<p>Sea surface temperature conditions in the central-eastern tropical Pacific indicated a mild El Ni&#241;o event in October 2018, which continued throughout the spring of 2019. The global El Ni&#241;o Southern Oscillation (ENSO) forecast consensus was that these generally weak warm patterns would persist at least until the end of the summer. El Ni&#241;o and its impact on local climatic conditions in southern coastal Ecuador influence the inter-annual transmission of dengue fever in the region. In this study, we use an ENSO model to issue forecasts of El Ni&#241;o for the year 2019, which are then used to predict local climate variables, precipitation and minimum temperature, in the city of Machala, Ecuador. All these forecasts are incorporated in a dengue transmission model, specifically developed and tested for this area, to produce out-of-sample predictions of dengue risk. Predictions are issued at the beginning of January 2019 for the whole year, thus providing the longest forecast lead time of 12 months. Preliminary results indicated that the mild El Ni&#241;o event did not provide the optimum climate conditions for dengue transmission, with the model predicting a very low probability of a dengue outbreak during the typical peak season in Machala in 2019. This is contrary to 2016, when a large El Ni&#241;o event resulted in excess rainfall and warmer temperatures in the region, and a dengue outbreak occurred 3 months earlier than expected. This event was successfully predicted using a similar prediction framework to the one applied here. With the present study, we continue our &#160;efforts to build and test a climate service tool to issue early warnings of dengue outbreaks in the region.</p>
Sensitivity, uncertainty and identifiability analyses to define a dengue transmission model with real data of an endemic municipality of Colombia
