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

圭尔夫大学、卡尔加里大学、不列颠哥伦比亚大学、蒙特雷亚尔大学正在与赛诺菲公司、L L气候变化观察中心以及即将成立的呼吸道病原体卓越中心(呼吸病原体研究中心-由里昂大学医院网络托管)合作，以加强对新冠肺炎疫情后加拿大呼吸道病原体流行病的准备。该提案有国内和国际的合作者，并通过与即将到来的研究人员的合作，将加拿大新出现的传染病的建模扩展到法国。这场大流行对呼吸道病原体(如流感、呼吸道合胞病毒等)的正常模式造成了扰动，这主要是由于为预防新冠肺炎而采取的非药物干预措施：戴口罩、洗手和保持身体距离。与大流行有关的疫苗接种政策的到来和实施使人们普遍注意到疫苗迟疑率的增加。新冠肺炎公共卫生政策的遵从性疲劳目前在世界各地都存在，并可能延伸到其他疫苗接种计划，而任何剩余的新产品导入措施可能会变得越来越被忽视。这将导致易感人群的增加，并可能导致例如严重的流感季节。我们合作的目标是更好地了解和量化人群的行为和决策机制如何对病原体传播的动态做出贡献。在病原体的流行病学及其传播和人群对其存在的反应之间存在双向反馈渠道。决策者和公共卫生专家为政策提供信息，政策得到执行，民众作出反应。政策的成功与其在人群中的采用水平直接相关，而采用的变化会导致病原体传播的增加/减少。更具体地说，我们希望展示个人层面、群体层面和人口层面的政策采纳决策如何影响病原体传播的控制。

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.