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COVID-19 individual illness trajectory model

Model code for Hospital load and increased COVID-19 related mortality in Israel (Nature communications 2021)

Based on the model developed and described in:
Development and validation of a machine learning model for predicting illness trajectory and hospital resource utilization of COVID-19 hospitalized patients - a nationwide study
Original model code here

Updated to include new patient states (including PCR positive to hospitalization transitions) and based on Israel data from July-December

This repository contains code for a multi-state survival analysis model which can be used to predict covid-19 patients' illness trajectories from time of positive PCR diagnosis or hospitalization up to time of recovery or death.
Transitions between states (such as: "severe" to "death") are modeled using survival models with competing risks, and the patient's trajectory is estimated via Monte-Carlo path sampling over these transitions, while updating time-dependent patient covariates.

Jonathan Somer, Rom Gutman, Asaf Ben Arie, Malka Gorfine & Uri Shalit
Hagai Rossman, Tomer Meir & Eran Segal