Laura C. Gonzalez Villeta

The aim of my project is to understand and predict the patterns in the prevalence and incidence of salmonellosis and how these patterns depend on key influential weather parameters, such as temperature. We are developing a mechanistic model for the prevalence of salmonellosis to be validated with records from national diagnostic laboratories across England and Wales provided by Public Health England. The models are based on a Poisson process with a rate of infection that incorporates the dynamics of bacterial growth and survival in relevant sources responsible for transmission (e.g. eggs, chicken meat) assuming that the number of cases is proportional to the average bacterial load in food, in response to the local weather data (e.g. air temperature, humidity and radiation) provided by the MetOffice.