Big data driven COVID-19 pandemic crisis management: Potential approach for global health
Yang Lv, Chenwei Ma, Xiaohan Li, Min Wu
Abstract
INTRODUCTION: Information has the power to protect against unexpected events and control any crisis such as the COVID-19 pandemic. Since COVID-19 has already rapidly spread all over the world, only technology-driven data management can provide accurate information to manage the crisis. This study aims to explore the potential of big data technologies for controlling COVID-19 transmission and managing it effectively. METHODS: A systematic review guided by PRISMA guidelines has been performed to obtain the key elements. RESULTS: This study identified the thirty-two most relevant documents for qualitative analysis. This study also reveals 10 possible sources and 8 key applications of big data for analyzing the virus infection trend, transmission pattern, virus association, and differences of genetic modifications. It also explores several limitations of big data usage including unethical use, privacy, and exploitative use of data. CONCLUSIONS: The findings of the study will provide new insight and help policymakers and administrators to develop data-driven initiatives to tackle and manage the COVID-19 crisis.