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Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia

Geographic information systems (GISs) with emerging technologies are being harnessed for studying spatial patterns in vector-borne diseases to reduce transmission. To implement effective vector control, increased knowledge on interactions of epidemiological and entomological malaria transmission det...

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Detalles Bibliográficos
Autores principales: Chanda, Emmanuel, Mukonka, Victor Munyongwe, Mthembu, David, Kamuliwo, Mulakwa, Coetzer, Sarel, Shinondo, Cecilia Jill
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3323906/
https://www.ncbi.nlm.nih.gov/pubmed/22548086
http://dx.doi.org/10.1155/2012/363520
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author Chanda, Emmanuel
Mukonka, Victor Munyongwe
Mthembu, David
Kamuliwo, Mulakwa
Coetzer, Sarel
Shinondo, Cecilia Jill
author_facet Chanda, Emmanuel
Mukonka, Victor Munyongwe
Mthembu, David
Kamuliwo, Mulakwa
Coetzer, Sarel
Shinondo, Cecilia Jill
author_sort Chanda, Emmanuel
collection PubMed
description Geographic information systems (GISs) with emerging technologies are being harnessed for studying spatial patterns in vector-borne diseases to reduce transmission. To implement effective vector control, increased knowledge on interactions of epidemiological and entomological malaria transmission determinants in the assessment of impact of interventions is critical. This requires availability of relevant spatial and attribute data to support malaria surveillance, monitoring, and evaluation. Monitoring the impact of vector control through a GIS-based decision support (DSS) has revealed spatial relative change in prevalence of infection and vector susceptibility to insecticides and has enabled measurement of spatial heterogeneity of trend or impact. The revealed trends and interrelationships have allowed the identification of areas with reduced parasitaemia and increased insecticide resistance thus demonstrating the impact of resistance on vector control. The GIS-based DSS provides opportunity for rational policy formulation and cost-effective utilization of limited resources for enhanced malaria vector control.
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spelling pubmed-33239062012-04-30 Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia Chanda, Emmanuel Mukonka, Victor Munyongwe Mthembu, David Kamuliwo, Mulakwa Coetzer, Sarel Shinondo, Cecilia Jill J Trop Med Review Article Geographic information systems (GISs) with emerging technologies are being harnessed for studying spatial patterns in vector-borne diseases to reduce transmission. To implement effective vector control, increased knowledge on interactions of epidemiological and entomological malaria transmission determinants in the assessment of impact of interventions is critical. This requires availability of relevant spatial and attribute data to support malaria surveillance, monitoring, and evaluation. Monitoring the impact of vector control through a GIS-based decision support (DSS) has revealed spatial relative change in prevalence of infection and vector susceptibility to insecticides and has enabled measurement of spatial heterogeneity of trend or impact. The revealed trends and interrelationships have allowed the identification of areas with reduced parasitaemia and increased insecticide resistance thus demonstrating the impact of resistance on vector control. The GIS-based DSS provides opportunity for rational policy formulation and cost-effective utilization of limited resources for enhanced malaria vector control. Hindawi Publishing Corporation 2012 2012-04-02 /pmc/articles/PMC3323906/ /pubmed/22548086 http://dx.doi.org/10.1155/2012/363520 Text en Copyright © 2012 Emmanuel Chanda et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Chanda, Emmanuel
Mukonka, Victor Munyongwe
Mthembu, David
Kamuliwo, Mulakwa
Coetzer, Sarel
Shinondo, Cecilia Jill
Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia
title Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia
title_full Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia
title_fullStr Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia
title_full_unstemmed Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia
title_short Using a Geographical-Information-System-Based Decision Support to Enhance Malaria Vector Control in Zambia
title_sort using a geographical-information-system-based decision support to enhance malaria vector control in zambia
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3323906/
https://www.ncbi.nlm.nih.gov/pubmed/22548086
http://dx.doi.org/10.1155/2012/363520
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