Back

Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo

Antillon, M.; Huang, C.-I.; Sutherland, S. A.; Crump, R. E.; Brown, P. E.; Bessel, P. R.; Crowley, E. H.; Snijders, R.; Hope, A.; Tirados, I.; Dunkley, S.; Verle, P.; Lebuki, J.; Shampa, C.; Mwamba Miaka, E.; Tediosi, F.; Rock, K. S.

2024-03-30 health economics Community evaluation
10.1101/2024.03.29.24305066 medRxiv
Show abstract

BackgroundGambiense 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, which has the highest global gHAT burden. MethodsIn 165 health zones (HZs), we modelled the transmission dynamics, health outcomes, and economic costs of six strategies during 2026-40, including the cessation of activities after cases reported reach zero. Uncertainty in CE was assessed within the net monetary framework, which presents the optimal strategies at a range of willingness- to-pay (WTP) values, denominated in costs per disability-adjusted life-year averted. We assessed the optimal strategy for CE and EoT in each health zone separately, but we present results by health zone as well as aggregated by coordination and for the whole country. ResultsStatus quo strategies, CE strategies (WTP=$500), and strategies with a high 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 could 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]. ConclusionsThe current arsenal of tools could make considerable progress to maximise the probability of EoT by 2030, but select health zones are facing a low probability of EoT even with more ambitious strategies. Investments need to be front-loaded, but we would witness considerable returns on investment by 2040.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.