Modelling exposure between populations using networks of mobility during Covid-19
Tuomas Takko, Kunal Bhattacharya, Kimmo Kaski

TL;DR
This study models human exposure networks during Covid-19 using mobile phone data and evaluates gravity and radiation models to understand changes in mobility and contact patterns across postal code areas in Finland.
Contribution
It introduces a novel application of weighted exposure-networks based on mobile data and compares gravity and radiation models for reconstructing these networks during the pandemic.
Findings
Exposure networks decreased during Covid-19 pandemic.
Post-pandemic networks became more proximity weighted.
Gravity and radiation models effectively fit the empirical exposure data.
Abstract
The use of mobile phone call detail records and device location data for the calling patterns, movements, and social contacts of individuals, has proven to be valuable for devising models and understanding of their mobility and behaviour patterns. In this study we investigate weighted exposure-networks of human daily activities in the capital region of Finland as a proxy for contacts between postal code areas during the pre-pandemic year 2019 and pandemic years 2020, 2021 and early 2022. We investigate the suitability of gravity and radiation type models for reconstructing the exposure-networks based on geo-spatial and population mobility information. For this we use a mobile phone dataset of aggregated daily visits from a postal code area to cellphone grid locations, and treat it as a bipartite network to create weighted one mode projections using a weighted co-occurrence function. We…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · Data-Driven Disease Surveillance · COVID-19 epidemiological studies
