[COLLOQUIUM] Transmission dynamics of COVID-19 in complex networks

Classical epidemiological models assume mass action. However, this assumption is violated when interactions are not random. With the recent COVID-19 pandemic, and resulting shelter in place social distancing directives, mass action models must be modified to account for limited social interactions. In this talk we apply a pairwise network model with moment closure to study the early transmission of COVID-19 in New York and San Francisco and to investigate the factors determining the severity and duration of outbreak in these two cities. In particular, we consider the role of population density, transmission rates and social distancing on the disease dynamics and outcomes. Sensitivity analysis shows that there is a strongly negative correlation between the clustering coefficient in the pairwise model and the basic reproduction number and the effective reproduction number.

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报告人简介：
靳祯，山西大学二级教授。现任山西省“疾病防控的数学技术与大数据分析”重点实验室主任，山西省数学会理事长，享受国务院政府特殊津贴。主要从事生物动力系统研究，先后主持国家自然基金项目10项，其中国家基金重点项目2项，国家重点研发计划子项目1项。曾获山西省科学技术奖（自然科学类）一等奖2项，教育部高等学校优秀成果二等（自然科学类）奖1项。