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Ecology and Evolution of Disease Interference

疾病干扰的生态学和进化

基本信息

批准号：
7417987
负责人：
Pejman Rohani
金额：
$ 4.92万
依托单位：
UNIVERSITY OF GEORGIA
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-05-01 至 2008-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7417987
关键词：
Acute Address Adhesions Affect Age Age Distribution Area Attention Bacterial Interference Books Calendar Case Study Cessation of life Chickenpox Childhood Classification Communicable Diseases Communities Complement Condition Contracts Convalescence Data Data Reporting Data Set Dengue Detection Developed Countries Developing Countries Development Disease Disease Outbreaks Echo Viruses Ecology Epidemic Epidemiologist Epidemiology Europe European Event Evolution Excision Extinction (Psychology)Gambia Genetic Polymorphism Geographic Locations Goals Human Immune Incidence Individual Infection Infection prevention Infectious Agent Influentials Influenza Literature Malaria Markov Chains Measles Medical Methodology Methods Modeling Morbidity - disease rate Multi-Drug Resistance Mumps Numbers Parasitic Diseases Personal Satisfaction Pertussis Physiologic pulse Population Principal Investigator Public Health Published Comment Pulse taking Quarantine Reading Recording of previous events Records Relative (related person)Reporting Research Research Personnel Rubella Scheme Scourge Senegal Series Shapes Snow Structure Study models Suggestion System Techniques Testing Thinking Time Vaccination Vaccines Virulence Whooping cough due to unspecified organism Work analytical tool base burden of illness cohort concept experience infancy insight interest mathematical model microorganism mortality novel pathogen pathogenic bacteria pressure programs statistics success tool

项目摘要

The proposed work will develop a general framework for the ecological and evolutionary dynamics of "disease communities". Although the field of epidemiology has a distinguished history with notable successes, the potential for interaction between unrelated infections has not received much attention. A mechanism for interaction between antigenically distinct infections is proposed: following an acute infection, individuals are temporarily unavailable to contract other diseases (primarily because quarantining during convalescence). Hence, the number of potential "hosts" available for each pathogen is affected by the outbreak dynamics of other infections. If an infection is associated with substantial mortality, then potential hosts become permanently removed and the interaction takes the form of competition between diseases. This mechanism leads to what is called "disease interference". This proposal aims to develop this conceptual framework, answering a number of fundamental ecological and evolutionary questions. Do all infections interact with all other infections? The answer to this is clearly no. Intuitively, it would be expected that the strength of this negative interaction between infections would depend on the degree similarity in hosts infected. For human infections, this would be determined by the amount of overlap between the distributions of the host age at infection. Does disease interference affect evolutionary dynamics? A central hypothesis of this work is that interference is likely to select for increased disease virulence. Can we use interference effects in systems where antigenic polymorphism is well established (eg Dengue)? The interference mechanism provides a null model for the study of infections with multiple strains. Is this work likely to have any important public health implications? Preliminary work suggests interference effects may be beneficially used to eradicate infections using fewer vaccine units than using conventional estimates. This proposal also aims to construct statistical tools whereby the signature of interference may be confidently detected from data. Due to their excellent spatio-temporal data-sets, much of this work will focus on childhood infections (eg as measles, pertussis, chickenpox and rubella), though the proposed mechanism is quite general. The analytical tools developed will be applied to numerous long-term disease records to explore the ubiquity of the interference phenomenon.

拟议的工作将为生态和进化动力学制定一个总体框架 “疾病社区”。尽管流行病学领域有着悠久的历史尽管取得了成功，但无关感染之间相互作用的可能性并未受到太多关注。一个提出了抗原不同感染之间相互作用的机制：急性感染后，个人暂时无法感染其他疾病（主要是因为隔离期间）恢复期）。因此，每种病原体的潜在“宿主”数量受到其他感染的爆发动态。如果感染与大量死亡率相关，那么潜在的宿主被永久移除，相互作用表现为疾病之间的竞争形式。这种机制导致了所谓的“疾病干扰”。本提案旨在发展这一概念框架，回答了一些基本的生态和进化问题。做所有的事感染与所有其他感染相互作用吗？答案显然是否定的。直觉上应该是预期的感染之间这种负面相互作用的强度取决于感染之间的相似程度主机被感染。对于人类感染，这将取决于病毒之间的重叠程度感染时宿主年龄的分布。疾病干扰会影响进化动力学吗？一个中央这项工作的假设是干扰可能会选择增加疾病毒力。我们可以使用抗原多态性已明确的系统（例如登革热）中的干扰效应？这干扰机制为多菌株感染的研究提供了零模型。这是作品吗可能对公共卫生产生任何重要影响吗？初步工作表明干扰效应可能使用比传统估计更少的疫苗单位可以有益地用于根除感染。这该提案还旨在构建统计工具，从而可以自信地识别干扰信号从数据中检测到。由于其出色的时空数据集，这项工作的大部分内容将集中于儿童感染（例如麻疹、百日咳、水痘和风疹），尽管拟议的机制是相当一般。开发的分析工具将应用于大量长期疾病记录，以探索普遍存在的干扰现象。