A173-04
Using Subseasonal Forecasts to Predict the 2018 Dengue Outbreak in Réunion

Tuesday, 15 December 2020: 04:14
Virtual
Laurel DiSera1, Henrik Sjödin2, Joacim Rocklöv2, Yesim Tozan3, Bertrand Súdre4, Herve Zeller4 and Angel Munoz1, (1)International Research Institute for Climate and Society, Columbia University, Palisades, NY, United States, (2)Umeå University, Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå, Sweden, (3)New York University, School of Global Public Health, New York, NY, United States, (4)European Centre for Disease Prevention and Control, Stockholm, Sweden
Abstract:
The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and lead to the dengue outbreak in early 2018. A stage-structured model was run using observed temperature and rainfall data to simulate the lifecycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias-corrected sub-seasonal forecasts to determine if the event could have been forecast up to four weeks in advance. With unseasonably warm temperatures remaining above 25° C, along with large tropical-cyclone-related rainfall events accumulating 10-15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although sub-seasonal forecasts of rainfall for the Dec-Jan period in Réunion are skillful up to four weeks in advance, the outbreak could only have been forecast two weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state-of-the-art sub-seasonal climate forecasts to produce actionable sub-seasonal dengue predictions. To the best of the authors’ knowledge, this is the first time sub-seasonal forecasts have been used this way.