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Statistical epidemic modeling with hospital outbreak data
Author(s) -
Wolkewitz M.,
Dettenkofer M.,
Bertz H.,
Schumacher M.,
Huebner J.
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3419
Subject(s) - outbreak , nonparametric statistics , statistics , transmission (telecommunications) , medicine , epidemiology , computer science , mathematics , virology , telecommunications
The analysis of epidemic data has one special feature: individuals are highly dependent, i.e. infected cases are the cause of further infected cases (cross‐infection). The main epidemiological parameter of interest is the transmission rate: the rate with which an infectious individual has close contacts with other patients in the hospital unit resulting in colonization or infection. In order to estimate this parameter, the statistical analysis should be based on an appropriate compartmental model that describes the transmission dynamics of an epidemic process. Nonparametric methodology is available for closed populations without migration, but especially in hospitals, admission and discharge have to be taken into account in addition. Transmission and discharge have to be considered as competing events. Martingale‐based methodology takes the time‐dependent feature of the rates adequately into account and yields useful estimates. These methods are applied to an outbreak of the specific hospital pathogen vancomycin‐resistant enterococci (VRE) in an onco‐haematological unit at the University Medical Center Freiburg in Germany. Copyright © 2008 John Wiley & Sons, Ltd.