TY - JOUR
T1 - Modelling costs of community-based HIV self-testing programmes in Southern Africa at scale: An econometric cost function analysis across five countries: An econometric cost function analysis across five countries
AU - D'Elbée, Marc
AU - Gomez, Gabriela B.
AU - Sande, Linda Alinafe
AU - Mwenge, Lawrence
AU - Mangenah, Collin
AU - Johnson, Cheryl
AU - Medley, Graham F.
AU - Neuman, Melissa
AU - Hatzold, Karin
AU - Corbett, Elizabeth Lucy
AU - Meyer-Rath, Gesine
AU - Terris-Prestholt, Fern
PY - 2021/7/18
Y1 - 2021/7/18
N2 - Background Following success demonstrated with the HIV Self-Testing AfRica Initiative, HIV self-testing (HIVST) is being added to national HIV testing strategies in Southern Africa. An analysis of the costs of scaling up HIVST is needed to inform national plans, but there is a dearth of evidence on methods for forecasting costs at scale from pilot projects. Econometric cost functions (ECFs) apply statistical inference to predict costs; however, we often do not have the luxury of collecting large amounts of location-specific data. We fit an ECF to identify key drivers of costs, then use a simpler model to guide cost projections at scale. Methods We estimated the full economic costs of community-based HIVST distribution in 92 locales across Malawi, Zambia, Zimbabwe, South Africa and Lesotho between June 2016 and June 2019. We fitted a cost function with determinants related to scale, locales organisational and environmental characteristics, target populations, and per capita Growth Domestic Product (GDP). We used models differing in data intensity to predict costs at scale. We compared predicted estimates with scale-up costs in Lesotho observed over a 2-year period. Results The scale of distribution, type of community-based intervention, percentage of kits distributed to men, distance from implementer's warehouse and per capita GDP predicted average costs per HIVST kit distributed. Our model simplification approach showed that a parsimonious model could predict costs without losing accuracy. Overall, ECF showed a good predictive capacity, that is, forecast costs were close to observed costs. However, at larger scale, variations of programme efficiency over time (number of kits distributed per agent monthly) could potentially influence cost predictions. Discussion Our empirical cost function can inform community-based HIVST scale-up in Southern African countries. Our findings suggest that a parsimonious ECF can be used to forecast costs at scale in the context of financial planning and budgeting.
AB - Background Following success demonstrated with the HIV Self-Testing AfRica Initiative, HIV self-testing (HIVST) is being added to national HIV testing strategies in Southern Africa. An analysis of the costs of scaling up HIVST is needed to inform national plans, but there is a dearth of evidence on methods for forecasting costs at scale from pilot projects. Econometric cost functions (ECFs) apply statistical inference to predict costs; however, we often do not have the luxury of collecting large amounts of location-specific data. We fit an ECF to identify key drivers of costs, then use a simpler model to guide cost projections at scale. Methods We estimated the full economic costs of community-based HIVST distribution in 92 locales across Malawi, Zambia, Zimbabwe, South Africa and Lesotho between June 2016 and June 2019. We fitted a cost function with determinants related to scale, locales organisational and environmental characteristics, target populations, and per capita Growth Domestic Product (GDP). We used models differing in data intensity to predict costs at scale. We compared predicted estimates with scale-up costs in Lesotho observed over a 2-year period. Results The scale of distribution, type of community-based intervention, percentage of kits distributed to men, distance from implementer's warehouse and per capita GDP predicted average costs per HIVST kit distributed. Our model simplification approach showed that a parsimonious model could predict costs without losing accuracy. Overall, ECF showed a good predictive capacity, that is, forecast costs were close to observed costs. However, at larger scale, variations of programme efficiency over time (number of kits distributed per agent monthly) could potentially influence cost predictions. Discussion Our empirical cost function can inform community-based HIVST scale-up in Southern African countries. Our findings suggest that a parsimonious ECF can be used to forecast costs at scale in the context of financial planning and budgeting.
KW - health economics
KW - health services research
KW - HIV
U2 - 10.1136/bmjgh-2021-005554
DO - 10.1136/bmjgh-2021-005554
M3 - Article
VL - 6
JO - BMJ Global Health
JF - BMJ Global Health
M1 - e005554
ER -