The purpose of these brief epidemiology tutorials is to provide students with an introduction to spatial epidemiology and infectious disease transmission models. All tutorials will be conducted using R and publicly available data. The link for the github repository containing all 2023 tutorials can be found here: link. The original tutorial materials were created by Brinkley Raynor, PhD in 2022, and revised by Kira Nightingale in 2023.
Friday, June 30
This tutorial covers the basics of creating maps in R via three methods: layering shape files, adding a background of imported tiles, and using leaflet to create interactive maps. Uses publicly available data on hospital locations in Philadelphia.
Building on the mapping techniques in the prior tutorial, this session covers the creation of more complex maps and basic summary statistics. Uses publicly available data on litter index and trashcan locations in Philadelphia.
Friday, July 7
Using data from a GPS collar fitted to a buffalo (Toni) in Kruger National Park, South Africa from 2005-2006, this tutorial introduces methods to analyze location data. Methods include basic plotting, kernel density estimation, and time local convex hull (t-LoCoH).
This module covers methods that can be used to identify clusters, such as scan statistics, spatial relative risk, and Moran’s I.
Friday, July 14
This module contains a brief overview of the basics of compartmental models for infectious disease modeling, including key terminology and concepts. Covers SIR models and some variations; includes a practice exercise.
Metapopulation models take two levels of disease transmission into account - transmission within individual “patches” and transmission across patches. This module covers the basics of how to model disease in metapopulations.
Friday, July 21
This module provides an example of how parameters can be estimated using Beysian methods.