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Bibliography

bibliography.Rmd

See Authors and Citation for the two standard JSS references to cite surveillance in publications. This page gives a more comprehensive list of papers feeding surveillance:

  • Held L, Höhle M, Hofmann M (2005). “A statistical framework for the analysis of multivariate infectious disease surveillance counts.” Statistical Modelling, 5(3), 187–199. doi:10.1191/1471082X05st098oa.

  • Paul M, Held L, Toschke AM (2008). “Multivariate modelling of infectious disease surveillance data.” Statistics in Medicine, 27(29), 6250–6267. doi:10.1002/sim.3440.

  • Paul M, Held L (2011). “Predictive assessment of a non-linear random effects model for multivariate time series of infectious disease counts.” Statistics in Medicine, 30(10), 1118–1136. doi:10.1002/sim.4177.

  • Meyer S, Held L (2014). “Power-law models for infectious disease spread.” The Annals of Applied Statistics, 8(3), 1612–1639. doi:10.1214/14-AOAS743.

  • Höhle M (2009). “Additive-multiplicative regression models for spatio-temporal epidemics.” Biometrical Journal, 51(6), 961–978. doi:10.1002/bimj.200900050.

  • Meyer S, Elias J, Höhle M (2012). “A space-time conditional intensity model for invasive meningococcal disease occurrence.” Biometrics, 68(2), 607–616. doi:10.1111/j.1541-0420.2011.01684.x.

  • Meyer S, Warnke I, Rössler W, Held L (2016). “Model-based testing for space-time interaction using point processes: An application to psychiatric hospital admissions in an urban area.” Spatial and Spatio-temporal Epidemiology, 17, 15–25. doi:10.1016/j.sste.2016.03.002.

  • Höhle M (2007). “surveillance: An R package for the monitoring of infectious diseases.” Computational Statistics, 22(4), 571–582. doi:10.1007/s00180-007-0074-8.

  • Höhle M, Paul M (2008). “Count data regression charts for the monitoring of surveillance time series.” Computational Statistics & Data Analysis, 52(9), 4357–4368. doi:10.1016/j.csda.2008.02.015.

  • Manitz J, Höhle M (2013). “Bayesian outbreak detection algorithm for monitoring reported cases of campylobacteriosis in Germany.” Biometrical Journal, 55(4), 509–526. doi:10.1002/bimj.201200141.

  • Salmon M, Schumacher D, Stark K, Höhle M (2015). “Bayesian outbreak detection in the presence of reporting delays.” Biometrical Journal, 57(6), 1051–1067. doi:10.1002/bimj.201400159.

  • Höhle M, an der Heiden M (2014). “Bayesian nowcasting during the STEC O104:H4 outbreak in Germany, 2011.” Biometrics, 70(4), 993–1002. doi:10.1111/biom.12194.

  • Salmon M, Schumacher D, Höhle M (2016). “Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance.” Journal of Statistical Software, 70(10), 1–35. doi:10.18637/jss.v070.i10.

  • Meyer S, Held L, Höhle M (2017). “Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance.” Journal of Statistical Software, 77(11), 1–55. doi:10.18637/jss.v077.i11.