Modeling impact of vaccination on COVID-19 dynamics in St. Louis

The region of St. Louis, Missouri, has displayed a high level of heterogeneity in COVID-19 cases, hospitalization, and vaccination coverage. We investigate how human mobility, vaccination, and time-varying transmission rates influenced SARS-CoV-2 transmission in five counties in the St. Louis area. A COVID-19 model with a system of ordinary differential equations was developed to illustrate the dynamics with a fully vaccinated class. Using the weekly number of vaccinations, cases, and hospitalization data from five counties in the greater St. Louis area in 2021, parameter estimation for the model was completed. The transmission coefficients for each county changed four times in that year to fit the model and the changing behaviour. We predicted the changes in disease spread under scenarios with increased vaccination coverage. SafeGraph local movement data were used to connect the forces of infection across various counties.

Automated summary

This study investigates the heterogeneity of COVID-19 cases, hospitalization, and vaccination coverage in the St. Louis region of Missouri. The impact of human mobility, vaccination, and time-varying transmission rates on SARS-CoV-2 transmission in five counties is examined. A COVID-19 model with ordinary differential equations is developed, and parameter estimation is performed using weekly data from 2021. The study predicts changes in disease spread under scenarios with increased vaccination coverage and utilizes local movement data to connect infection forces across different counties.