Developing a COVID-19 mortality risk prediction model when individual-level data are not available

Developing a COVID-19 mortality risk prediction model when individual-level data are not available

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...

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Autores principales: 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
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Science
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Acceso en línea:https://doaj.org/article/b6f41c67d1bb44c58e4540ffa24f6729
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Sumario: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.

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