Show simple item record

dc.contributor.authorShaw, Souradet Y
dc.contributor.authorReed, Neil
dc.contributor.authorWanjiru, Tabitha
dc.contributor.authorMuriuki, Festus
dc.contributor.authorMunyao, Julius
dc.contributor.authorAkolo, Maureen
dc.contributor.authorTago, Achieng
dc.contributor.authorGelmon, Lawrence
dc.contributor.authorKimani, Joshua
dc.contributor.authorMcKinnon, Lyle R
dc.date.accessioned2023-08-01T07:23:06Z
dc.date.available2023-08-01T07:23:06Z
dc.date.issued2023
dc.identifier.citationShaw SY, Reed N, Wanjiru T, Muriuki F, Munyao J, Akolo M, Tago A, Gelmon L, Kimani J, McKinnon LR. Geographical Associations of HIV Prevalence in Female Sex Workers From Nairobi, Kenya (2014-2017). J Acquir Immune Defic Syndr. 2023 Aug 15;93(5):364-373. doi: 10.1097/QAI.0000000000003219. PMID: 37229546.en_US
dc.identifier.urihttps://pubmed.ncbi.nlm.nih.gov/37229546/
dc.identifier.urihttp://erepository.uonbi.ac.ke/handle/11295/163739
dc.description.abstractBackground: Kenya's HIV epidemic is heterogeneously distributed. Although HIV incidence in Kenya has shown signs of recent decline, focused interventions are still needed for female sex workers (FSWs). Geospatially informed approaches have been advocated for targeted HIV prevention. We quantified heterogeneity in HIV burden in Nairobi-based FSWs by place of origin within Kenya and hotspots and residence within Nairobi. Methods: Data were collected as part of enrolment in the Sex Workers Outreach Program in Nairobi between 2014 and 2017. Prevalence ratios were used to quantify the risk of HIV by high-prevalence counties using modified Poisson regression analyses. Crude and fully adjusted models were fitted to the data. In heterogeneity analyses, hotspots and residences were aggregated to the Nairobi constituency level (n = 17). Inequality in the geographic distribution of HIV prevalence was measured using the Gini coefficient. Results: A total of 11,899 FSWs were included. Overall HIV prevalence was 16%. FSWs originating from a high-prevalence country were at 2-fold increased risk of living with HIV in adjusted analysis (prevalence ratio 1.95; 95% CI: 1.76 to 2.17). HIV prevalence was also highly heterogeneous by hotspot, ranging from 7% to 52% by hotspot (Gini coefficient: 0.37; 95% CI: 0.23 to 0.50). By contrast, the constituency of residence had a Gini coefficient of 0.08 (95% CI: 0.06 to 0.10), suggesting minimal heterogeneity by residence. Conclusion: HIV prevalence in FSWs is heterogeneous by place of work within Nairobi and by county of birth within Kenya. As HIV incidence declines and financial commitments flatline, tailoring interventions to FSWs at highest HIV risk becomes increasingly important.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleGeographical Associations of HIV Prevalence in Female Sex Workers From Nairobi, Kenya (2014-2017)en_US
dc.typeArticleen_US


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States