Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review
Jayatilaka, G. C.; Hassan, J.; Marikkar, U.; Perera, R.; Sritharan, S.; Weligampola, H.; Ekanayake, M.; Godaliyadda, R.; Ekanayake, P.; Herath, V.; Godaliyadda, G. M. D.; Rathnayake, A.; Dharmaratne, S. D.; Ekanayake, J.
Show abstract
The COVID-19 pandemic, within a short time span, has had a significant impact on every aspect of life in almost every country on the planet. As it evolved from a local epidemic isolated to certain regions of China, to the deadliest pandemic since the influenza outbreak of 1918, scientists all over the world have only amplified their efforts to combat it. In that battle, Artificial Intelligence, or AI, with its wide ranging capabilities and versatility, has played a vital role and thus has had a sizable impact. In this review, we present a comprehensive analysis of the use of AI techniques for spatio-temporal modeling and forecasting and impact modeling on diverse populations as it relates to COVID-19. Furthermore, we catalogue the articles in these areas based on spatio-temporal modeling, intrinsic parameters, extrinsic parameters, dynamic parameters and multivariate inputs (to ascertain the penetration of AI usage in each sub area). The manner in which AI is used and the associated techniques utilized vary for each body of work. Majority of articles use deep learning models, compartment models, stochastic methods and numerous statistical methods. We conclude by listing potential paths of research for which AI based techniques can be used for greater impact in tackling the pandemic.
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