Cost-effectiveness of facility-based, stand-alone and mobile-based voluntary counseling and testing for HIV in Addis Ababa, Ethiopia

Amanuel Yigezu; Senait Alemayehu; Shallo Daba Hamusse; Getachew Teshome Ergeta; Damen Hailemariam; Alemayehu Hailu

doi:10.1186/s12962-020-00231-x

Cost-effectiveness of facility-based, stand-alone and mobile-based voluntary counseling and testing for HIV in Addis Ababa, Ethiopia

Cost Eff Resour Alloc. 2020 Sep 11:18:34. doi: 10.1186/s12962-020-00231-x. eCollection 2020.

Authors

Amanuel Yigezu^{1

2}, Senait Alemayehu², Shallo Daba Hamusse³, Getachew Teshome Ergeta⁴, Damen Hailemariam¹, Alemayehu Hailu^{1

4}

Affiliations

¹ School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia.
² Ethiopian Public Health Institute, Addis Ababa, Ethiopia.
³ Federal Ministry of Health, Grand Challenge Ethiopia, Addis Ababa, Ethiopia.
⁴ Bergen Center for Ethics and Priority Setting, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.

Abstract

Background: Globally, there is a consensus to end the HIV/AIDS epidemic by 2030, and one of the strategies to achieve this target is that 90% of people living with HIV should know their HIV status. Even if there is strong evidence of clients' preference for testing in the community, HIV voluntary counseling and testing (VCT) continue to be undertaken predominantly in health facilities. Hence, empirical cost-effectiveness evidence about different HIV counseling and testing models is essential to inform whether such community-based testing are justifiable compared with additional resources required. Therefore, the purpose of this study was to compare the cost-effectiveness of facility-based, stand-alone and mobile-based HIV voluntary counseling and testing methods in Addis Ababa, Ethiopia.

Methods: Annual economic costs of counseling and testing methods were collected from the providers' perspective from July 2016 to June 2017. Ingredients based bottom-up costing approach was applied. The effectiveness of the interventions was measured in terms of the number of HIV seropositive clients identified. Decision tree modeling was built using TreeAge Pro 2018 software, and one-way and probabilistic sensitivity analyses were conducted by varying HIV positivity rate, costs, and probabilities.

Results: The cost of test per client for facility-based, stand-alone and mobile-based VCT was $5.06, $6.55 and $3.35, respectively. The unit costs of test per HIV seropositive client for the corresponding models were $158.82, $150.97 and $135.82, respectively. Of the three models, stand-alone-based VCT was extendedly dominated. Mobile-based VCT costs, an additional cost of USD 239 for every HIV positive client identified when compared to facility-based VCT.

Conclusion: Using a mobile-based VCT approach costs less than both the facility-based and stand-alone approaches, in terms of both unit cost per tested individual and unit cost per HIV seropositive cases identified. The stand-alone VCT approach was not cost-effective compared to facility-based and mobile-based VCT. The incremental cost-effectiveness ratio for mobile-based VCT compared with facility-based VCT was USD 239 per HIV positive case.

Keywords: Cost-effectiveness analysis; Decision tree modeling; Ingredients costing; Reciprocal cost allocation; VCT models.