Estimation of risk factors for COVID-19 mortality - preliminary results

Francisco Caramelo; Nuno Ferreira; Barbara Oliveiros

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.02.24.20027268 doi: medRxiv preprint be computed from the China CDC report; thus, for each situation we can calculate the probability of being dead and, therefore, to randomly draw a value describing the status of each subject (Figure 3) . Once the dataset is created, a logistic regression model is fitted taking as dependent variable the death variable and as independent variables age, gender and comorbidity. The values of the regression coefficients are then transformed with an exponential function in order to obtain the adjusted OR, which are stored. The procedure is repeated 1000 times, allowing to obtain different datasets, each one with corresponding ORs (Figure 4) . After ending the random sampling procedure, the median is computed as well as percentiles 2.5 and 97.5, which allows to obtain the 95% confidence interval of ORs. . CC-BY-NC 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.