Cost-effectiveness of screening, decolonisation and isolation strategies for carbapenem-resistant Enterobacterales and methicillin-resistant <i>Staphylococcus aureus</i> infections in hospitals: a sex-stratified mathematical modelling study

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Summary

Background

Methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Enterobacterales (CRE) impose the greatest burden among critical bacterial pathogens. Evidence for sex differences among antibiotic resistant bacterial infections is increasing but a focus on policy implications is needed. We assessed impact of CRE/MRSA on excess length of hospital stay, intensive care unit admission, and mortality by sex from a retrospective cohort study (n = 873) of patients in three Chilean hospitals, 2018–2021.

Methods

We used inverse-probability weighting combined with descriptive, logistic, and competing-risks analyses. We developed a sex-stratified deterministic compartmental model to analyse hospital transmission dynamics and the cost-effectiveness of nine interventions. We compared interventions based on the incremental cost-effectiveness ratio (ICER) per quality-adjusted life year (QALY) gained and estimated net benefits.

Findings

The adjusted odds of women acquiring CRE and MRSA were 0.44 (0.28–0.70; p = 0.0013) and 0.73 (95% CI = 0.48–1.01; p = 0.050), respectively. Competing-risk models indicated higher mortality rates among women, compared to men. Mathematical model projections showed that pre-emptive isolation across all newly admitted high-risk men was the most cost-effective intervention (ICER = $1366/QALY and $1083/QALY for CRE and MRSA, respectively). Chromogenic agar coupled with MRSA decolonisation was the second most cost-effective intervention ($2099/QALY), followed by screening plus isolation or pre-emptive isolation strategies (ICER ranged between $2411/QALY and $4216/QALY across CRE and MRSA models). Probabilistic sensitivity analysis showed that strategies were ICER < willingness-to-pay in 80% of simulations, except for testing plus digestive decolonisation for CRE. At a 20% national hospital coverage at least $12.2 million could be saved.

Interpretation

Our model suggests that targeted infection control strategies would effectively address rising CRE and MRSA infections. Maximising health-economic gains may be achieved by focusing on control measures for men as primary drivers for transmission, thereby reducing the disproportionate disease burden borne by women.

Funding

Agencia Nacional de Investigación y Desarrollo doi 10.13039/501100020884, ANID; , Chile.

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Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

(2022)

Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

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A methodology for performing global uncertainty and sensitivity analysis in systems biology.

Simeone Marino, Ian B Hogue, Christian J Ray … (2008)

Accuracy of results from mathematical and computer models of biological systems is often complicated by the presence of uncertainties in experimental data that are used to estimate parameter values. Current mathematical modeling approaches typically use either single-parameter or local sensitivity analyses. However, these methods do not accurately assess uncertainty and sensitivity in the system as, by default, they hold all other parameters fixed at baseline values. Using techniques described within we demonstrate how a multi-dimensional parameter space can be studied globally so all uncertainties can be identified. Further, uncertainty and sensitivity analysis techniques can help to identify and ultimately control uncertainties. In this work we develop methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models. We compare two specific types of global sensitivity analysis indexes that have proven to be among the most robust and efficient. Through familiar and new examples of mathematical and computer models, we provide a complete methodology for performing these analyses, in both deterministic and stochastic settings, and propose novel techniques to handle problems encountered during these types of analyses.

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Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement

D Husereau, M. Drummond, S. Petrou … (2013)

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Author and article information

Contributors

Kasim Allel

Journal

Journal ID (nlm-ta): Lancet Reg Health Am

Journal ID (iso-abbrev): Lancet Reg Health Am

Title: Lancet Regional Health - Americas

Publisher: Elsevier

ISSN (Electronic): 2667-193X

Publication date PMC-release: 15 February 2025

Publication date Collection: March 2025

Publication date (Electronic): 15 February 2025

Volume: 43

Electronic Location Identifier: 101019

Affiliations

[a ]Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxfordshire, United Kingdom

[b ]School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile

[c ]Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom

[d ]Genomics and Resistant Microbes (GeRM), Facultad de Medicina Clínica Alemana, Instituto de Ciencias e Innovación en Medicina (ICIM), Universidad del Desarrollo, Santiago, Chile

[e ]School of Government, Pontificia Universidad Católica de Chile, Santiago, Chile

[f ]Research Center for Integrated Disaster Risk Management (CIGIDEN), Chile

Author notes

[∗ ]Corresponding author. Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX26GG, Oxfordshire, United Kingdom. kasim.allelhenriquez@ 123456phc.ox.ac.uk

Article

Publisher Item ID: S2667-193X(25)00029-8 Publisher ID: 101019

DOI: 10.1016/j.lana.2025.101019

PMC ID: 11872075

PubMed ID: 40027374

SO-VID: 1efc3041-ff69-4095-8815-02afcf6b1ea3

License:

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

History

Date received : 20 July 2024

Date revision received : 25 December 2024

Date accepted : 26 January 2025

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Cost-effectiveness of screening, decolonisation and isolation strategies for carbapenem-resistant Enterobacterales and methicillin-resistant Staphylococcus aureus infections in hospitals: a sex-stratified mathematical modelling study

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