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Call detail record aggregation methodology impacts infectious disease models informed by human mobility

Gibbs, Hamish; Musah, Anwar; Seidu, Omar; Ampofo, William; Asiedu-Bekoe, Franklin; Gray, Jonathan; Adewole, Wole A; ... Eggo, Rosalind M; + view all (2023) Call detail record aggregation methodology impacts infectious disease models informed by human mobility. PLOS Computational Biology , 19 (8) , Article e1011368. 10.1371/journal.pcbi.1011368. Green open access

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Abstract

This paper demonstrates how two different methods used to calculate population-level mobility from Call Detail Records (CDR) produce varying predictions of the spread of epidemics informed by these data. Our findings are based on one CDR dataset describing inter-district movement in Ghana in 2021, produced using two different aggregation methodologies. One methodology, "all pairs," is designed to retain long distance network connections while the other, "sequential" methodology is designed to accurately reflect the volume of travel between locations. We show how the choice of methodology feeds through models of human mobility to the predictions of a metapopulation SEIR model of disease transmission. We also show that this impact varies depending on the location of pathogen introduction and the transmissibility of infections. For central locations or highly transmissible diseases, we do not observe significant differences between aggregation methodologies on the predicted spread of disease. For less transmissible diseases or those introduced into remote locations, we find that the choice of aggregation methodology influences the speed of spatial spread as well as the size of the peak number of infections in individual districts. Our findings can help researchers and users of epidemiological models to understand how methodological choices at the level of model inputs may influence the results of models of infectious disease transmission, as well as the circumstances in which these choices do not alter model predictions.

Type: Article
Title: Call detail record aggregation methodology impacts infectious disease models informed by human mobility
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pcbi.1011368
Publisher version: https://doi.org/10.1371/journal.pcbi.1011368
Language: English
Additional information: Copyright © 2023 Gibbs et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Epidemiological methods and statistics, Human mobility, Ghana, Network analysis, Infectious disease epidemiology, Spatial epidemiology, Telecommunications, Population mobility
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography
URI: https://discovery.ucl.ac.uk/id/eprint/10175406
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