Gambiense Human African trypanosomiasis (gHAT), also known as sleeping sickness, is almost always fatal without treatment. The vector-borne parasitic disease transmitted by infected tsetse flies affects mainly West and Central African countries, with the Democratic Republic of Congo (DRC) being the most impacted.
To contribute to reaching the WHO targets of elimination by 2030, Swiss TPH and partners have devised a health economic framework to quantify the efficiency of sleeping sickness elimination, and to aid discussions among stakeholders with different objectives.
“Our framework presents an extension to the net-benefits framework to improve what is currently used by decision-makers in order to support them with efficient resource allocation,” said Fabrizio Tediosi, Group Leader of Health Systems and Policies at Swiss TPH. “This framework considers the implications of switching to a strategy with a higher likelihood of meeting the global target of elimination.”
Frameworks for disease elimination
The analytical framework was applied to three distinct regions of the DRC “We chose these regions because they highlight the strengths of our framework and its applications under different circumstances, include circumstances of uncertainty,” said Marina Antillon, Scientific collaborator Health Systems and Policy at Swiss TPH. “This method could also be applied directly to simulation-based studies of the cost-effectiveness of other disease elimination efforts.”
The net-benefit framework guides decision-makers to select among various strategies in order to maximize health benefits in the presence of budget constraints.
However, disease elimination programmes with global target requirements are socially desirable but not always cost-effective: “Elimination campaigns can be increasingly costly on a per-case basis, and there is never absolute certainty that the elimination goal will be reached,” said Tediosi. “This is where innovative analytical frameworks are necessary, such as our new framework, which allows evaluating the impact of strategies with different probability of reaching elimination.”