Document Type
Article
Source Publication Title
PLOS ONE
DOI
http://dx.doi.org/10.1371/journal.pone.0220106
Abstract
Local climate conditions play a major role in the biology of the Aedes aegypti mosquito, the main vector responsible for transmitting dengue, zika, chikungunya and yellow fever in urban centers. For this reason, a detailed assessment of periods in which changes in climate conditions affect the number of human cases may improve the timing of vector-control efforts. In this work, we develop new machine-learning algorithms to analyze climate time series and their connection to the occurrence of dengue epidemic years for seven Brazilian state capitals. Our method explores the impact of two key variables—frequency of precipitation and average temperature—during a wide range of time windows in the annual cycle. Our results indicate that each Brazilian state capital considered has its own climate signatures that correlate with the overall number of human dengue-cases. However, for most of the studied cities, the winter preceding an epidemic year shows a strong predictive power. Understanding such climate contributions to the vector’s biology could lead to more accurate prediction models and early warning systems. [ © 2019 Stolerman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. DOI: https://doi.org/10.1371/journal.pone.0220106]
Disciplines
Mathematics | Physical Sciences and Mathematics
Publication Date
8-8-2019
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Stolerman, Lucas M.; Maia, Pedro D.; and Kutz, Nathan, "Forecasting dengue fever in Brazil: An assessment of climate conditions" (2019). Mathematics Faculty Publications. 41.
https://mavmatrix.uta.edu/math_facpubs/41