In Viet Nam there is currently no system in place to forecast the probability of dengue outbreaks. Since 2000, there has been an increase of over 100% in the number of cases of dengue fever in Viet Nam due to the failure to maintain adequate control of the Ae. aegypti species of mosquito that spreads dengue fever. Considering the current regional trends in dengue epidemics, the setting up of a seasonal dengue forecasting system utilizing Earth observation (EO)-based information to provide probabilistic predictions of dengue outbreaks would greatly assist the Vietnamese Government to put cost-effective early actions in place. From a water resources perspective, seven of the nine major river basins that drain to Viet Nam are transboundary in nature, and it is estimated that some two thirds of Viet Nam’s water resources comes from neighbouring countries, making water management challenging. In recent years, countries upstream of Viet Nam have increased their water use and Viet Nam is currently facing reduction of water flow in the rivers. Climate-driven rainfall variability, especially the intensified rainfall, is causing flooding and water pollution in various old and coastal cities where there are inadequate drainage systems. In addition, sea-level rise and land subsidence are causing more frequent inundation and water pollution in populous and low-land deltas such as the Mekong river delta. The development of an EO-based water availability system will help the Vietnamese Government to improve its water resources monitoring and management in transboundary river basins. The dengue fever and water management challenges are similar in other countries in South Asia, and the project has now been extended to cover Sri Lanka, Lao People’s Democratic Republic, Cambodia, Thailand, the Philippines and Malaysia.

The objective was to develop a suite of innovative tools that will allow beneficiaries to issue alerts for dengue fever (with a view to developing the same for Zika virus, which is transmitted by the same mosquito species) and to provide assessments of vector-borne disease risk under future climate and land-use change scenarios. This will allow local communities to mobilize in order to pre-emptively eliminate mosquito breeding sites, thus reducing incidence of dengue. In combination with better outbreak response, the project is expected to contribute towards a reduction in dengue incidence over the project lifetime.

The dengue fever forecasting Model Satellite-based System (D-MOSS) project is developing a forecasting system in which Earth observation data sets are combined with weather forecasts and a hydrological model in order to predict the likelihood of future dengue epidemics up to six months in advance.153 The early warning system includes a water availability component. Although water availability directly impacts dengue epidemics, due to the provision of mosquito breeding sites, it is rarely accounted for in dengue prediction models. The water availability forecasts are fed into statistical forecasting models of disease incidence, which integrate a range of other covariates important for dengue transmission (such as the number of dengue cases, land-cover, precipitation and temperature). Key lessons from Viet Nam include the importance of national ownership and downscaling of climate data for local forecasting, and allocation of resources for timely early warning and response.

Since 2000, there has been an increase of over 100% in the number of cases of dengue fever in Viet Nam.