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  • Presentation | GH31C: Early Warning Systems for Infectious Disease Based on Climate and Environmental Variability I Poster
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  • GH31C-0688: Interdecadal changes in ENSO characteristics at the turn of the century influenced Dengue epidemics in Thailand
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  • Board 0688‚ Hall EFG (Poster Hall)
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Author(s):
Jaime Cascante Vega, New York University (First Author, Presenting Author)
Julian Gottfried, New York University
Alessandra Giannini, Laboratoire de Météorologie Dynamique/IPSL, Ecole Normale Supérieure, PSL Research University, Sorbonne Université and Columbia Climate School, Columbia University
Leonardo Souto Ferreira, New York University
Mercedes Pascual, New York University


A reduction in the size of dengue outbreaks was observed after the 2000s, coinciding with changes in ENSO characteristics. In particular, with a reduced intensity of warming, El Niños, and increased La Niñas. We first explore how decadal changes in ENSO impact Dengue transmission by fitting a stochastic epidemiological model up to the 2000s and then simulating it forward in time until 2018. We find a model including ENSO strength with a relative index that controls for decadal oscillations has the best training AIC. However, a model that includes the effect of ENSO with these low-frequency oscillations has a lower out-of-sample prediction error. We re-incorporate decadal information into the relative index using the geometry of Sea Surface Temperature during El Niños, and found that training AIC improves. These results together suggest interdecadal changes in ENSO and climate were an important source of variability in Dengue incidence post-2000



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