Evaluating the social influences that impact vaccination decisions
评估影响疫苗接种决策的社会影响
基本信息
- 批准号:8477594
- 负责人:
- 金额:$ 33.85万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-07-10 至 2018-03-31
- 项目状态:已结题
- 来源:
- 关键词:AdherenceAgeBehaviorBehavioralBudgetsCommunicable DiseasesCost of IllnessCountryDataData SetDecision MakingDisease OutbreaksEconomic ModelsEconomicsEnsureEpidemiologyEquilibriumGame TheoryGoalsHabitsHealthHealth behaviorHouseholdIncentivesIndividualInfluenzaInfluenza vaccinationInternationalInterventionMedicalModelingMorbidity - disease rateMotivationOutcomeParticipantPersonal SatisfactionPlayPoliciesPopulationProcessPublic HealthRecommendationRelative (related person)ResearchRiskRoleShapesSocial DistanceSurveysTimeUncertaintyVaccinatedVaccinationage relatedbasebehavior influencedesigndisease transmissioneffective interventionflu transmissionimprovedinfluenza virus vaccineinsightinterestmathematical modelmortalitynetwork modelsnovelpreferencepreventprogramspsychologicpublic health relevanceresponsesocialtraittransmission processtrendvaccination strategy
项目摘要
DESCRIPTION (provided by applicant): A key to predicting medical decisions, such as vaccinations, is to understand individual behavior and its determinants, including self-interest and self-determined goals (desire to benefit oneself or enhance one's utility), prosociality (preferences for the well-being of others), imitation (imitating decisions of others), habitual behavior (tendency to repeat past actions), as well as time and budget constraints. As these behavioral factors influence vaccination decisions, they need to be incorporated into models of alternative vaccination strategies in order to provide policy decision-making guidance. Here, we propose to evaluate how behavioral factors shape influenza vaccination decisions, vary across nations, and can be used to inform vaccination strategies. To do so, we will use epidemiological-economic models including game theory and network models of influenza transmission, parameterized by psychological, economic and sociological data. Specifically, our transdisciplinary team will employ surveys, statistical analysis, and mathematical modeling to assess the interplay among decision-making processes of individuals, infectious disease transmission, and social influences in different countries. We will evaluate behavior, decision-making and epidemiological outcomes at multiple interrelated scales, including at the individual, household, age class, national, and population levels. Individual-level vaccination decisions can profoundly influence the fate of outbreaks, and thus have far reaching public health consequences for regional, national, and international populations. Understanding the factors underlying vaccination decisions and adherence to public health recommendations will enable the design of more effective vaccination programs. Therefore, we will also evaluate the capacity to influence behavioral factors, including prosociality, imitation, and habitual behavior, to promote vaccination policies that are optimal at both the individual and public health scales. Our results will increase our understanding of health decision-making and inform intervention strategies to improve vaccination rates.
描述(由申请人提供):预测医疗决策(如接种疫苗)的关键是了解个人行为及其决定因素,包括自利和自我确定的目标(有利于自己或提高自己的效用的愿望)、亲社会性(对他人福祉的偏好)、模仿(模仿他人的决定)、习惯性行为(倾向于重复过去的行为),以及时间和预算限制。由于这些行为因素影响疫苗接种决策,因此需要将其纳入替代疫苗接种策略模型,以便提供政策决策指导。在这里,我们建议评估行为因素如何影响流感疫苗接种决策,在各国之间存在差异,并可用于为疫苗接种策略提供信息。为此,我们将使用流行病学-经济学模型,包括博弈论和流感传播的网络模型,通过心理学,经济学和社会学数据参数化。具体而言,我们的跨学科团队将采用调查、统计分析和数学模型来评估不同国家的个人决策过程、传染病传播和社会影响之间的相互作用。我们将在多个相互关联的尺度上评估行为、决策和流行病学结果,包括个人、家庭、年龄阶层、国家和人口水平。个人层面的疫苗接种决定可深刻影响疫情的命运,从而对区域、国家和国际人口产生深远的公共卫生后果。了解疫苗接种决定的基本因素和遵守公共卫生建议将有助于设计更有效的疫苗接种计划。因此,我们还将评估影响行为因素的能力,包括亲社会、模仿和习惯行为,以促进在个人和公共卫生尺度上都是最佳的疫苗接种政策。我们的结果将增加我们对卫生决策的理解,并为提高疫苗接种率的干预策略提供信息。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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ALISON P GALVANI其他文献
ALISON P GALVANI的其他文献
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{{ truncateString('ALISON P GALVANI', 18)}}的其他基金
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial data
使用机械模型、机器学习和多样化地理空间数据加速美国城市的病毒爆发检测
- 批准号:
10399134 - 财政年份:2020
- 资助金额:
$ 33.85万 - 项目类别:
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial data
使用机械模型、机器学习和多样化地理空间数据加速美国城市的病毒爆发检测
- 批准号:
10571939 - 财政年份:2020
- 资助金额:
$ 33.85万 - 项目类别:
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial data
使用机械模型、机器学习和多样化地理空间数据加速美国城市的病毒爆发检测
- 批准号:
10113533 - 财政年份:2020
- 资助金额:
$ 33.85万 - 项目类别:
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial data
使用机械模型、机器学习和多样化地理空间数据加速美国城市的病毒爆发检测
- 批准号:
10341179 - 财政年份:2020
- 资助金额:
$ 33.85万 - 项目类别:
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial data
使用机械模型、机器学习和多样化地理空间数据加速美国城市的病毒爆发检测
- 批准号:
10265769 - 财政年份:2020
- 资助金额:
$ 33.85万 - 项目类别:
Evaluating the social influences that impact vaccination decisions
评估影响疫苗接种决策的社会影响
- 批准号:
9266796 - 财政年份:2013
- 资助金额:
$ 33.85万 - 项目类别:
Evaluating the social influences that impact vaccination decisions
评估影响疫苗接种决策的社会影响
- 批准号:
8698777 - 财政年份:2013
- 资助金额:
$ 33.85万 - 项目类别:
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
- 批准号:
7851274 - 财政年份:2009
- 资助金额:
$ 33.85万 - 项目类别:
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
- 批准号:
8069304 - 财政年份:2009
- 资助金额:
$ 33.85万 - 项目类别:
Dynamic data-driven decision models for infectious disease control
用于传染病控制的动态数据驱动决策模型
- 批准号:
8703900 - 财政年份:2009
- 资助金额:
$ 33.85万 - 项目类别:
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