Dengue and malaria are considered the most health burden under changing climate in Vietnam and Philippines, where impacts of climate change appear severely due to more frequent flooding and typhoons. The objective of the project is to improve the knowledge of the above vector-borne diseases and their vulnerability to climate variability for rural population in both countries by using advanced geospatial technology. The study will cover a period of 20 years over disease exposure areas determined by pattern matching approach. The project activities are comprised of collecting data and field survey to develop a geospatial database; data analysis; and mapping vulnerability of health to climate change. Expected outputs of the project include the database of climate change related diseases, temporal trends and distribution patterns of disease incidence and its relations to variability of climate and socio-economic conditions, and vulnerability maps of mosquito-borne diseases under climate change. The project results will support adaption planning and decision making in health sector via providing disease information and vulnerability.
Project leader
Project publications
Assessing and modelling vulnerability to dengue in the Mekong Delta of Vietnam by geospatial and time-series approaches
Time-series modelling of dengue incidence in the Mekong Delta region of Viet Nam using remote sensing data
Mapping health vulnerability to climate change for rural population in Vietnam and Philippines using geospatial technology
Modeling and predicting dengue fever cases in key regions of the Philippines using remote sensing data
Correlation of dengue diseases and climate variable using geospatial data for Vietnam
Modelling dengue disease with climate variables using geospatial data for Vietnam and Philippines
Study on Vector-Born Diseases in the Context of Climate Change using Geospatial Data and Modelling for Philippines and Vietnam
Mapping of dengue vulnerability in the Mekong Delta region of Viet Nam using a water-associated disease index and remote sensing approach
Modelling dengue disease with climate variables using geospatial data for Vietnam and Philippines