Feasibility, effectiveness, budget impact and surveillance of partner services for HIV in Kenya
Cherutich, Peter K.
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Abstract Introduction: HIV assisted partner services (aPS), is widely practiced in the United States and Europe but less so in Africa largely due to limited data on their effectiveness and feasibility in routine health care settings. Yet aPS could increase HIV testing rates, reduce STI/HIV exposure, and assure prompt linkage to antiretroviral therapy (ART) initiation. We report the effect of immediate aPS in improving 1) the rate of HIV testing, 2) case-finding of HIV-infected individuals, and 3) linkages to HIV care for their partners. The trial determined the number needed to interview to identify one new case of HIV and explored, geographical differences in case finding rates. Additionally we assess the budget impact of scaling up aPS in Kisumu County, the region with the third highest number of HIV-infected persons in Kenya. We also present results of the pilot of a surveillance system for aPS. Methods: A cluster-randomized design was used to recruit eligible HIV-infected index cases from 18 clusters allocated to two study arms, immediate and delayed. The intervention was elicitation of sexual history from index cases and enumeration of sexual partners of HIV infected index cases in the preceding three years, notification, testing and referral to care if HIV-infected, of the named sexual partners. Participants in the delayed arm received a similar service only that this was delivered six weeks later. We used generalized estimating equations to evaluate the effect of the intervention on rates of HIV testing, identification of new HIV tests, HIV infections and enrollment to HIV care. The number of index cases needed to interview and the case finding rates were also evaluated using a similar approach. The study was registered in ClinicalTrials.gov as number NCT01616420. To estimate the budget impact, we constructed an Excel-based costing tool to simulate the budget impact analysis of HIV partner services on an annual basis over a 5 year time horizon. HIV Testing and Counseling (HTC) and aPS unit and total costs were estimated and allocated using ingredient-based approaches. Time motion was used to determine full-time equivalent of tracing sexual partners of index patients. Weighted costs of ART, clinic visits and hospitalizations that accrued due to aPS were generated through decision tree modeling. We estimated a range, where the lower-bound cost assumed that all sexual partners tested were HIV-negative and the upper-bound cost assumed that all sexual partners were HIV-positive. All costs were undiscounted and reported separately for the task-shifting scenarios. Appendix I outlines the assumptions regarding the patient workload and the number of providers available to do aPS in Kisumu County. Appendices II & III are the assumptions for calculating HIV testing costs and budget impact respectively. Appendix IV is the decision trees for determining expected costs for antiretroviral therapy, clinic visits and hospitalization visits. For the pilot of the surveillance system, we revised the national HTC data collection tool to include specific questions on whether clients testing for HIV were doing so due to an exposure from an HIV-infected partner. Results: The study enrolled 1119 index cases from 18 different clusters (550 in the intervention arm and 569 in the control arm) who mentioned 1872 sexual partners. Of the sexual partners, 1292 (69%), [620 in the intervention arm and 672 in the control arm] were enrolled. Enrollment and follow-up data were available for 579 (63%) of sexual partners mentioned in the immediate arm and enrollment data available for 672 (70%) in the delayed arm. 388 in the immediate arm during enrolment and within the study after enrollment, and 118 in the delayed arm in the preceding two months before enrollment (Incidence Rate Ratio (IRR) 3.78, 95% CI: 3.08-4.65). The incidence rate ratio comparing rates of new testing for HIV between the immediate and delayed groups was 11.50 (95% CI: 5.56-23.78). Immediate aPS also increased the number testing positive and those enrolled in HIV care, IRR 3.22 (95% CI: 2.26-4.61) and 3.95 (95% CI: 2.48-6.28) respectively. The number of index cases needed to interview (NNTI) to identify an HIV infection in the partners was 4.08, and that to identify a newly testing partner was 3.34. No study-related intimate partner violence was reported. The average annual aPS costs are US$ 1,092,161 and US$ 753,547 for Kisumu County using nurses and CHWs, respectively. The weighted average cost of scaling up aPS over a five period using nurses was 45% higher compared to CHWs (US$ 5,460,837 and US$ 3,767,738 respectively). Overall, the differences between the upper and lower bound costs were 8.7% for nurse-based aPS and 2.5% for the CHW-based approach. Over the time horizon, the total budget impact of nurse-model was US$ 1,726,832, 69.2% and 29.5% of which were accounted for by aPS costs and ART costs respectively. The CHW model incurred an incremental cost of US$ 1,184,640, 68.6% lower than the nurse-based model. Proportional distribution of impact across budget categories was similar in the two models, although CHWs model had lower aPS related impact The weighted unit costs of HIV testing across the three levels of facilities for HIV-infected index clients using nurses were US$ 25.36 and US$ 17.86 using CHWs. Costs for testing sexual partners of infected index clients were higher overall, with an HIV test costing US$ 19.18 per person if all tests were negative and US$31.07 per person if all tests were positive for nurses and US$ 11.74 per person and US$ 14.14 per person for CHWS respectively. Median time for data capture using the HTC form was 4 minutes (IQR: 3-15), with a longer duration for HIV-infected participants, and there was no reported data loss. Interpretation: aPS is safe, effective and feasible at the population level and should be implemented as part of HIV Testing and Counseling (HTC delivery). In addition to early ART initiation, aPS may have considerable effect on HIV transmission at the population level. Furthermore, aPS is affordable although not cost-saving and routine Health Information Systems (HIS) may be used to monitor aPS outcomes.
- Global health