True epidemic growth construction through harmonic analysis

Steven G Krantz; Peter Polyakov; Arni S R Srinivasa Rao

doi:10.1016/j.jtbi.2020.110243

True epidemic growth construction through harmonic analysis

J Theor Biol. 2020 Jun 7:494:110243. doi: 10.1016/j.jtbi.2020.110243. Epub 2020 Mar 12.

Authors

Steven G Krantz¹, Peter Polyakov², Arni S R Srinivasa Rao³

Affiliations

¹ Department of Mathematics, Washington University in St. Louis, Campus Box 1146 One Brookings Drive St. Louis, Missouri, MI 63130, USA. Electronic address: sk@math.wustl.edu.
² Department of Mathematics, University of Wyoming, Laramie, Wyoming, 82071, USA. Electronic address: polyakov@uwyo.edu.
³ Division of Health Economics and Modeling, Department of Population Health Sciences, Augusta, USA; Laboratory for Theory and Mathematical Modeling, Department of Medicine - Division of Infectious Diseases, Medical College of Georgia, USA; Department of Mathematics, Augusta University, Georgia, 30912 USA. Electronic address: arrao@augusta.edu.

Abstract

In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second phase, we used this partial data to generate plausible complete data through wavelets. We have provided two numerical examples. This procedure is novel and implementable and adaptable to machine learning modeling framework.

Keywords: Convergence of graphs; Partial to complete data; Wavelets.

MeSH terms

Epidemics*
Machine Learning*
Models, Biological*