Modelling methicillin-resistant Staphylococcus aureus decolonization: interactions between body sites and the impact of site-specific clearance

Decolonization in Nursing Homes to Prevent Infection and Hospitalization

BACKGROUND

Nursing home residents are at high risk for infection, hospitalization, and colonization with multidrug-resistant organisms.

METHODS

We performed a cluster-randomized trial of universal decolonization as compared with routine-care bathing in nursing homes. The trial included an 18-month baseline period and an 18-month intervention period. Decolonization entailed the use of chlorhexidine for all routine bathing and showering and administration of nasal povidone-iodine twice daily for the first 5 days after admission and then twice daily for 5 days every other week. The primary outcome was transfer to a hospital due to infection. The secondary outcome was transfer to a hospital for any reason. An intention-to-treat (as-assigned) difference-in-differences analysis was performed for each outcome with the use of generalized linear mixed models to compare the intervention period with the baseline period across trial groups.

RESULTS

Data were obtained from 28 nursing homes with a total of 28,956 residents. Among the transfers to a hospital in the routine-care group, 62.2% (the mean across facilities) were due to infection during the baseline period and 62.6% were due to infection during the intervention period (risk ratio, 1.00; 95% confidence interval [CI], 0.96 to 1.04). The corresponding values in the decolonization group were 62.9% and 52.2% (risk ratio, 0.83; 95% CI, 0.79 to 0.88), for a difference in risk ratio, as compared with routine care, of 16.6% (95% CI, 11.0 to 21.8; P<0.001). Among the discharges from the nursing home in the routine-care group, transfer to a hospital for any reason accounted for 36.6% during the baseline period and for 39.2% during the intervention period (risk ratio, 1.08; 95% CI, 1.04 to 1.12). The corresponding values in the decolonization group were 35.5% and 32.4% (risk ratio, 0.92; 95% CI, 0.88 to 0.96), for a difference in risk ratio, as compared with routine care, of 14.6% (95% CI, 9.7 to 19.2). The number needed to treat was 9.7 to prevent one infection-related hospitalization and 8.9 to prevent one hospitalization for any reason.

CONCLUSIONS

In nursing homes, universal decolonization with chlorhexidine and nasal iodophor led to a significantly lower risk of transfer to a hospital due to infection than routine care. (Funded by the Agency for Healthcare Research and Quality; Protect ClinicalTrials.gov number, NCT03118232.).

Inferring longitudinal patterns of group B Streptococcus colonization during pregnancy

Maternal colonization by Group B Streptococcus (GBS) can lead to severe infection in neonates and has also been associated with prematurity and stillbirth. Better quantitative understanding of the trajectories of GBS carriage during pregnancy is essential for the design of informative epidemiological studies. Here, we describe analyses of published longitudinal data using Bayesian hidden Markov models, which involve the estimation of parameters related to the succession of latent states (infection status) and observations (culture positivity). In addition to quantifying infection acquisition and clearance probabilities, the statistical approach also suggests that for some longitudinal patterns of culture results, pregnant women were likely to have been GBS-colonized despite a negative diagnostic result. We believe this method, if used in future longitudinal studies of maternal GBS colonization, would improve our understanding of the pathologies linked to this bacterium and could also inform maternal GBS vaccine trial design.

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study

BACKGROUND

Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. We sought to evaluate how such collateral impacts of COVID-19 impacted the nosocomial spread of MRB in an early pandemic context.

METHODS AND FINDINGS

We developed a mathematical model in which Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and MRB cocirculate among patients and staff in a theoretical hospital population. Responses to COVID-19 were captured mechanistically via a range of parameters that reflect impacts of SARS-CoV-2 outbreaks on factors relevant for pathogen transmission. COVID-19 responses include both "policy responses" willingly enacted to limit SARS-CoV-2 transmission (e.g., universal masking, patient lockdown, and reinforced hand hygiene) and "caseload responses" unwillingly resulting from surges in COVID-19 caseloads (e.g., abandonment of antibiotic stewardship, disorganization of infection control programmes, and extended length of stay for COVID-19 patients). We conducted 2 main sets of model simulations, in which we quantified impacts of SARS-CoV-2 outbreaks on MRB colonization incidence and antibiotic resistance rates (the share of colonization due to antibiotic-resistant versus antibiotic-sensitive strains). The first set of simulations represents diverse MRB and nosocomial environments, accounting for high levels of heterogeneity across bacterial parameters (e.g., rates of transmission, antibiotic sensitivity, and colonization prevalence among newly admitted patients) and hospital parameters (e.g., rates of interindividual contact, antibiotic exposure, and patient admission/discharge). On average, COVID-19 control policies coincided with MRB prevention, including 28.2% [95% uncertainty interval: 2.5%, 60.2%] fewer incident cases of patient MRB colonization. Conversely, surges in COVID-19 caseloads favoured MRB transmission, resulting in a 13.8% [-3.5%, 77.0%] increase in colonization incidence and a 10.4% [0.2%, 46.9%] increase in antibiotic resistance rates in the absence of concomitant COVID-19 control policies. When COVID-19 policy responses and caseload responses were combined, MRB colonization incidence decreased by 24.2% [-7.8%, 59.3%], while resistance rates increased by 2.9% [-5.4%, 23.2%]. Impacts of COVID-19 responses varied across patients and staff and their respective routes of pathogen acquisition. The second set of simulations was tailored to specific hospital wards and nosocomial bacteria (methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase producing Escherichia coli). Consequences of nosocomial SARS-CoV-2 outbreaks were found to be highly context specific, with impacts depending on the specific ward and bacteria evaluated. In particular, SARS-CoV-2 outbreaks significantly impacted patient MRB colonization only in settings with high underlying risk of bacterial transmission. Yet across settings and species, antibiotic resistance burden was reduced in facilities with timelier implementation of effective COVID-19 control policies.

CONCLUSIONS

Our model suggests that surges in nosocomial SARS-CoV-2 transmission generate selection for the spread of antibiotic-resistant bacteria. Timely implementation of efficient COVID-19 control measures thus has 2-fold benefits, preventing the transmission of both SARS-CoV-2 and MRB, and highlighting antibiotic resistance control as a collateral benefit of pandemic preparedness.