Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil
ABSTRACT Leprosy is a public health problem due to the physical disabilities and deformities it causes. This study aimed to describe new leprosy cases using an operational classification and analyzing spatial patterns by means of epidemiological and quality indicators of health services in Pernambuc...
Published in: | Revista do Instituto de Medicina Tropical de São Paulo |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Universidade de São Paulo (USP)
2020
|
Subjects: | |
Online Access: | https://doi.org/10.1590/s1678-9946202062093 https://doaj.org/article/720fd8e10d4d4c38a5104467733ecb88 |
id |
ftdoajarticles:oai:doaj.org/article:720fd8e10d4d4c38a5104467733ecb88 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:720fd8e10d4d4c38a5104467733ecb88 2024-09-09T19:26:45+00:00 Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil Celivane Cavalcanti Barbosa Cristine Vieira do Bonfim Cintia Michele Gondim de Brito Wayner Vieira de Souza Marcella Fernandes de Oliveira Melo Zulma Maria de Medeiros 2020-11-01T00:00:00Z https://doi.org/10.1590/s1678-9946202062093 https://doaj.org/article/720fd8e10d4d4c38a5104467733ecb88 EN eng Universidade de São Paulo (USP) http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0036-46652020000100245&tlng=en https://doaj.org/toc/1678-9946 1678-9946 doi:10.1590/s1678-9946202062093 https://doaj.org/article/720fd8e10d4d4c38a5104467733ecb88 Revista do Instituto de Medicina Tropical de São Paulo, Vol 62 (2020) Leprosy Epidemiology Health information systems Spatial analysis Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2020 ftdoajarticles https://doi.org/10.1590/s1678-9946202062093 2024-08-05T17:49:31Z ABSTRACT Leprosy is a public health problem due to the physical disabilities and deformities it causes. This study aimed to describe new leprosy cases using an operational classification and analyzing spatial patterns by means of epidemiological and quality indicators of health services in Pernambuco State, Brazil, between 2005 and 2014. This was an ecological study performed in 184 municipalities grouped into 12 health regions units for analysis. To analyze spatial patterns, the Bayesian local empirical method and Moran's spatial autocorrelation indicator were applied and box and Moran maps were used. Individuals aged ≥15 years old, grade zero physical disability and complete remission as the treatment outcome were predominant in both paucibacillary and multibacillary cases, the only difference was the predominance of females (n=9,286; 63.00%) and males (n=8,564; 60.70%), respectively. These variables were correlated (p<0.05) with the operational classification. The overall detection rate showed three high-priority areas; the indicator rate of grade 2 physical disability revealed clusters in regions IV, V, and VI; and the indicator rate of cases with some degree of disability showed precarious municipalities in seven health regions. Pernambuco maintains an active chain of transmission and ongoing endemicity of leprosy. Therefore, spatial analysis methods allow the identification of priority areas for intervention, thereby supporting the disease elimination strategy. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Revista do Instituto de Medicina Tropical de São Paulo 62 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Leprosy Epidemiology Health information systems Spatial analysis Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
spellingShingle |
Leprosy Epidemiology Health information systems Spatial analysis Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Celivane Cavalcanti Barbosa Cristine Vieira do Bonfim Cintia Michele Gondim de Brito Wayner Vieira de Souza Marcella Fernandes de Oliveira Melo Zulma Maria de Medeiros Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil |
topic_facet |
Leprosy Epidemiology Health information systems Spatial analysis Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
ABSTRACT Leprosy is a public health problem due to the physical disabilities and deformities it causes. This study aimed to describe new leprosy cases using an operational classification and analyzing spatial patterns by means of epidemiological and quality indicators of health services in Pernambuco State, Brazil, between 2005 and 2014. This was an ecological study performed in 184 municipalities grouped into 12 health regions units for analysis. To analyze spatial patterns, the Bayesian local empirical method and Moran's spatial autocorrelation indicator were applied and box and Moran maps were used. Individuals aged ≥15 years old, grade zero physical disability and complete remission as the treatment outcome were predominant in both paucibacillary and multibacillary cases, the only difference was the predominance of females (n=9,286; 63.00%) and males (n=8,564; 60.70%), respectively. These variables were correlated (p<0.05) with the operational classification. The overall detection rate showed three high-priority areas; the indicator rate of grade 2 physical disability revealed clusters in regions IV, V, and VI; and the indicator rate of cases with some degree of disability showed precarious municipalities in seven health regions. Pernambuco maintains an active chain of transmission and ongoing endemicity of leprosy. Therefore, spatial analysis methods allow the identification of priority areas for intervention, thereby supporting the disease elimination strategy. |
format |
Article in Journal/Newspaper |
author |
Celivane Cavalcanti Barbosa Cristine Vieira do Bonfim Cintia Michele Gondim de Brito Wayner Vieira de Souza Marcella Fernandes de Oliveira Melo Zulma Maria de Medeiros |
author_facet |
Celivane Cavalcanti Barbosa Cristine Vieira do Bonfim Cintia Michele Gondim de Brito Wayner Vieira de Souza Marcella Fernandes de Oliveira Melo Zulma Maria de Medeiros |
author_sort |
Celivane Cavalcanti Barbosa |
title |
Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil |
title_short |
Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil |
title_full |
Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil |
title_fullStr |
Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil |
title_full_unstemmed |
Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil |
title_sort |
spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in northeastern brazil |
publisher |
Universidade de São Paulo (USP) |
publishDate |
2020 |
url |
https://doi.org/10.1590/s1678-9946202062093 https://doaj.org/article/720fd8e10d4d4c38a5104467733ecb88 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Revista do Instituto de Medicina Tropical de São Paulo, Vol 62 (2020) |
op_relation |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0036-46652020000100245&tlng=en https://doaj.org/toc/1678-9946 1678-9946 doi:10.1590/s1678-9946202062093 https://doaj.org/article/720fd8e10d4d4c38a5104467733ecb88 |
op_doi |
https://doi.org/10.1590/s1678-9946202062093 |
container_title |
Revista do Instituto de Medicina Tropical de São Paulo |
container_volume |
62 |
_version_ |
1809896305561960448 |