Modeling how keystone individuals emerge and influence disease transmission

模拟关键个体如何出现并影响疾病传播

基本信息

项目摘要

Collective behavior emerges from the coordinated actions of agents comprising complex systems. Humans live in intricate societies such as states and countries, cells in a tissue collectively coordinate their actions during development, and animal groups perform collective behaviors such as flocking. Thus, understanding how collective behaviors emerge has fundamental implications for a wide range of disciplines. Traditional studies of collective behavior have treated all individuals in a group as identical agents. However, individual variation is prevalent in nature and collectives are almost always comprised of phenotypically heterogeneous individuals. This heterogeneity results in a disproportionately large influence of certain individuals referred to here as ‘keystone individuals’, over the collective performance of the group. Such keystone individuals are prevalent in biology, for example, ‘super-spreaders’ facilitate the rapid spread of epidemics in human societies, ‘pioneer’ cells coordinate the movement of other cells during development, and certain individuals police the behavior of others in human and non-human primate groups. Therefore, it is surprising that there has been only little theoretical or empirical work explaining the causes and consequences of keystone individuals on collective behavior. Our goal is to uncover the role of keystone individuals in shaping collective outcomes, and in particular disease dynamics, by studying the social spider, Stegodyphus dumicola, which is highly amenable to experimental manipulations. We will begin by uncovering how keystone individuals lead to tradeoffs between beneficial collective outcomes and disease transmission. We will combine empirical work with agent-based simulations and ordinary differential equations to produce a cost-benefit analysis of collective outcomes. This analysis will reveal how the effect of keystones on collective success changes when multiple collective outcomes are considered simultaneously. We will then determine the genetic and social mechanisms by which keystone individuals influence other group members. In many study systems, including ours, the keystone individual catalyzes behavioral changes in its fellow group members. Using gene expression analysis and social network theory we will uncover how keystone individuals cause behavioral changes through social interactions and influence on gene expression. In particular, we will focus on the changes caused by keystone individuals to the expression of genes that are responsible for proper immune function. Our last aim is to dissect how disease dynamics are mediated by keystone individuals. Based on model predictions, we will examine if pathogen spread dynamics are influenced by both the identity of the first infected individual (patient zero) and the behavioral rules that determine colony composition. We will test this by tracing the spread of tagged bacteria throughout the colony when a keystone or generic individual are the first infected individual. By investigating mechanisms and function using a combination of experiments and modeling, our work will fill empirical and theoretical gaps in our understanding of how keystone individuals influence collective outcomes focusing on disease spread through a society.
集体行为产生于由复杂系统组成的主体的协调行动。人类生活

项目成果

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Noa Michal Pinter-Wollman其他文献

Noa Michal Pinter-Wollman的其他文献

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{{ truncateString('Noa Michal Pinter-Wollman', 18)}}的其他基金

Modeling how keystone individuals emerge and influence disease transmission
模拟关键个体如何出现并影响疾病传播
  • 批准号:
    9920155
  • 财政年份:
    2016
  • 资助金额:
    $ 44.2万
  • 项目类别:
Modeling how keystone individuals emerge and influence disease transmission
模拟关键个体如何出现并影响疾病传播
  • 批准号:
    9321471
  • 财政年份:
    2016
  • 资助金额:
    $ 44.2万
  • 项目类别:
EDUCATION AND OUTREACH CORE
教育和外展核心
  • 批准号:
    9127266
  • 财政年份:
    2010
  • 资助金额:
    $ 44.2万
  • 项目类别:
EDUCATION AND OUTREACH CORE
教育和外展核心
  • 批准号:
    8957395
  • 财政年份:
    2010
  • 资助金额:
    $ 44.2万
  • 项目类别:

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