Tendências temporais de agravos à saúde antes e após a catástrofe climática do ano de 2024 no estado do Rio Grande do Sul.

Abstract

General Introduction: Extreme weather events have intensified in recent decades, producing significant impacts on public health. In Rio Grande do Sul, the floods of May 2024 constituted the largest climate catastrophe in the state's recent history, with substantial health repercussions. General Objective: To analyze the influence of the 2024 climate catastrophe on the temporal distribution of notifiable health conditions in the municipality of Campo Bom (RS). Manuscript I. Effects of the 2024 climate catastrophe on health conditions reported in a municipality in the state of Rio Grande do Sul: a study using interrupted time series. Introduction: Extreme weather events have become more frequent with significant repercussions on disease patterns. The May 2024 floods in Rio Grande do Sul affected hundreds of municipalities, including Campo Bom, historically vulnerable to flooding. Objective: To examine the temporal behavior of notifiable health conditions in the municipality of Campo Bom between 2014 and 2024, with emphasis on changes associated with the hydrometeorological catastrophe of May 2024. Methods: A retrospective ecological study using data from the Notifiable Health Conditions Information System (SINAN) to compose monthly time series analysis of viral hepatitis, venomous animal accidents, leptospirosis, human anti-rabies care, dengue, Coronavirus Disease 2019 – Covid-19, and severe acute respiratory syndrome (SARS). Negative binomial regression, Zero-Inflated Negative Binomial (ZINB) models, and interrupted time series were applied, with May 2024 as the interruption point. Results: Leptospirosis showed a 45-fold increase in incidence immediately after the floods (IRR= 45.0; p= 0.002) and human anti-rabies care almost doubled (IRR= 1.96; p= 0.002). Viral hepatitis, dengue, and SARS showed no significant changes. The increase in venomous animal accidents resulted from a pre-existing upward trend. Covid-19 showed a 99% decline (IRR= 0.01; p<0.001), reflecting the decline of an epidemic wave prior to the disaster. Conclusion: The 2024 climate catastrophe primarily impacted leptospirosis and anti-rabies care, while other conditions maintained their patterns, reinforcing the importance of sensitive and technically structured epidemiological surveillance to guide rapid responses in future climate disasters. Manuscript II. Epidemiological behavior of dengue in Rio Grande do Sul: temporal and spatial analysis in the context of the 2024 climate catastrophe. Objective: To analyze the epidemiological behavior of dengue in the state of Rio Grande do Sul in 2024, a year marked by a significant climate catastrophe, and to describe its temporal and spatial distribution and demographic profile compared to the 2017–2023 period. Methods: A descriptive ecological study using data from the Notifiable Health Conditions Information System (SINAN) for the period 2017–2024. Temporal analysis was performed using cubic spline smoothing and Prais-Winsten regression for estimating annual percentage change. Spatial distribution was analyzed by municipality, comparing 2024 to the historical average of 2017–2023. Local spatial autocorrelation analysis (LISA) was applied with a queen contiguity matrix, permutations with α= 0.05, and adjustment by the False Discovery Rate method. The sociodemographic profile was characterized by sex, age group, and race/ethnicity. Results: A total of 209,668 confirmed cases were recorded between 2017 and 2024, with concentration in 2024. Temporal analysis revealed an epidemic outbreak between March and May 2024, peaking in April and exceeding the historical median fivefold. Annual percentage variation ranged from 270 to 308% (p<0.001), being highest in the ≥60 years age group (308%). Spatial distribution showed strong concentration in the Northwest/Missões region, with 39 municipalities identified in a High-High pattern (hotspots), notably Tenente Portela (27,260 cases/100,000 inhabitants). Low-transmission areas (coldspots) were identified in Serra Gaúcha and Campanha/Southern Coast. The sociodemographic profile revealed female predominance (54.8%), a shift toward older age groups (relative increase in ≥50 years), and proportional growth in the Black population. Conclusion: The year 2024 presented an atypical dengue pattern in the state of Rio Grande do Sul, with intensified transmission, spatial heterogeneity, and changes in the profile of the affected population. The temporal coincidence between the climate disaster and epidemic intensification suggests an interface between extreme hydrometeorological events and the dynamics of arbovirus transmission. Stratification of control actions by municipal risk level and integration between epidemiological surveillance and civil defense for response to climate emergencies is recommended. E-book Chapter. Climate catastrophe in the state of Rio Grande do Sul: when health conditions advance. Objective: To address the subject of climate catastrophes in accessible language to support the training of health professionals, continuing education, and scientific dissemination on the impacts of climate catastrophes on public health. Structure: The chapter is organized into four sections: (1) historical contextualization of extreme weather events in Rio Grande do Sul from the 1941 floods to the 2024 events; (2) presentation of climate-sensitive notifiable health conditions analyzed in the dissertation; (3) synthesis of the main empirical findings, highlighting heterogeneity in impacts by type of condition, spatial distribution, and territorial characteristics; and (4) discussion of implications for public health policies, epidemiological surveillance systems, and preparedness for future climate disasters. Contribution: Documents in a systematic and accessible manner the impact of the 2024 extreme climate events on morbidity patterns in Rio Grande do Sul and provides input for the critical training of health professionals and the enrichment of public debates on climate justice and socioenvironmental health inequalities. Dashboard RADAR-CB – Registry and Analysis of Data on Health Conditions Related to the Municipality of Campo Bom. Objective: To develop an interactive web tool for descriptive exploration of time series of health conditions in Campo Bom from 2014 to 2024, supporting municipal epidemiological surveillance. Platform and functionalities: Application developed in R language with the Shiny framework, hosted on ShinyApps.io, containing time series charts with interactive filters by health condition and period, boxplots for seasonality visualization, basic epidemiological indicators, and a responsive interface accessible via computer, tablet, and smartphone. Contribution: Translates complex statistical analyses presented in Manuscript I into easy-to-understand graphical representations, brings scientific production closer to municipal epidemiological surveillance routines, functions as a tool to support evidence-based decision-making, and presents potential for replication in other municipalities with similar technological resources. General Conclusion: The 2024 climate catastrophe impacted the analyzed health conditions heterogeneously, evidencing the sensitivity of certain diseases to abrupt environmental changes. The technical products developed (e-book chapter and RADAR-CB dashboard) demonstrate the feasibility of translating scientific knowledge into applied practice, contributing to professional training, management support, and the strengthening of integrated and territorialized surveillance strategies.