Geographic information systems analysis to focus TB screening among people born in endemic countries

<sec><title>BACKGROUND</title>Geographic information systems may help focus TB screening and treatment efforts to populations in greatest need, such as people born in endemic countries (PBEC).</sec><sec><title>DESIGN/METHODS</title>North Carolina USA census and TB surveillance data were used to examine the relationship between the population proportion of PBEC and incident TB cases in the subsequent 5-year period by census tract. Census tract population:incident TB ratios for thresholds of PBEC were used to measure screening efficiency.</sec><sec><title>RESULTS</title>Of 3,290 PBEC TB cases, 2,764 (84%) had a mappable address. The proportion of census tract PBEC during 2006-2010 was strongly associated with incident TB in that tract in 2011-2015 (<i>p</i> < 0.001). Thresholds of 6%, 12%, and 19% PBEC in a tract during 2006-2010 as cutoffs for screening would have detected 75%, 50%, and 25% of incident TB cases in 2011-2015 with respective population:incident TB ratios of 11,840, 6,864, and 5,524 population/case. The same thresholds using 2011-2015 census data would have detected 75%, 50%, and 25% of incident TB cases during 2016-2018 with population:incident TB ratios of 17,804, 10,807, and 7,031 population/case.</sec><sec><title>CONCLUSION</title>Census tract demographics are a simple and powerful tool to focus targeted testing and treatment of latent TB in areas likely to have incident TB disease.</sec>.

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Publication Details

Journal
The International Journal of Tuberculosis and Lung Disease
Published
2025-03-29
DOI
https://doi.org/10.5588/ijtld.24.0471
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Geographic information systems analysis to focus TB screening among people born in endemic countries

Silvio Zavala, Michael C Kiritsy, Jason E. Stout, Nicholas Turner et al.
The International Journal of Tuberculosis and Lung Disease
Tuberculosis Research and Epidemiology
article

Geographic information systems analysis to focus TB screening among people born in endemic countries

Silvio Zavala, Michael C Kiritsy, Jason E. Stout, Nicholas Turner, Afzal Ahmed, G. M. Cox
article en

Abstract

<sec><title>BACKGROUND</title>Geographic information systems may help focus TB screening and treatment efforts to populations in greatest need, such as people born in endemic countries (PBEC).</sec><sec><title>DESIGN/METHODS</title>North Carolina USA census and TB surveillance data were used to examine the relationship between the population proportion of PBEC and incident TB cases in the subsequent 5-year period by census tract. Census tract population:incident TB ratios for thresholds of PBEC were used to measure screening efficiency.</sec><sec><title>RESULTS</title>Of 3,290 PBEC TB cases, 2,764 (84%) had a mappable address. The proportion of census tract PBEC during 2006-2010 was strongly associated with incident TB in that tract in 2011-2015 (<i>p</i> < 0.001). Thresholds of 6%, 12%, and 19% PBEC in a tract during 2006-2010 as cutoffs for screening would have detected 75%, 50%, and 25% of incident TB cases in 2011-2015 with respective population:incident TB ratios of 11,840, 6,864, and 5,524 population/case. The same thresholds using 2011-2015 census data would have detected 75%, 50%, and 25% of incident TB cases during 2016-2018 with population:incident TB ratios of 17,804, 10,807, and 7,031 population/case.</sec><sec><title>CONCLUSION</title>Census tract demographics are a simple and powerful tool to focus targeted testing and treatment of latent TB in areas likely to have incident TB disease.</sec>.

The International Journal of Tuberculosis and Lung DiseaseVol. 29(4)
Duke University (US), Atrium Medical Cente (US)
Openalex Percentile: Top 91%
Tuberculosis Research and Epidemiology
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Geographic information systems analysis to focus TB screening among people born in endemic countries — Silvio Zavala, Michael C Kiritsy, et al. · The International Journal of Tuberculosis and Lung Disease (2025) | TGRS Research Map | TGRS