Emergence and spatiotemporal incidence of dengue in Rio Grande do Sul, Brazil

This ecological study used surveillance data to examine the spatiotemporal dynamics of dengue in RS from 2007 to 2023. The temporal progression and geographic distribution of the cases were analyzed using generalized additive models (GAM), Local Indicators of Spatial Association (LISA), and spatiotemporal scan statistics. During the study period, 126,067 dengue cases and 142 deaths were reported, with 80.5% of cases and 85.2% of deaths occurring between 2022 and 2023. The mean incidence rate was 65.3 per 100,000 inhabitants, and the mortality rate was 0.11 per 100,000. The GAM analysis demonstrated a marked escalation in dengue risk beginning in 2019, with pronounced intensification from 2022 onward, indicating an ongoing epidemic. Most cases and fatalities were concentrated in the Northwest Rio Grande and Metropolitan Porto Alegre mesoregions. Significant spatial clusters were detected in the Central Eastern Rio Grande and Central Western Rio Grande mesoregions between 2021 and 2023, encompassing approximately 2.8 million individuals. These findings underscore the critical need to enhance surveillance and implement robust primary-prevention measures. Such measures are vital for curbing the current epidemic and mitigating the risk of future outbreaks. This study provides a detailed epidemiological assessment of dengue expansion in RS, highlighting priority areas for intervention and resource distribution to effectively manage evolving public health threats.

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Publication Details

Journal
Scientific Reports
Published
2025-05-29
DOI
https://doi.org/10.1038/s41598-025-02548-0
Citations
4
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
7.51

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article

Emergence and spatiotemporal incidence of dengue in Rio Grande do Sul, Brazil

Bianca Conrad Bohm, Fábio Raphael Pascoti Bruhn, Angelita dos Reis Gomes, Nádia Campos Pereira Bruhn et al.
4 citations
Scientific Reports
Mosquito-borne diseases and control
7.51
article

Emergence and spatiotemporal incidence of dengue in Rio Grande do Sul, Brazil

Bianca Conrad Bohm, Fábio Raphael Pascoti Bruhn, Angelita dos Reis Gomes, Nádia Campos Pereira Bruhn, Sergiane Baes Pereira, Viní­cius Silva Belo, Glênio Aguiar Gonçalves, Francisco Aguilera-Benavente
article en
4 citations

Abstract

This ecological study used surveillance data to examine the spatiotemporal dynamics of dengue in RS from 2007 to 2023. The temporal progression and geographic distribution of the cases were analyzed using generalized additive models (GAM), Local Indicators of Spatial Association (LISA), and spatiotemporal scan statistics. During the study period, 126,067 dengue cases and 142 deaths were reported, with 80.5% of cases and 85.2% of deaths occurring between 2022 and 2023. The mean incidence rate was 65.3 per 100,000 inhabitants, and the mortality rate was 0.11 per 100,000. The GAM analysis demonstrated a marked escalation in dengue risk beginning in 2019, with pronounced intensification from 2022 onward, indicating an ongoing epidemic. Most cases and fatalities were concentrated in the Northwest Rio Grande and Metropolitan Porto Alegre mesoregions. Significant spatial clusters were detected in the Central Eastern Rio Grande and Central Western Rio Grande mesoregions between 2021 and 2023, encompassing approximately 2.8 million individuals. These findings underscore the critical need to enhance surveillance and implement robust primary-prevention measures. Such measures are vital for curbing the current epidemic and mitigating the risk of future outbreaks. This study provides a detailed epidemiological assessment of dengue expansion in RS, highlighting priority areas for intervention and resource distribution to effectively manage evolving public health threats.

Scientific ReportsVol. 15(1)
Universidade Federal de Pelotas (BR), Universidad de Alcalá (ES), Federal University of São João del-Rei (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Universidad de Alcalá
Openalex Percentile: Top 3%
Mosquito-borne diseases and control
7.51
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