Full dataset for dengue forecasting in Brazil for Infodengue-Mosqlimate sprint 2024

Authors: Coelho, Flávio Codeço; Codeço, Claudia Torres; Almeida, Iasmim; Carvalho, Luiz Max; Araújo, Eduardo Correa; Bastos, Leonardo; Vacaro, Luã Bida; +1 Authors

doi: 10.5281/zenodo.13328231 , 10.5281/zenodo.13328230

Full dataset for dengue forecasting in Brazil for Infodengue-Mosqlimate sprint 2024

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Abstract

The year 2024 has seen an exceptional number of reported dengue fever cases in various parts of the world. In Brazil, the disease has spread to areas in the south and at altitudes where epidemics were not previously recorded, and the incidence rate has far exceeded that of previous years. The objective of this dataset is to promote, in a standardized way, the training of predictive models with the aim of developing forecast models for dengue in Brazil.

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Keywords

Epidemiology, Machine learning, Infectious diseases, Climatic changes, Bayesian statistics

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