Gateway to Think Tanks
来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w26965 |
来源ID | Working Paper 26965 |
How Deadly Is COVID-19? Understanding The Difficulties With Estimation Of Its Fatality Rate | |
Andrew Atkeson | |
发表日期 | 2020-04-13 |
出版年 | 2020 |
语种 | 英语 |
摘要 | To understand how best to combat COVID-19, we must understand how deadly is the disease. There is a substantial debate in the epidemiological lit- erature as to whether the fatality rate is 1% or 0.1% or somewhere in between. In this note, I use an SIR model to examine why it is difficult to estimate the fatality rate from the disease and how long we might have to wait to resolve this question absent a large-scale randomized testing program. I focus on un- certainty over the joint distribution of the fatality rate and the initial number of active cases at the start of the epidemic around January 15, 2020. I show how the model with a high initial number of active cases and a low fatality rate gives the same predictions for the evolution of the number of deaths in the early stages of the pandemic as the same model with a low initial number of active cases and a high fatality rate. The problem of distinguishing these two parameterizations of the model becomes more severe in the presence of effective mitigation measures. As discussed by many, this uncertainty could be resolved now with large-scale randomized testing. |
主题 | Other ; General, Teaching ; Econometrics ; Estimation Methods ; COVID-19 |
URL | https://www.nber.org/papers/w26965 |
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/584638 |
推荐引用方式 GB/T 7714 | Andrew Atkeson. How Deadly Is COVID-19? Understanding The Difficulties With Estimation Of Its Fatality Rate. 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 | ||
w26965.pdf(394KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
个性服务 |
推荐该条目 |
保存到收藏夹 |
导出为Endnote文件 |
谷歌学术 |
谷歌学术中相似的文章 |
[Andrew Atkeson]的文章 |
百度学术 |
百度学术中相似的文章 |
[Andrew Atkeson]的文章 |
必应学术 |
必应学术中相似的文章 |
[Andrew Atkeson]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。