Analysis of the Rate of Confirmed COVID-19 Cases in Seoul and Factors Affecting It Using Big Data Analysis

Abstract

Coronavirus disease (COVID-19) is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and presents with mild to severe symptoms. Vaccines have been developed, but COVID-19 persists. Therefore, it is necessary to analyze big data at an early stage to establish an effective infection prevention strategy. To reduce SARS-CoV-2 infection, this study aimed to analyze the infection factors by region within Seoul, Korea and identify the major factors affecting the infection rate. For ease of data aggregation, the study was conducted after a data refinement operation that organized data in the same group into categories, and classified them in detail by specific keywords. Based on the results of this study, if preventive measures are established after identifying the representative infectious factors, periods, and routes of COVID-19 infection, the infection rate could be effectively reduced in the future.