Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo
Marina Antillon, Ching-I Huang, Samuel A. Sutherland, Ronald E. Crump, Paul E. Brown, Paul R. Bessell, Emily H. Crowley, Rian Snijders, Andrew Hope, Iñaki Tirados, Sophie Dunkley, Paul Verlé, Junior Lebuki, Chansy Shampa, Erick Mwamba Miaka, Fabrizio Tediosi, Kat S. RockBackground
Gambiense human African trypanosomiasis (gHAT) is marked for elimination of transmission (EoT) by 2030. We examined the cost-effectiveness (CE) of EoT in the Democratic Republic of Congo, the country with the highest burden.
Methods
In 165 health zones (HZs), we modelled the transmission dynamics, health outcomes, and economic costs of six strategies during 2026–40, including cessation activities once reported cases reach zero. Uncertainty in CE was assessed within the net monetary framework, presenting optimal strategies across willingness-to-pay (WTP) values, in costs per disability-adjusted life-year averted. We assessed the optimal strategy for CE and EoT in each health zone separately, but present results by health zone, by coordination, and for the whole country.
Results
Status Quo strategies, CE strategies (WTP = $500), and strategies that maximise the probability of EoT by 2030 are predicted to yield EoT by 2030 in 118 HZs, 123 HZs, and 134 HZs respectively, at a cost by 2040 of $67.8M [95% PI: $36.7M–113M], $93.3M [95% PI: $51.6M–153M], $185M [95% PI: $111M–309M]. A more lenient timeline of EoT by 2040 would lead to EoT in 152 HZs at a cost of $158M [95% PI: $91.6-265M], leaving 13 HZs shy of the goal. Costs would have to be front-loaded; in 2026, while Status Quo strategies would cost $8.75M [95% PI: $7.01M–11.2M], elimination strategies would cost $27.0 [95% PI: $21.0M–35.2M]. Investing in EoT by 2030 is predicted to reduce 68% of gHAT deaths from 7979 [95% PI: 770–27,868] with Status Quo strategies to 2576 [95% PI: 255–9133].
Conclusions
Current tools could make considerable progress to maximise the probability of EoT by 2030, but novel tools could help in select health zones that are facing a low probability of EoT even with more ambitious strategies.