Simulating Infectious Disease Dynamics using Discrete Compartmental Models
Published in Providence, RI, 2021
Project Summary:
In this collaborative project, we develop a dynamic and interactive web-based application using Shiny Dashboards and the R statistical programming environment to simulate infectious disease dynamics using discrete compartmental models including the SI, SIR, and SEIR. The application provides an interactive interface for modeling and visualizing trends of infectious diseases, and allows data download given parameters including the type of model to simulate, the infection rate, the total susceptible population, the total number infected, rate of recovery, total number recovered, total population exposed, the simulation time (in days), and also explores the effect of an intervention e.g., vaccination on the subsequent trends in the disease dynamics.
Explore the dashboard:
The interactive app can be explored here
Keywords: SI, SIR, SEIR, Infectious disease modeling, compartmental models, simulation methods, Programming in R.
Collaborators:
Amos Okutse
Yingjie Zhou
Kyla Finlayson