Publication: Power law approximations of movement network data for modeling infectious disease spread
Power law approximations of movement network data for modeling infectious disease spread
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Geilhufe, M., Held, L., Skrøvseth, S. O., Simonsen, G. S., & Godtliebsen, F. (2014). Power law approximations of movement network data for modeling infectious disease spread. Biometrical Journal, 56(3), 363–382. https://doi.org/10.1002/bimj.201200262
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Globalization and increased mobility of individuals enable person-to-person transmitted infectious diseases to spread faster to distant places around the world, making good models for the spread increasingly important. We study the spatiotemporal pattern of spread in the remotely located and sparsely populated region of North Norway in various models with fixed, seasonal, and random effects. The models are applied to influenza A counts using data from positive microbiology laboratory tests as proxy for the underlying disease incidence
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- Geilhufe, Marc
- Held, Leonhard
- Skrøvseth, Stein Olav
- Simonsen, Gunnar S
- Godtliebsen, Fred
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Geilhufe, M., Held, L., Skrøvseth, S. O., Simonsen, G. S., & Godtliebsen, F. (2014). Power law approximations of movement network data for modeling infectious disease spread. Biometrical Journal, 56(3), 363–382. https://doi.org/10.1002/bimj.201200262