Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance

Internet publication

Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the COVID-19 pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. Yet collateral impacts of pandemic COVID-19 on MRB epidemiology remain poorly understood. Here, we present a dynamic transmission model in which SARS-CoV-2 and MRB co-circulate among patients and staff in a hospital population in an early pandemic context. Responses to SARS-CoV-2 outbreaks are captured mechanistically, reflecting impacts on factors relevant for MRB transmission, including contact behaviour, hand hygiene compliance, antibiotic prescribing and population structure. In a first set of simulations, broad parameter ranges are accounted for, representative of diverse bacterial species and hospital settings. On average, COVID-19 control measures coincide with MRB prevention, including fewer incident cases and fewer cumulative person-days of patient MRB colonization. However, surges in COVID-19 caseloads favour MRB transmission and lead to increased rates of antibiotic resistance, especially in the absence of concomitant control measures. In a second set of simulations, methicillin-resistant Staphylococcus aureus and extended-spectrum beta-lactamase-producing Escherichia coli are simulated in specific hospital wards and pandemic response scenarios. Antibiotic resistance dynamics are highly context-specific in these cases, and SARS-CoV-2 outbreaks significantly impact bacterial epidemiology only in facilities with high underlying risk of bacterial transmission. Crucially, antibiotic resistance burden is reduced in facilities with timelier, more effective implementation of COVID-19 control measures. This highlights the control of antibiotic resistance as an important collateral benefit of robust pandemic preparedness.

Significance Statement Impacts of COVID-19 on the spread of antibiotic resistance are poorly understood. Here, an epidemiological model accounting for the simultaneous spread of SARS-CoV-2 and antibiotic-resistant bacteria is presented. The model is tailored to healthcare settings during the first wave of the COVID-19 pandemic, and accounts for hand hygiene, inter-individual contact behaviour, and other factors relevant for pathogen spread. Simulations demonstrate that public health policies enacted to slow the spread of COVID-19 also tend to limit bacterial transmission. However, surges in COVID-19 cases simultaneously select for higher rates of antibiotic resistance. Selection for resistance is thus mitigated by prompt implementation of effective COVID-19 prevention policies. This highlights the control of antibiotic resistance as an important collateral benefit of pandemic preparedness.

Authors: Smith, DRM; Shirreff, G; Temime, L; Opatowski, L

• Publication status: Published
• Peer review status: Not peer reviewed
• Host title: bioRxiv
• Publication date: 2022-08-16
• DOI: 10.1101/2022.08.15.503946
• Language: English
• Keywords: computer simulation; healthcare-associated infection; mathematical 27 modelling; co-infection; transmission dynamics