PT  - JOURNAL ARTICLE
AU  - Niklas Willrich
AU  - Sebastian Haller
AU  - Tim Eckmanns
AU  - Benedikt Zacher
AU  - Tommi Kärki
AU  - Diamantis Plachouras
AU  - Alessandro Cassini
AU  - Carl Suetens
AU  - Michael Behnke
AU  - Petra Gastmeier
AU  - Jan Walter
TI  - From prevalence to incidence - a new approach in the hospital setting
AID  - 10.1101/554725
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 554725
4099  - http://biorxiv.org/content/early/2019/02/22/554725.short
4100  - http://biorxiv.org/content/early/2019/02/22/554725.full
AB  - Point-prevalence surveys (PPSs) are often used to estimate the prevalence of healthcare-associated infections (HAIs). Methods for estimating incidence of HAIs from prevalence have been developed, but application of these methods is often difficult because key quantities, like the average length of infection, cannot be derived directly from the data available in a PPS. We propose a new theory-based method to estimate incidence from prevalence data dealing with these limitations and compare it to other estimation methods in a simulation study. In contrast to previous methods, our method does not depend on any assumptions on the underlying distributions of length of infection and length of stay. As a basis for the simulation study we use data from the second study of nosocomial infections in Germany (Nosokomiale Infektionen in Deutschland, Erfassung und Prävention - NIDEP2) and the European surveillance of HAIs in intensive care units (HAI-Net ICU). The new method compares favourably with the other estimation methods and has the advantage of being consistent in its behaviour across the different setups. It is implemented in an R-package prevtoinc which will be freely available on CRAN (http://cran.r-project.org/).CDC–Centers for Disease Control and PreventionECDC–European for Disease Control and PreventionHAI–healthcare-associated infectionHAI-Net ICU–European surveillance of HAIs in intensive care unitsNIDEP2–second study of nosocomial infections in Germany (Nosokomiale Infektionen in Deutschland, Erfassung und Prävention)PPS–point-prevalence survey RMSD - root mean squared deviation