G2TT
来源类型Discussion paper
规范类型论文
来源IDDP15229
DP15229 Pandemic Control in ECON-EPI Networks
Marina Azzimonti; Alessandra Fogli; fabrizio perri; Mark Ponder
发表日期2020-08-30
出版年2020
语种英语
摘要We develop an ECON-EPI network model to evaluate policies designed to improve health and economic outcomes during a pandemic. Relative to the standard epidemiological SIR set-up, we explicitly model social contacts among individuals and allow for heterogeneity in their number and stability. In addition, we embed the network in a structural economic model describing how contacts generate economic activity. We calibrate it to the New York metro area during the 2020 COVID-19 crisis and show three main results. First, the ECON-EPI network implies patterns of infections that better match the data compared to the standard SIR. The switching during the early phase of the pandemic from unstable to stable contacts is crucial for this result. Second, the model suggests the design of smart policies that reduce infections and at the same time boost economic activity. Third, the model shows that re-opening sectors characterized by numerous and unstable contacts (such as large events or schools) too early leads to fast growth of infections.
主题Macroeconomics and Growth ; Public Economics
关键词Complex networks Covid-19 Epidemiology Sir Social distance
URLhttps://cepr.org/publications/dp15229
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/544203
推荐引用方式
GB/T 7714
Marina Azzimonti,Alessandra Fogli,fabrizio perri,et al. DP15229 Pandemic Control in ECON-EPI Networks. 2020.
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