A Mathematical Study of COVID-19 Spread by Vaccination Status in Virginia

We introduce a novel n-stage vaccination model and corresponding system of differential equations that stratify a population according to their vaccination status. The model is an extension of the classical SIR-type models commonly used for time-course simulations of infectious disease spread and al...

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Veröffentlicht in:Applied sciences 2022-02, Vol.12 (3), p.1723
Hauptverfasser: Johnston, Matthew D., Pell, Bruce, Nelson, Patrick
Format: Artikel
Sprache:eng
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Zusammenfassung:We introduce a novel n-stage vaccination model and corresponding system of differential equations that stratify a population according to their vaccination status. The model is an extension of the classical SIR-type models commonly used for time-course simulations of infectious disease spread and allows for the mitigation effects of vaccination to be uncoupled from other factors, such as changes in social behavior and the prevalence of virus variants. We fit the model to the Virginia Department of Health data on new COVID-19 cases, hospitalizations, and deaths broken down by vaccination status. The model suggests that, from 23 January through 11 September, fully vaccinated individuals were 89.8% less likely to become infected with COVID-19 and that the B.1.617.2 (Delta) variant is 2.08 times more transmissible than previously circulating strains of COVID-19. We project the model trajectories into the future to predict the impact of booster shots.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12031723