A linear dynamical perspective on epidemiology: interplay between early COVID-19 outbreak and human mobility

Abstract

This paper investigates the impact of human activity and mobility (HAM) in the spreading dynamics of an epidemic. Specifically, it explores the interconnections between HAM and its effect on the early spread of the COVID-19 virus. During the early stages of the pandemic, effective reproduction numbers exhibited a high correlation with human mobility patterns, leading to a hypothesis that the HAM system can be studied as a coupled system with disease spread dynamics. This study applies the generalized Koopman framework with control inputs to determine the nonlinear disease spread dynamics and the input-output characteristics as a locally linear controlled dynamical system. The approach solely relies on the snapshots of spatiotemporal data and does not require any knowledge of the system's underlying physical laws. We exploit the Koopman operator framework by utilizing the Hankel dynamic mode decomposition with Control

Dynamic Patterns and Modeling of Early COVID-19 Transmission by Dynamic Mode Decomposition

“…Since the onset of the COVID-19 pandemic, researchers have applied DMD to examine the spatiotemporal characteristics of the spread of COVID-19 ( 11 , 12 ) and found that changes in the mobility of people over geographic space influence its spread ( 13 ). However, these studies focused on either a single US state (Florida) or a single nation (South Korea, a country with a land area smaller than Florida).…”