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

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 inclu...

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Autores principales: Pandey, Abhishek, Atkins, Katherine E., Bucheton, Bruno, Camara, Mamadou, Aksoy, Serap, Galvani, Alison P., Ndeffo-Mbah, Martial L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4618537/
https://www.ncbi.nlm.nih.gov/pubmed/26490037
http://dx.doi.org/10.1186/s13071-015-1121-x
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author Pandey, Abhishek
Atkins, Katherine E.
Bucheton, Bruno
Camara, Mamadou
Aksoy, Serap
Galvani, Alison P.
Ndeffo-Mbah, Martial L.
author_facet Pandey, Abhishek
Atkins, Katherine E.
Bucheton, Bruno
Camara, Mamadou
Aksoy, Serap
Galvani, Alison P.
Ndeffo-Mbah, Martial L.
author_sort Pandey, Abhishek
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-015-1121-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-46185372015-10-25 Evaluating long-term effectiveness of sleeping sickness control measures in Guinea Pandey, Abhishek Atkins, Katherine E. Bucheton, Bruno Camara, Mamadou Aksoy, Serap Galvani, Alison P. Ndeffo-Mbah, Martial L. Parasit Vectors Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-015-1121-x) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-22 /pmc/articles/PMC4618537/ /pubmed/26490037 http://dx.doi.org/10.1186/s13071-015-1121-x Text en © Pandey et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Pandey, Abhishek
Atkins, Katherine E.
Bucheton, Bruno
Camara, Mamadou
Aksoy, Serap
Galvani, Alison P.
Ndeffo-Mbah, Martial L.
Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
title Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
title_full Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
title_fullStr Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
title_full_unstemmed Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
title_short Evaluating long-term effectiveness of sleeping sickness control measures in Guinea
title_sort evaluating long-term effectiveness of sleeping sickness control measures in guinea
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4618537/
https://www.ncbi.nlm.nih.gov/pubmed/26490037
http://dx.doi.org/10.1186/s13071-015-1121-x
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