Analysis of the interrelationship between precipitation and confirmed dengue cases in the city of Recife (Brazil) covering climate and public health information
Year: 2024
Type: article
Abstract: 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.
Source: Frontiers in Public Health
Authors: Iuri Valerio Graciano Borges, Anwar Musah, Livia Marcia Mosso Dutra, Merve Tunali, Clarisse Lins Lima, Mehmet Meric Tunali, Ana Clara Gomes da Silva, Aisha Aldosery, Giselle Machado Magalhães Moreno, Wellington P. dos Santos, Tiago Massoni, Orhan Yenigün, Patty Kostkova, Rosmeri Porfirio da Rocha, Luiza C. Campos, Tercio Ambrizzi
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,295
Awards: G1916461578, G29316538, G295657101, G3286386338, G4758137901, Mosquitoes populations modelling for early warning system and rapid response public by health authorities correlating climate, weather and spatial-tem, G7011755334, Mosquitoes populations modelling for early warning system and rapid response public by health authorities correlating climate, weather and spatial-temporal mobile surveillance data, G8916978094
OpenAlex ID: W4403700132
