Call detail record aggregation methodology impacts infectious disease models informed by human mobility
Loading...
Date
2023
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
PLOS Computational Biology
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.
Description
Research Article
Keywords
population-level, mobility, transmissibility of infections, metapopulation SEIR model of disease transmission