Evidence map›Paper›PMID 42346170›Full record

ArticleEpidemiologia (Basel, Switzerland)2026

Quantifying Epidemiological Risk Transitions of COVID-19 in the Brazilian State of Ceará (2020-2023): A Generalized Linear Modeling Approach.

Matheus Paiva Emidio Cavalcanti, Carlos Mendes Tavares, Yasmin Esther Barreto, Alexandre Castelo Branco Araujo, Rosalina Semedo de Andrade, Luiz Carlos de Abreu

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Article in Epidemiologia (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Matheus Paiva Emidio CavalcantiCOVID-19 Observatory Brazil and Ireland, School of Medicine, University of Limerick, V94 T9PX Limerick, Ireland.
Carlos Mendes TavaresInstitute of Applied Social Sciences, University of International Integration of Afro-Brazilian Lusophony (UNILAB), Redenção 62790-000, CE, Brazil.ORCID 0000-0002-2874-0866
Yasmin Esther BarretoCOVID-19 Observatory Brazil and Ireland, School of Medicine, University of Limerick, V94 T9PX Limerick, Ireland.
Alexandre Castelo Branco AraujoPostgraduate Program in Medical Sciences, Faculty of Medicine, University of São Paulo, Sao Paulo 01246-903, SP, Brazil.ORCID 0009-0009-0963-7116
Rosalina Semedo de AndradeInstitute of Applied Social Sciences, University of International Integration of Afro-Brazilian Lusophony (UNILAB), Redenção 62790-000, CE, Brazil.
Luiz Carlos de AbreuCOVID-19 Observatory Brazil and Ireland, School of Medicine, University of Limerick, V94 T9PX Limerick, Ireland.ORCID 0000-0002-7618-2109

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesWhile 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.

methodsEcological 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).

resultsModeling 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).

conclusionsBetween 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.

Indexed as

COVID-19epidemiological monitoringhealth transitionLinear Modelstime series studies

Identifiers

PMID42346170
PMCPMC13298685

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