Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data

Conde-Gutiérrez, R. A.; Colorado, D.; Márquez-Nolasco, A.; Gonzalez-Flores, P. B.

doi:10.1007/s00484-024-02643-3

Int J Biometeorol

2024

DOI: 10.1007/s00484-024-02643-3

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Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data

R. A. Conde-Gutiérrez,

D. Colorado,

A. Márquez-Nolasco

et al.

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Analysis of the interrelationship between precipitation and confirmed dengue cases in the city of Recife (Brazil) covering climate and public health information

Borges,

Musah,

Dutra

et al. 2024

Front. Public Health

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Large-scale epidemics of arboviruses, such as dengue, have heightened societal awareness regarding the necessity of combating the primary transmission vectors. Equally critical is the identification of environmental conditions and variables that influence vector population dynamics. Aedes aegypti, the primary vector of arboviruses such as dengue and Zika in Brazil, is closely associated with the climatic and geographical conditions of urban environments. This study examines the relationship between precipitation and confirmed dengue cases in Recife (Brazil), employing regression and quantile analyses to evaluate the influence of meteorological conditions on the disease’s spread. The findings reveal a direct correlation between monthly averages of precipitation and confirmed cases, although this is apparent only when excluding years of epidemic peaks. The highest number of cases generally aligns with the rainy season, and the lowest with the dry season, with weak, moderate and strong precipitation events being closely linked to increased dengue incidence. However, notable discrepancies were identified: four out of six major outbreaks occurred in drier months, challenging the assumption of a straightforward relationship between rainfall and dengue incidence. These findings underscore the multifaceted nature of dengue dynamics, suggesting that while precipitation plays a significant role, other factors, including serotype circulation and broader climatic phenomena, are equally critical in driving outbreaks. This complexity highlights the need for a more comprehensive understanding of the mechanisms influencing dengue epidemics.

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Analysis of the interrelationship between precipitation and confirmed dengue cases in the city of Recife (Brazil) covering climate and public health information

Borges,

Musah,

Dutra

et al. 2024

Front. Public Health

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show abstract

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Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data

Cited by 1 publication

References 35 publications

Analysis of the interrelationship between precipitation and confirmed dengue cases in the city of Recife (Brazil) covering climate and public health information

Analysis of the interrelationship between precipitation and confirmed dengue cases in the city of Recife (Brazil) covering climate and public health information

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