Events

2022

• hhh4() workshop hosted at the Centre for Mathematical Modelling of Infectious Diseases, London. Material of the tutorial session is available at https://github.com/cmmid/hhh4-workshop/.

2020

• The surveillance package is part of the COVID-19 outbreak response. For example:

  • The nowcast() function is used to provide situational awareness, both in Bavaria and in Berlin.

  • The hhh4() modelling framework has been used in several retrospective studies of disease dynamics in Italy, England, Germany, Italy, Africa (country-level), Italy, and Switzerland and Italy

2019

• The Handbook of Infectious Disease Data Analysis features the surveillance package in several chapters of Part V (“Analysis of Surveillance Data”):

  • twinstim() is mentioned in Chapter 20 on “Applications of Point Process Methods” by Peter J. Diggle.

  • The ?imdepi data is used to illustrate prospective outbreak detection methods, such as earsC(), farrington()/farringtonFlexible(), and stcd(), in Chapter 21 by Benjamin Allévius and Michael Höhle (see replication code).

  • bodaDelay() is mentioned in Chapter 22 on “Underreporting and Reporting Delays” by Angela Noufaily.

  • hhh4() is discussed and applied with a focus on

    • spatio-temporal modelling in Chapter 23 by Jon Wakefield et al., see the replication code applied to the ?measlesWeserEms data
    • forecasting in Chapter 25 by Leonhard Held and Sebastian Meyer, see the replication code applied to count time series of ILI in Switzerland and norovirus gastroenteritis in Berlin (from hhh4contacts::noroBE())

• The paper Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction describes an extension of hhh4() for distributed lags as implemented in the hhh4addon package by Johannes Bracher.

2017

• 2017/05/03: A standard reference describing the spatio-temporal modelling frameworks of the package has appeared in the Journal of Statistical Software: https://doi.org/10.18637/jss.v077.i11. Sections 3 to 5 of this paper are available as
  • vignette("twinstim", package = "surveillance") to analyze a spatio-temporal point pattern of infective events
  • vignette("twinSIR", package = "surveillance") to analyze the susceptible-infectious-recovered (SIR) event history of a fixed population
  • vignette("hhh4_spacetime", package = "surveillance") to analyze areal time series of infectious disease counts

2016

• 2016/11/30: We arranged a small surveillance hackathon as part of the ESCAIDE 2016 conference in Stockholm, Sweden. One output is a set of tutorials on how to use the package.

• 2016/05/20: A standard reference describing the monitoring aspects of the package has appeared in the Journal of Statistical Software: https://doi.org/10.18637/jss.v070.i10. This paper is also available as vignette("monitoringCounts", package = "surveillance").

• 2016/04/13: A paper on model-based testing for space-time interaction using point processes describes a new global test for clustering based on the endemic-epidemic point process model twinstim().

• 2016/03/31: The paper A system for automated outbreak detection of communicable diseases in Germany describes use of the package as backbone for the German infectious disease monitoring system.

• 2016/01/21: The paper Bayesian nowcasting during the STEC O104:H4 outbreak in Germany, 2011, which builds on the surveillance package, won the Best 2014 Paper in Biometrics by an IBS member award. The award will be given at the IBC 2016 in Victoria, Canada.

2015

• 2015/12/03: Working paper on incorporating age-structured social contact data in the spatio-temporal hhh4 model for stratified, areal time series of infectious disease counts: https://arxiv.org/abs/1512.01065

• 2015/09/21: ISDS Webinar on Aberration Detection in Public Health Surveillance using the R package surveillance. (recording, material)

• 2015/07/01: Two talks about the surveillance package given at the useR2015! conference:

  • Zombie Preparedness by Michael Höhle
  • Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance by Sebastian Meyer

2014

• 2014/11/08: Two preprints published on arXiv illustrate the newest package features:
  • Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance
  • Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance

2013

• 2013/04/23: Talk at the Stockholm R useR group (StockholmR) on Making R packages (and) Shiny.

2011

• 2011/10/10-13: Lecture on Temporal and spatio-temporal modelling of infectious diseases at the Department of Statistics, University of Munich

2008

• 2008/11/27-28: Short-course on Statistical surveillance of infectious diseases held at the Department of Statistics, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil

• 2008/11/17: Invited talk held at the 2008 ESCAIDE satellite workshop on Computer supported outbreak detection and signal management (R-File, Data)