Introduction: among the main causes of death, the stroke representing a public health problem that is difficult to control, with high death rates. Analysis of mortality patterns reveals risk factors and pre-existing conditions that increase the risk of cerebrovascular diseases, highlighting the importance of tracing the regional epidemiological profile. Objective: evaluating the temporal trends in the mortality coefficient and proportional mortality due to stroke in the populations of the states of Rio Grande do Norte and Paraíba, in the Northeast region of Brazil. Methods: a time series study analyzed secondary data on deaths from stroke in adults in the states of Paraíba and Rio Grande do Norte, from 2004 to 2023. The data was extracted from the Unified Health System database. Joinpoint regression, annual percentage changes and annual averages with 95% confidence intervals were used. Results: in the state of Paraíba, the highest number of deaths occurred in females with 1,5206 deaths (51.3%) and in the age group 65 years or older with 22,238 deaths (75.0%). In the state of Rio Grande do Norte, the majority of deaths were registered among females with 9,558 deaths (51.2%) and in the age group 65 years or older with 14,092 (75.4%). Conclusion: in the period analyzed from 2004 to 2023, the state of Paraíba maintained the highest mortality coefficients compared to Rio Grande do Norte. However, proportional mortality showed a reversal in 2023, with Rio Grande do Norte excelling, especially in the 65 and over age group.

Introduction: COVID-19 is a respiratory disease caused by the SARS-CoV-2 virus, which belongs to the coronavirus family. SARS-CoV-2 is related to other viruses that cause severe acute respiratory syndrome. The emergence of cases of pneumonia of unknown origin triggered the largest viral pandemic in modern times, presenting major challenges to global public health. Objective: To analyze the evolution of the COVID-19 pandemic in the state of São Paulo from 2020 to 2023, focusing on trends in incidence, mortality, and lethality. Methods: Ecological study of time series of incidence, mortality and lethality by COVID-19 in the state of São Paulo using Prais-Winsten regression considering the Weekly Percentage Change (WPC) and probability values (p), considering a significance level of 95% (95% CI). To ensure the reliability of the entered data, double-blind typing was performed by different researchers in the same database extracted from the 2024 Ministry of Health Coronavirus dashboard. Results: From February 2020 and the end of December 2023, 6,763,310 accumulated cases and 182,254 deaths were recorded. Stationary trends were observed for the year 2022, with a reduction in incidence and mortality in the year 2023. However, the epidemiological variable lethality showed a stationary trend. Conclusion: The analysis of the trends in incidence, mortality, and lethality revealed variable dynamics over time, with emphasis on the significant reduction of these indicators in 2023.

Background/Objectives: While the descriptive trajectory of COVID-19 is well-documented, there is a methodological gap in quantifying the precise magnitude of risk reduction across multi-year pandemic phases in Brazilian subnational units. This study aimed to fill this gap by applying Generalized Linear Models (GLMs) to quantify the temporal transition of epidemiological risks (Incidence, Mortality, and Case Fatality) in Ceará (2020–2023), using the first year of the pandemic as a statistical baseline. Methods: Ecological time-series study was conducted using official surveillance data. We employed GLMs with Poisson distribution to calculate Rate Ratios (RRs) and 95% Confidence Intervals, allowing for a robust comparative risk modeling between 2020 (reference) and subsequent years (2021–2023). Results: Modeling revealed a significant epidemiological dissociation between transmission and severity. While the risk of incidence remained high through 2022 (RR = 1.42), the mortality risk showed an earlier and more drastic decline, with a 68% reduction as early as 2022 (RR = 0.32) and 99% in 2023 (RR = 0.01). The Case Fatality Rate (CFR) risk decreased consistently from 2021 onwards, reaching its lowest point in 2023 (RR = 0.09; 91% reduction). Conclusions: Between 2020 and 2023, Ceará transitioned to reduced COVID-19 severity. Despite ecological design and data limitations, these findings underscore the importance of resilient health systems and equitable immunization.

Background/Objectives: COVID-19 placed substantial pressure on health systems and showed marked spatial and temporal heterogeneity in Brazil. We analyzed monthly and annual patterns of incidence, mortality, and period-specific case fatality in Pernambuco from 2020 to 2023. Methods: This ecological time-series study used 48 monthly surveillance observations. Monthly case and death counts were modeled with calendar year as a categorical predictor. Negative binomial generalized linear models with log offsets were selected as the primary models because Poisson models showed marked overdispersion; heteroscedasticity—and autocorrelation-consistent (HAC) standard errors were used to reduce sensitivity to serial dependence. A log-linear model estimated Monthly Percent Change (MPC) using a four-month moving-block bootstrap. A quasi-Poisson generalized additive model (GAM) with k = 10 was examined as an exploratory description of non-linearity. Results: Annual incidence increased from 2310.85 per 100,000 in 2020 to 4905.65 per 100,000 in 2022 and decreased to 908.18 per 100,000 in 2023. Mortality peaked in 2021 and period-specific CFR declined markedly thereafter. In the primary negative binomial models with HAC inference, incidence was lower in 2023 than in 2020 (RR = 0.39; 95% CI: 0.17–0.89; p = 0.0247). Mortality in 2021 did not differ from 2020 (RR = 1.11; 95% CI: 0.43–2.89; p = 0.8270), whereas mortality was lower in 2022 (RR = 0.22; 95% CI: 0.09–0.52; p = 0.0006) and 2023 (RR = 0.06; 95% CI: 0.03–0.14; p < 0.0001). The global MPC was +2.52% (moving-block bootstrap 95% CI: −5.42% to 11.00%; p = 0.5152), providing no evidence of a consistent global log-linear trend. The exploratory GAM suggested a non-linear trajectory, but its basis-dimension check indicated that k = 10 was insufficient (k-index = 0.469; p < 0.001); therefore, no inferential conclusion was based on the GAM. Conclusions: Pernambuco surveillance data show an epidemiological divergence between reported incidence and severe outcomes, particularly from 2022 onward. Because vaccination, hybrid immunity, circulating variants, testing practices, and clinical management were not directly modeled, these findings support epidemiological decoupling but do not by themselves establish its biological mechanisms.