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. 2015 Oct 22:8:550.
doi: 10.1186/s13071-015-1121-x.

Evaluating long-term effectiveness of sleeping sickness control measures in Guinea

Affiliations

Evaluating long-term effectiveness of sleeping sickness control measures in Guinea

Abhishek Pandey et al. Parasit Vectors. .

Abstract

Background: Human African Trypanosomiasis threatens human health across Africa. The subspecies T.b. gambiense is responsible for the vast majority of reported HAT cases. Over the past decade, expanded control efforts accomplished a substantial reduction in HAT transmission, spurring the WHO to include Gambian HAT on its roadmap for 2020 elimination. To inform the implementation of this elimination goal, we evaluated the likelihood that current control interventions will achieve the 2020 target in Boffa prefecture in Guinea, which has one of the highest prevalences for HAT in the country, and where vector control measures have been implemented in combination with the traditional screen and treat strategy.

Methods: We developed a three-species mathematical model of HAT and used a Bayesian melding approach to calibrate the model to epidemiological and entomological data from Boffa. From the calibrated model, we generated the probabilistic predictions regarding the likelihood that the current HAT control programs could achieve elimination by 2020 in Boffa.

Results: Our model projections indicate that if annual vector control is implemented in combination with annual or biennial active case detection and treatment, the probability of eliminating HAT as public health problem in Boffa by 2020 is over 90%. Annual implementation of vector control alone has a significant impact but a decreased chance of reaching the objective (77%). However, if the ongoing control efforts are interrupted, HAT will continue to remain a public health problem. In the presence of a non-human animal transmission reservoir, intervention strategies must be maintained at high coverage, even after 2020 elimination, to prevent HAT reemerging as a public health problem.

Conclusions: Complementing active screening and treatment with vector control has the potential to achieve the elimination target before 2020 in the Boffa focus. However, surveillance must continue after elimination to prevent reemergence.

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Figures

Fig. 1
Fig. 1
Model diagram of epidemiological compartments (circles) with rates of movement between each compartment (arrows). Further details are presented in the Methods
Fig. 2
Fig. 2
Model fits (a) base-case model without a non-human animal (NHA) reservoir, and (b) model with an NHA reservoir. Trajectories of the model fitted to prevalence data for stage I and stage II HAT cases from Boffa East mainland using Bayesian melding for years 2008 and 2013 and validated using 2010 and 2012. The red lines represent the HAT phase I and phase II prevalence estimated by our model for baseline epidemiological parameters (the grey areas represent the 95 % confidence intervals)
Fig. 3
Fig. 3
Probability of HAT elimination as public health problem under various control strategies (a) in absence of a non-human animal (NHA) reservoir, and (b) with an NHA reservoir. Vector control and active screening and treatment are implemented with the 2012 efficacy and coverage
Fig. 4
Fig. 4
Probabilities of HAT elimination as public health problem by the end of 2020 (a) in the absence of a non-human animal (NHA) reservoir, and (b) with an NHA reservoir. All controls were implemented either annually or biennially and different colors represent different reduction levels of vector control efficacy and active screening coverage relative to 2012 efficacy and coverage
Fig. 5
Fig. 5
Years to elimination with 100% probability under threshold of less than 1 new case per 100,000 people for the different control strategies. Different colors represent different proportional reduction of vector control efficacy and active screening coverage relative to 2012 efficacy and coverage

References

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