Abstract
Background Gambiense human African trypanosomiasis (gHAT) is marked for elimination of transmission (EOT) by 2030, but the disease persists in several low-income countries. We examine the cost-effectiveness of four gHAT elimination strategies in Democratic Republic of Congo (DRC), which has the highest burden of gHAT.
Methods We compared four strategies against gHAT by coupling a transmission model with a health outcomes model in five settings - spanning low- to high-risk. Alongside passive surveillance (PS) infixed health facilities, the strategies included active screening (AS) at average or high coverage levels, both alone or with vector control (VC). A scale-back algorithm was devised to simulate cessation of AS and VC when no cases were reported for three consecutive years. Outcomes were denominated in disability-adjusted life-years (DALYs) and costs until 2040 were denominated in 2018 US$.
Results In high or moderate-risk settings, costs of gHAT strategies are primarily driven by AS and, if used, VC. Due to the cessation of AS and VC most investments (75-80%) will be made by 2030 and VC might be cost-saving while ensuring EOT. In low-risk settings, costs are driven by PS, and minimum-cost strategies consisting of AS and PS lead to EOT by 2030 with high probability.
Conclusion In many settings, the case for EOT by 2030 is a sensible use of resources, and investments in gHAT will decelerate within this decade in moderate- and low-risk regions.
Evidence before this study The databases PubMed and ScienceDirect were searched on 28 April 2020 to identify previous studies undertaken on cost-effectiveness of strategies to control gHAT. We used an unrestricted language search and dates from January 2000 to focus on contemporary interventions and prevalence. The search terms were “sleeping sickness” OR “trypanosomiasis” AND “cost effective”. We excluded studies on rhodesiense HAT, animal trypanosomiasis and Chagas disease. A few intervention-specific studies have examined the cost-effectiveness of different tools, such as treatment and diagnostic tools or algorithms, but only a cost-effective analysis by Sutherland and colleagues (2017) examines the potential of multi-faceted strategies to avert burden and achieve elimination. Sutherland and colleagues showed that the deployment of emerging technologies - new treatments, new diagnostics, and/or vector control - would make elimination of transmission (EOT) feasible and cost-effective at thresholds below $1500-$1800 per DALY averted in theoretical settings of low, medium, and high prevalence.
Added value of this study Using a dynamic modelling framework, the present study is the first to perform a DRC-specific cost-effectiveness analysis for gHAT strategies that accounts for local epidemiological and operational characteristics. Using detailed cost-functions and updated information on the impact of interventions, we have projected the epidemiological and health economic implications by 2040 of gHAT control and EOT by 2030. We have simulated four alternative strategies combining passive surveillance with moderate and high coverage levels of active screening by mobile units. We have also simulated strategies with and without vector control. We found that in high-risk settings, strategies that lead to EOT are in line with strategies that aim to minimise costs, but in moderate-risk settings strategies with a high risk to EOT would require a relatively high willingness to pay to be considered cost-effective; this is similar to investments made for other infectious disease elimination programs.
Implications of all the available evidence gHAT elimination strategies can represent a justifiable use of resources even in resource-constrained settings. Investments in EOT in the near-term will enable a good degree of reduced costs post-2030, and in high-incidence settings, these investments will pay back by 2040.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This work was supported by the Bill and Melinda Gates Foundation (www.gatesfoundation.org) through the Human African Trypanosomiasis Modelling and Economic Predictions for Policy (HAT MEPP) project [OPP1177824] (MA, CH, REC, PB, MJK, KSR, and FT), through the NTD Modelling Consortium [OPP1184344, OPP1156227, and OPP1186851] (KSR and MJK), and through the TRYP-ELIM-BANDUNDU project [OPP1155293] (EMM and RS) and the Directorate-general Development Cooperation and Humanitarian Aid (EMM). The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
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Data Availability
Full model (including the fitting code) and documentation are available through OpenScienceFramework (OSF).