R package and Shiny app for SEIR models
The main aim of this project is twofold. First, I am creating a set of tools with which users can better understand the dynamics of an epidemic. These tools include R functions where the user can change the parameter values and inspect the results and a resulting simple Shiny application where these parameter changes can be made dynamically.
Second, the R package will be capable of estimating the parameters of the system when observed data is present.
The logic of SEIR model is very similar to other compartmental epidemic models like SIS and SIR. We assume that the population consist of Susceptible (S), Exposed (more on that later), Infectious (E), and Recovered/Removed (R). In case of many infections there is a incubation period during the people are infected, but not infectious (E - Exposed). The following system of differential equation encapsulates the model, where beta is the contact rate, mu is mortality, gamma is recovery rate and a is the incubation period.
Bence Gergely Email: [email protected]
Twitter: @GergelyBence7