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Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating Malaria
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نویسنده
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shearer f.m. ,huang z. ,weiss d.j. ,wiebe a. ,gibson h.s. ,battle k.e. ,pigott d.m. ,brady o.j. ,putaporntip c. ,jongwutiwes s. ,lau y.l. ,manske m. ,amato r. ,elyazar i.r.f. ,vythilingam i. ,bhatt s. ,gething p.w. ,singh b. ,golding n. ,hay s.i. ,moyes c.l.
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منبع
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plos neglected tropical diseases - 2016 - دوره : 10 - شماره : 8
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چکیده
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Background: infection by the simian malaria parasite,plasmodium knowlesi,can lead to severe and fatal disease in humans,and is the most common cause of malaria in parts of malaysia. despite being a serious public health concern,the geographical distribution of p. knowlesi malaria risk is poorly understood because the parasite is often misidentified as one of the human malarias. human cases have been confirmed in at least nine southeast asian countries,many of which are making progress towards eliminating the human malarias. understanding the geographical distribution of p. knowlesi is important for identifying areas where malaria transmission will continue after the human malarias have been eliminated. methodology/principal findings: a total of 439 records of p. knowlesi infections in humans,macaque reservoir and vector species were collated. to predict spatial variation in disease risk,a model was fitted using records from countries where the infection data coverage is high. predictions were then made throughout southeast asia,including regions where infection data are sparse. the resulting map predicts areas of high risk for p. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (malaysia,cambodia,thailand and vietnam) as well as countries projected to be eliminating malaria (myanmar,laos,indonesia and the philippines). conclusions/significance: we have produced the first map of p. knowlesi malaria risk,at a fine-scale resolution,to identify priority areas for surveillance based on regions with sparse data and high estimated risk. our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. considering malaria elimination goals,areas for prioritised surveillance are identified. © 2016 shearer et al.
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آدرس
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spatial ecology & epidemiology group,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, malaria atlas project,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, malaria atlas project,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, spatial ecology & epidemiology group,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, malaria atlas project,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, malaria atlas project,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, institute of health metrics and evaluation,university of washington,seattle,wa, United States, spatial ecology & epidemiology group,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, molecular biology of malaria and opportunistic parasites research unit,department of parasitology,faculty of medicine,chulalongkorn university,bangkok, Thailand, molecular biology of malaria and opportunistic parasites research unit,department of parasitology,faculty of medicine,chulalongkorn university,bangkok, Thailand, department of parasitology,faculty of medicine,university of malaya,kuala lumpur, Malaysia, wellcome trust sanger institute,hinxton,united kingdom,medical research council (mrc) centre for genomics and global health,university of oxford,oxford, United Kingdom, wellcome trust sanger institute,hinxton,united kingdom,medical research council (mrc) centre for genomics and global health,university of oxford,oxford,united kingdom,wellcome trust centre for human genetics,university of oxford,oxford, United Kingdom, eijkman-oxford clinical research unit,jakarta, Indonesia, department of parasitology,faculty of medicine,university of malaya,kuala lumpur, Malaysia, malaria atlas project,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford,united kingdom,department of infectious disease epidemiology,imperial college london,london, United Kingdom, malaria atlas project,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom, malaria research centre,universiti malaysia sarawak,kuching,sarawak, Malaysia, spatial ecology & epidemiology group,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford,united kingdom,department of biosciences,university of melbourne,parkville,vic, Australia, spatial ecology & epidemiology group,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford,united kingdom,institute of health metrics and evaluation,university of washington,seattle,wa, United States, spatial ecology & epidemiology group,oxford big data institute,li ka shing centre for health information and discovery,university of oxford,oxford, United Kingdom
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Authors
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