# On the use of multiple compartment epidemiological models to describe the dynamics of influenza in Europe

## TL;DR

This paper presents a multi-compartment SIR model for influenza spread in Europe, incorporating data-quality considerations, revealing stable disease parameters, minimal mobility impact, and aiding in disease surveillance and control.

## Contribution

The paper introduces a data-sensitive optimization framework for fitting a multi-compartment SIR model to influenza data across Europe, highlighting stable parameters and mobility's limited role.

## Key findings

- Disease parameters are stable across seasons and strains.
- Influenza strains cluster according to genome sub-types.
- Inter-country mobility has negligible impact on influenza spread.

## Abstract

We develop a multiple compartment Susceptible-Infected-Recovered (SIR) model to analyze the spread of several infectious diseases through different geographic areas. Additionally, we propose a data-quality sensitive optimization framework for fitting this model to observed data. We fit the model to the temporal profile of the number of people infected by one of six influenza strains in Europe over $7$ influenza seasons. In addition to describing the temporal and spatial spread of influenza, the model provides an estimate of the inter-country and intra-country infection and recovery rates of each strain and in each season. We find that disease parameters remain relatively stable, with a correlation greater than $0.5$ over seasons and stains. Clustering of influenza strains by the inferred disease parameters is consistent with genome sub-types. Surprisingly, our analysis suggests that inter-country human mobility plays a negligible role in the spread of influenza in Europe. Finally, we show that the model allows the estimation of disease load in countries with poor or none existent data from the disease load in adjacent countries. Our findings reveal information on the spreading mechanism of influenza and on disease parameters. These can be used to assist in disease surveillance and in control of influenza as well as of other infectious pathogens in a heterogenic environment.