@article{article, keywords = {Schistosomiasis , arpraziquantel, Pre-school age children, Early economic evaluation, Economic model}, author = {Chua B and Chaowanasawat P and Tsui T and Teerawattananon Y and Mwing{\textquoteright}a G and Omolo J and Kazyoba P}, title = {Cost-benefit analysis of arpraziquantel compared to standard of care for schistosomiasis among pre-school age children in Tanzania: an early health economic evaluation}, abstract = {

Background

Pre-school age children (pre-SAC) have been excluded from schistosomiasis mass drug administration (MDA) programs, as suitable pediatric formulations were lacking. Arpraziquantel, a newly approved oral dispersible tablet, addresses this gap. We conducted an early economic evaluation to assess the potential value of arpraziquantel in Tanzania, informing implementation research and evidence generation priorities.

Methods

Following the cost-benefit analysis (CBA) reference case, we conducted a CBA from the societal perspective using a Markov model, simulating a cohort of Tanzanian 2-year-olds over 3-year and 12-year horizons. Potential future wage gains were assessed with a lifetime horizon. Two arpraziquantel strategies were compared against standard of care (no treatment): MDA, and test-and-treat (T\&T). Disability-adjusted life years (DALYs) averted, averted healthcare and caregiver costs, and wage gains were monetized. Results were summarized as net benefit (NB) and benefit-cost ratio (BCR). Probabilistic, threshold, scenario and value-of-information analyses were performed.

Findings

Over three years, for approximately 57,000 pre-SAC, the estimated NB of MDA was $522,289 (BCR: 2.10); T\&T yielded $227 (BCR: 1.00). Over 12 years, projected NB was higher for MDA ($1,119,330) and T\&T ($378,953). Both MDA and T\&T estimated positive NB when potential future wages were considered. In probabilistic analysis, MDA estimated positive NB in \>86\% of simulations, but T\&T estimated net losses in 50\% of simulations over 3 years. Arpraziquantel cost drove decision uncertainty.

}, year = {2026}, journal = {The Lancet Regional Health - Africa}, pages = {1 - 14}, month = {10/2026}, publisher = {Elsevier BV}, issn = {3050-5011}, url = {https://www.thelancet.com/action/showPdf?pii=S3050-5011\%2826\%2900155-0}, doi = {10.1016/j.lanafr.2026.100174}, language = {ENG}, }