Module dates/times: Wednesday, July 17, 1:30-5 p.m.; Thursday, July 18, 8:30 a.m.-5 p.m., and Friday, July 19, 8:30 a.m.-5 p.m.

Prerequisites: This module assumes knowledge of the material in Module 1: Probability and Statistical Inference, though not necessarily from taking that module. This module assumes knowledge of the material in Module 2: Mathematical Models of Infectious Diseases, though not necessarily from taking that module. Familiarity with a programming language is expected (Python, R, Matlab or other).

This module focuses on digital data sources and novel data streams such as geo-localized population and mobility data, wearable devices, web participatory platforms and web search data or social media updates. We will provide an introduction to different digital data sources and technical challenges in their collection, storage, and analysis. We will review the integration of digital data sources with statistical and mechanistic modeling of infectious diseases. The course will provide an introduction to the use of novel data streams time series for epidemic forecasting. We will describe the construction of synthetic populations and the calibration of highly detailed individual based models.