| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27335 |
| 来源ID | Working Paper 27335 |
| Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model | |
| Andrew Atkeson; Karen Kopecky; Tao Zha | |
| 发表日期 | 2020-06-08 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | This paper presents a procedure for estimating and forecasting disease scenarios for COVID-19 using a structural SIR model of the pandemic. Our procedure combines the flexibility of noteworthy reduced-form approaches for estimating the progression of the COVID-19 pandemic to date with the benefits of a simple SIR structural model for interpreting these estimates and constructing forecast and counterfactual scenarios. We present forecast scenarios for a devastating second wave of the pandemic as well as for a long and slow continuation of current levels of infections and daily deaths. In our counterfactual scenarios, we find that there is no clear answer to the question of whether earlier mitigation measures would have reduced the long run cumulative death toll from this disease. In some cases, we find that it would have, but in other cases, we find the opposite — earlier mitigation would have led to a higher long-run death toll. |
| 主题 | Econometrics ; Estimation Methods ; COVID-19 |
| URL | https://www.nber.org/papers/w27335 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/585006 |
| 推荐引用方式 GB/T 7714 | Andrew Atkeson,Karen Kopecky,Tao Zha. Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model. 2020. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w27335.pdf（13585KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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