Clustering of countries based on the associated social contact patterns in epidemiological modelling

TL;DR

This paper introduces a framework for clustering countries based on their social contact patterns derived from contact matrices, aiding epidemiological modeling and comparison during pandemics like COVID-19.

Contribution

The paper presents a generic, modular framework for clustering countries using contact matrices within epidemic models, facilitating comparative analysis during infectious disease outbreaks.

Findings

Clusters reveal distinct social contact patterns across countries.

Application to COVID-19 models shows potential for targeted interventions.

Framework aids in identifying comparable countries during pandemics.

Abstract

Mathematical models have been used to understand the spread patterns of infectious diseases such as Coronavirus Disease 2019 (COVID-19). The transmission component of the models can be modelled in an age-dependent manner via introducing contact matrix for the population, which describes the contact rates between the age groups. Since social contact patterns vary from country to country, we can compare and group the countries using the corresponding contact matrices. In this paper, we present a framework for clustering countries based on their contact matrices with respect to an underlying epidemic model. Since the pipeline is generic and modular, we demonstrate its application in a COVID-19 model from R\"ost et. al. which gives a hint about which countries can be compared in a pandemic situation, when only non-pharmaceutical interventions are available.