The The effect of antiviral treatment on SARS-CoV-2 infectious disease progression: A comparison of the multi-state models

Abstract

Combating SARS-CoV-2 is the first concern and goal of the whole world as it is face with this global health problem. Since 2019, the SARS-CoV-2 infection (Covid-19) and even mutated infection cases have been increasing rapidly. From 2019 through 27 August 2021, a total of 214,468,601 individuals were confirmed cases of SARS-CoV-2, including 4,470,969 deaths.
Some of these individuals were able to access treatment and some could not, but for a while there was complete uncertainty. It is not known whether those who accessed treatment were lucky, but treatment was based on trial and error because of this uncertainty around the world until data was collected. Therefore, the aim of this study was to model SARS-CoV-2 infectious disease progression from the date of polymerase chain reaction (PCR) test to the date of negative outcome via Bayesian multi-state model approaches considering risk factors such as gender, age, and antiviral treatment. Data from 746 inpatients were collected from 1st August until the 1st of December 2019. For the multi-state model, five various discrete states were selected according to the Republic of Turkey Ministery of Health treatment algorithm. The results showed that Bayesian multi-state models with the Weibull distributed baseline hazard function were more appropriate models in the presence of risk factors and antiviral treatment.