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Gambiense human African trypanosomiasis (gHAT), also known as gambiense sleeping sickness, is a parasitic infection caused by

Since the turn of the century, the global community has made great progress towards the elimination of gambiense human African trypanosomiasis (HAT). Elimination programs, primarily relying on screening and treatment campaigns, have also created a rich database of HAT epidemiology. Mathematical models calibrated with these data can help to fill remaining gaps in our understanding of HAT transmission dynamics, including key operational research questions such as whether integrating vector control with current intervention strategies is needed to achieve HAT elimination. Here we explore, via an ensemble of models and simulation studies, which aspects of the available data and level of data aggregation, such as separation by disease stage, would be most useful for better understanding transmission dynamics and improving model reliability in making future predictions of control and elimination strategies.Author summaryHuman African tryposonomiasis (HAT), also known as sleeping sickness, is a parasitic disease with over 65 million people estimated to be living at risk of infection. Sleeping sickness consists of two stages: the first one is relatively mild but the second stage is usually fatal if untreated. The World Health Organization has targeted HAT for elimination as a public health problem by 2020 and for elimination of transmission by 2030. Regular monitoring updates indicate that 2020 elimination goals are likely to be achieved. This monitoring relies mainly on case report data that is collected through medical-based control activities — the main strategy employed so far in HAT control. This epidemiological data are also used to calibrate mathematical models that can be used to analyse current interventions and provide projections of potential intensified strategies.We investigated the role of the type and level of aggregation of this HAT case data on model calibrations and projections. We highlight that the lack of detailed epidemiological information, such as missing stage of disease or truncated time series data, impacts model recommendations for strategy choice: it can misrepresent the underlying HAT epidemiology (for example, the ratio of stage 1 to stage 2 cases) and increase uncertainty in predictions. Consistently including new data from control activities as well as enriching it through cross-sectional (e.g. demographic or behavioural data) and geo-located data is likely to improve modelling accuracy to support planning, monitoring and adapting HAT interventions.

In recent years, the number of reported Human African Trypanosomiasis (HAT) cases caused by Trypanosoma brucei (T.b.) gambiense has been markedly declining, and the goal of ‘elimination as a public health problem’ is within reach. For the next stage, i.e. interruption of HAT transmission by 2030, intensive screening and surveillance will need to be maintained, but with tools and strategies more efficiently tailored to the very low prevalence. We assessed the sequential use of ELISA and Immune Trypanolysis (ITL) on dried blood spot (DBS) samples as an alternative to the traditional HAT field testing and confirmation approach. A cross-sectional study was conducted in HAT endemic and previously endemic zones in Kongo Central province, and a non-endemic zone in Haut Katanga province in the Democratic Republic of the Congo (DRC). Door-to-door visits were performed to collect dried blood spot (DBS) samples on filter paper. ELISA/T.b. gambiense was conducted followed by ITL for those testing positive by ELISA and in a subset of ELISA negatives. In total, 11,642 participants were enrolled. Of these, 11,535 DBS were collected and stored in appropriate condition for ELISA testing. Ninety-seven DBS samples tested positive on ELISA. In the endemic zone, ELISA positivity was 1.34% (95%CI: 1.04–1.64). In the previously endemic zone and non-endemic zone, ELISA positivity was 0.34% (95% CI: 0.13–0.55) and 0.37% (95% CI: 0.15–0.60) respectively. Among the ELISA positives, only two samples had a positive ITL result, both from the endemic zone. One of those was from a former HAT patient treated in 2008 and the other from an individual who unfortunately had deceased prior to the follow-up visit. Our study showed that a surveillance strategy, based on DBS samples and centralized testing with retracing of patients if needed, is feasible in DRC. ELISA seems well suited as initial test with a similar positivity rate as traditional screening tests, but ITL remains complex. Alternatives for the latter, also analyzable on DBS, should be further explored., Author summary Human African Trypanosomiasis (HAT), also known as sleeping sickness is a parasitic disease, transmitted by tsetse flies, that is usually fatal if untreated. The number of cases have been rapidly declining over the past years indicating that elimination of the disease as a public health problem is within reach. To achieve the next stage, i.e. interruption of HAT transmission by 2030, intensive screening and surveillance will need to be maintained, but with tools and strategies more efficiently tailored to the very low prevalence. In contrast to the traditional approach of sending laboratory expertise to the field, we assessed an alternative approach based on the collection of dried blood samples on filter paper that were tested in a regional laboratory. Samples were taken in endemic, previously endemic and non-endemic villages and tested by ELISA and Immune Trypanolysis. The ELISA positivity rates were similar to those of other screening techniques currently used and Immune Trypanolysis was highly specific. Hence for surveillance in HAT endemic areas, collecting dried blood samples followed by centralized testing could become an alternative to the current strategy of active screening by mobile teams with on the spot confirmation. It has also potential for post-elimination surveillance to monitor resurgence and for exploratory surveillance in historic foci. Though highly specific, Immune Trypanolysis remains too complex for use in intermediate level laboratories, to further expand this strategy an alternative second step test is required.