A dynamic transmission model to evaluate the effectiveness of infection control strategies

Karim Khader, Alun Thomas, W Charles Huskins, Molly Leecaster, Yue Zhang, Tom Greene, Andrew Redd, Matthew H. Samore

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background. The advancement of knowledge about control of antibiotic resistance depends on the rigorous evaluation of alternative intervention strategies. The STAR*ICU trial examined the effects of active surveillance and expanded barrier precautions on acquisition of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) in intensive care units. We report a reanalyses of the STAR*ICU trial using a Bayesian transmission modeling framework. Methods. The data included admission and discharge times and surveillance test times and results. Markov chain Monte Carlo stochastic integration was used to estimate the transmission rate, importation, false negativity, and clearance separately for MRSA and VRE. The primary outcome was the intervention effect, which when less than (or greater than) zero, indicated a decreased (or increased) transmission rate attributable to the intervention. Results. The transmission rate increased in both arms from pre- to postintervention (by 20% and 26% for MRSA and VRE). The estimated intervention effect was 0.00 (95% confidence interval [CI], -0.57 to 0.56) for MRSA and 0.05 (95% CI, -0.39 to 0.48) for VRE. Compared with MRSA, VRE had a higher transmission rate (preintervention, 0.0069 vs 0.0039; postintervention, 0.0087 vs 0.0046), higher importation probability (0.22 vs 0.17), and a lower clearance rate per colonized patient-day (0.016 vs 0.035). Conclusions. Transmission rates in the 2 treatment arms were statistically indistinguishable from the pre- to postintervention phase, consistent with the original analysis of the STAR*ICU trial. Our statistical framework was able to disentangle transmission from importation and account for imperfect testing. Epidemiological differences between VRE and MRSA were revealed.

Original languageEnglish (US)
Article numberofw247
JournalOpen Forum Infectious Diseases
Volume4
Issue number1
DOIs
StatePublished - 2017

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Methicillin-Resistant Staphylococcus aureus
Infection Control
Confidence Intervals
Markov Chains
Microbial Drug Resistance
Intensive Care Units
Vancomycin-Resistant Enterococci

Keywords

  • Dynamic transmission model
  • Infection control
  • Randomized control trial

ASJC Scopus subject areas

  • Oncology
  • Clinical Neurology

Cite this

A dynamic transmission model to evaluate the effectiveness of infection control strategies. / Khader, Karim; Thomas, Alun; Huskins, W Charles; Leecaster, Molly; Zhang, Yue; Greene, Tom; Redd, Andrew; Samore, Matthew H.

In: Open Forum Infectious Diseases, Vol. 4, No. 1, ofw247, 2017.

Research output: Contribution to journalArticle

Khader, K, Thomas, A, Huskins, WC, Leecaster, M, Zhang, Y, Greene, T, Redd, A & Samore, MH 2017, 'A dynamic transmission model to evaluate the effectiveness of infection control strategies', Open Forum Infectious Diseases, vol. 4, no. 1, ofw247. https://doi.org/10.1093/oid/ofw247
Khader, Karim ; Thomas, Alun ; Huskins, W Charles ; Leecaster, Molly ; Zhang, Yue ; Greene, Tom ; Redd, Andrew ; Samore, Matthew H. / A dynamic transmission model to evaluate the effectiveness of infection control strategies. In: Open Forum Infectious Diseases. 2017 ; Vol. 4, No. 1.
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abstract = "Background. The advancement of knowledge about control of antibiotic resistance depends on the rigorous evaluation of alternative intervention strategies. The STAR*ICU trial examined the effects of active surveillance and expanded barrier precautions on acquisition of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) in intensive care units. We report a reanalyses of the STAR*ICU trial using a Bayesian transmission modeling framework. Methods. The data included admission and discharge times and surveillance test times and results. Markov chain Monte Carlo stochastic integration was used to estimate the transmission rate, importation, false negativity, and clearance separately for MRSA and VRE. The primary outcome was the intervention effect, which when less than (or greater than) zero, indicated a decreased (or increased) transmission rate attributable to the intervention. Results. The transmission rate increased in both arms from pre- to postintervention (by 20{\%} and 26{\%} for MRSA and VRE). The estimated intervention effect was 0.00 (95{\%} confidence interval [CI], -0.57 to 0.56) for MRSA and 0.05 (95{\%} CI, -0.39 to 0.48) for VRE. Compared with MRSA, VRE had a higher transmission rate (preintervention, 0.0069 vs 0.0039; postintervention, 0.0087 vs 0.0046), higher importation probability (0.22 vs 0.17), and a lower clearance rate per colonized patient-day (0.016 vs 0.035). Conclusions. Transmission rates in the 2 treatment arms were statistically indistinguishable from the pre- to postintervention phase, consistent with the original analysis of the STAR*ICU trial. Our statistical framework was able to disentangle transmission from importation and account for imperfect testing. Epidemiological differences between VRE and MRSA were revealed.",
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