Association of Visitor Contact Precautions With Estimated Hospital-Onset <i>Clostridioides difficile</i> Infection Rates in Acute Care Hospitals

Scaria, Elizabeth; Barker, Anna; Alagöz, Oğuzhan; Safdar, Nasia

doi:10.1001/jamanetworkopen.2021.0361

Cited by 6 publications

(4 citation statements)

References 35 publications

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“…Barker (2020) 76 Conduct comparative-effectiveness studies to identify optimal methods for audit and feedback to improve cleaning and disinfection. Scaria (2021) 77 Ziegler (2022) 78 What is the role of enhanced terminal cleaning using novel technology on HAI and MDRO infection rates? Rock (2022) 71 Determine the frequency and sites of UV-C room device use in VA facilities and develop effective strategies to monitor use.…”

Section: Biosurveillancementioning

confidence: 99%

Research agenda for transmission prevention within the Veterans Health Administration, 2024–2028

Smith,

Crnich,

Donskey

et al. 2024

Infect. Control Hosp. Epidemiol.

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Section: Biosurveillancementioning

confidence: 99%

Research agenda for transmission prevention within the Veterans Health Administration, 2024–2028

Smith,

Crnich,

Donskey

et al. 2024

Infect. Control Hosp. Epidemiol.

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“…Each set of 5000 replications of the ABM required roughly one hour on a single desktop computer with an Intel Core i5-8500 CPU and 16GB RAM. Further details of the generic ABM are available in previous publications [5,8,20].…”

Section: Overview Of the Existing Agent-based Simulation Model Develo...mentioning

confidence: 99%

Validating agent-based simulation model of hospital-associated Clostridioides difficile infection using primary hospital data

2023

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As agent-based models (ABMs) are increasingly used for modeling infectious diseases, model validation is becoming more crucial. In this study, we present an alternate approach to validating hospital ABMs that focuses on replicating hospital-specific conditions and proposes a new metric for validating the social-environmental network structure of ABMs. We adapted an established ABM representing Clostridioides difficile infection (CDI) spread in a generic hospital to a 426-bed Midwestern academic hospital. We incorporated hospital-specific layout, agent behaviors, and input parameters estimated from primary hospital data into the model, referred to as H-ABM. We compared the predicted CDI rate against the observed rate from 2013–2018. We used colonization pressure, a measure of nearby infectious agents, to validate the socio-environmental agent networks in the ABM. Finally, we conducted additional experiments to compare the performance of individual infection control interventions in the H-ABM and the generic model. We find that the H-ABM is able to replicate CDI trends during 2013–2018, including a roughly 46% drop during a period of greater infection control investment. High CDI burden in socio-environmental networks was associated with a significantly increased risk of C. difficile colonization or infection (Risk ratio: 1.37; 95% CI: [1.17, 1.59]). Finally, we found that several high-impact infection control interventions have diminished impact in the H-ABM. This study presents an alternate approach to validation of ABMs when large-scale calibration is not appropriate for specific settings and proposes a new metric for validating socio-environmental network structure of ABMs. Our findings also demonstrate the utility of hospital-specific modeling.

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“…Intervention 7 (testing and cohorting symptomatic patients on admission) was reversed by allowing patients to be admitted into any ward regardless of their SARS-CoV-2 status. Intervention 8 (suspension of visitors) was reversed by allowing up to two visitors per patient per day as described by [19], and assuming that each visitor stayed for an average of 14 minutes, constituting a transmission risk of 0.00125 per minute of visit [20,21]. Intervention 9 (decreased occupancy) was reversed by increasing modelled occupancy to re ect that observed in the NHS historically, allowing up to 85% of beds to be occupied [22].…”

Section: Modelling the Counterfactual By 'Reversal' Of Interventionsmentioning

confidence: 99%

Efficacy of interventions to reduce nosocomial transmission of SARS-CoV-2 in English NHS Trusts in Wave 1: A computational modelling study

Evans¹,

White

Wilcox

et al. 2021

Preprint

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Nosocomial transmission of SARS-CoV-2 has the potential to place a large burden on the healthcare system through, for example, increased patient length of stay, pressure on specialist care capacity and staff shortages. In England, a number of interventions were applied in hospitals over wave 1 of the COVID-19 pandemic to limit the spread of SARS-CoV-2 among both hospital inpatients and healthcare workers (HCWs). Using a computational modelling approach, we have estimated the combined effect of these, and other changes within the hospital setting, to determine how many nosocomial infections were averted. While highly uncertain, due primarily to important gaps in the evidence base, model results suggest that in a scenario with high occupancy, no testing, reduced infection prevention and control (IPC) measures, increased visitors, and longer patient stays, approximately 5.2% (3.9-7.2%) of all susceptible inpatients (n=140,603; 95% CI, 89,352-197,977 patients in total), and 51.1% (43.6, 55.3%) of patient-facing HCWs could have been nosocomially infected with SARS-CoV-2 over wave 1 compared with the 1.0% (0.7, 1.2%) of patients (33,922; 24,089- 41,015) and 20.3% (15.8-29.4%) of HCW observed to be nosocomially infected. The most effective interventions for prevention of nosocomial infections in patients were decreasing occupancy, increasing spacing between beds, and testing patients on admission, resulting in a reduction of 23,434 (14,544, 31,341), 10,979 (2,458, 16,979), and 9,505, (4588, 12,823) infections, respectively. Although every intervention had some impact, it was the collective impact of all interventions that demonstrated greatest effect, averting 140,603 (89,352, 197,977) infections in inpatients. In HCWs, the most effective intervention was universal mask use, with inclusion of universal masking as part of IPC measures averting 46.0% (42.9-54.5%) of infections in HCWs resulting in 17,980 (2,772-28,450) fewer infections per 100,000 patient-facing HCWs. Interventions introduced over wave 1 of the SARS-CoV-2 pandemic in England reduced HCW infection rates by 51.1% (43.6-55.3%).

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Association of Visitor Contact Precautions With Estimated Hospital-Onset Clostridioides difficile Infection Rates in Acute Care Hospitals

Abstract: This simulation study estimates the association between visitor contact precautions and the rate of hospital-onset C difficile infection in an acute care hospital.

Cited by 6 publications

References 35 publications

Research agenda for transmission prevention within the Veterans Health Administration, 2024–2028

Research agenda for transmission prevention within the Veterans Health Administration, 2024–2028

Validating agent-based simulation model of hospital-associated Clostridioides difficile infection using primary hospital data

Efficacy of interventions to reduce nosocomial transmission of SARS-CoV-2 in English NHS Trusts in Wave 1: A computational modelling study

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