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Dryad2017-01-01 更新2026-04-13 收录

寄生虫传播动力学

传播函数模型选择

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Table 2a: Results of the varying parasite number (constant density) experiment including the AICc and deltaAIC of each of the transmission functions.

创建时间：

2017-01-01

Signs of a vector’s adaptive choice: on the evasion of infectious hosts and parasite-induced mortality

媒介生态学

寄生虫传播动力学

Laboratory and field experiments have demonstrated in many cases that malaria vectors do not feed randomly, but show important preferences either for infected or non-infected hosts. These preferences

NIAID Data Ecosystem90

Additional file 5: of Exploration of Plasmodium vivax transmission dynamics and recurrent infections in the Peruvian Amazon using whole genome sequencing

疟疾基因组

寄生虫传播动力学

Table S4. Clonality calculations for the 69 P. vivax samples using the Fws (within-host heterozygosity) statistic and number of heterozygous calls in the core single nucleotide polymorphisms (SNPs). A

Figshare2018-11-08 更新60

Data supporting the results presented in Stephenson et al. from Host heterogeneity affects both parasite transmission to and fitness on subsequent hosts

寄生虫传播动力学

宿主-寄生虫相互作用

This file contains the raw data from the experiment described in Stephenson et al

NIAID Data Ecosystem40

Predators and patterns of within-host growth can mediate both among-host competition and the evolution of transmission potential of parasites

寄生虫传播动力学

捕食者-寄生虫互作

Parasite prevalence shows tremendous spatiotemporal variation. Theory indicates this variation might stem from life history characteristics of parasites and key ecological factors. Here, we illustrate

NIAID Data Ecosystem80

Temporal dynamics of direct reciprocal and indirect effects in a host-parasite network

宿主-寄生虫网络动态

寄生虫传播动力学

1. Temporal variation in the direct and indirect influence that hosts and parasites exert on each other is still poorly understood. However, variation in species’ influence due to species and interact

NIAID Data Ecosystem50

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