Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.

BACKGROUND:Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late. DATA AND METHODS:This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi...

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Main Authors: Luan Nguyen Quang Vo, Thanh Nguyen Vu, Hoa Trung Nguyen, Tung Thanh Truong, Canh Minh Khuu, Phuong Quoc Pham, Lan Huu Nguyen, Giang Truong Le, Jacob Creswell
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0209290
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spelling doaj-41e27a87a2fe4cdeaac2945d4d9d03182021-03-03T21:01:45ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-011312e020929010.1371/journal.pone.0209290Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.Luan Nguyen Quang VoThanh Nguyen VuHoa Trung NguyenTung Thanh TruongCanh Minh KhuuPhuong Quoc PhamLan Huu NguyenGiang Truong LeJacob CreswellBACKGROUND:Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late. DATA AND METHODS:This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi Minh City. We geocoded TB notifications from 2011 to 2015 and calculated theoretical yields of simulated door-to-door screening in three concentric catchment areas (50m, 100m, 200m) and three notification window scenarios (one, two and four quarters) for each index case. We calculated average yields, compared them to published reference values and fit a GEE (Generalized Estimating Equation) linear regression model onto the data. RESULTS:The sample included 3,046 TB patients. Adjusted theoretical yields in 50m, 100m and 200m catchment areas were 0.32% (95%CI: 0.27,0.37), 0.21% (95%CI: 0.14,0.29) and 0.17% (95%CI: 0.09,0.25), respectively, in the baseline notification window scenario. Theoretical yields in the 50m-catchment area for all notification window scenarios were significantly higher than a reference yield from literature. Yield was positively associated with treatment failure index cases (beta = 0.12, p = 0.001) and short-term inter-province migrants (beta = 0.06, p = 0.022), while greater distance to the DTU (beta = -0.02, p<0.001) was associated with lower yield. CONCLUSIONS:This study is an example of inter-departmental collaboration and application of repurposed cadastral data to progress towards the end TB objectives. The results from Go Vap showed that the use of spatial analysis may be able to identify areas where targeted active case finding in Vietnam can help improve TB case detection.https://doi.org/10.1371/journal.pone.0209290
collection DOAJ
language English
format Article
sources DOAJ
author Luan Nguyen Quang Vo
Thanh Nguyen Vu
Hoa Trung Nguyen
Tung Thanh Truong
Canh Minh Khuu
Phuong Quoc Pham
Lan Huu Nguyen
Giang Truong Le
Jacob Creswell
spellingShingle Luan Nguyen Quang Vo
Thanh Nguyen Vu
Hoa Trung Nguyen
Tung Thanh Truong
Canh Minh Khuu
Phuong Quoc Pham
Lan Huu Nguyen
Giang Truong Le
Jacob Creswell
Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.
PLoS ONE
author_facet Luan Nguyen Quang Vo
Thanh Nguyen Vu
Hoa Trung Nguyen
Tung Thanh Truong
Canh Minh Khuu
Phuong Quoc Pham
Lan Huu Nguyen
Giang Truong Le
Jacob Creswell
author_sort Luan Nguyen Quang Vo
title Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.
title_short Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.
title_full Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.
title_fullStr Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.
title_full_unstemmed Optimizing community screening for tuberculosis: Spatial analysis of localized case finding from door-to-door screening for TB in an urban district of Ho Chi Minh City, Viet Nam.
title_sort optimizing community screening for tuberculosis: spatial analysis of localized case finding from door-to-door screening for tb in an urban district of ho chi minh city, viet nam.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2018-01-01
description BACKGROUND:Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late. DATA AND METHODS:This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi Minh City. We geocoded TB notifications from 2011 to 2015 and calculated theoretical yields of simulated door-to-door screening in three concentric catchment areas (50m, 100m, 200m) and three notification window scenarios (one, two and four quarters) for each index case. We calculated average yields, compared them to published reference values and fit a GEE (Generalized Estimating Equation) linear regression model onto the data. RESULTS:The sample included 3,046 TB patients. Adjusted theoretical yields in 50m, 100m and 200m catchment areas were 0.32% (95%CI: 0.27,0.37), 0.21% (95%CI: 0.14,0.29) and 0.17% (95%CI: 0.09,0.25), respectively, in the baseline notification window scenario. Theoretical yields in the 50m-catchment area for all notification window scenarios were significantly higher than a reference yield from literature. Yield was positively associated with treatment failure index cases (beta = 0.12, p = 0.001) and short-term inter-province migrants (beta = 0.06, p = 0.022), while greater distance to the DTU (beta = -0.02, p<0.001) was associated with lower yield. CONCLUSIONS:This study is an example of inter-departmental collaboration and application of repurposed cadastral data to progress towards the end TB objectives. The results from Go Vap showed that the use of spatial analysis may be able to identify areas where targeted active case finding in Vietnam can help improve TB case detection.
url https://doi.org/10.1371/journal.pone.0209290
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