Cost and cost-effectiveness of nationwide school-based helminth control in Uganda: intra-country variation and effects of scaling-up.
Brooker, Simon;
Kabatereine, Narcis B;
Fleming, Fiona;
Devlin, Nancy;
(2007)
Cost and cost-effectiveness of nationwide school-based helminth control in Uganda: intra-country variation and effects of scaling-up.
Health policy and planning, 23 (1).
pp. 24-35.
ISSN 0268-1080
DOI: https://doi.org/10.1093/heapol/czm041
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Estimates of cost and cost-effectiveness are typically based on a limited number of small-scale studies with no investigation of the existence of economies to scale or intra-country variation in cost and cost-effectiveness. This information gap hinders the efficient allocation of health care resources and the ability to generalize estimates to other settings. The current study investigates the intra-country variation in the cost and cost-effectiveness of nationwide school-based treatment of helminth (worm) infection in Uganda. Programme cost data were collected through semi-structured interviews with district officials and from accounting records in six of the 23 intervention districts. Both financial and economic costs were assessed. Costs were estimated on the basis of cost in US$ per schoolchild treated, and an incremental cost-effectiveness ratio (cost in US$ per case of anaemia averted) was used to evaluate programme cost-effectiveness. Sensitivity analysis was performed to assess the effect of discount rate and drug price. The overall economic cost per child treated in the six districts was US$0.54 and the cost-effectiveness was US$3.19 per case of anaemia averted. Analysis indicated that estimates of both cost and cost-effectiveness differ markedly with the total number of children who received treatment, indicating economies of scale. There was also substantial variation between districts in the cost per individual treated (US$0.41-0.91) and cost per anaemia case averted (US$1.70-9.51). Independent variables were shown to be statistically associated with both sets of estimates. This study highlights the potential bias in transferring data across settings without understanding the nature of observed variations.