Moving away from the "unit cost". Predicting country-specific average cost curves of VMMC services accounting for variations in service delivery platforms in sub-Saharan Africa.

BACKGROUND: One critical element to optimize funding decisions involves the cost and efficiency implications of implementing alternative program components and configurations. Program planners, policy makers and funders alike are in need of relevant, strategic data and analyses to help them plan and implement effective and efficient programs. Contrary to widely accepted conceptions in both policy and academic arenas, average costs per service (so-called "unit costs") vary considerably across implementation settings and facilities. The objective of this work is twofold: 1) to estimate the variation of VMMC unit costs across service delivery platforms (SDP) in Sub-Saharan countries, and 2) to develop and validate a strategy to extrapolate unit costs to settings for which no data exists. METHODS: We identified high-quality VMMC cost studies through a literature review. Authors were contacted to request the facility-level datasets (primary data) underlying their results. We standardized the disparate datasets into an aggregated database which included 228 facilities in eight countries. We estimated multivariate models to assess the correlation between VMMC unit costs and scale, while simultaneously accounting for the influence of the SDP (which we defined as all possible combinations of type of facility, ownership, urbanicity, and country), on the unit cost variation. We defined SDP as any combination of such four characteristics. Finally, we extrapolated VMMC unit costs for all SDPs in 13 countries, including those not contained in our dataset. RESULTS: The average unit cost was 73 USD (IQR: 28.3, 100.7). South Africa showed the highest within-country cost variation, as well as the highest mean unit cost (135 USD). Uganda and Namibia had minimal within-country cost variation, and Uganda had the lowest mean VMMC unit cost (22 USD). Our results showed evidence consistent with economies of scale. Private ownership and Hospitals were significant determinants of higher unit costs. By identifying key cost drivers, including country- and facility-level characteristics, as well as the effects of scale we developed econometric models to estimate unit cost curves for VMMC services in a variety of clinical and geographical settings. CONCLUSION: While our study did not produce new empirical data, our results did increase by a tenfold the availability of unit costs estimates for 128 SDPs in 14 priority countries for VMMC. It is to our knowledge, the most comprehensive analysis of VMMC unit costs to date. Furthermore, we provide a proof of concept of the ability to generate predictive cost estimates for settings where empirical data does not exist.

Meta-analysis of average costs of HIV testing and counselling and voluntary medical male circumcision across thirteen countries.

Objective: Explore facility-level average costs per client of HIV testing and counselling (HTC) and voluntary medical male circumcision (VMMC) services in 13 countries.Methods: Through a literature search we identified studies that reported facility-level costs of HTC or VMMC programmes. We requested the primary data from authors and standardised the disparate data sources to make them comparable. We then conducted descriptive statistics and a meta-analysis to assess the cost variation among facilities. All costs were converted to 2017 US dollars ($).Results: We gathered data from 14 studies across 13 countries and 772 facilities (552 HTC, 220 VMMC). The weighted average unit cost per client served was $15 (95% CI 12, 18) for HTC and $59 (95% CI 45, 74) for VMMC. On average, 38% of the mean unit cost for HTC corresponded to recurrent costs, 56% to personnel costs, and 6% to capital costs. For VMMC, 41% of the average unit cost corresponded to recurrent costs, 55% to personnel costs, and 4% to capital costs. We observed unit cost variation within and between countries, and lower costs in higher scale categories in all interventions.