Invasion Modeling of Zebra Mussels and COVID-19

The invasive species of zebra mussels have caused significant damage to many lakes and rivers. By using a hybrid population model with discrete-time equations and ordinary differential equations, we represent the zebra mussel’s life cycle and its population spread. The goal is to investigate the effects of zebra mussel movement between different spatial locations. Zebra mussel data and temperature values from the Hudson River over several years were used to estimate model parameters. We illustrate numerically the hybrid population model for several scenarios.

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 behavior. 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.

Evidence suggests that there are geographic disparities in COVID-19 vaccination risks in Missouri. Socioeconomic and demographic predictors may explain these disparities. The objectives of this study are to investigate county-level geographic disparities of COVID-19 vaccination risks and identify socioeconomic and demographic predictors of county-level vaccination risks in Missouri. Global ordinary least squares (OLS) regression model and local geographically weighted OLS regression models were used to identify predictors of county-level COVID-19 vaccination risk.