Evidence map›Paper›PMID 38787038›Full record

ArticleTropical medicine and infectious disease2024

High-Risk Areas for Congenital Zika Syndrome in Rio de Janeiro: Spatial Cluster Detection.

Danielle Amaral de Freitas, Mayumi Duarte Wakimoto, Sónia Dias, Reinaldo Souza-Santos

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Danielle Amaral de FreitasEscola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rua Leopoldo Bulhões, Rio de Janeiro 1480, RJ, Brazil.ORCID 0000-0002-5460-8316
Mayumi Duarte WakimotoInstituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Av. Brasil, Rio de Janeiro 4365, RJ, Brazil.ORCID 0000-0001-9380-3387
Sónia DiasNational School of Public Health, Public Health Research Centre, Comprehensive Health Research Center (CHRC), REAL, NOVA University of Lisbon, Avenida Padre Cruz, 1600-560 Lisboa, Portugal.ORCID 0000-0001-5085-0685
Reinaldo Souza-SantosEscola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rua Leopoldo Bulhões, Rio de Janeiro 1480, RJ, Brazil.ORCID 0000-0003-2387-6999

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brazil reported 18,282 suspected congenital Zika syndrome (CZS) cases up to 2018 and accounts for 61.4% of the total reported Zika cases in the Americas in the period. To detect high-risk areas for children with CZS in the city of Rio de Janeiro, we used cluster detection and thematic maps. We analyzed data using a Poisson model in Satscan 10.1.3 software. We also analyzed the records of children with CZS from 2015 to 2016 to describe the clinical and epidemiological maternal and child profile, as well as live births in 2016 and the social development index (SDI) by neighborhood. In 2015 and 2016, the incidence rates of CZS were 8.84 and 46.96 per 100,000 live births in the city, respectively. Severe congenital findings such as microcephaly and brain damage, osteoarticular impairment, ocular abnormalities, and hearing loss were observed in 47 children. The spatial distribution of CZS was concentrated in the north and west zones in heterogeneous neighborhoods. The neighborhoods with the highest occurrence of CZS cases were found to have the worst SDIs. Stascan detected three spatial clusters in the north zone, where the SDI is lower. The clusters presented high relative risks for CZS (7.86, 1.46, and 2.08), although they were not statistically significant. Our findings highlight a higher occurrence of CZS in areas with less favorable socioeconomic conditions.

Indexed as

cluster analysiscongenital abnormalitiescongenital Zika virus infectionepidemiologysocial vulnerabilityspatial analysisZika virus infection

Identifiers

PMID38787038
PMCPMC11125739

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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.