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A novel spatio-temporal interpolation algorithm and its application to the COVID-19 pandemic

Authors:

Junzhe Cai,

Peter Z. ReveszAuthors Info & Claims

IDEAS '20: Proceedings of the 24th Symposium on International Database Engineering & Applications

Article No.: 9, Pages 1 - 10

https://doi.org/10.1145/3410566.3410602

Published: 25 August 2020 Publication History

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Abstract

This paper describes several interpolation methods for predicting the number of cases of the COVID-19 pandemic. The interpolation methods include some well-known temporal interpolation algorithms including Lagrange interpolation, cubic spline interpolation, and exponential decay interpolation. These temporal interpolation algorithms enable the interpolation of the COVID-19 cases at locations where measures on prior days are available. However, pandemics are not purely temporal but spatio-temporal phenomena. Therefore, the neighboring locations need to be considered too in order to derive accurate interpolation values for future days. This paper introduces a novel spatio-temporal interpolation algorithm that is shown to be better than any purely temporal interpolation algorithm in predicting the COVID-19 cases in the continental United States. In particular, the novel spatio-temporal interpolation method achieves a mean absolute error of 8.44 cases over a million people when predicting two days ahead the number of cases of the COVID-19 pandemic.

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Cai JRevesz P(2021)A Novel Spatiotemporal Method for Predicting Covid-19 CasesWSEAS TRANSACTIONS ON MATHEMATICS10.37394/23206.2021.20.3120(300-311)Online publication date: 11-Jun-2021
https://doi.org/10.37394/23206.2021.20.31
Chen HYang HChao YNicholls JLin JChen CYu WHwang F(2021)A parallel hierarchical tensor product method for n-dimensional interpolation in the Fourier domain2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)10.1109/ICECIE52348.2021.9664682(1-9)Online publication date: 27-Nov-2021
https://doi.org/10.1109/ICECIE52348.2021.9664682

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A novel spatio-temporal interpolation algorithm and its application to the COVID-19 pandemic

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Published In

IDEAS '20: Proceedings of the 24th Symposium on International Database Engineering & Applications

August 2020

252 pages

ISBN:9781450375030

DOI:10.1145/3410566

General Chairs:
Bipin C. Desai
Concordia University, Canada
,
Wan-Sup Cho
Chungbuk National University, Korea

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Published: 25 August 2020

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IDEAS 2020: 24th International Database Engineering & Applications Symposium

August 12 - 14, 2020

Seoul, Republic of Korea

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IDEAS '20 Paper Acceptance Rate 27 of 57 submissions, 47%;

Overall Acceptance Rate 74 of 210 submissions, 35%

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Cai JRevesz P(2021)A Novel Spatiotemporal Method for Predicting Covid-19 CasesWSEAS TRANSACTIONS ON MATHEMATICS10.37394/23206.2021.20.3120(300-311)Online publication date: 11-Jun-2021
https://doi.org/10.37394/23206.2021.20.31
Chen HYang HChao YNicholls JLin JChen CYu WHwang F(2021)A parallel hierarchical tensor product method for n-dimensional interpolation in the Fourier domain2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)10.1109/ICECIE52348.2021.9664682(1-9)Online publication date: 27-Nov-2021
https://doi.org/10.1109/ICECIE52348.2021.9664682

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High accuracy geometric Hermite interpolation

Shape-preserving, multiscale interpolation by univariate curvature-based cubic L₁ splines in cartesian and polar coordinates

C1 Hermite interpolation with spatial Pythagorean-hodograph cubic biarcs

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High accuracy geometric Hermite interpolation

Shape-preserving, multiscale interpolation by univariate curvature-based cubic L1 splines in cartesian and polar coordinates

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Shape-preserving, multiscale interpolation by univariate curvature-based cubic L₁ splines in cartesian and polar coordinates