Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas

Background: Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of th...

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Main Authors: Moyes, Catherine L., Shearer, Freya M., Zhi, Huang, Wiebe, Antoinette, Gibson, Harry S., Nijman, Vincent, Jayasilan, Mohd-Azlan, Jedediah, F. Brodie, Suchinda, Malaivijitnond, Linkie, Matthew, Hiromitsu, Samejima, O’Brien, Timothy G., Trainor, Colin R.
Format: E-Article
Language:English
Published: BioMed Central Ltd. 2016
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Online Access:http://ir.unimas.my/id/eprint/14051/1/Predicting%20the%20geographical%20distributions%20of%20the%20macaque%20hosts%20and%20mosquito%20vectors%20of%20Plasmodium%20knowlesi%20malaria%20in%20forested%20and%20non-forested%20areas%20%28abstract%29.pdf
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spelling my.unimas.ir.140512016-10-24T01:13:43Z http://ir.unimas.my/id/eprint/14051/ Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas Moyes, Catherine L. Shearer, Freya M. Zhi, Huang Wiebe, Antoinette Gibson, Harry S. Nijman, Vincent Jayasilan, Mohd-Azlan Jedediah, F. Brodie Suchinda, Malaivijitnond Linkie, Matthew Hiromitsu, Samejima O’Brien, Timothy G. Trainor, Colin R. RA Public aspects of medicine Background: Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of the reservoir and vector species. Methods: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class. Results: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60 % tree cover) whereas the Dirus Complex was predicted to occur in areas with 10–100 % tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas. Conclusions: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk. BioMed Central Ltd. 2016 E-Article PeerReviewed text en http://ir.unimas.my/id/eprint/14051/1/Predicting%20the%20geographical%20distributions%20of%20the%20macaque%20hosts%20and%20mosquito%20vectors%20of%20Plasmodium%20knowlesi%20malaria%20in%20forested%20and%20non-forested%20areas%20%28abstract%29.pdf Moyes, Catherine L. and Shearer, Freya M. and Zhi, Huang and Wiebe, Antoinette and Gibson, Harry S. and Nijman, Vincent and Jayasilan, Mohd-Azlan and Jedediah, F. Brodie and Suchinda, Malaivijitnond and Linkie, Matthew and Hiromitsu, Samejima and O’Brien, Timothy G. and Trainor, Colin R. (2016) Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas. Parasites and Vectors, 9 (1). ISSN 1756-3305 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966365375&partnerID=40&md5=53bd913fcbb26c9874b79ee744f95caf DOI: 10.1186/s13071-016-1527-0
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic RA Public aspects of medicine
spellingShingle RA Public aspects of medicine
Moyes, Catherine L.
Shearer, Freya M.
Zhi, Huang
Wiebe, Antoinette
Gibson, Harry S.
Nijman, Vincent
Jayasilan, Mohd-Azlan
Jedediah, F. Brodie
Suchinda, Malaivijitnond
Linkie, Matthew
Hiromitsu, Samejima
O’Brien, Timothy G.
Trainor, Colin R.
Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
description Background: Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of the reservoir and vector species. Methods: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class. Results: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60 % tree cover) whereas the Dirus Complex was predicted to occur in areas with 10–100 % tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas. Conclusions: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.
format E-Article
author Moyes, Catherine L.
Shearer, Freya M.
Zhi, Huang
Wiebe, Antoinette
Gibson, Harry S.
Nijman, Vincent
Jayasilan, Mohd-Azlan
Jedediah, F. Brodie
Suchinda, Malaivijitnond
Linkie, Matthew
Hiromitsu, Samejima
O’Brien, Timothy G.
Trainor, Colin R.
author_facet Moyes, Catherine L.
Shearer, Freya M.
Zhi, Huang
Wiebe, Antoinette
Gibson, Harry S.
Nijman, Vincent
Jayasilan, Mohd-Azlan
Jedediah, F. Brodie
Suchinda, Malaivijitnond
Linkie, Matthew
Hiromitsu, Samejima
O’Brien, Timothy G.
Trainor, Colin R.
author_sort Moyes, Catherine L.
title Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
title_short Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
title_full Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
title_fullStr Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
title_full_unstemmed Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
title_sort predicting the geographical distributions of the macaque hosts and mosquito vectors of plasmodium knowlesi malaria in forested and non-forested areas
publisher BioMed Central Ltd.
publishDate 2016
url http://ir.unimas.my/id/eprint/14051/1/Predicting%20the%20geographical%20distributions%20of%20the%20macaque%20hosts%20and%20mosquito%20vectors%20of%20Plasmodium%20knowlesi%20malaria%20in%20forested%20and%20non-forested%20areas%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/14051/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966365375&partnerID=40&md5=53bd913fcbb26c9874b79ee744f95caf
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