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arXiv · 2104.07172

COVID-19 Clinical footprint to infer about mortality

Carlos E. Rodríguez·Ramsés H. Mena
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Abstract

Information of 1.6 million patients identified as SARS-CoV-2 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalizations and deaths due to the COVID-19 disease. Using the presence or absence of these latter variables a clinical footprint for each patient is created. The risk, expected mortality and the prediction of death outcomes, among other relevant quantities, are obtained and analyzed by means of a multivariate Bernoulli distribution. The proposal considers all possible footprint combinations resulting in a robust model suitable for Bayesian inference.

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Carlos E. Rodríguez, Ramsés H. Mena. 2021-04-15. COVID-19 Clinical footprint to infer about mortality. https://doi.org/10.1111/rssa.12947

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