Abstract
The COVID-19 pandemic is a major health threat and its global spread has led governments worldwide to take a series of public health and social measures and restrictions, aiming to reduce its transmission. As COVID-19 outbreak continues, there is a crucial need for further analysis and evaluation of the main features that seem to affect the clinical status of a patient infected by SARS-CoV-2. In this context, the present paper introduces a Covid Patient Assessment Analysis (CPAA) based on operational research, which examines the patient profile, taking into consideration characteristics like gender and age, and also categorizes the experiencing COVID-19 symptoms and the dependency of patient’s clinical status from potential comorbidities. Finally, evaluating all the aforementioned features, CPAA ranks COVID-19 cases based on the severity of each case in low-, medium-, and high-risk groups. For the modeling and the implementation of the CPAA, the Pairwise Comparison (PWC) has been used as an integral part of a decision-making process. The outcomes of the paper are the first step towards an overall operational research framework that would be used to evaluate the clinical status of patients and take automate decisions for their potential hospitalization.
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