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Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance

Publikationsart Peer-reviewed
Publikationsform Originalbeitrag (peer-reviewed)
Autor/in Meyer Sebastian, Held Leonhard, Höhle Michael,
Projekt Statistical methods for spatio-temporal modelling and prediction of infectious diseases
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Originalbeitrag (peer-reviewed)

Zeitschrift Journal of Statistical Software
Titel der Proceedings Journal of Statistical Software

Open Access

URL https://arxiv.org/abs/1411.0416
OA-Form Repositorium (Green Open Access)

Abstract

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.
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