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Health economics/ Économie de la santé

The Cost of Elimination for the Democratic Republic of the Congo

In collaboration with the DRC sleeping sickness control program and their partners, this study evaluated several potential intervention strategies at the health-zone level, focusing on cost-effectiveness in terms of disease burden (DALYsLink opens in a new window) and enhancing the likelihood of eliminating transmission (EoTLink opens in a new window) by 2030.

The findings indicate that Kongo Central and Équateur Nord coordinations have a promising outlook under current (Status Quo) strategies with others requiring adjustments to optimise outcomes. A total of 95 health zones are highlighted as requiring a shift in strategies to boost the likelihood of EoT by 2030. Among these, 48 face the additional challenge that even the strategy maximising EoT falls short of a 90% probability by 2030 as indicated by hatched health zones in the map opposite.

Based on existing strategies (Status Quo),117 out of 166 health zones are on track to achieve EoT by 2030. This endeavour comes with a projected cost of $159M and an accumulation of an estimated 765K DALYsLink opens in a new window over a 16-year time horizon. Introducing new interventions aimed at reaching EoT with greater than 90% probability, we anticipate that 21 more health zones could reach EoT requiring only $47M of additional investment. This move could prevent 561K DALYsLink opens in a new window. Despite this being a relatively small investment, it's crucial to highlight that nearly one-fifth of this ($9M) would be required in the first year of switching strategies and would require a huge operational undertaking.

Explore all the results of the Whole DRC cost-effectiveness analysis in our graphical user interfaceLink opens in a new window.

Antillon M, Huang C, Sutherland SA, Crump RE, Brown PE, Bessell PR, Crowley EH, Snijders R, Hope A, Tirados I, Dunkley S, Verlé P, Lebuki J, Shampa C, Miaka EM, Tediosi F, Rock KS (2024) Cost-effectiveness of end-game strategies against sleeping sickness across the Democratic Republic of Congo Link opens in a new windowMedRXiV (not yet peer-reviewed) Paper summaries: English Link opens in a new windowFrenchLink opens in a new window 

Health Economics in Mandoul

PNLTHA-Chad and their partners made substantial changes to their gHAT interventions in Mandoul from 2014 including improved screening in health facilities and the use of vector control. In our most recent article we explore whether these past interventions were an effective use of resources and what the health economic implications would have been had less ambitious strategies been performed. Improvements rolled out for active and passive screening from 2015 have paved the way for more rapid diagnosis and accessible treatment. However, including vector control as part of the strategy from 2014 has been shown to be good value-for-money and substantially increased the probability of reaching the target of elimination of transmission (EoTLink opens in a new window) in Mandoul. While investment in vector control was computed to be cost-saving, the investment in improved passive screening was cost-effective at a willingness-to-pay (WTPLink opens in a new window) of $747/disability-adjusted-life year (DALYLink opens in a new window) averted. At $500/DALYLink opens in a new window averted, there is 37% probability that the implemented strategy (Improved passive screening & vector control) was optimal, while at a WTPLink opens in a new window of $1000/DALYLink opens in a new window averted, the probability that the implemented strategy was optimal is 60% (see figure).

The paper also considers future strategies and concludes that the scaleback of vertical interventions appears cost-effective if passive screening remains robust in Mandoul and that any strategies with interventions other than basic continuation of passive screening are not cost-effective. The analysis also showed that imperfect test specificity in active screening (see strategy Mean AS & VC (spec = 99.93%)) is very likely to incur some direct costs in over-treatment, but that these costs would be overshadowed by the inability to confidently stop vertical activities. If vector control and active screening continue until no more parasitologically positive cases are detected, costs are predicted to be at most $676,000 for the period of 2021–2040. This could enable the shifting of resources to tackle other extant foci in Chad (Maro and Moissala).

Explore the results from the Mandoul cost-effectiveness analysis through our graphical-user interface.

Click here Link opens in a new windowto view our infographic

Peer-reviewed paper: Antillon M, Huang C, Sutherland S, Crump RE, Bessell PR, Shaw APM, Tirados I, Picado A, Biéler S, Brown PE, Solano P, Mbainda S, Darnas J, Wang-Steverding XW, Crowley EH, Mallaye P, Tedioso F, Rock KS (2023). Health economic evaluation of strategies to eliminate gambiense human African trypanosomiasis in the Mandoul disease focus of Chad.Link opens in a new window PLoS Neglected Tropical Diseases. Paper summaries: EnglishLink opens in a new window French

Cost and cost-effectiveness evaluations

The Warwick gHAT model has been further expanded to provide the cost and cost-effectiveness of the four intervention strategies (see opposite) in terms of net benefit (cost of interventions vs cost of ill-health/disability/death), which is added to the model. Costs include diagnosis, confirmation, and staging via lumbar puncture, well as the cost of the drug itself and the administration. The research offers a number of different options highlighting the most efficient intervention strategy to achieve elimination by 2030 and the optimal strategy to lower costs.

Data and analysis toolLink opens in a new window: Projected costs of different intervention strategies and cost-effectiveness for 5 health zones in DRC are available to view online via a data and analysis tool (GUI), providing online access to the vast amount of data and results of this research project in a user-friendly way.

Peer-reviewed paper: Antillon M, Huang C, Crump RE, Brown P, Snijders R, Miaka EM, Keeling MJ, Rock KS, Tediosi F (2020). Cost-effectiveness of sleeping sickness elimination campaigns in five settings of the Democratic Republic of Congo.Link opens in a new window Nature Communications. Paper summaries:  EnglishLink opens in a new window,  FrenchLink opens in a new window

Optimising screening with low and falling case numbers

With limited numbers of active screening teams and resources, it is important to optimise their activities with the aim of driving towards elimination. With gHAT case numbers decreasing, we investigate how to optimise active screening visits to individual villages in DRC, such that the costs of the screening programmes can be minimised, while continuing to avert disability-adjusted life years. A stochastic gHAT infection model has been implemented across a range of active screening strategies and the net monetary benefit (NMB - cost of interventions vs cost of ill-health/disability/death) of each calculated.

Extending a cost-effectiveness framework to account for elimination goals

Various diseases are earmarked for elimination by the global health community. While the health economic implications of elimination have been discussed before, the combination of uncertainty, cost-effectiveness in terms of cases averted, and elimination in the face of rising per-case costs has not been tackled before.

We propose an approach that considers the tension between the dual objectives of cost-effectiveness and elimination while incorporating uncertainty in these objectives. This framework enables us to compute the additional costs of implementing a strategy which is more likely to achieve elimination beyond what would normally be considered cost-effective - which we call the premium of elimination.

We apply our method to strategies against human African trypanosomiasis in three settings, but this method could be directly applied to simulation-based studies of the cost-effectiveness of other disease elimination efforts. The method yields common metrics of efficiency for stakeholders who have different objectives.