Healthcare workers are thought to play a role in nosocomial transmission of norovirus, but the level and direction of norovirus transmission between patients and healthcare workers in sustaining transmission during an outbreak have not been quantified.
We developed a method for finding plausible transmission trees of who acquired their infection from whom. We applied the method to data from an outbreak of norovirus in 4 wards of a psychiatric institution in the Netherlands in 2008. The simulated transmission trees were based on serial intervals for time between symptom onsets, weighted for the number of days that healthcare workers were present. The obtained transmission trees were linked to the Barthel Index, a measure of patient reliance on healthcare in their basic daily activities.
The dominant recognized transmission route was from patient to patient (64%), followed by patient to healthcare worker (29%). The overall estimated reproduction number for healthcare workers was low compared with patients (0.25 vs. 1.20; mean difference = 0.95 [95% confidence interval (CI) = 0.60 to 1.30]). The average number of all subsequent cases attributable to the downstream branch of one single infected healthcare worker in the transmission tree was 4.4 compared with 6.5 for cases attributable to one single infected patient (mean difference = 2.1 [95% CI = −4.7 to 8.9]). In the ward with patients requiring the highest level of care from healthcare workers, the attack rate among healthcare workers was highest.
This approach provides a framework to quantify the magnitude and direction of transmission between healthcare workers and patients during a norovirus outbreak. The utility of this method in outbreaks of other infections and in different settings should be explored.
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From the aDivision of Clinical Epidemiology & Biostatistics, Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland; bEpidemiology and Surveillance Unit, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands; cEuropean Programme for Intervention Epidemiology Training (EPIET), European Centre for Disease Prevention and Control (ECDC), Stockholm, Sweden; dLaboratory for Infectious Diseases and Perinatal Screening, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands; eJulius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands; fVirology Department, Erasmus MC, Rotterdam, the Netherlands; and gHubert Department of Global Health, Rollins school of Public Health, Emory University, Atlanta, GA.
Submitted 1 June 2011; accepted 5 October 2011.
Supported by Swiss National Science Foundation (grant numbers 320030_118424 and 320030_135654) (to J.C.M.H.). The authors reported no other financial interests related to this research.
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Correspondence: Janneke Heijne, Division of Clinical Epidemiology & Biostatistics, Institute of Social and Preventive Medicine (ISPM), University of Bern, Finkenhubelweg 11, CH-3012, Bern, Switzerland. E-mail: firstname.lastname@example.org.