Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review

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.

Application of big data and artificial intelligence in epidemic surveillance and containment

“…Finding the source of an infectious disease is critical and challenging. According to features like travel trajectory flow information, social information, consumption information, geographical location, etc., some methods based on machine learning (ML) or deep learning (DL) like spatio-temporal modeling can calculate the path of disease transmission and provide a theoretical basis for the traceability analysis of infectious diseases [23] .…”

Contagion Modeling and Simulation in Transport and Air Travel Networks During the COVID-19 Pandemic: A Survey

“…Some of these works arose early, related to contagion risks inside airplanes [30] or behavioral models of contagious diseases [31]. From computer science, there exist surveys on big data and artificial intelligence techniques regarding the pandemic context [32]- [34], as well as other studies more focused on virus traceability: tracking apps [35], [36], geolocated [37] and spatio-temporal [38] data analysis techniques, among others.…”

Modeling of Various Spatial Patterns of SARS-CoV-2: The Case of Germany

“…Pourghasemi et al [ 26 ] performed spatial modeling, risk mapping, and change detection of COVID-19 in Iran using regression modelling and random forest classification. A more general review of artificial intelligence usage on COVID-19 spatio-temporal data in 49 selected research papers was presented by Jayatilaka et al [ 27 ].…”