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Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland

BACKGROUND: In Swaziland, as in many high HIV/TB burden settings, there is not information available regarding the household location of TB cases for identifying areas of increased TB incidence, limiting the development of targeted interventions. Data from “Butimba”, a TB REACH active case finding p...

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Autores principales: Brunetti, Marie, Rajasekharan, Sathyanath, Ustero, Piluca, Ngo, Katherine, Sikhondze, Welile, Mzileni, Buli, Mandalakas, Anna, Kay, Alexander W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798177/
https://www.ncbi.nlm.nih.gov/pubmed/29445773
http://dx.doi.org/10.1186/s41256-018-0058-y
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author Brunetti, Marie
Rajasekharan, Sathyanath
Ustero, Piluca
Ngo, Katherine
Sikhondze, Welile
Mzileni, Buli
Mandalakas, Anna
Kay, Alexander W.
author_facet Brunetti, Marie
Rajasekharan, Sathyanath
Ustero, Piluca
Ngo, Katherine
Sikhondze, Welile
Mzileni, Buli
Mandalakas, Anna
Kay, Alexander W.
author_sort Brunetti, Marie
collection PubMed
description BACKGROUND: In Swaziland, as in many high HIV/TB burden settings, there is not information available regarding the household location of TB cases for identifying areas of increased TB incidence, limiting the development of targeted interventions. Data from “Butimba”, a TB REACH active case finding project, was re-analyzed to provide insight into the location of TB cases surrounding Mbabane, Swaziland. OBJECTIVE: The project aimed to identify geographical areas with high TB burdens to inform active case finding efforts. METHODS: Butimba implemented household contact tracing; obtaining landmark based, informal directions, to index case homes, defined here as relative locations. The relative locations were matched to census enumeration areas (known location reference areas) using the Microsoft Excel Fuzzy Lookup function. Of 403 relative locations, an enumeration area reference was detected in 388 (96%). TB cases in each census enumeration area and the active case finders in each Tinkhundla, a local governmental region, were mapped using the geographic information system, QGIS 2.16. RESULTS: Urban Tinkhundla predictably accounted for most cases; however, after adjusting for population, the highest density of cases was found in rural Tinkhundla. There was no correlation between the number of active case finders currently assigned to the 7 Tinkhundla surrounding Mbabane and the total number of TB cases (Spearman rho = −0.57, p = 0.17) or the population adjusted TB cases (Spearman rho = 0.14, p = 0.75) per Tinkhundla. DISCUSSION: Reducing TB incidence in high-burden settings demands novel analytic approaches to study TB case locations. We demonstrated the feasibility of linking relative locations to more precise geographical areas, enabling data-driven guidance for National Tuberculosis Programs’ resource allocation. In collaboration with the Swazi National Tuberculosis Control Program, this analysis highlighted opportunities to better align the active case finding national strategy with the TB disease burden.
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spelling pubmed-57981772018-02-14 Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland Brunetti, Marie Rajasekharan, Sathyanath Ustero, Piluca Ngo, Katherine Sikhondze, Welile Mzileni, Buli Mandalakas, Anna Kay, Alexander W. Glob Health Res Policy Short Report BACKGROUND: In Swaziland, as in many high HIV/TB burden settings, there is not information available regarding the household location of TB cases for identifying areas of increased TB incidence, limiting the development of targeted interventions. Data from “Butimba”, a TB REACH active case finding project, was re-analyzed to provide insight into the location of TB cases surrounding Mbabane, Swaziland. OBJECTIVE: The project aimed to identify geographical areas with high TB burdens to inform active case finding efforts. METHODS: Butimba implemented household contact tracing; obtaining landmark based, informal directions, to index case homes, defined here as relative locations. The relative locations were matched to census enumeration areas (known location reference areas) using the Microsoft Excel Fuzzy Lookup function. Of 403 relative locations, an enumeration area reference was detected in 388 (96%). TB cases in each census enumeration area and the active case finders in each Tinkhundla, a local governmental region, were mapped using the geographic information system, QGIS 2.16. RESULTS: Urban Tinkhundla predictably accounted for most cases; however, after adjusting for population, the highest density of cases was found in rural Tinkhundla. There was no correlation between the number of active case finders currently assigned to the 7 Tinkhundla surrounding Mbabane and the total number of TB cases (Spearman rho = −0.57, p = 0.17) or the population adjusted TB cases (Spearman rho = 0.14, p = 0.75) per Tinkhundla. DISCUSSION: Reducing TB incidence in high-burden settings demands novel analytic approaches to study TB case locations. We demonstrated the feasibility of linking relative locations to more precise geographical areas, enabling data-driven guidance for National Tuberculosis Programs’ resource allocation. In collaboration with the Swazi National Tuberculosis Control Program, this analysis highlighted opportunities to better align the active case finding national strategy with the TB disease burden. BioMed Central 2018-02-05 /pmc/articles/PMC5798177/ /pubmed/29445773 http://dx.doi.org/10.1186/s41256-018-0058-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Short Report
Brunetti, Marie
Rajasekharan, Sathyanath
Ustero, Piluca
Ngo, Katherine
Sikhondze, Welile
Mzileni, Buli
Mandalakas, Anna
Kay, Alexander W.
Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland
title Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland
title_full Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland
title_fullStr Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland
title_full_unstemmed Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland
title_short Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in Swaziland
title_sort leveraging tuberculosis case relative locations to enhance case detection and linkage to care in swaziland
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798177/
https://www.ncbi.nlm.nih.gov/pubmed/29445773
http://dx.doi.org/10.1186/s41256-018-0058-y
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