The Past, Present, and Future of COVID-19: A Data-Driven Perspective

• URL: http://arxiv.org/abs/2008.05531v1
• Date: Wed, 12 Aug 2020 19:03:57 GMT
• Title: The Past, Present, and Future of COVID-19: A Data-Driven Perspective
• Authors: Ajwad Akil, Ishrat Jahan Eliza, Md. Hasibul Hussain Hisham, Fahim Morshed, Nazmus Sakib, Nuwaisir Rabi, Abir Mohammad Turza, Sriram Chellappan, A. B. M. Alim Al Islam
• Abstract summary: We report results on our development and deployment of a web-based integrated real-time operational dashboard as an important decision support system for COVID-19. We conducted data-driven analysis based on available data from diverse authenticated sources to predict upcoming consequences of the pandemic. We also explored correlations between pandemic spread and important socio-economic and environmental factors.
• Score: 4.373183416616983
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Epidemics and pandemics have ravaged human life since time. To combat these, novel ideas have always been created and deployed by humanity, with varying degrees of success. At this very moment, the COVID-19 pandemic is the singular global health crisis. Now, perhaps for the first time in human history, almost the whole of humanity is experiencing some form of hardship as a result of one invisible pathogen. This once again entails novel ideas for quick eradication, healing and recovery, whether it is healthcare, banking, travel, education or any other. For efficient policy-making, clear trends of past, present and future are vital for policy-makers. With the global impacts of COVID-19 so severe, equally important is the analysis of correlations between disease spread and various socio-economic and environmental factors. Furthermore, all of these need to be presented in an integrated manner in real-time to facilitate efficient policy making. To address these issues, in this study, we report results on our development and deployment of a web-based integrated real-time operational dashboard as an important decision support system for COVID-19. In our study, we conducted data-driven analysis based on available data from diverse authenticated sources to predict upcoming consequences of the pandemic through rigorous modeling and statistical analyses. We also explored correlations between pandemic spread and important socio-economic and environmental factors. Furthermore, we also present how outcomes of our work can facilitate efficient policy making in this critical hour.

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