Simulating City-level Airborne Infectious Diseases

TL;DR

This paper presents a novel simulation approach that integrates traffic, geo-spatial data, and infection dynamics to better understand and predict airborne disease spread in urban environments.

Contribution

It introduces an integrated simulation framework combining multiple data sources for urban airborne disease transmission analysis.

Findings

Enhanced understanding of transmission pathways in urban areas

Ability to test different intervention scenarios

Framework supports decision-making for epidemic control

Abstract

With the exponential growth in the world population and the constant increase in human mobility, the danger of outbreaks of epidemics is rising. Especially in high density urban areas such as public transport and transfer points, where people come in close proximity of each other, we observe a dramatic increase in the transmission of airborne viruses and related pathogens. It is essential to have a good understanding of the `transmission highways' in such areas, in order to prevent or to predict the spreading of infectious diseases. The approach we take is to combine as much information as is possible, from all relevant sources and integrate this in a simulation environment that allows for scenario testing and decision support. In this paper we lay out a novel approach to study Urban Airborne Disease spreading by combining traffic information, with geo-spatial data, infection dynamics and spreading characteristics.