Related Experiment Video
Updated: Sep 5, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
DISCOVID: discovering patterns of COVID-19 infection from recovered patients: a case study in Saudi Arabia
Tarik Alafif1, Alaa Etaiwi2, Yousef Hawsawi3
1Computer Science Department, Jamoum University College, Umm Al-Qura University, Jamoum, 25375 Makkah Saudi Arabia.
Abstract:
A respiratory syndrome COVID-19 pandemic has become a serious global concern. Still, a large number of people have been daily infected worldwide. Discovering COVID-19 infection patterns is significant for health providers towards understanding the infection factors. Current COVID-19 research works have not been attempted to discover the infection patterns, yet. In this paper, we employ an Association Rules Apriori (ARA) algorithm to discover the infection patterns from COVID-19 recovered patients' data. A non-clinical COVID-19 dataset is introduced and analyzed. A sample of recovered patients' data is manually collected in Saudi Arabia. Our manual computation and experimental results show strong associative rules with high confidence scores among males, weight above 70 kilograms, height above 160 centimeters, and fever patterns. These patterns are the strongest infection patterns discovered from COVID-19 recovered patients' data.
More Related Videos
Related Concept Videos
Principles of Disease Surveillance
Single Nucleotide Polymorphisms-SNPs

