Mathematical Modeling of the Current COVID-19 Epidemic and Potential Second Wave in Alberta to Improve Public Health Responses

对艾伯塔省当前的 COVID-19 疫情和潜在的第二波疫情进行数学建模，以改善公共卫生应对措施

• 批准号: 555037-2020
• 负责人: Li, Michael
• 金额: $ 3.64万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=705771
• 关键词: Mathematical; Modeling; Current; COVID; 19

The COVID-19 has shaped to be one of the worst and deadliest pandemics the world has seen in recent times, in terms of how widely it has spread, its overall morbidity and mortality, and its huge economic impact. The COVID-19 pandemic has put the public health systems of all impacted countries and jurisdictions to test, with a varying degree of successes and failures. As provinces plan to open up and relax some social distancing measures, it is imperative that we study the lessons learned during the responses to the current epidemics in Canada, and better prepare for the widely anticipated second waves. During the COVID-19 pandemic, mathematical modeling has been adopted by public health agencies in many jurisdictions around the world as an essential tool to forecast the scale, time course, and the potential impacts to the public health and health systems. The insights from mathematical modeling have assisted public health authorities to make evidence-based decisions on the public health responses to the local epidemics. In partnership and collaboration with Alberta Health, the main objectives of the proposed research are to analyzed the COVID-19 data in Alberta using mathematical models, to identify key factors that contributed to the much larger scale of the COVID-19 epidemic in Calgary in comparison to Edmonton, and the large outbreaks in long-term care facilities and meat processing plants in Alberta. Lessons learned will be valuable to Alberta Health to better prepare for its public health responses to the potential second wave of COVID-19 in the Fall of 2020, and more effectively mitigate another large scale epidemic and prevent outbreaks in vulnerable populations.

就其传播范围、整体发病率和死亡率以及巨大的经济影响而言，COVID-19已成为近年来世界上最严重和最致命的大流行病之一。COVID-19大流行使所有受影响国家和司法管辖区的公共卫生系统受到考验，成功和失败的程度各不相同。随着各省计划开放和放宽一些社交距离措施，我们必须研究加拿大应对当前疫情期间的经验教训，并为广泛预期的第二波疫情做好准备。 在COVID-19大流行期间，全球多个司法管辖区的公共卫生机构已采用数学建模作为预测规模、时间进程以及对公共卫生和卫生系统的潜在影响的重要工具。数学建模的见解有助于公共卫生当局对当地流行病的公共卫生反应做出基于证据的决策。 与阿尔伯塔卫生部合作，拟议研究的主要目标是使用数学模型分析阿尔伯塔的COVID-19数据，以确定导致卡尔加里的COVID-19疫情规模远大于埃德蒙顿的关键因素，以及阿尔伯塔长期护理设施和肉类加工厂的大规模爆发。所汲取的经验教训将对阿尔伯塔卫生部非常宝贵，有助于其更好地准备应对2020年秋季可能出现的第二波COVID-19疫情的公共卫生应对措施，并更有效地缓解另一场大规模疫情，防止弱势群体爆发疫情。