COVID-19 Infection Wave Mortality from Surveillance Data in the Philippines Using Machine Learning

• Main Authors: Migriño, Julius, Jr, Batangan, Ani Regina U., Abello, Rizal Michael R.
• 格式: text
• 出版: Archīum Ateneo 2024
• 主題: COVID-19; mortality; variant; machine learning; surveillance; Medicine and Health Sciences; Public Health
• 在線閱讀: https://archium.ateneo.edu/asmph-pubs/292; https://archium.ateneo.edu/context/asmph-pubs/article/1296/viewcontent/2023.11.28.23299037v1.full.pdf
• 機構: Ateneo De Manila University

The Philippines had several COVID-19 infection waves brought about by different strains and variants of SARS-CoV-2. This study aimed to describe COVID-19 outcomes by infection waves using machine learning. A cross-sectional surveillance data review design was employed using the DOH COVID Data Drop d...