Developing a COVID-19 mortality risk prediction model when individual-level data are not available
oleh: Noam Barda, Dan Riesel, Amichay Akriv, Joseph Levy, Uriah Finkel, Gal Yona, Daniel Greenfeld, Shimon Sheiba, Jonathan Somer, Eitan Bachmat, Guy N. Rothblum, Uri Shalit, Doron Netzer, Ran Balicer, Noa Dagan
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2020-09-01 |
Deskripsi
Identification of individuals at risk of severe COVID-19 disease could inform treatment and public health planning. Here, the authors develop and validate a risk prediction model for COVID-19 mortality in Israel by building a model for severe respiratory infection and recalibrating it using COVID-19 case fatality rates.