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Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance
Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.ORCID-id: 0000-0002-0423-6702
Rekke forfattare: 32017 (engelsk)Inngår i: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 77, nr 11Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surveillance can handle various levels of aggregation at which infective events have been recorded: individual-level time-stamped geo-referenced data (case reports) in either continuous space or discrete space, as well as counts aggregated by period and region. For each of these data types, the surveillance package implements tools for visualization, likelihoood inference and simulation from recently developed statistical regression frameworks capturing endemic and epidemic dynamics. Altogether, this paper is a guide to the spatio-temporal modeling of epidemic phenomena, exemplified by analyses of public health surveillance data on measles and invasive meningococcal disease.

sted, utgiver, år, opplag, sider
2017. Vol. 77, nr 11
Emneord [en]
spatio-temporal surveillance data, endemic-epidemic modeling, infectious disease epidemiology, self-exciting point process, multivariate time series of counts, branching process with immigration
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-144739DOI: 10.18637/jss.v077.i11ISI: 000401086600001OAI: oai:DiVA.org:su-144739DiVA, id: diva2:1127876
Tilgjengelig fra: 2017-07-20 Laget: 2017-07-20 Sist oppdatert: 2019-12-04bibliografisk kontrollert

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