Surveillance

R package surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena: The intention of the R-package surveillance is to provide open source software for the temporal and spatio-temporal visualization, modelling and monitoring of epidemic phenomena. This includes count, binary and categorical data time series as well as continuous-time processes having discrete or continuous spatial resolution.


References in zbMATH (referenced in 30 articles , 3 standard articles )

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  1. Abolhassani, Ali; Prates, Marcos O.: An up-to-date review of scan statistics (2021)
  2. Rodríguez-Berrio, Felipe; Rodríguez-Cortés, Francisco J.; Mateu, Jorge; Adelfio, Giada: On some statistical properties of the spatio-temporal product density (2021)
  3. Waleed Almutiry, Vineetha Warriyar K V, Rob Deardon: Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT (2020) arXiv
  4. Álvaro Briz-Redón, Francisco Martínez-Ruiz, Francisco Montes: DRHotNet: An R package for detecting differential risk hotspots on a linear network (2019) arXiv
  5. Virgilio Gómez-Rubio; Paula Moraga; John Molitor; Barry Rowlingson: DClusterm: Model-Based Detection of Disease Clusters (2019) not zbMATH
  6. Brelsford, Christa; De Bacco, Caterina: Are `water smart landscapes’ contagious? An epidemic approach on networks to study peer effects (2018)
  7. Chris Groendyke; David Welch: epinet: An R Package to Analyze Epidemics Spread across Contact Networks (2018) not zbMATH
  8. Duncan Lee; Alastair Rushworth; Gary Napier: Spatio-Temporal Areal Unit Modeling in R with Conditional Autoregressive Priors Using the CARBayesST Package (2018) not zbMATH
  9. Meyer, Sebastian: Self-exciting point processes: infections and implementations (2018)
  10. Samuel Jenness; Steven Goodreau; Martina Morris: EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks (2018) not zbMATH
  11. Sebastian Meyer and Leonhard Held and Michael Höhle: Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance (2017) not zbMATH
  12. Veloso, Bráulio M.; Correa, Thais R.; Prates, Marcos O.; Oliveira, Gabriel F.; Tavares, Andréa I.: \textitMAD-STEC: a method for multiple automatic detection of space-time emerging clusters (2017)
  13. Wei, Wei; Balabdaoui, Fadoua; Held, Leonhard: Calibration tests for multivariate Gaussian forecasts (2017)
  14. Maëlle Salmon; Dirk Schumacher; Michael Höhle: Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance (2016) not zbMATH
  15. Paiva, Thais; Assunção, Renato; Simões, Taynãna: Prospective space-time surveillance with cumulative surfaces for geographical identification of the emerging cluster (2015)
  16. Salmon, Maëlle; Schumacher, Dirk; Stark, Klaus; Höhle, Michael: Bayesian outbreak detection in the presence of reporting delays (2015)
  17. Höhle, Michael; an der Heiden, Matthias: Bayesian nowcasting during the STEC O104:H4 outbreak in Germany, 2011 (2014)
  18. Meyer, Sebastian; Held, Leonhard: Power-law models for infectious disease spread (2014)
  19. Manitz, Juliane; Höhle, Michael: Bayesian outbreak detection algorithm for monitoring reported cases of campylobacteriosis in Germany (2013)
  20. Mehmood, Rashid; Riaz, Muhammad; Does, Ronald J. M. M.: Efficient power computation for (r) out of (m) runs rules schemes (2013)

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