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Data Science Methods to Develop Decision Support Systems for Real-time Monitoring of COVID-19 Outbreak

Arun Mitra, Biju Soman, Rakhal Gaitonde, Gurpreet Singh, Adrija Roy

Abstract


Data analysis and visualization are essential for exploring and communicating findings in medical research, especially in epidemiological surveillance. Data on COVID-19 diagnosed cases and mortality from crowdsourced website COVID-19 India Tracker, Census 2011, and Google Mobility reports has been used to develop a real-time analytics and monitoring system for the COVID-19 outbreak in India. We have developed a dashboard application for data visualization and analysis of several indicators to follow the SARS-CoV-2 epidemic using data science techniques. A district-level tool for basic epidemiological surveillance, in an interactive and user-friendly manner, which includes time trends, epidemic curves, and key epidemiological parameters such as growth rate, doubling time, and effective reproduction number, has been estimated. This demonstrates the application of data science methods and epidemiological techniques in public health decision-making while addressing the gap of timely and reliable decision-aiding tools.

 

Doi: 10.28991/HEF-2022-03-02-08

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Keywords


Public Health Data Science; COVID-19 Dashboard; Outbreak Monitoring; Decision Support System.

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DOI: 10.28991/HEF-2022-03-02-08

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