Evidence map›Paper›PMID 41417302›Full record

ArticleRevista da Sociedade Brasileira de Medicina Tropical2025

Chikungunya clusters in the state of Bahia: influence of environmental and social factors.

Maryly Weyll Sant Anna, Raquel Gardini Sanches Palasio, Alec Brian Lacerda, Maurício Lamano Ferreira, Francisco Chiaravalloti-Neto, Fabricio Bau Dalmas, Pedro Luiz Côrtes

Abstract read
In one paragraph

Article in Revista da Sociedade Brasileira de Medicina Tropical, 2025. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Maryly Weyll Sant AnnaUniversidade de São Paulo, Instituto de Energia e Ambiente, São Paulo, SP, Brasil.ORCID http://orcid.org/0009-0001-9890-9313
Raquel Gardini Sanches PalasioUniversidade de São Paulo, Faculdade de Saúde Pública, Laboratório de Análise Espacial em Saúde, Departamento de Epidemiologia, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0003-1564-0871
Alec Brian LacerdaUniversidade de São Paulo, Faculdade de Saúde Pública, Laboratório de Análise Espacial em Saúde, Departamento de Epidemiologia, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0002-2971-0327
Maurício Lamano FerreiraUniversidade de São Paulo, Escola de Engenharia de Lorena, Departamento de Ciências Básicas e Ambientais, Lorena, SP, Brasil.ORCID http://orcid.org/0000-0002-7647-3635
Francisco Chiaravalloti-NetoUniversidade de São Paulo, Faculdade de Saúde Pública, Laboratório de Análise Espacial em Saúde, Departamento de Epidemiologia, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0003-2686-8740
Fabricio Bau DalmasUniversidade de Guarulhos, Programa de Mestrado em Análise Ambiental, Guarulhos, SP, Brasil.ORCID http://orcid.org/0000-0001-7547-6642
Pedro Luiz CôrtesUniversidade de São Paulo, Instituto de Energia e Ambiente, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0003-4160-4073

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChikungunya is an emerging disease that significantly impacts global public health and is associated with various environmental and social factors. This study aimed to identify the spatial and spatiotemporal clusters of chikungunya in the state of Brazilian Bahia, as well as their relationships with environmental and socioeconomic variables.

methodsHigh- and low-risk clusters were analyzed for 2014-2023 using SatScan. Associations among socioeconomic, climatic, and vegetation characteristics were established using geostatistical estimates.

resultsMany high-risk clusters were observed at high densities in the southern, north-central, and south-central mesoregions. The months with the highest risk were February and March. A decreasing chikungunya trend of -0.6% per year was identified in the Bahian territory when the spatial variation of the temporal trends was analyzed. High-risk municipalities within the spatial chikungunya clusters generally had higher minimum annual and summer temperatures, lower thermal amplitudes, higher monthly and average summer precipitation levels, and higher socioeconomic indicators. The lowest vegetation cover was observed in the Caatinga biome, and the highest in the Atlantic Forest.

conclusionsBahia has many high-risk clusters for chikungunya, underscoring the need to strengthen preventive and control measures through coordinated epidemiological surveillance services across the state.

Indexed as

Chikungunya FeverAnimalsBrazilHumansRisk FactorsSeasonsSocioeconomic FactorsSpatio-Temporal Analysis

Identifiers

PMID41417302
PMCPMC12700500

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.