The challenges of modeling and forecasting the spread of COVID-19
dc.contributor.author | Bertozzi, Andrea L. | |
dc.contributor.author | Franco, Elisa | |
dc.contributor.author | Mohler, George | |
dc.contributor.author | Short, Martin B. | |
dc.contributor.author | Sledge, Daniel | |
dc.contributor.department | Computer and Information Science, School of Science | en_US |
dc.date.accessioned | 2020-07-09T14:36:25Z | |
dc.date.available | 2020-07-09T14:36:25Z | |
dc.date.issued | 2020-07-02 | |
dc.description.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. | en_US |
dc.eprint.version | Final published version | en_US |
dc.identifier.citation | Bertozzi, 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.2006520117 | en_US |
dc.identifier.issn | 1091-6490 | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/23207 | |
dc.language.iso | en_US | en_US |
dc.publisher | National Academy of Sciences | en_US |
dc.relation.isversionof | 10.1073/pnas.2006520117 | en_US |
dc.relation.journal | Proceedings of the National Academy of Sciences | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source | Publisher | en_US |
dc.subject | COVID-19 | en_US |
dc.subject | Compartmental Models | en_US |
dc.subject | Modeling | en_US |
dc.subject | Forecasting | en_US |
dc.title | The challenges of modeling and forecasting the spread of COVID-19 | en_US |
dc.type | Article | en_US |
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