Disease risk mapping
The integration of environmental, climatic, socioeconomic and demographic information, including human and animal mobility data, with the disease inputs can enhance the predictions of spatio-temporal, dynamic distributions that drive risk and spread assessment, and also decode the role of the environment, in infectious disease emergence.
MOOD CASE STUDIES
Modeling seven diseases
The MOOD case studies establish a close collaborative space where MOOD researchers and end-users discuss together the development of Epidemic Intelligence (EI) tools for a routine use.
The disease-specific module (3) provides users with risk maps and other modelled outputs, aiming at highlighting areas suitable for the occurrence of (mainly) HPAI, WNV and TBE in animals and humans, to support improved disease detection, monitoring and surveillance.
Are you working on one or more diseases? Get involved!