dc.contributor.author |
Peterson, Meaghan L.
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|
dc.contributor.author |
Gandhi, Neel R.
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|
dc.contributor.author |
Clennon, Julie
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|
dc.contributor.author |
Nelson, Kristin N.
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dc.contributor.author |
Morris, Natashia
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dc.contributor.author |
Ismail, Nazir Ahmed
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dc.contributor.author |
Allana, Salim
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dc.contributor.author |
Campbell, Angie
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dc.contributor.author |
Brust, James C.M.
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dc.contributor.author |
Auld, Sara C.
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dc.contributor.author |
Mathema, Barun
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dc.contributor.author |
Mlisana, Koleka
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dc.contributor.author |
Moodley, Pravi
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dc.contributor.author |
Shah, N. Sarita
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dc.date.accessioned |
2020-03-10T08:07:35Z |
|
dc.date.available |
2020-03-10T08:07:35Z |
|
dc.date.issued |
2019-06 |
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dc.description.abstract |
BACKGROUND : Extensively drug-resistant tuberculosis (XDR-TB) incidence is driven by transmission of resistant strains in KwaZulu-Natal, South Africa. Data suggests cases may be spatially clustered; we therefore sought to identify hotspots and describe these communities.
METHODS : We enrolled XDR-TB patients diagnosed from 2011–2014 in eThekwini. GPS coordinates for participant homes were collected and hotspots were identified based on population-adjusted XDR-TB incidence. Sociodemographic features of hotspots were characterized using census data. For a subset of participants, we mapped XDR-TB case non-home congregate locations and compared to results including only homes.
RESULTS : Among 132 participants, 75 (57%) were female and 87 (66%) lived in urban or suburban locations. Fifteen of 197 census tracts were identified as XDR-TB hotspots with ≥ 95% confidence. Four spatial mapping methods identified one large hotspot in northeastern eThekwini. Hotspot communities had higher percentages of low educational attainment (12% vs 9%), higher unemployment (29.3% vs 20.4%), and lower percentage of homes with flush toilets (36.4% vs 68.9%). Mapping congregate locations, including workplaces, for 43 (33%) participants shifted case density towards Durban.
CONCLUSIONS : In eThekwini, XDR-TB case homes were clustered into hotspots with more indicators of poverty than non-hotspots. Prevention efforts targeting hotspot communities and congregate settings may be effective in reducing community transmission. |
en_ZA |
dc.description.department |
Medical Microbiology |
en_ZA |
dc.description.librarian |
hj2020 |
en_ZA |
dc.description.sponsorship |
A grant from the US National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH): R01AI089349 (PI Gandhi) and R01AI087465 (PI Gandhi). It was also supported in part by NIH/NIAID grants: K23AI083088 (PI Brust), K23AI134182 (PI Auld), K24AI114444 (PI Gandhi), R01AI138646 (PI Gandhi), Emory CFAR P30AI050409 (PI Curran), Einstein CFAR P30AI124414 (PI Goldstein), by Einstein/Montefiore ICTR UL1 TR001073 (PI Shamoon), and by NIH/NHLBI T32 HL116271 (PI Guidot). |
en_ZA |
dc.description.uri |
https://www.ingentaconnect.com/content/iuatld/ijtld |
en_ZA |
dc.identifier.citation |
Peterson, M.L., Gandhi, N.R., Clennon, J. et al. 2019, 'Extensively drug-resistant tuberculosis hotspots and sociodemographic associations in Durban, South Africa', International Journal of Tuberculosis and Lung Disease. vol. 23, no. 6, pp. 720–727. doi: 10.5588/ijtld.18.0575. |
en_ZA |
dc.identifier.issn |
1027-3719 (print) |
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dc.identifier.issn |
1815-7920 (online) |
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dc.identifier.other |
10.5588/ijtld.18.0575 |
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dc.identifier.uri |
http://hdl.handle.net/2263/73697 |
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dc.language.iso |
en |
en_ZA |
dc.publisher |
International Union Against Tuberculosis and Lung Disease |
en_ZA |
dc.rights |
International Union Against Tuberculosis and Lung Disease |
en_ZA |
dc.subject |
Tuberculosis (TB) |
en_ZA |
dc.subject |
Extensively drug-resistant tuberculosis (XDR-TB) |
en_ZA |
dc.subject |
Activity space |
en_ZA |
dc.subject |
Sociodemographic |
en_ZA |
dc.subject |
Hotspot |
en_ZA |
dc.subject |
South Africa (SA) |
en_ZA |
dc.title |
Extensively drug-resistant tuberculosis hotspots and sociodemographic associations in Durban, South Africa |
en_ZA |
dc.type |
Postprint Article |
en_ZA |