed in Scilit:
- The R0 package: a toolbox to estimate reproduction numbers for epidemic outbreaksBMC Medical Informatics and Decision Making, 2012
- A Note on the Derivation of Epidemic Final SizesBulletin of Mathematical Biology, 2012
- The Effective Reproduction Number of Pandemic InfluenzaEpidemiology, 2010
- A likelihood‐based method for real‐time estimation of the serial interval and reproductive number of an epidemicStatistics in Medicine, 2007
- The effect of public health measures on the 1918 influenza pandemic in U.S. citiesProceedings of the National Academy of Sciences of the United States of America, 2007
- Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control MeasuresAmerican Journal of Epidemiology, 2004
- Transmission Dynamics of the Etiological Agent of SARS in Hong Kong: Impact of Public Health InterventionsScience, 2003
- Branching process models for surveillance of infectious diseases controlled by mass vaccinationBiostatistics, 2003
- A new look at the statistical model identificationIEEE Transactions on Automatic Control, 1974
- A contribution to the mathematical theory of epidemicsProceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 1927