Impacts of Individual and Social Behavior on Influenza Dynamics and Control

个人和社会行为对流感动态和控制的影响

基本信息

批准号：
7851274
负责人：
ALISON P GALVANI
金额：
$ 55.5万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-06-01 至 2014-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7851274
关键词：
Adherence Antiviral Agents Antiviral resistance Attention Bayesian Analysis Behavior Behavioral Sciences Boston Censuses Communities Complex Costs and Benefits Data Decision Making Development Discipline Disease Economics Effectiveness Effectiveness of Interventions Epidemic Epidemiologic Methods Epidemiology Equilibrium Evaluation Evolution Experimental Psychology Game Theory Goals Health Health Status Immunity Incentives Individual Influenza Intervention Knowledge Massachusetts Measures Medical Methods Modeling Morbidity - disease rate Outcome Pattern Perception Pharmacologic Substance Policies Population Principal Investigator Protocols documentation Public Health Publishing Questionnaires Research Risk Role Schools Social Behavior Societies Statistical Methods Stream Structure Surveys Therapeutic Time Vaccinated Vaccination Viral Work base cost effectiveness disease transmission epidemiological model flu transmission health care service utilization improved influenza outbreak mathematical model meetings mortality network models novel pandemic disease pandemic influenza programs prophylactic psychologic public health relevance response success surveillance data therapy development transmission process

Adherence Antiviral Agents Antiviral resistance Attention Bayesian Analysis Behavior Behavioral Sciences Boston Censuses Communities Complex Costs and Benefits Data Decision Making Development Discipline Disease Economics Effectiveness Effectiveness of Interventions Epidemic Epidemiologic Methods Epidemiology Equilibrium Evaluation Evolution Experimental Psychology Game Theory Goals Health Health Status Immunity Incentives Individual Influenza Intervention Knowledge Massachusetts Measures Medical Methods Modeling Morbidity - disease rate Outcome Pattern Perception Pharmacologic Substance Policies Population Principal Investigator Protocols documentation Public Health Publishing Questionnaires Research Risk Role Schools Social Behavior Societies Statistical Methods Stream Structure Surveys Therapeutic Time Vaccinated Vaccination Viral Work base cost effectiveness disease transmission epidemiological model flu transmission health care service utilization improved influenza outbreak mathematical model meetings mortality network models novel pandemic disease pandemic influenza programs prophylactic psychologic public health relevance response success surveillance data therapy development transmission process

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项目摘要

DESCRIPTION (provided by applicant): Influenza transmission and its resulting morbidity and mortality are of great concern to society. Strategic intervention may greatly reduce these factors, but the effectiveness of an intervention depends on public adherence, and, more generally, on individual decision making in response to actual and perceived health risks. This project aims to define optimal intervention strategies and policies that significantly improve intervention adherence for both epidemic and pandemic influenza outbreaks. To meet this objective, we will integrate knowledge and methods from epidemiology, mathematical modeling, economics, game theory, and experimental psychology. Contact patterns, which are often dynamic and highly variable, fundamentally influence the spread of disease. These patterns change as individuals make decisions to be vaccinated, accept treatment, take hygienic precautions, or avoid work, school, or public spaces. We will develop new epidemiological models that explicitly consider individual-level perceptions and decisions and their impacts on the contact networks underlying influenza transmission. These models will capture the evolutionary dynamics of influenza, including antigenic drift and the emergence of antiviral resistance. We will apply game-theoretical methods to these models to evaluate different influenza intervention strategies, including vaccination, antiviral-based interventions, and non-pharmaceutical interventions, and to identify strategic opportunities for improving adherence through informational and incentive programs that change individual perceptions and decisions. The contact patterns and psychological components of the models will be based on Bayesian analysis of census data, workflow and recreational mobility data, and real-time influenza surveillance data, as well as on survey studies that evaluate public knowledge and perceptions about the disease. The latter will also provide information on adherence behavior, contact patterns, and the impact of real-time influenza-related decisions on these patterns. Integrating realistic, perception-driven individual-level decision making into epidemiological models will facilitate the evaluation of interventions and the development of strategies to improve adherence both in epidemic and pandemic outbreaks of influenza. Public Health Relevance: By integrating realistic, perception-driven individual-level decision making into epidemiological models, this project will advance methods for predicting the success of interventions and for developing effective strategies for improving intervention adherence.

描述（由申请人提供）：流感传播及其由此产生的发病率和死亡率引起了社会的极大关注。战略干预可能会大大减少这些因素，但是干预的有效性取决于公众的依从性，更普遍地是根据响应实际和感知的健康风险来做出个人决策。该项目旨在定义最佳的干预策略和政策，从而显着改善流行病和大流行性流感爆发的干预依从性。为了满足这一目标，我们将整合流行病学，数学建模，经济学，游戏理论和实验心理学的知识和方法。接触模式通常是动态且高度可变的，从根本上影响疾病的传播。这些模式随着个人做出疫苗接种，接受治疗，采取卫生预防措施或避免工作，学校或公共场所的决定而发生变化。我们将开发新的流行病学模型，这些模型明确考虑个人级别的看法和决策及其对流感传播基础接触网络的影响。这些模型将捕获流感的进化动力学，包括抗原漂移和抗病毒抗性的出现。我们将对这些模型应用游戏理论方法，以评估不同的流感干预策略，包括疫苗接种，基于抗病毒的干预措施以及非药物干预措施，并通过改变个人看法和决策的信息和激励计划来确定改善依从性的战略机会。模型的接触模式和心理组成部分将基于对人口普查数据，工作流程和娱乐性流动数据的贝叶斯分析以及实时流感监测数据，以及评估公众知识和对疾病的看法的调查研究。后者还将提供有关依从性行为，接触模式以及与实际流感相关的决策对这些模式的影响的信息。将现实的，感知驱动的个人水平决策整合到流行病学模型中，将有助于评估干预措施，并发展策略，以提高流行性流行性和流行病暴发的依从性。公共卫生相关性：通过将现实的，感知驱动的个人水平决策整合到流行病学模型中，该项目将推进预测干预措施成功并制定改善干预依从性的有效策略的方法。