Predictive scenarios of health in Southeast Asia: linking land use and climate changes to infectious diseases – FutureHealthSEA

The project located in Southeast Asia aims at developing scenarios of future health embodied in the One Health approach at the human-animal-environment interface. By investigating the impacts of the intensification of the circulation along the economic corridor (Thailand-Laos) on the evolution of infectious diseases (IDs) of public health interests it intends to:
a) integrate ecology and environmental sciences with health sciences and policies;
b) foster scientific knowledge integration at various decision levels (regional to local); c) analyze retrospectively and comparatively IDs' dynamics associated to policies, land use and biodiversity changes; d) combine predictive process-based scenarios and policy-driven scenarios of health incorporating disease ecology, biodiversity erosion, future land use and climate changes.
Important role will be devoted to ICT Sciences based on a strong partnership between France and Thailand. An integrative data / knowledge base will be created that will include three types of information:
a) quantitative data (socio-economics at the village level; infectious diseases including zoonoses; domestic animal populations; resources from wildlife; distributions of precipitation, temperature and impacts of climate change on these variables; soils; agricultural inputs such as pesticides, herbicides and antibiotics);
b) a large textual corpus on the strategies and targets to implement international law regionally and nationally and results of text mining to be generated, as well as information on local policy measures and customary law;
c) qualitative data obtained from interviews and surveys conducted with decision-makers and community leaders about their representations and perceptions of agriculture, land planning / infrastructure, health and conservation policies. Given their importance in health-environment dynamics, LULC changes will be restored over nearly three decades and projected for the coming decades at various scales (region, habitats, landscapes) by combining various data sources (including satellite products). The interactions between variables and information will be identified and modeled by relying on a variety of tools combining simple correlations (linear or nonlinear), modeling reticular causalities (Bayesian networks), process-based epidemiological models and knowledge representation. The data / knowledge base and models will finally be exploited to produce scenarios combining predictions and story-telling about the likely impacts of strategies and legal and policy measures on health, biodiversity and resource uses (agriculture, LULC, living resources). Scientific evidences gained from the project results will be disseminated among decision-makers and community leaders through workshops and conferences. Indeed those evidences will play a pivotal role in helping decision-makers at different levels to associate socio-ecosystems dynamics and IDs' dynamics, at various spatial scales (villages to districts to transboundary provinces), in their public action.