The study modelled transmission dynamics, health outcomes and economic costs across 165 health zones for the period 2026 to 2040. Six strategies were compared, including continued status quo control and more ambitious elimination strategies that cease activities once reported cases reach zero. Uncertainty was assessed within a net monetary framework, expressing outcomes as costs per disability-adjusted life-year averted and identifying optimal strategies across different willingness-to-pay values for each health zone and for the country as a whole.

The results show a steep trade-off between cost and speed. Status quo strategies, cost-effective strategies at a willingness-to-pay of 500 dollars, and strategies prioritising a high probability of elimination by 2030 are predicted to achieve elimination of transmission by 2030 in 118, 123 and 134 health zones respectively. By 2040, these approaches would cost 67.8 million dollars, 93.3 million dollars and 185 million dollars, with prediction intervals spanning 36.7 to 113 million, 51.6 to 153 million and 111 to 309 million dollars.

Relaxing the timeline shifts the picture considerably. A more lenient target of elimination by 2040 would bring elimination to 152 health zones at a predicted cost of 158 million dollars, leaving 13 health zones short of the goal even then.

The timing of spending matters as much as the total. In 2026 alone, status quo strategies would cost 8.75 million dollars, with a prediction interval of 7.01 to 11.2 million, whereas elimination strategies would require 27.0 million dollars, ranging from 21.0 to 35.2 million. Investment in the 2030 goal therefore has to be front-loaded, concentrating resources early in the period covered by the model.

The health gains of acting early are substantial. Pursuing elimination by 2030 is predicted to reduce gHAT deaths by 68 percent compared with continuing current strategies. Under the status quo, the model projects 7,979 deaths, with a wide prediction interval of 770 to 27,868, while the elimination strategy reduces this to 2,576 deaths, with a prediction interval of 255 to 9,133.

The analysis assessed the optimal strategy separately for each health zone, weighing where intensified efforts pay off and where moderate approaches suffice. The authors present findings by health zone, by coordination level and nationally, allowing planners to see which strategies are predicted to perform best in different parts of the country.

Overall, the study supports the conclusion that existing diagnostic and treatment tools could make considerable progress toward the 2030 elimination target across much of the DRC. However, in select health zones facing a low probability of elimination even under the most ambitious strategies, the models suggest novel tools would help close the remaining gap. As with any modelling projection, the results are presented as ranges with stated prediction intervals rather than precise forecasts.

Subject of Research: Cost-effectiveness modelling of elimination strategies for Gambiense human African trypanosomiasis in the Democratic Republic of Congo

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

Article References: Antillon, M., Huang, C.-I., Sutherland, S. A., Crump, R. E., Brown, P. E., Bessell, P. R., Crowley, E. H., Snijders, R., Hope, A., Tirados, I., Dunkley, S., Verle, P., Lebuki, J., Shampa, C., Miaka, E. M., Tediosi, F., & Rock, K. S. (2026). Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo. PLOS Neglected Tropical Diseases, 20(10), e0014777. https://doi.org/10.1371/journal.pntd.0014777

Image Credits: AI Generated

DOI: 10.1371/journal.pntd.0014777

Keywords: sleeping sickness, gHAT, elimination of transmission, cost-effectiveness, Democratic Republic of Congo, mathematical modelling, DALYs averted, willingness to pay, neglected tropical diseases, health economics, end-game strategies, end-game