Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021

ABSTRACT Objective: To analyze the spatial patterns of leprosy in Pernambuco from 2011 to 2021. Methods: This is an ecological epidemiological study, carried out with data from the Notifiable Diseases Information System, based on new cases of leprosy among inhabitants of Pernambuco, between 2011–2...

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Main Authors: Maria Luiza Ferreira Imburana da Silva, Shirlley Jackllanny Martins de Farias, Amanda Priscila de Santana Cabral Silva, Maria Olívia Soares Rodrigues, Emília Carolle Azevedo de Oliveira
Format: Article
Language:English
Published: Associação Brasileira de Pós-Graduação em Saúde Coletiva 2023-02-01
Series:Revista Brasileira de Epidemiologia
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2023000100412&lng=en&tlng=en
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author Maria Luiza Ferreira Imburana da Silva
Shirlley Jackllanny Martins de Farias
Amanda Priscila de Santana Cabral Silva
Maria Olívia Soares Rodrigues
Emília Carolle Azevedo de Oliveira
author_facet Maria Luiza Ferreira Imburana da Silva
Shirlley Jackllanny Martins de Farias
Amanda Priscila de Santana Cabral Silva
Maria Olívia Soares Rodrigues
Emília Carolle Azevedo de Oliveira
author_sort Maria Luiza Ferreira Imburana da Silva
collection DOAJ
description ABSTRACT Objective: To analyze the spatial patterns of leprosy in Pernambuco from 2011 to 2021. Methods: This is an ecological epidemiological study, carried out with data from the Notifiable Diseases Information System, based on new cases of leprosy among inhabitants of Pernambuco, between 2011–2021. An empirical Bayesian analysis of local and spatial dependence was performed with the global and local Moran indices. Results: 25,008 new cases of leprosy were registered with an annual case detection rate in the general population of 16.51 cases/100,000 inhabitants — which is considered high. Among those younger than 15 years of age, there were 5.16 cases/100,000 inhabitants (high) and 0.89/100,000 inhabitants with degree II of physical disability (low); there were also many high-risk cases with an overall Moran index of 0.33 (p<0.001), active transmission (0.26; p<0.001), and subsequent diagnosis of the disease (0.12; p<0.006), as well as distribution in macro-region 1 and macro-region 4. Conclusion: There was a heterogeneous spatial distribution in the state, showing two overviews, the first being the presence of municipalities with high risk of disease transmission and the second with clusters of silent municipalities, reinforcing the character of leprosy neglect as a major public health problem. This study brings reflections for leprosy control actions, due to the identification of priority areas to combat this disease in Pernambuco.
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spelling doaj.art-f59c1deb7121412b86cca28b4bd5381c2023-02-21T07:34:52ZengAssociação Brasileira de Pós-Graduação em Saúde ColetivaRevista Brasileira de Epidemiologia1980-54972023-02-012610.1590/1980-549720230014Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021Maria Luiza Ferreira Imburana da Silvahttps://orcid.org/0000-0003-3131-6166Shirlley Jackllanny Martins de Fariashttps://orcid.org/0000-0002-2782-5462Amanda Priscila de Santana Cabral Silvahttps://orcid.org/0000-0003-2337-9925Maria Olívia Soares Rodrigueshttps://orcid.org/0000-0002-2048-1038Emília Carolle Azevedo de Oliveirahttps://orcid.org/0000-0002-0957-1542ABSTRACT Objective: To analyze the spatial patterns of leprosy in Pernambuco from 2011 to 2021. Methods: This is an ecological epidemiological study, carried out with data from the Notifiable Diseases Information System, based on new cases of leprosy among inhabitants of Pernambuco, between 2011–2021. An empirical Bayesian analysis of local and spatial dependence was performed with the global and local Moran indices. Results: 25,008 new cases of leprosy were registered with an annual case detection rate in the general population of 16.51 cases/100,000 inhabitants — which is considered high. Among those younger than 15 years of age, there were 5.16 cases/100,000 inhabitants (high) and 0.89/100,000 inhabitants with degree II of physical disability (low); there were also many high-risk cases with an overall Moran index of 0.33 (p<0.001), active transmission (0.26; p<0.001), and subsequent diagnosis of the disease (0.12; p<0.006), as well as distribution in macro-region 1 and macro-region 4. Conclusion: There was a heterogeneous spatial distribution in the state, showing two overviews, the first being the presence of municipalities with high risk of disease transmission and the second with clusters of silent municipalities, reinforcing the character of leprosy neglect as a major public health problem. This study brings reflections for leprosy control actions, due to the identification of priority areas to combat this disease in Pernambuco.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2023000100412&lng=en&tlng=enLeprosySpatial analysisNeglected diseasesEpidemiology
spellingShingle Maria Luiza Ferreira Imburana da Silva
Shirlley Jackllanny Martins de Farias
Amanda Priscila de Santana Cabral Silva
Maria Olívia Soares Rodrigues
Emília Carolle Azevedo de Oliveira
Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021
Revista Brasileira de Epidemiologia
Leprosy
Spatial analysis
Neglected diseases
Epidemiology
title Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021
title_full Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021
title_fullStr Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021
title_full_unstemmed Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021
title_short Spatial patterns of new leprosy cases in a northeastern state of Brazil, 2011–2021
title_sort spatial patterns of new leprosy cases in a northeastern state of brazil 2011 2021
topic Leprosy
Spatial analysis
Neglected diseases
Epidemiology
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2023000100412&lng=en&tlng=en
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