Air-travel network change during COVID-19
A reproducible temporal-network analysis of changing connectivity across Canada, the USA, and Europe.
The problem
Pandemic travel restrictions changed not only passenger volume but the structure of the air-transportation network. Understanding those structural changes matters for mobility, resilience, and infectious-disease importation models.
My contribution
I helped develop a reproducible workflow that constructs and compares temporal air-travel networks from open data. The analysis tracks changes in connectivity and network structure across Canada, the United States, and Europe, connecting statistical analysis with an epidemiological modelling question.
Methods and tools: Python, R, temporal networks, graph analysis, open-data pipelines, reproducible research.