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Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ

BACKGROUND: In places where malaria transmission is unstable or is transmitted under hypoendemic conditions, there are periods where limited foci of cases still occur and people become infected. These residual “hot spots” are likely reservoirs of the parasite population and so are fundamental to the...

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Autores principales: Ricotta, Emily E, Frese, Steven A, Choobwe, Cornelius, Louis, Thomas A, Shiff, Clive J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007634/
https://www.ncbi.nlm.nih.gov/pubmed/24620929
http://dx.doi.org/10.1186/1475-2875-13-94
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author Ricotta, Emily E
Frese, Steven A
Choobwe, Cornelius
Louis, Thomas A
Shiff, Clive J
author_facet Ricotta, Emily E
Frese, Steven A
Choobwe, Cornelius
Louis, Thomas A
Shiff, Clive J
author_sort Ricotta, Emily E
collection PubMed
description BACKGROUND: In places where malaria transmission is unstable or is transmitted under hypoendemic conditions, there are periods where limited foci of cases still occur and people become infected. These residual “hot spots” are likely reservoirs of the parasite population and so are fundamental to the seasonal spread and decline of malaria. It is, therefore, important to understand the ecological conditions that permit vector mosquitoes to survive and forage in these specific areas. Features such as local waterways and vegetation, as well as local ecology, particularly nocturnal temperature, humidity, and vegetative sustainability, are important for modeling local mosquito behavior. Vegetation around a homestead likely provides refuge for outdoor resting of these insects and may be a risk factor for malaria transmission. Analysis of this vegetation can be done using satellite information and mapping programs, such as Google Earth, but manual quantification is difficult and can be tedious and subjective. A more objective method is required. METHODS: Vegetation cover in the environment is reasonably static, particularly in and around homesteads. In order to evaluate and enumerate such information, ImageJ, an image processing software, was used to analyse Google Earth satellite imagery. The number of plants, total amount of vegetation around a homestead and its percentage of the total area were calculated and related to homesteads where cases of malaria were recorded. RESULTS: Preliminary results were obtained from a series of field trials carried out in South East Zambia in the Choma and Namwala districts from a base at the Macha District Hospital. CONCLUSIONS: This technique is objective, clear and simple to manipulate and has potential application to determine the role that vegetation proximal to houses may play in affecting mosquito behaviour, foraging and subsequent malaria incidence.
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spelling pubmed-40076342014-05-03 Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ Ricotta, Emily E Frese, Steven A Choobwe, Cornelius Louis, Thomas A Shiff, Clive J Malar J Methodology BACKGROUND: In places where malaria transmission is unstable or is transmitted under hypoendemic conditions, there are periods where limited foci of cases still occur and people become infected. These residual “hot spots” are likely reservoirs of the parasite population and so are fundamental to the seasonal spread and decline of malaria. It is, therefore, important to understand the ecological conditions that permit vector mosquitoes to survive and forage in these specific areas. Features such as local waterways and vegetation, as well as local ecology, particularly nocturnal temperature, humidity, and vegetative sustainability, are important for modeling local mosquito behavior. Vegetation around a homestead likely provides refuge for outdoor resting of these insects and may be a risk factor for malaria transmission. Analysis of this vegetation can be done using satellite information and mapping programs, such as Google Earth, but manual quantification is difficult and can be tedious and subjective. A more objective method is required. METHODS: Vegetation cover in the environment is reasonably static, particularly in and around homesteads. In order to evaluate and enumerate such information, ImageJ, an image processing software, was used to analyse Google Earth satellite imagery. The number of plants, total amount of vegetation around a homestead and its percentage of the total area were calculated and related to homesteads where cases of malaria were recorded. RESULTS: Preliminary results were obtained from a series of field trials carried out in South East Zambia in the Choma and Namwala districts from a base at the Macha District Hospital. CONCLUSIONS: This technique is objective, clear and simple to manipulate and has potential application to determine the role that vegetation proximal to houses may play in affecting mosquito behaviour, foraging and subsequent malaria incidence. BioMed Central 2014-03-13 /pmc/articles/PMC4007634/ /pubmed/24620929 http://dx.doi.org/10.1186/1475-2875-13-94 Text en Copyright © 2014 Ricotta et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), 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 Methodology
Ricotta, Emily E
Frese, Steven A
Choobwe, Cornelius
Louis, Thomas A
Shiff, Clive J
Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ
title Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ
title_full Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ
title_fullStr Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ
title_full_unstemmed Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ
title_short Evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using ImageJ
title_sort evaluating local vegetation cover as a risk factor for malaria transmission: a new analytical approach using imagej
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007634/
https://www.ncbi.nlm.nih.gov/pubmed/24620929
http://dx.doi.org/10.1186/1475-2875-13-94
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