Functional data analysis: Application to the second and third wave of COVID-19 pandemic in Poland

TL;DR

This paper applies functional data analysis techniques to model and understand the COVID-19 pandemic's second and third waves in Poland, focusing on various health metrics across regions.

Contribution

It introduces a novel application of functional data analysis to COVID-19 data, including smoothing, PCA, and function-on-function regression for regional analysis.

Findings

Identification of key functional patterns in COVID-19 metrics

Regional differences in pandemic dynamics

Effective modeling of pandemic waves using functional methods

Abstract

In this article we use the methods of functional data analysis to analyze the number of positive tests, deaths, convalescents, hospitalized and intensive care people during second and third wave of the COVID-19 pandemic in Poland. For this purpose firstly we convert the data to smooth functions. Then we use principal component analysis and multiple function-on-function linear regression model to analyze waves of COVID-19 pandemic in Polish voivodeships.