On the regularity of human mobility patterns at times of a pandemic

TL;DR

This paper explores how information entropy can quantify the regularity of human mobility patterns during a pandemic, revealing correlations with demographic, economic factors, and social distancing behaviors.

Contribution

It introduces an analytical approach linking entropy measures to mobility, social distancing, and economic indicators, enhancing understanding of pandemic-related human movement.

Findings

Entropy correlates with demographic and economic trends.

Mobility entropy reflects social distancing attitudes.

Entropy measures test assumptions in epidemiological models.

Abstract

The study of human mobility patterns is a crucially important research field for its impact on several socio-economic aspects and, in particular, the measure of regularity patters of human mobility can provide a across-the-board view of many social distancing variables in epidemics such as: human movement trends, physical interpersonal distances and population density. We will show that the notion of information entropy is also strongly related to demographic and economic trends by the use and analysis of real-time data. In the present research paper we address three different problems. First, we provide an evidence-based analytical approach which relates the human mobility patterns, social distancing attitudes and population density, with entropic measures which depict for erraticity of human contact behaviors. Second, we investigate the correlations between the aggregated mobility and entropic measures versus five external economic indicators. Finally,we show how entropic measures represents a useful tool for testing the limitations of typical assumptions in epidemiological and mobility models.