In the last decade, the prevalence of Trypanosoma brucei gambiense (Tbg) human African trypanosomiasis (HAT) has fallen and HAT has been targeted for elimination. At low disease prevalence, HAT control is increasingly integrated into routine activities of peripheral health centres. However, the weak capacity of fixed health structures to implement control activities, lack of coverage, the unspecific clinical picture of HAT, and the existence of asymptomatic cases and animal reservoirs may result in under detection of HAT. To ensure sustainability of zero transmission and to avoid re-emergence caused by remaining Tbg reservoirs, continued post-elimination monitoring is therefore required.
Health workers performing house to house visits in foci with very low HAT prevalence can easily collect blood on filter paper and send it to regional HAT reference centres for analysis. The objective of the DiTECT-HAT-WP3 study is to determine the feasibility and cost of diagnostic algorithms of serological and molecular high-throughput tests on blood on filter paper for post-elimination monitoring, with or without a previous screening with rapid diagnostic tests.
In villages in low to zero prevalence foci in Democratic Republic (DR) Congo, Côte d'Ivoire and Burkina Faso, a health worker will go from house to house to 1) register all consenting inhabitants in a Personal Digital Assistant; 2) take a blood sample on filter paper 3) perform 3 rapid diagnostic tests. All dried blood spots (DBS) are sent to the reference laboratory for high-throughput testing (ELISA, trypanolysis, loop-mediated isothermal amplification method (LAMP) and real time (RT) -PCR). Subjects positive in at least 1 test - the RDTs or high-throughput tests - are revisited twice for parasitological confirmation.
In each country, blood specimens of 6000 persons will be tested. The relative effectiveness and overall cost of the different diagnostic algorithms will be investigated. We will quantify the break-even point for an imperfect test algorithm by formulating a decision criterion to assess how many false negatives, but particularly how many false positives can be tolerated while still achieving an intervention with a reasonable cost burden. The results will enable us to propose a test algorithm and a threshold to send out specialised mobile teams for stopping HAT re-emergence, without unnecessarily raising the alarm.
