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 earl...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.展开更多
基金This research was funded in part by the National Science Foundation,grant number 134651,to the MASAMU Advanced Study Institute.FBAwas supported by the National Science Foundation under grant number DMS 2028297CJEwas supported by the AMS-Simons Travel Grants,which are administered by the American Mathematical Society with support from the Simons Foundation.FC was supported by the University of Johanneburg URC Grant。
文摘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.
