Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance
Stockholm University, Faculty of Science, Department of Mathematics.
Number of Authors: 3
2017 (English)In: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 77, no 11Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
2017. Vol. 77, no 11
Keyword [en]
spatio-temporal surveillance data, endemic-epidemic modeling, infectious disease epidemiology, self-exciting point process, multivariate time series of counts, branching process with immigration
National Category
Computer and Information Science Mathematics
Identifiers
URN: urn:nbn:se:su:diva-144739DOI: 10.18637/jss.v077.i11ISI: 000401086600001OAI: oai:DiVA.org:su-144739DiVA: diva2:1127876
Available from: 2017-07-20 Created: 2017-07-20 Last updated: 2017-11-29Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Höhle, Michael
By organisation
Department of Mathematics
In the same journal
Journal of Statistical Software
Computer and Information ScienceMathematics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 2 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf