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Present and future incidence of dengue fever in Ecuador nationwide and coast region scale using species distribution modeling for climate variability’s effect

Author

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  • Jácome, Gabriel
  • Vilela, Paulina
  • Yoo, ChangKyoo

Abstract

Dengue fever, a vector-borne disease, represents a priority public health problem in Ecuador. Previous studies indicated that the ecology of the transmitter vector (Aedes aegypti) is influenced by environmental parameters and human behavior; however, the effects of those variables on mosquito population dynamics depend on local environmental features. In this study, we identified the most important factors influencing the risk of dengue virus infection in Ecuador. The maximum entropy algorithm (MaxEnt) was used to determine the areas with a high probability of the presence of Aedes aegypti under current and future (2050) climatic conditions, using the location of reported dengue cases and potential environmental factors. The model performance was quantified based on an accuracy assessment. Additionally, we used meteorological data from the study period in a partial least square regression (PLS-R) to predict the number of total dengue cases (TDC) and then estimated the future number of cases using the equation obtained with the PLS-R. Population density, elevation, and mean temperatures of the warmest and wettest quarters were found to be the most important variables influencing the mosquito’s geographical distribution. Maximum temperature and minimum temperature were the climatic factors with the best projecting capacity in predicting the TDC in the Ecuadorian coast region. The results show a greater mosquito presence probability in populated areas, with a considerable expansion of suitable habitat across the central and southern provinces by 2050. The temporal analysis revealed that the regional dengue outbreak season goes from March to June, and the future estimation predicted that the next large outbreak would occur in 2018. These results present a good intel for solutions of reduction of dengue cases in the country. This further will allow the responsible authorities to pinpoint proper vector control measurements by province.

Suggested Citation

  • Jácome, Gabriel & Vilela, Paulina & Yoo, ChangKyoo, 2019. "Present and future incidence of dengue fever in Ecuador nationwide and coast region scale using species distribution modeling for climate variability’s effect," Ecological Modelling, Elsevier, vol. 400(C), pages 60-72.
    • Handle: RePEc:eee:ecomod:v:400:y:2019:i:c:p:60-72
    DOI: 10.1016/j.ecolmodel.2019.03.014
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    References listed on IDEAS

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    1. Sara Varela & Matheus S Lima-Ribeiro & Levi Carina Terribile, 2015. "A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-15, June.
    2. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
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    Cited by:

    1. Wieland, Ralf & Kuhls, Katrin & Lentz, Hartmut H.K. & Conraths, Franz & Kampen, Helge & Werner, Doreen, 2021. "Combined climate and regional mosquito habitat model based on machine learning," Ecological Modelling, Elsevier, vol. 452(C).
    2. Paulina Vilela & Gabriel Jácome & Wladimir Moya & Pouya Ifaei & Sungku Heo & Changkyoo Yoo, 2023. "A Brief Insight into the Toxicity Conundrum: Modeling, Measuring, Monitoring and Evaluating Ecotoxicity for Water Quality towards Environmental Sustainability," Sustainability, MDPI, vol. 15(11), pages 1-28, May.

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