Predictors of the Occurrence of Post Coronavirus Disease Syndrome Among COVID-19 Patients in Indonesia

Background and Objective Persistent symptoms after COVID 19 episodes (or referred to as Long COVID) can appear at a certain period and affect the quality of life of the patients, as well as introduce other comorbidities. It is important to address the associated factors of persistent symptoms after the COVID 19 episode. By identifying these factors, a screening method could be deployed to detect individuals that are prone to persistent COVID 19 symptoms.

Method:

This cohort study recruit COVID 19 patients at all stages in Indonesia (including people who underwent home isolation). Patient-based clinical information is collected from the patient including the demographic information, general health status, COVID 19 vaccination, and COVID 19 treatment. The outcome is the occurrence of persistent COVID 19-related symptoms after being declared as cured. A logistic regression model and Cox Regression are applied to the model to find the associated factors. Machine learning and Deep Learning model will be constructed and deployed into a web-based application for a further screening program.

Hypothesis:

1. There is an association between duration of COVID episode, repeated COVID episode, and the presence of persistent COVID 19 Symptoms
2. Vaccinated individual who was infected with Severe Acute Respiratory Syndrome (SARS) Coronavirus 2 (COV2) will have less persistent COVID 19 symptoms
3. Individuals with comorbidities are prone to persistent COVID 19 Symptoms
4. Appropriate medications (including early administration of antiviral therapy) lead to a lower probability of persistent COVID 19 Symptoms