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During the COVID-19 pandemic, various social distancing measures were implemented to mitigate epidemic spread. To evaluate the spatial effects of these measures, mobility data were often used as a proxy for disease transmission \cite{schlosser_covid-19_2020, gibbs_detecting_2021}. Here, we analyzed the spatial patterns of 141,881 self-reported transmission pairs that occurred during household visits in the Netherlands from September 2020 until May 2021. We assessed whether the implementation and lifting of restrictions on household visits aligned with observed changes to spatial transmission patterns. In particular, we focused on transmissions with a long geographical distance between the residences of the infector and infectee, because they were a critical determinant of the speed of the epidemic. We found that long-distance transmissions reduced disproportionately at the start of the second COVID-19 wave (Sep. – Oct. ‘20), which supposedly slowed down epidemic spread. Interestingly, we did not observe similar reductions during the third (Dec. ‘20) and fourth wave (Mar. - Apr. ‘21). Overall, we found no robust association between the strictness of household visit restrictions and the proportion of long-range transmissions. Our findings demonstrated the usefulness of transmission data for evaluating social distancing measures, and suggested that policy changes did not always translate to changes in spatial transmission patterns.
Bibliography
@article{schlosser_covid-19_2020,
title = {{COVID}-19 lockdown induces disease-mitigating structural changes in mobility networks},
volume = {117},
url = {https://www.pnas.org/doi/10.1073/pnas.2012326117},
doi = {10.1073/pnas.2012326117},,
number = {52},
urldate = {2025-06-11},
journal = {Proceedings of the National Academy of Sciences},
author = {Schlosser, Frank and Maier, Benjamin F. and Jack, Olivia and Hinrichs, David and Zachariae, Adrian and Brockmann, Dirk},
month = dec,
year = {2020},
note = {Publisher: Proceedings of the National Academy of Sciences},
pages = {32883--32890},
}
@article{gibbs_detecting_2021,
title = {Detecting behavioural changes in human movement to inform the spatial scale of interventions against {COVID}-19},
volume = {17},
issn = {1553-7358},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009162},
doi = {10.1371/journal.pcbi.1009162},
language = {en},
number = {7},
urldate = {2025-10-09},
journal = {PLOS Computational Biology},
author = {Gibbs, Hamish and Nightingale, Emily and Liu, Yang and Cheshire, James and Danon, Leon and Smeeth, Liam and Pearson, Carl A. B. and Grundy, Chris and Group, LSHTM CMMID COVID-19 working and Kucharski, Adam J. and Eggo, Rosalind M.},
month = jul,
year = {2021},
note = {Publisher: Public Library of Science},
keywords = {Pandemics, Centrality, Community structure, COVID 19, Facebook, Population density, SARS CoV 2, Virus testing},
pages = {e1009162},
file = {Full Text PDF:N\:\Data\Zotero\Data\storage\66ESE9VZ\Gibbs et al. - 2021 - Detecting behavioural changes in human movement to inform the spatial scale of interventions against.pdf:application/pdf},
}
