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Other literature type . 2020
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Modeling, post COVID-19

Authors: Press, William H.; Levin, Richard C.;

Modeling, post COVID-19

Abstract

Much of the public first learned about epidemiological modeling during the early months of the coronavirus disease 2019 (COVID-19) pandemic. The first models resulted in more confusion than clarity. Even though coronavirus cases were rising exponentially in the United States and Europe, some models predicted a rapid peak followed by a rapid decline, whereas other models predicted cycles of infection continuing over several years. Much has been learned since those early months. In retrospect, it is clear that modeling requires both reliable data and an accurate understanding of how disease spreads, and that the field of epidemiological modeling requires a diversity of approaches. Support for this field must increase and be coordinated, with a designation of responsibilities among funding agencies.

Keywords

Multidisciplinary, COVID-19, Humans, Models, Biological, Pandemics, United States, Forecasting

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    20
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
bronze