Accelerated Failure Time (Aft) Model: Determining the Factors Associated in the Recovery of Patients Diagnosed with Covid-19

ABSTRACT

In this survival study, the range on the days of observation is from January 2020 to December 2020 consisting of the patients diagnosed with COVID-19. An accelerated failure time (AFT) model is used to identify covariates associated with recovery time (days from result of test to death/recovery of patients). AFT models with five different distributions (exponential, log-normal, Weibull, generalized gamma, and log-logistic) are generated. Akaike's information criterion (AIC) is used to identify the most suitable model. The total number of patients used in this study is 66142 and is broken into 2116 events and 64026 censored patients. This study shows that generalized gamma having the lowest AIC value made the best fit of the model. The covariates used in determining the factors associated to the recovery of patient are age, sex, admitted and quarantined. The model shows that when patients are being quarantined, the recovery time of patients increases.