Digital and computational epidemiology for pandemic management

Computational models and digitally acquired data are increasingly becoming integrated into the decision making process with respect to pandemic control. Nation-wide lockdowns have been issued or released based on results from model simulation outputs. In this collection, we highlight research published in Nature Communications contributing to the development of a more prepared and transparent disease surveillance system, using the wealth of digital data on human behaviour and health, without compromising privacy rights.


Monitoring human behaviour and epidemiological patterns with digital data

Computational models for pandemic management and control

Multi-disciplinary decision support systems for policy making in a pandemic