Arrival Time Statistics in Global Disease Spread

TL;DR

This paper develops an analytical model to predict disease arrival times in cities connected by air travel, providing insights into epidemic spread patterns on a global scale.

Contribution

It introduces a new analytical approach to estimate disease arrival times and validates it on the worldwide air transportation network.

Findings

Accurately predicts the order of disease arrival in global cities.

Provides a new analytical framework for epidemic spread analysis.

Validates the model with real-world air transportation data.

Abstract

Metapopulation models describing cities with different populations coupled by the travel of individuals are of great importance in the understanding of disease spread on a large scale. An important example is the Rvachev-Longini model [{\it Math. Biosci.} {\bf 75}, 3-22 (1985)] which is widely used in computational epidemiology. Few analytical results are however available and in particular little is known about paths followed by epidemics and disease arrival times. We study the arrival time of a disease in a city as a function of the starting seed of the epidemics. We propose an analytical Ansatz, test it in the case of a spreading on the world wide air transportation network, and show that it predicts accurately the arrival order of a disease in world-wide cities.