Estimating the Per-Application Effectiveness of Chlorhexidine Gluconate and Mupirocin in Methicillin-resistant Staphylococcus aureus Decolonization in Intensive Care Units

Introduction Chlorhexidine gluconate and mupirocin are widely used to decolonize patients with methicillin-resistant Staphylococcus aureus (MRSA) and reduce risks of infection in hospitalized populations. The probability that a treated patient would be decolonized, which we term per-application effectiveness, is difficult to directly measure. Quantifying the efficacy of per-application effectiveness of CHG and mupirocin is important for studies evaluating alternative decolonization strategies or schedules as well as identifying whether there is room for improved decolonizing agents. Methods Using a stochastic compartmental model of an intensive care unit (ICU), the per-application effectiveness of chlorhexidine and mupirocin were estimated using approximate Bayesian computation. Extended sensitivity analysis examined the potential impact of a latent period between MRSA colonization and detection, the timing of decolonization administration, and parameter uncertainty. Results The estimated per-application effectiveness of chlorhexidine was 0.15 (95% Credible Interval: 0.01, 0.42), while the estimated effectiveness of mupirocin was is 0.15 (95% CI: 0.01, 0.54). A lag in colonization detection markedly reduced both estimates, which were particularly sensitive to the value to the modeled contact rate between nurses and patients. Gaps longer than 24-hours in the administration of decolonizing agents still resulted in substantial reduction of within-ICU MRSA transmission. Discussion The per-application effectiveness estimates for chlorhexidine and mupirocin suggest there is room for substantial improvement in anti-MRSA disinfectants, either in the compounds themselves, or in their delivery mechanism. Despite these estimates, these agents are robust to delays in administration, which may help in alleviating concerns over patient comfort or toxicity. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the CDC Cooperative Agreement RFA-CK-17-001-Modeling Infectious Diseases in Healthcare Program (MInD-Healthcare). ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Simulation code, data and analysis code is available on a public Github repository.