ReviewInfectious Disease Modelling2026
Outfitting the quest for spatial spread of infections: A review of mobility datasets for population health modelling.
Review in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Understanding the spatial dynamics of infectious disease spread is essential for modeling population health. A key component in such modeling is human mobility data, which informs how infections propagate across time and space. This review provides a comprehensive survey of both real-world and synthetic mobility datasets that have been used in the context of infectious disease modeling. Through the survey, we identified 57 publicly available datasets-52 real-world and 5 synthetic-offering a structured overview of current data sources. Additionally, because real-world data are often inaccessible due to privacy or technical constraints, we provide a concise overview of pseudo-mobility data generation methodologies to contextualize the synthetic datasets and guide future data-production efforts. The review highlights the need to advance synthetic data generation methodologies and improve the accessibility of high-resolution mobility data for future research in this domain.
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Registered trials
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