1. Finding Hidden HIV Clusters to Support Geographic-Oriented HIV Interventions in Kenya
- Author
-
Muthama E, Mary Mwangi, Tom Oluoch, James L. Tobias, Ngʼangʼa J, Emily Zielinski-Gutierrez, Thorkild Tylleskär, Joyce Wamicwe, Anthony Waruru, and Achia Tno
- Subjects
Adult ,Male ,0301 basic medicine ,Adolescent ,Epidemiology ,Sexual Behavior ,Human immunodeficiency virus (HIV) ,Psychological intervention ,HIV Infections ,medicine.disease_cause ,Hiv risk ,Odds ,geographic differences ,Kulldorff spatial-scan statistics ,Young Adult ,03 medical and health sciences ,symbols.namesake ,0302 clinical medicine ,Risk Factors ,Prevalence ,medicine ,Cluster Analysis ,Humans ,Pharmacology (medical) ,030212 general & internal medicine ,Poisson regression ,Geography ,business.industry ,AIDS Serodiagnosis ,Odds ratio ,Middle Aged ,Kenya ,030112 virology ,Confidence interval ,Infectious Diseases ,Circumcision, Male ,symbols ,Lower prevalence ,HIV/AIDS ,Female ,business ,clustering ,Demography - Abstract
Background: In a spatially well known and dispersed HIV epidemic, identifying geographic clusters with significantly higher HIV prevalence is important for focusing interventions for people living with HIV (PLHIV). Methods: We used Kulldorff spatial-scan Poisson model to identify clusters with high numbers of HIV-infected persons 15–64 years old. We classified PLHIV as belonging to either higher prevalence or lower prevalence (HP/LP) clusters, then assessed distributions of sociodemographic and biobehavioral HIV risk factors and associations with clustering. Results: About half of survey locations, 112/238 (47%) had high rates of HIV (HP clusters), with 1.1–4.6 times greater PLHIV adults observed than expected. Richer persons compared with respondents in lowest wealth index had higher odds of belonging to a HP cluster, adjusted odds ratio (aOR) 1.61 [95% confidence interval (CI): 1.13 to 2.3], aOR 1.66 (95% CI: 1.09 to 2.53), aOR 3.2 (95% CI: 1.82 to 5.65), and aOR 2.28 (95% CI: 1.09 to 4.78) in second, middle, fourth, and highest quintiles, respectively. Respondents who perceived themselves to have greater HIV risk or were already HIV-infected had higher odds of belonging to a HP cluster, aOR 1.96 (95% CI: 1.13 to 3.4) and aOR 5.51 (95% CI: 2.42 to 12.55), respectively; compared with perceived low risk. Men who had ever been clients of female sex worker had higher odds of belonging to a HP cluster than those who had never been, aOR 1.47 (95% CI: 1.04 to 2.08); and uncircumcised men vs circumcised, aOR 3.2 (95% CI: 1.74 to 5.8). Conclusions: HIV infection in Kenya exhibits localized geographic clustering associated with sociodemographic and behavioral factors, suggesting disproportionate exposure to higher HIV risk. Identification of these clusters reveals the right places for targeting priority-tailored HIV interventions.
- Published
- 2018