Marie Forrester1, Anthony N Pettitt. 1. School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Abstract
OBJECTIVE: To consider statistical methods for estimating transmission rates for colonization of patients with methicillin-resistant Staphylococcus aureus (MRSA) in an intensive care unit (ICU) from three different sources: background contamination, non-isolated patients, and isolated patients. METHODS: We developed statistical methods that allowed for the analysis of interval-censored, routine surveillance data and extended the general epidemic model for the flow of patients through the ICU. RESULTS: Within this ICU, the rate of transmission to susceptible patients from a background source of MRSA (0.0092 case per day; 95% confidence interval [CI95], 0.0062-0.0126) is approximately double the rate of transmission from a non-isolated patient (0.0052 case per day; CI95, 0.0013-0.0096) and six times the rate of transmission from an isolated patient (0.0015 case per day; CI95, 0.0001-0.0043). We used the methodology to investigate whether transmission rates vary with workload. CONCLUSION: Our methodology has general application to infection by and transmission of pathogens in a hospital setting and is appropriate for quantifying the effect of infection control interventions.
OBJECTIVE: To consider statistical methods for estimating transmission rates for colonization of patients with methicillin-resistant Staphylococcus aureus (MRSA) in an intensive care unit (ICU) from three different sources: background contamination, non-isolated patients, and isolated patients. METHODS: We developed statistical methods that allowed for the analysis of interval-censored, routine surveillance data and extended the general epidemic model for the flow of patients through the ICU. RESULTS: Within this ICU, the rate of transmission to susceptible patients from a background source of MRSA (0.0092 case per day; 95% confidence interval [CI95], 0.0062-0.0126) is approximately double the rate of transmission from a non-isolated patient (0.0052 case per day; CI95, 0.0013-0.0096) and six times the rate of transmission from an isolated patient (0.0015 case per day; CI95, 0.0001-0.0043). We used the methodology to investigate whether transmission rates vary with workload. CONCLUSION: Our methodology has general application to infection by and transmission of pathogens in a hospital setting and is appropriate for quantifying the effect of infection control interventions.
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