Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
about
Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating MalariaDistribution and prevalence of malaria parasites among long-tailed macaques (Macaca fascicularis) in regional populations across Southeast Asia.Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance.Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk.Three Divergent Subpopulations of the Malaria Parasite Plasmodium knowlesi.Plasmodium knowlesi: a relevant, versatile experimental malaria model.Eco-social processes influencing infectious disease emergence and spread.Analysis of nuclear and organellar genomes of Plasmodium knowlesi in humans reveals ancient population structure and recent recombination among host-specific subpopulations.Genome-wide mosaicism in divergence between zoonotic malaria parasite subpopulations with separate sympatric transmission cycles.Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis.Exposure and infection to Plasmodium knowlesi in case study communities in Northern Sabah, Malaysia and Palawan, The Philippines.Two clusters of Plasmodium knowlesi cases in a malaria elimination area, Sabang Municipality, Aceh, Indonesia.
P2860
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P2860
Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
description
2016 nî lūn-bûn
@nan
2016 թուականին հրատարակուած գիտական յօդուած
@hyw
2016 թվականին հրատարակված գիտական հոդված
@hy
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
name
Predicting the geographical di ...... orested and non-forested areas
@ast
Predicting the geographical di ...... orested and non-forested areas
@en
Predicting the geographical di ...... orested and non-forested areas
@nl
type
label
Predicting the geographical di ...... orested and non-forested areas
@ast
Predicting the geographical di ...... orested and non-forested areas
@en
Predicting the geographical di ...... orested and non-forested areas
@nl
prefLabel
Predicting the geographical di ...... orested and non-forested areas
@ast
Predicting the geographical di ...... orested and non-forested areas
@en
Predicting the geographical di ...... orested and non-forested areas
@nl
P2093
P2860
P50
P3181
P1433
P1476
Predicting the geographical di ...... orested and non-forested areas
@en
P2093
Colin R Trainor
Daniel J Weiss
Freya M Shearer
Harry S Gibson
Hiromitsu Samejima
Iqbal R F Elyazar
Jayasilan Mohd-Azlan
Jedediah F Brodie
Margaret F Kinnaird
Marianne E Sinka
P2860
P2888
P3181
P356
10.1186/S13071-016-1527-0
P407
P50
P577
2016-01-01T00:00:00Z
P5875
P6179
1008994311