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Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal

The onchocerciasis transmission models EPIONCHO and ONCHOSIM have been independently developed and used to explore the feasibility of eliminating onchocerciasis from Africa with mass (annual or biannual) distribution of ivermectin within the timeframes proposed by the World Health Organization (WHO)...

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Autores principales: Walker, Martin, Stolk, Wilma A., Dixon, Matthew A., Bottomley, Christian, Diawara, Lamine, Traoré, Mamadou O., de Vlas, Sake J., Basáñez, María-Gloria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5340858/
https://www.ncbi.nlm.nih.gov/pubmed/28279455
http://dx.doi.org/10.1016/j.epidem.2017.02.005
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author Walker, Martin
Stolk, Wilma A.
Dixon, Matthew A.
Bottomley, Christian
Diawara, Lamine
Traoré, Mamadou O.
de Vlas, Sake J.
Basáñez, María-Gloria
author_facet Walker, Martin
Stolk, Wilma A.
Dixon, Matthew A.
Bottomley, Christian
Diawara, Lamine
Traoré, Mamadou O.
de Vlas, Sake J.
Basáñez, María-Gloria
author_sort Walker, Martin
collection PubMed
description The onchocerciasis transmission models EPIONCHO and ONCHOSIM have been independently developed and used to explore the feasibility of eliminating onchocerciasis from Africa with mass (annual or biannual) distribution of ivermectin within the timeframes proposed by the World Health Organization (WHO) and endorsed by the 2012 London Declaration on Neglected Tropical Diseases (i.e. by 2020/2025). Based on the findings of our previous model comparison, we implemented technical refinements and tested the projections of EPIONCHO and ONCHOSIM against long-term epidemiological data from two West African transmission foci in Mali and Senegal where the observed prevalence of infection was brought to zero circa 2007–2009 after 15–17 years of mass ivermectin treatment. We simulated these interventions using programmatic information on the frequency and coverage of mass treatments and trained the model projections using longitudinal parasitological data from 27 communities, evaluating the projected outcome of elimination (local parasite extinction) or resurgence. We found that EPIONCHO and ONCHOSIM captured adequately the epidemiological trends during mass treatment but that resurgence, while never predicted by ONCHOSIM, was predicted by EPIONCHO in some communities with the highest (inferred) vector biting rates and associated pre-intervention endemicities. Resurgence can be extremely protracted such that low (microfilarial) prevalence between 1% and 5% can be maintained for 3–5 years before manifesting more prominently. We highlight that post-treatment and post-elimination surveillance protocols must be implemented for long enough and with high enough sensitivity to detect possible residual latent infections potentially indicative of resurgence. We also discuss uncertainty and differences between EPIONCHO and ONCHOSIM projections, the potential importance of vector control in high-transmission settings as a complementary intervention strategy, and the short remaining timeline for African countries to be ready to stop treatment safely and begin surveillance in order to meet the impending 2020/2025 elimination targets.
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spelling pubmed-53408582017-03-13 Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal Walker, Martin Stolk, Wilma A. Dixon, Matthew A. Bottomley, Christian Diawara, Lamine Traoré, Mamadou O. de Vlas, Sake J. Basáñez, María-Gloria Epidemics Article The onchocerciasis transmission models EPIONCHO and ONCHOSIM have been independently developed and used to explore the feasibility of eliminating onchocerciasis from Africa with mass (annual or biannual) distribution of ivermectin within the timeframes proposed by the World Health Organization (WHO) and endorsed by the 2012 London Declaration on Neglected Tropical Diseases (i.e. by 2020/2025). Based on the findings of our previous model comparison, we implemented technical refinements and tested the projections of EPIONCHO and ONCHOSIM against long-term epidemiological data from two West African transmission foci in Mali and Senegal where the observed prevalence of infection was brought to zero circa 2007–2009 after 15–17 years of mass ivermectin treatment. We simulated these interventions using programmatic information on the frequency and coverage of mass treatments and trained the model projections using longitudinal parasitological data from 27 communities, evaluating the projected outcome of elimination (local parasite extinction) or resurgence. We found that EPIONCHO and ONCHOSIM captured adequately the epidemiological trends during mass treatment but that resurgence, while never predicted by ONCHOSIM, was predicted by EPIONCHO in some communities with the highest (inferred) vector biting rates and associated pre-intervention endemicities. Resurgence can be extremely protracted such that low (microfilarial) prevalence between 1% and 5% can be maintained for 3–5 years before manifesting more prominently. We highlight that post-treatment and post-elimination surveillance protocols must be implemented for long enough and with high enough sensitivity to detect possible residual latent infections potentially indicative of resurgence. We also discuss uncertainty and differences between EPIONCHO and ONCHOSIM projections, the potential importance of vector control in high-transmission settings as a complementary intervention strategy, and the short remaining timeline for African countries to be ready to stop treatment safely and begin surveillance in order to meet the impending 2020/2025 elimination targets. Elsevier 2017-03 /pmc/articles/PMC5340858/ /pubmed/28279455 http://dx.doi.org/10.1016/j.epidem.2017.02.005 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Walker, Martin
Stolk, Wilma A.
Dixon, Matthew A.
Bottomley, Christian
Diawara, Lamine
Traoré, Mamadou O.
de Vlas, Sake J.
Basáñez, María-Gloria
Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal
title Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal
title_full Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal
title_fullStr Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal
title_full_unstemmed Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal
title_short Modelling the elimination of river blindness using long-term epidemiological and programmatic data from Mali and Senegal
title_sort modelling the elimination of river blindness using long-term epidemiological and programmatic data from mali and senegal
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5340858/
https://www.ncbi.nlm.nih.gov/pubmed/28279455
http://dx.doi.org/10.1016/j.epidem.2017.02.005
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