Modelling human behaviour response to public policy and its impact on infectious disease spread - case studies using AI/ML, data science, game theory and optimization

模拟人类对公共政策的行为反应及其对传染病传播的影响 - 使用人工智能/机器学习、数据科学、博弈论和优化进行案例研究

• 批准号: 572512-2022
• 负责人: Cojocaru, MonicaGabrielaMG
• 金额: $ 7.29万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758771
• 关键词: Modelling; human; behaviour; response; public

The Universities of Guelph, Calgary, University of British Columbia, Université de Montréal are partnering with Sanofi, Spectus L'Observatoire Québécois de l'Adaptation aux Changements Climatiques (OQACC) and the upcoming Center of Excellence for Respiratory Pathogens (CERP - hosted at Les Hospices Civils de Lyon University Hospital Network) to improve preparedness for respiratory pathogen epidemics in Canada, in the wake of the COVID-19 pandemic. The proposal has national and international collaborators and expands the Canadian emerging infectious disese modelling to France via the collaboration with the upcoming The pandemic has created perturbations to the normal patterns of respiratory pathogens (such as influenza, RSV, etc.), largely due to non-pharmaceutical interventions (NPIs) adopted for COVID-19 prevention: mask wearing, handwashing, and physical distancing. The arrival and implementation of vaccinating policies related to the pandemic has brought into focus an increased rate of vaccine hesitancy in general. Compliance fatigue with COVID-19 public health policy is currently experienced all over the world and might extend to other vaccination programs, while any remaining NPI measures may become increasingly ignored. This will result in an increase of susceptible individuals and may cause for instance a severe influenza season.Our partnership's goal is to better understand and quantify how populations' behaviour and decision-making mechanisms contribute to the dynamics of pathogen transmission. There is a two-way feedback channel between the epidemiology of a pathogen and its spread, and the population's reaction to its presence. Decision-makers and public health experts inform policy, policy is implemented, and the population reacts. Policy success is directly correlated to its adoption levels in the population, while changes in adoption lead to an increase/decrease of pathogen spread. More specifically, we wish to show how individual-level, group-level and population-level decision-making on policy adoption may influence the control of a pathogen transmission.

The University of Guelph, Calgary, University of British Columbia, University of the British Columbia, the University of Montréal are partnering with Sanofi, Spectus L'Observatoire Québécois de l'Adaptation aux Changes Climatiques (OQACC) and the upcoming Center of Excellence for Respiratory Pathogens (CERP - hosted at Les Hospitals Civils de Lyon University Hospital Network) to improve preparation for在19日大流行后，加拿大的呼吸病原体发作。 The proposal has national and international collaborators and expands the Canadian emerging infectious disse modelling to France via the collaboration with the upcoming The pandemic has created perturbations to the normal patterns of respiratory pathogens (such as influenceza, RSV, etc.), largely due to non-pharmaceutical interventions (NPIs) adopted for COVID-19 prevention: mask wearing, handwashing, and physical远处。一般而言，与大流行有关的疫苗接种政策的到来和实施总体上增加了疫苗愈合的速度。合规性疲劳与COVID-19的公共卫生政策目前在世界各地都有经历，并可能扩展到其他疫苗计划，而剩下的任何NPI措施都可能越来越被忽略。这将导致易感人物的增加，例如可能导致严重影响者。我们的伙伴关系的目标是更好地理解和量化人口的行为和决策机制如何有助于病原体传播的动态。病原体的流行病学及其扩散与人口对其存在的反应之间有一个双向反馈通道。决策者和公共卫生专家为政策，政策提供了信息，人口做出反应。政策成功与其在人口中的采用水平直接相关，而采用率的变化导致病原体传播的增加/减少。更具体地说，我们希望展示个人级别，群体级别和人口水平采用政策采用的决策如何影响病原体传播的控制。