Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo
10 affiliations
- 1Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Basel-Land, Switzerland
- 2University of Basel, Basel-Stadt, Switzerland
- 3Zeeman Institute, University of Warwick, Coventry, United Kingdom
- 4Mathematics Institute, University of Warwick, Coventry, United Kingdom
- 5Warwick Medical School, University of Warwick, Coventry, United Kingdom
- 6Warwick Centre for Global Health, University of Warwick, Coventry, United Kingdom
- 7Independent Consultant, Edinburgh, United Kingdom
- 8Institute of Tropical Medicine, Antwerp, Belgium
- 9Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- 10Programme National de Lutte contre la Trypanosomiase Humaine Africaine, Kinshasa, Democratic Republic of Congo
Abstract
Background: 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. Author summary: The Democratic Republic of Congo bears the world’s heaviest burden of sleeping sickness. Control and elimination efforts have driven reported cases down from a peak of 26,318 in 1998 to 330 in 2024. Yet it remains unclear whether current tools can achieve elimination, and at what cost. We conducted a cost-effectiveness analysis using a dynamic transmission model calibrated on 2000–2020 epidemiological data, paired with a cost model. Under current strategies, we project that 118 of 165 health zones will reach elimination of transmission (EoT) by 2030 at a cost of $67.8M. Switching to strategies more likely to achieve EoT by 2030 would help 16 additional health zones reach the goal, avert 7,754 deaths, and reduce reported cases by 701 for an additional $117M by 2040. Extending the timeline to 2040 would still leave 13 health zones short of elimination, saving only $27M. Across investment levels, screening activities absorb the largest share of costs, concentrated in Isangi, Kasaï Oriental, and Maniema-Katanga. Our outputs can be used by the national programme and its partners for strategy planning in the next decade and a half of operations. The analysis indicates that novel tools may be needed to reach elimination in all health zones.
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BibTeX
@article{antillon2026costeffectiveness,
title = {{Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo}},
author = {Marina Antillon and Ching-I Huang and Samuel A. Sutherland and Ronald E. Crump and Paul E. Brown and Paul R. Bessell and Emily H. Crowley and Rian Snijders and Andrew Hope and Iñaki Tirados and Sophie Dunkley and Paul Verlé and Junior Lebuki and Chansy Shampa and Erick Mwamba Miaka and Fabrizio Tediosi and Kat S. Rock},
journal = {PLOS Neglected Tropical Diseases},
year = {2026},
month = oct,
doi = {10.1371/journal.pntd.0014777},
url = {https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0014777},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo
AU - Marina Antillon
AU - Ching-I Huang
AU - Samuel A. Sutherland
AU - Ronald E. Crump
AU - Paul E. Brown
AU - Paul R. Bessell
AU - Emily H. Crowley
AU - Rian Snijders
AU - Andrew Hope
AU - Iñaki Tirados
AU - Sophie Dunkley
AU - Paul Verlé
AU - Junior Lebuki
AU - Chansy Shampa
AU - Erick Mwamba Miaka
AU - Fabrizio Tediosi
AU - Kat S. Rock
PY - 2026
DA - 2026/10/22
JO - PLOS Neglected Tropical Diseases
DO - 10.1371/journal.pntd.0014777
UR - https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0014777
AB - Background: 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. Author summary: The Democratic Republic of Congo bears the world’s heaviest burden of sleeping sickness. Control and elimination efforts have driven reported cases down from a peak of 26,318 in 1998 to 330 in 2024. Yet it remains unclear whether current tools can achieve elimination, and at what cost. We conducted a cost-effectiveness analysis using a dynamic transmission model calibrated on 2000–2020 epidemiological data, paired with a cost model. Under current strategies, we project that 118 of 165 health zones will reach elimination of transmission (EoT) by 2030 at a cost of $67.8M. Switching to strategies more likely to achieve EoT by 2030 would help 16 additional health zones reach the goal, avert 7,754 deaths, and reduce reported cases by 701 for an additional $117M by 2040. Extending the timeline to 2040 would still leave 13 health zones short of elimination, saving only $27M. Across investment levels, screening activities absorb the largest share of costs, concentrated in Isangi, Kasaï Oriental, and Maniema-Katanga. Our outputs can be used by the national programme and its partners for strategy planning in the next decade and a half of operations. The analysis indicates that novel tools may be needed to reach elimination in all health zones.
SN - 1935-2735
SN - 1935-2727
ER -