Modelling exposure between populations using networks of mobility during COVID-19

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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2023
Major/Subject
Mcode
Degree programme
Language
en
Pages
Series
Frontiers in Physics, Volume 11
Abstract
The use of mobile phone call detail records and device location data for the calling patterns, movements, and social contacts of individuals, have 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 fit a classical gravity model and a radiation model to the averaged weekly and yearly projection networks with geo-spatial and socioeconomic variables of the postal code areas and their populations. We also consider an extended gravity type model comprising of additional postal area information such as distance via public transportation and population density. The results show that the co-occurrence of human activities, or exposure, between postal code areas follows both the gravity and radiation type interactions, once fitted to the empirical network. The effects of the pandemic beginning in 2020 can be observed as a decrease of the overall activity as well as of the exposure of the projected networks. These effects can also be observed in the network structure as changes towards lower clustering and higher assortativity. Evaluating the parameters of the fitted models over time shows on average a shift towards a higher exposure of areas in closer proximity as well as a higher exposure towards areas with larger population. In general, the results show that the postal code level networks changed to be more proximity weighted after the pandemic began, following the government imposed non-pharmaceutical interventions, with differences based on the geo-spatial and socioeconomic structure of the areas.
Description
Funding Information: TT acknowledges funding from the Vilho, Yrjö and Kalle Väisälä Foundation of the Finnish Academy of Science and Letters. This work was partly supported by NordForsk through the funding to The Network Dynamics of Ethnic Integration, project number 105147. KB and KK acknowledge support from EU HORIZON 2020 INFRAIA-2019-1 (SoBigData++) No. 871042. | openaire: EC/H2020/871042/EU//SoBigData-PlusPlus
Keywords
collective human mobility, complex networks, COVID-19, data-driven modelling, social physics
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Citation
Takko , T , Bhattacharya , K & Kaski , K 2023 , ' Modelling exposure between populations using networks of mobility during COVID-19 ' , Frontiers in Physics , vol. 11 , 1138323 . https://doi.org/10.3389/fphy.2023.1138323