Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting

Pople, Diane; Kypraios, Theodore; Donker, Tjibbe; Stoesser, Nicole; Seale, Anna C.; George, Ryan; Dodgson, Andrew; Freeman, Rachel; Hope, Russell; Walker, Ann Sarah; Hopkins, Susan; Robotham, Julie

Abstract

Background
Globally, detections of carbapenemase-producing Enterobacterales (CPE) colonisations and infections are increasing. The spread of these highly resistant bacteria poses a serious threat to public health. However, understanding of CPE transmission and evidence on effectiveness of control measures is severely lacking. This paper provides evidence to inform effective admission screening protocols, which could be important in controlling nosocomial CPE transmission.

Methods
CPE transmission within an English hospital setting was simulated with a data-driven individual-based mathematical model. This model was used to evaluate the ability of the 2016 England CPE screening recommendations, and of potential alternative protocols, to identify patients with CPE-colonisation on admission (including those colonised during previous stays or from elsewhere). The model included nosocomial transmission from colonised and infected patients, as well as environmental contamination. Model parameters were estimated using primary data where possible, including estimation of transmission using detailed epidemiological data within a Bayesian framework. Separate models were parameterised to represent hospitals in English areas with low and high CPE risk (based on prevalence).

Results
The proportion of truly colonised admissions which met the 2016 screening criteria was 43% in low-prevalence and 54% in high-prevalence areas respectively. Selection of CPE carriers for screening was improved in low-prevalence areas by adding readmission as a screening criterion, which doubled how many colonised admissions were selected. A minority of CPE carriers were confirmed as CPE positive during their hospital stay (10 and 14% in low- and high-prevalence areas); switching to a faster screening test pathway with a single-swab test (rather than three swab regimen) increased the overall positive predictive value with negligible reduction in negative predictive value.

Conclusions
Using a novel within-hospital CPE transmission model, this study assesses CPE admission screening protocols, across the range of CPE prevalence observed in England. It identifies protocol changes—adding readmissions to screening criteria and a single-swab test pathway—which could detect similar numbers of CPE carriers (or twice as many in low CPE prevalence areas), but faster, and hence with lower demand on pre-emptive infection-control resources. Study findings can inform interventions to control this emerging threat, although further work is required to understand within-hospital transmission sources.

Citation

Pople, D., Kypraios, T., Donker, T., Stoesser, N., Seale, A. C., George, R., Dodgson, A., Freeman, R., Hope, R., Walker, A. S., Hopkins, S., & Robotham, J. (2023). Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting. BMC Medicine, 21(1), Article 492. https://doi.org/10.1186/s12916-023-03007-1

• Journal Article Type: Article
• Acceptance Date: Jul 27, 2023
• Online Publication Date: Dec 12, 2023
• Publication Date: Dec 12, 2023
• Deposit Date: Dec 14, 2023
• Publicly Available Date: Dec 14, 2023
• Journal: BMC Medicine
• Electronic ISSN: 1741-7015
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 21
• Issue: 1
• Article Number: 492
• DOI: https://doi.org/10.1186/s12916-023-03007-1
• Keywords: Mathematical model, Screening, Nosocomial transmission, Carbapenemase-producing Enterobacterales
• Public URL: https://nottingham-repository.worktribe.com/output/28430394
• Publisher URL: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-023-03007-1
• Additional Information: Ethics approval was not required for this computational modelling study. The linked data from a UK hospital analysed in the transmission parameterisation model were sourced from a study which did not require individual participant consent and research ethics committee approval as it used routinely collected hospital admission and laboratory data for a service evaluation and data were anonymised prior to analysis.; : Not applicable.; : The authors declare that they have no competing interests.