Survival Analysis and Critical Risk Factors in Covid-19 Patients Using Cox Regression

Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

^* Corresponding author : jerrypurnomo@gmail.com

Abstract

Coronavirus Disease 2019 (Covid-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The average incubation period of SARS-CoV-2 is 5 days (ranging from 2 to 14 days), and people experiencing symptoms occur within 12 days after infection (ranging from 8 to 16 days). Most person-to-person transmission of the virus can occur before the infected person shows symptoms (presymptomatic). A small percentage of infected people never experience symptoms but can contribute substantially to the transmission of the disease. Research continues to be carried out to determine the estimated length of recovery of Covid-19 patients. In this study, survival analysis of Covid-19 patients will be studied at Haji Hospital in Surabaya using Cox Proportional Hazard regression. Cox regression is one of the methods that can measure the relationship between Hazard rate and predictor variables without any assumptions as found in parametric models, therefore the Cox regression model is included as a semi-parametric model. This model allows the test to look at the survival time differences of two or more interest groups and can describe the effect of the predictor variables used to predict the status of the response variables to survival. The results of the Cox Proportional Hazard regression modeling showed two variables that influenced the survival time of Covid-19 patients, namely the gender variable and the symptom variable.