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Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study
BACKGROUND: Although several studies have estimated gestational syphilis (GS) incidence in several countries, underreporting correction is rarely considered. This study aimed to estimate the level of under-registration and correct the GS incidence rates in the 557 Brazilian microregions. METHODS: Br...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415804/ https://www.ncbi.nlm.nih.gov/pubmed/37575963 http://dx.doi.org/10.1016/j.lana.2023.100564 |
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author | Lopes de Oliveira, Guilherme Ferreira, Andrêa J.F. Teles, Carlos Antônio de S.S. Paixao, Enny S. Fiaccone, Rosemeire Lana, Raquel Aquino, Rosana Cardoso, Andrey Moreira Soares, Maria Auxiliadora Oliveira dos Santos, Idália Pereira, Marcos Barreto, Maurício L. Ichihara, Maria Yury |
author_facet | Lopes de Oliveira, Guilherme Ferreira, Andrêa J.F. Teles, Carlos Antônio de S.S. Paixao, Enny S. Fiaccone, Rosemeire Lana, Raquel Aquino, Rosana Cardoso, Andrey Moreira Soares, Maria Auxiliadora Oliveira dos Santos, Idália Pereira, Marcos Barreto, Maurício L. Ichihara, Maria Yury |
author_sort | Lopes de Oliveira, Guilherme |
collection | PubMed |
description | BACKGROUND: Although several studies have estimated gestational syphilis (GS) incidence in several countries, underreporting correction is rarely considered. This study aimed to estimate the level of under-registration and correct the GS incidence rates in the 557 Brazilian microregions. METHODS: Brazilian GS notifications between 2007 and 2018 were obtained from the SINAN-Syphilis system. A cluster analysis was performed to group microregions according to the quality of GS notification. A Bayesian hierarchical Poisson regression model was applied to estimate the reporting probabilities among the clusters and to correct the associated incidence rates. FINDINGS: We estimate that 45,196 (90%-HPD: 13,299; 79,310) GS cases were underreported in Brazil from 2007 to 2018, representing a coverage of 87.12% (90%-HPD: 79.40%; 95.83%) of registered cases, where HPD stands for the Bayesian highest posterior density credible interval. Underreporting levels differ across the country, with microregions in North and Northeast regions presenting the highest percentage of missed cases. After underreporting correction, Brazil’s estimated GS incidence rate increased from 8.74 to 10.02 per 1000 live births in the same period. INTERPRETATION: Our findings highlight disparities in the registration level and incidence rate of GS in Brazil, reflecting regional heterogeneity in the quality of syphilis surveillance, access to prenatal care, and childbirth assistance services. This study provides robust evidence to enhance national surveillance systems, guide specific policies for GS detection disease control, and potentially mitigate the harmful consequences of mother-to-child transmission. The methodology might be applied in other regions to correct disease underreporting. FUNDING: 10.13039/501100003593National Council for Scientific and Technological Development; The Bill Melinda Gates Foundation and 10.13039/100010269Wellcome Trust. |
format | Online Article Text |
id | pubmed-10415804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104158042023-08-12 Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study Lopes de Oliveira, Guilherme Ferreira, Andrêa J.F. Teles, Carlos Antônio de S.S. Paixao, Enny S. Fiaccone, Rosemeire Lana, Raquel Aquino, Rosana Cardoso, Andrey Moreira Soares, Maria Auxiliadora Oliveira dos Santos, Idália Pereira, Marcos Barreto, Maurício L. Ichihara, Maria Yury Lancet Reg Health Am Articles BACKGROUND: Although several studies have estimated gestational syphilis (GS) incidence in several countries, underreporting correction is rarely considered. This study aimed to estimate the level of under-registration and correct the GS incidence rates in the 557 Brazilian microregions. METHODS: Brazilian GS notifications between 2007 and 2018 were obtained from the SINAN-Syphilis system. A cluster analysis was performed to group microregions according to the quality of GS notification. A Bayesian hierarchical Poisson regression model was applied to estimate the reporting probabilities among the clusters and to correct the associated incidence rates. FINDINGS: We estimate that 45,196 (90%-HPD: 13,299; 79,310) GS cases were underreported in Brazil from 2007 to 2018, representing a coverage of 87.12% (90%-HPD: 79.40%; 95.83%) of registered cases, where HPD stands for the Bayesian highest posterior density credible interval. Underreporting levels differ across the country, with microregions in North and Northeast regions presenting the highest percentage of missed cases. After underreporting correction, Brazil’s estimated GS incidence rate increased from 8.74 to 10.02 per 1000 live births in the same period. INTERPRETATION: Our findings highlight disparities in the registration level and incidence rate of GS in Brazil, reflecting regional heterogeneity in the quality of syphilis surveillance, access to prenatal care, and childbirth assistance services. This study provides robust evidence to enhance national surveillance systems, guide specific policies for GS detection disease control, and potentially mitigate the harmful consequences of mother-to-child transmission. The methodology might be applied in other regions to correct disease underreporting. FUNDING: 10.13039/501100003593National Council for Scientific and Technological Development; The Bill Melinda Gates Foundation and 10.13039/100010269Wellcome Trust. Elsevier 2023-08-01 /pmc/articles/PMC10415804/ /pubmed/37575963 http://dx.doi.org/10.1016/j.lana.2023.100564 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles Lopes de Oliveira, Guilherme Ferreira, Andrêa J.F. Teles, Carlos Antônio de S.S. Paixao, Enny S. Fiaccone, Rosemeire Lana, Raquel Aquino, Rosana Cardoso, Andrey Moreira Soares, Maria Auxiliadora Oliveira dos Santos, Idália Pereira, Marcos Barreto, Maurício L. Ichihara, Maria Yury Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study |
title | Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study |
title_full | Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study |
title_fullStr | Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study |
title_full_unstemmed | Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study |
title_short | Estimating the real burden of gestational syphilis in Brazil, 2007–2018: a Bayesian modeling study |
title_sort | estimating the real burden of gestational syphilis in brazil, 2007–2018: a bayesian modeling study |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415804/ https://www.ncbi.nlm.nih.gov/pubmed/37575963 http://dx.doi.org/10.1016/j.lana.2023.100564 |
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