Simulating the Spread of Influenza Pandemic of 2009 Considering International Traffic

TL;DR

This paper presents a hybrid simulation model combining local SEIR dynamics and global travel networks to analyze and predict the spread of the 2009 influenza pandemic, emphasizing the importance of seasonal factors.

Contribution

It introduces a novel hybrid modeling approach that integrates local disease dynamics with international travel data to better predict pandemic spread and peaks.

Findings

Seasonal tendency significantly affects pandemic peak prediction.

The model accurately reproduces early pandemic spread patterns.

Considering seasonal factors predicts subsequent pandemic peaks.

Abstract

Pandemics have the potential to cause immense disruption and damage to communities and societies. In this paper, we model the Influenza Pandemic of 2009. We propose a hybrid model to determine how the pandemic spreads through the world. The model considers both the SEIR-based model for local areas and the network model for global connection between countries referring to data on international travelers. Our interest is to reproduce the situation using the data of early stage of pandemic and to predict the future transition by extending the simulation cycle. Without considering the tendency of seasonal flu, the simulation does not predict the second peak of the pandemic in the real world. However, considering the seasonal tendency, the simulation result predicts the next peak in winter. Thus we consider the seasonal tendency is an important factor for the spreading of the pandemic.