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Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach

BACKGROUND: Mpumalanga in South Africa is committed to eliminating malaria by 2018 and efforts are increasing beyond that necessary for malaria control. Differential Equation models may be used to study the incidence and spread of disease with an important benefit being the ability to enact exogenou...

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Autores principales: Silal, Sheetal P, Little, Francesca, Barnes, Karen I, White, Lisa J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4127654/
https://www.ncbi.nlm.nih.gov/pubmed/25086861
http://dx.doi.org/10.1186/1475-2875-13-297
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author Silal, Sheetal P
Little, Francesca
Barnes, Karen I
White, Lisa J
author_facet Silal, Sheetal P
Little, Francesca
Barnes, Karen I
White, Lisa J
author_sort Silal, Sheetal P
collection PubMed
description BACKGROUND: Mpumalanga in South Africa is committed to eliminating malaria by 2018 and efforts are increasing beyond that necessary for malaria control. Differential Equation models may be used to study the incidence and spread of disease with an important benefit being the ability to enact exogenous change on the system to predict impact without committing any real resources. The model is a deterministic non-linear ordinary differential equation representation of the dynamics of the human population. The model is fitted to weekly data of treated cases from 2002 to 2008, and then validated with data from 2009 to 2012. Elimination-focused interventions such as the scale-up of vector control, mass drug administration, a focused mass screen and treat campaign and foreign source reduction are applied to the model to assess their potential impact on transmission. RESULTS: Scaling up vector control by 10% and 20% resulted in substantial predicted decreases in local infections with little impact on imported infections. Mass drug administration is a high impact but short-lived intervention with predicted decreases in local infections of less that one infection per year. However, transmission reverted to pre-intervention levels within three years. Focused mass screen and treat campaigns at border-entry points are predicted to result in a knock-on decrease in local infections through a reduction in the infectious reservoir. This knock-on decrease in local infections was also predicted to be achieved through foreign source reduction. Elimination was only predicted to be possible under the scenario of zero imported infections in Mpumalanga. CONCLUSIONS: A constant influx of imported infections show that vector control alone will not be able to eliminate local malaria as it is insufficient to interrupt transmission. Both mass interventions have a large and immediate impact. Yet in countries with a large migrant population, these interventions may fail due to the reintroduction of parasites and their impact may be short-lived. While all strategies (in isolation or combined) contributed to decreasing local infections, none was predicted to decrease local infections to zero. The number of imported infections highlights the importance of reducing imported infections at source, and a regional approach to malaria elimination.
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spelling pubmed-41276542014-08-14 Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach Silal, Sheetal P Little, Francesca Barnes, Karen I White, Lisa J Malar J Research BACKGROUND: Mpumalanga in South Africa is committed to eliminating malaria by 2018 and efforts are increasing beyond that necessary for malaria control. Differential Equation models may be used to study the incidence and spread of disease with an important benefit being the ability to enact exogenous change on the system to predict impact without committing any real resources. The model is a deterministic non-linear ordinary differential equation representation of the dynamics of the human population. The model is fitted to weekly data of treated cases from 2002 to 2008, and then validated with data from 2009 to 2012. Elimination-focused interventions such as the scale-up of vector control, mass drug administration, a focused mass screen and treat campaign and foreign source reduction are applied to the model to assess their potential impact on transmission. RESULTS: Scaling up vector control by 10% and 20% resulted in substantial predicted decreases in local infections with little impact on imported infections. Mass drug administration is a high impact but short-lived intervention with predicted decreases in local infections of less that one infection per year. However, transmission reverted to pre-intervention levels within three years. Focused mass screen and treat campaigns at border-entry points are predicted to result in a knock-on decrease in local infections through a reduction in the infectious reservoir. This knock-on decrease in local infections was also predicted to be achieved through foreign source reduction. Elimination was only predicted to be possible under the scenario of zero imported infections in Mpumalanga. CONCLUSIONS: A constant influx of imported infections show that vector control alone will not be able to eliminate local malaria as it is insufficient to interrupt transmission. Both mass interventions have a large and immediate impact. Yet in countries with a large migrant population, these interventions may fail due to the reintroduction of parasites and their impact may be short-lived. While all strategies (in isolation or combined) contributed to decreasing local infections, none was predicted to decrease local infections to zero. The number of imported infections highlights the importance of reducing imported infections at source, and a regional approach to malaria elimination. BioMed Central 2014-08-03 /pmc/articles/PMC4127654/ /pubmed/25086861 http://dx.doi.org/10.1186/1475-2875-13-297 Text en Copyright © 2014 Silal et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
Silal, Sheetal P
Little, Francesca
Barnes, Karen I
White, Lisa J
Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach
title Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach
title_full Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach
title_fullStr Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach
title_full_unstemmed Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach
title_short Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach
title_sort towards malaria elimination in mpumalanga, south africa: a population-level mathematical modelling approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4127654/
https://www.ncbi.nlm.nih.gov/pubmed/25086861
http://dx.doi.org/10.1186/1475-2875-13-297
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