Dengue fever outbreaks impose a severe healthcare burden in Vietnam, therefore the development of an early Dengue warning system is key to improve public health planning and mitigate the future burden produced by this disease. This study assessed the ECMWF ensemble re-forecast skill for relative humidity, temperature and precipitation, which are key factors for vector-borne disease transmission in Vietnam between 1-4 weeks in advance. We focused the analysis on the rainy season (May-October) using ERA5 reanalysis as a reference dataset. Re-forecast data was pre-processed using a quantile mapping technique to reduce the bias between re-forecast and observations. Results showed that corrected re-forecasts of weekly mean temperature, relative humidity and accumulated precipitation are skilful up to 2-3 weeks in advance and rank histograms verified the forecast reliability. Nonetheless the model is less skillful for the region of South Vietnam and seems to struggle at predicting extremely high/low values of temperature, relative humidity and precipitation. Results from this study demonstrate that ECMWF ensemble forecasts are suitable to use as inputs for a dengue early warning system up to 14-21 days in advance
