Simulating the Spread of Pandemics with Different Origins Considering International Traffic

TL;DR

This paper introduces a hybrid simulation model combining local SEIR dynamics and global network connections to analyze how pandemic origins influence worldwide impact, using real traveler data across 65 countries.

Contribution

It presents a novel hybrid model integrating local and global factors to simulate pandemic spread from different origins, enhancing understanding of international impact.

Findings

Impact is higher when pandemics originate from the US, India, and China.

The model effectively captures the influence of origin on global pandemic spread.

Real traveler data improves simulation accuracy.

Abstract

Pandemics have the potential to cause immense disruption and damage to communities and societies. In this paper, we propose a hybrid model to determine how the pandemic spread through the world. The model combines the SEIR-based model for local areas and the network model for global connection between countries. We simulate the potential pandemic with different origins and find how the difference of the origin of a pandemic influences the impact in the world. We investigate the travelers network which is derived from real data, and simulate 65 countries, and see how the pandemic spread through the world from different 14 countries as origins of pandemic. We compare the difference in terms of the impact in countries and the impact in the world. As a result, the impact in the world increases when pandemic originates from the United States, India, and China.