期刊
INFECTIOUS DISEASE MODELLING
卷 7, 期 3, 页码 333-345出版社
KEAI PUBLISHING LTD
DOI: 10.1016/j.idm.2022.06.002
关键词
COVID-19; Gauteng; SouthAfrica; ODEepidemiologyModel; Vaccination; Parameterestimation
资金
- National Science Foundation [134651, DMS 2028297]
- AMS-Simons Travel Grants
- Simons Foundation
- University of Johanneburg URC Grant
The COVID-19 pandemic presents an opportunity to explore the effects of government mandates and non-pharmaceutical interventions on early-stage outbreak dynamics. Through mathematical modeling and data analysis, this study reveals the quantifiable impact of different policies and vaccination on the spread of the infection.
The COVID-19 pandemic provides an opportunity to explore the impact of government mandates on movement restrictions and non-pharmaceutical interventions on a novel infection, and we investigate these strategies in early-stage outbreak dynamics. The rate of disease spread in South Africa varied over time as individuals changed behavior in response to the ongoing pandemic and to changing government policies. Using a system of ordinary differential equations, we model the outbreak in the province of Gauteng, assuming that several parameters vary over time. Analyzing data from the time period before vaccination gives the approximate dates of parameter changes, and those dates are linked to government policies. Unknown parameters are then estimated from available case data and used to assess the impact of each policy. Looking forward in time, possible scenarios give projections involving the implementation of two different vaccines at varying times. Our results quantify the impact of different government policies and demonstrate how vaccinations can alter infection spread.(c) 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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