Sex-specific public health data: analyzing the arboviral impact on women in Brazil - Brena F. Sena; Danyelly Bruneska Gondim Martins; Carmen Simone Grilo Diniz; José Luiz Lima Filho (Revista de Saúde Pública)
ABSTRACT OBJECTIVE To evaluate the differential impact of arboviral infections, specifically dengue virus, chikungunya virus, and Zika virus, on women in Brazil, with a focus on sex- and age-disaggregated analyses. METHODS A comprehensive epidemiological and geospatial data analysis was conducted utilizing data from Brazil’s national health data system, including the disease notification system (Sistema de Informação de Agravos de Notificação) and mortality information system (Sistema de Informação sobre Mortalidade), covering national and municipal level data. Arboviral case notification rates were analyzed using generalized linear mixed models with negative binomial regression, stratified by sex, age group, and year. Geospatial visualizations mapped the case rate distribution highlighting the top municipalities with the most female case rate and hospitalizations rate. All analyses were implemented in the statistical software R. RESULTS Significant sex- and age-stratified differences were observed in the arbovirus notification rates for dengue virus, chikungunya virus, and Zika virus over the past seven years, with consistently higher rates among women compared to men. Stratified analyses revealed that females aged 20–59 years, particularly those of reproductive age, bore a disproportionately higher burden across all three viruses. The low serotyping resolution for the dengue virus constrained further granular analysis, particularly for severe outcomes such as hospitalizations and mortality based on dengue serotype. CONCLUSION Sex- and age-disaggregated epidemiological surveillance is critical to inform public health policies and interventions targeting arboviral diseases. This study underscores the necessity of incorporating sex-specific data analyses to optimize responses for vulnerable female populations. Geospatial visualizations reveal infection hotspots, providing actionable insights for region-specific interventions to improve health outcomes in Brazil.