Emergence of oscillations in a simple epidemic model with demographic data
| Autor: | Alex R. Gogliettino, Chialin Yu, Raj Saha, Meredith L. Greer, Kyle Zollo-Venecek |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Demographic data 01 natural sciences epidemic 010305 fluids & plasmas 03 medical and health sciences 0103 physical sciences Quantitative Biology::Populations and Evolution emergence Statistical physics Set (psychology) lcsh:Science 030304 developmental biology Simple (philosophy) 0303 health sciences Multidisciplinary Oscillation Mechanism (biology) oscillation Birth–death process Term (time) smallpox data lcsh:Q Epidemic model Mathematics mathematical model Research Article |
| Zdroj: | Royal Society Open Science, Vol 7, Iss 1 (2020) Royal Society Open Science |
| ISSN: | 2054-5703 |
| DOI: | 10.1098/rsos.191187 |
| Popis: | A simple susceptible–infectious–removed epidemic model for smallpox, with birth and death rates based on historical data, produces oscillatory dynamics with remarkably accurate periodicity. Stochastic population data cause oscillations to be sustained rather than damped, and data analysis regarding the oscillations provides insights into the same set of population data. Notably, oscillations arise naturally from the model, instead of from a periodic forcing term or other exogenous mechanism that guarantees oscillation: the model has no such mechanism. These emergent natural oscillations display appropriate periodicity for smallpox, even when the model is applied to different locations and populations. The model and datasets, in turn, offer new observations about disease dynamics and solution trajectories. These results call for renewed attention to relatively simple models, in combination with datasets from real outbreaks. |
| Databáze: | OpenAIRE |
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