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Antibiotic resistance in hospitals: a ward‐specific random effect model in a low antibiotic consumption environment
Authors:Magne Aldrin  Ragnhild Raastad  Ingunn Fride Tvete  Dag Berild  Arnoldo Frigessi  Truls Leegaard  Dominique L. Monnet  Mette Walberg  Fredrik Müller
Affiliation:1. The Norwegian Computing Center, , Oslo, Norway;2. Oslo University Hospital, , Oslo, Norway;3. Institute of Clinical Medicine, University of Oslo, , Oslo, Norway;4. Department of Biostatistics, University of Oslo, , Oslo, Norway;5. Akershus University Hospital, , Oslo, Norway;6. European Center for Disease Prevention and Control, , Stockholm, Sweden;7. Department of Infection Control, Vestre Viken Hospital Trust, , B?rum, Norway
Abstract:Association between previous antibiotic use and emergence of antibiotic resistance has been reported for several microorganisms. The relationship has been extensively studied, and although the causes of antibiotic resistance are multi‐factorial, clear evidence of antibiotic use as a major risk factor exists. Most studies are carried out in countries with high consumption of antibiotics and corresponding high levels of antibiotic resistance, and currently, little is known whether and at what level the associations are detectable in a low antibiotic consumption environment. We conduct an ecological, retrospective study aimed at determining the impact of antibiotic consumption on antibiotic‐resistant Pseudomonas aeruginosa in three hospitals in Norway, a country with low levels of antibiotic use. We construct a sophisticated statistical model to capture such low signals. To reduce noise, we conduct our study at hospital ward level. We propose a random effect Poisson or binomial regression model, with a reparametrisation that allows us to reduce the number of parameters. Inference is likelihood based. Through scenario simulation, we study the potential effects of reduced or increased antibiotic use. Results clearly indicate that the effects of consumption on resistance are present under conditions with relatively low use of antibiotic agents. This strengthens the recommendation on prudent use of antibiotics, even when consumption is relatively low. Copyright © 2012 John Wiley & Sons, Ltd.
Keywords:antibiotics  resistance  scenario analysis  Poisson regression  binomial regression
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