True Epidemic Growth Construction Through Harmonic Analysis

TL;DR

This paper introduces a two-phase method combining graph theory and wavelet analysis to accurately reconstruct true epidemic growth from partial data, aiming to improve epidemic modeling accuracy.

Contribution

The paper presents a novel two-phase approach integrating graph theory and wavelets for epidemic data reconstruction from partial observations.

Findings

Proposed a graph-based method to update partial epidemic data.

Used wavelet analysis to generate plausible complete epidemic data.

The approach is novel and implementable, though some questions remain.

Abstract

In this paper, we have proposed a two phase procedure (combining discrete graphs and wavelets) for constructing a true epidemic growth. In the first phase graph theory based approach was developed to update partial data available and in the second phase we used this partial data to generate a plausible complete data through wavelets. This procedure although novel and implementable, still leave some questions unanswered.