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

Overview of attention for article published in Parasites & Vectors, October 2015
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3 tweeters

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44 Mendeley
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Title
Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
Published in
Parasites & Vectors, October 2015
DOI 10.1186/s13071-015-1121-x
Pubmed ID
Authors

Abhishek Pandey, Katherine E. Atkins, Bruno Bucheton, Mamadou Camara, Serap Aksoy, Alison P. Galvani, Martial L. Ndeffo-Mbah

Abstract

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. 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. 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. 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.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 25%
Researcher 10 23%
Student > Ph. D. Student 6 14%
Other 3 7%
Lecturer 3 7%
Other 11 25%
Readers by discipline Count As %
Medicine and Dentistry 14 32%
Agricultural and Biological Sciences 11 25%
Social Sciences 5 11%
Unspecified 4 9%
Chemistry 3 7%
Other 7 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 October 2015.
All research outputs
#5,403,842
of 7,489,030 outputs
Outputs from Parasites & Vectors
#1,299
of 2,034 outputs
Outputs of similar age
#149,960
of 240,021 outputs
Outputs of similar age from Parasites & Vectors
#120
of 179 outputs
Altmetric has tracked 7,489,030 research outputs across all sources so far. This one is in the 24th percentile – i.e., 24% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,034 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 240,021 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 179 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.