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US-UK Collab: Heterogeneities, Diversity and the Evolution of Infectious Disease

美英合作：异质性、多样性和传染病的演变

基本信息

批准号：
2011109
负责人：
Michael Boots
金额：
$ 197.67万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2011109&HistoricalAwards=false
关键词：
US UK Collab Heterogeneities Diversity

项目摘要

The aim of this project is to understand the effect of disease severity on the spread and evolution of infectious diseases, and its significance for infectious disease management and control. Recent and current epidemics emphasize that there is a pressing need to understand what makes some infectious diseases so devastating. Pathogens from the common cold through seasonal flu, SARS-1, SARS-2, and Ebola vary remarkably in how deadly they are and how well they transmit between people. Moreover, there is considerable variation in the impact that a specific disease will have on different individuals in a population. For example, some individuals get sicker than others, and importantly some will act as superspreaders of the pathogen. This type of variation is typical of infectious diseases in humans and other species, including livestock, crops and wildlife. To answer these questions the researchers will combine mathematical and computational models to develop new evolutionary theory that will explain the important factors responsible for variation in the outcome of an infection. The findings from the theory will be tested experimentally using an insect disease system in the laboratories at UC Berkeley. The mathematical modelling and experimental analysis can then be applied to real systems. A particular focus will be to examine the impact of different agricultural management practice on the severity of disease in agricultural systems, for example, which farming practices lead to the evolution of more virulent disease. Understanding what determines the virulence of infectious disease is critical to the effective management of current and emerging disease threats.Individual hosts vary in their susceptibility and transmissibility through genetic and epigenetic effects, their condition, and their immune memory. Individual hosts also vary in their disease contacts within a population due to how individuals are arranged in space, how they move, and how they interact, all of which can generate population structure even in the absence of heterogeneities in the environment. These individual heterogeneities and the heterogeneity in transmission due to population structure can interact with heterogeneities that arise from specific interactons between host and parasites genotype. This project will test theories about the effects each of these three sources of heterogeneity (individual, population and interaction) have on the epidemiology of disease. How these different heterogeneities interact to determine the evolution of disease virulence and host defense is little studied. New theory is therefore required to test these interactions’ implications to both long-term evolutionary outcomes and short-term transient dynamics. This project will: (1) develop theory to predict how these heterogeneities interact to determine long-term outcomes and transient evolutionary behavior, (2) test these predictions in a tractable laboratory model system (larvae of the moth Plodia interpunctella infected with PiGV), and (3) develop models to predict the impact of heterogeneities on the evolution of pathogens in agricultural systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

本项目的目的是了解疾病严重程度对传染病传播和演变的影响，及其对传染病管理和控制的意义。最近和目前的流行病强调，迫切需要了解是什么使一些传染病如此具有破坏性。从普通感冒到季节性流感、SARS-1、SARS-2和埃博拉病毒的病原体在致命程度和在人与人之间传播的程度上有很大差异。此外，一种特定疾病对人口中不同个体的影响也有相当大的差异。例如，有些人比其他人病得更重，重要的是有些人会成为病原体的超级传播者。这种类型的变异是人类和其他物种（包括牲畜、农作物和野生动物）传染病的典型特征。为了回答这些问题，研究人员将联合收割机的数学和计算模型相结合，以发展新的进化理论，将解释的重要因素，负责在感染的结果变化。该理论的发现将在加州大学伯克利分校的实验室中使用昆虫疾病系统进行实验测试。数学建模和实验分析，然后可以应用到真实的系统。一个特别的重点将是审查不同的农业管理做法对农业系统中疾病严重程度的影响，例如，哪些耕作做法导致更致命的疾病的演变。了解是什么决定了传染病的毒力是有效管理当前和新出现的疾病威胁的关键。个体宿主通过遗传和表观遗传效应、自身状况和免疫记忆在易感性和传播性方面存在差异。由于个体在空间中的排列方式、移动方式和相互作用方式，个体宿主在种群中的疾病接触也会有所不同，所有这些都可以在环境中没有异质性的情况下产生种群结构。这些个体的异质性和由于种群结构引起的传播异质性可以与宿主和寄生虫基因型之间特定相互作用引起的异质性相互作用。该项目将测试关于这三种异质性来源（个体、群体和相互作用）对疾病流行病学的影响的理论。这些不同的异质性如何相互作用，以确定疾病的毒力和宿主防御的演变很少研究。因此，需要新的理论来测试这些相互作用对长期进化结果和短期瞬态动力学的影响。该项目将：（1）发展理论来预测这些异质性如何相互作用，以确定长期结果和短暂的进化行为，（2）在易于处理的实验室模型系统中测试这些预测（感染PiGV的蛾Plodia interpunctella的幼虫），以及（3）开发模型来预测异质性对农业系统中病原体进化的影响。该奖项反映了NSF的法定使命，通过使用基金会的知识价值和更广泛的影响审查标准进行评估，认为值得支持。

项目成果

期刊论文数量（13）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Optimizing COVID-19 control with asymptomatic surveillance testing in a university environment.

DOI：
10.1016/j.epidem.2021.100527
发表时间：
2021-12
期刊：
Epidemics
影响因子：
3.8
作者：
Brook CE;Northrup GR;Ehrenberg AJ;IGI SARS-CoV-2 Testing Consortium;Doudna JA;Boots M
通讯作者：
Boots M

Experimental evidence that local interactions select against selfish behaviour