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  An autonomous compartmental model for accelerating epidemics

Budanur, N. B., & Hof, B. (2022). An autonomous compartmental model for accelerating epidemics. PLoS One, 17(7): e0269975. doi:10.1371/journal.pone.0269975.

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2110.06352.pdf (Preprint), 863KB
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Budanur, Nazmi Burak1, Author           
Hof, Bjorn2, Author
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1Max Planck Institute for the Physics of Complex Systems, Max Planck Society, ou_2117288              
2external, ou_persistent22              

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 Abstract: In Fall 2020, several European countries reported rapid increases in COVID-19 cases along with growing estimates of the effective reproduction rates. Such an acceleration in epidemic spread is usually attributed to time-dependent effects, e.g. human travel, seasonal behavioral changes, mutations of the pathogen etc. In this case however the acceleration occurred when counter measures such as testing and contact tracing exceeded their capacity limit. Considering Austria as an example, here we show that this dynamics can be captured by a time-independent, i.e. autonomous, compartmental model that incorporates these capacity limits. In this model, the epidemic acceleration coincides with the exhaustion of mitigation efforts, resulting in an increasing fraction of undetected cases that drive the effective reproduction rate progressively higher. We demonstrate that standard models which does not include this effect necessarily result in a systematic underestimation of the effective reproduction rate.

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Language(s): eng - English
 Dates: 2022-07-182022-07-21
 Publication Status: Issued
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Title: PLoS One
  Abbreviation : PLoS One
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 17 (7) Sequence Number: e0269975 Start / End Page: - Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850