Predicting consequences of COVID-19 control measure de-escalation on nosocomial transmission and mortality: a modelling study in a French rehabilitation hospital.

COVID-19 agent-based model infection prevention and control risk assessment simulation model transmission dynamics

Journal

The Journal of hospital infection
ISSN: 1532-2939
Titre abrégé: J Hosp Infect
Pays: England
ID NLM: 8007166

Informations de publication

Date de publication:
09 Mar 2024
Historique:
received: 30 10 2023
revised: 13 02 2024
accepted: 21 02 2024
medline: 12 3 2024
pubmed: 12 3 2024
entrez: 11 3 2024
Statut: aheadofprint

Résumé

Infection control measures are effective for nosocomial COVID-19 prevention but bear substantial health-economic costs, motivating their "de-escalation" in settings at low risk of SARS-CoV-2 transmission. Yet consequences of de-escalation are difficult to predict, particularly in light of novel variants and heterogeneous population immunity. To estimate how infection control measure de-escalation influences nosocomial COVID-19 risk. An individual-based transmission model was used to simulate SARS-CoV-2 outbreaks and control measure de-escalation in a French long-term care hospital with multi-modal control measures in place (testing and isolation, universal masking, single-occupant rooms). Estimates of COVID-19 case fatality rates (CFRs) from reported outbreaks were used to quantify excess COVID-19 mortality due to de-escalation. In a population fully susceptibility to infection, de-escalating both universal masking and single rooms resulted in hospital-wide outbreaks of 114 (95% CI: 103-125) excess infections, compared to 5 (3-7) excess infections when de-escalating only universal masking or 15 (11-18) when de-escalating only single rooms. When de-escalating both measures and applying CFRs from the first wave of COVID-19, excess patient mortality ranged from 1.57 (1.41-1.71) to 9.66 (8.73-10.57) excess deaths/1,000 patient-days. By contrast, when applying CFRs from subsequent pandemic waves and assuming susceptibility to infection among 40-60% of individuals, excess mortality ranged from 0 (0-0) to 0.92 (0.77-1.07) excess deaths/1,000 patient-days. The de-escalation of bundled COVID-19 control measures may facilitate widespread nosocomial SARS-CoV-2 transmission. However, excess mortality is likely limited in populations at least moderately immune to infection and given CFRs resembling those estimated during the "post-vaccine" era.

Identifiants

pubmed: 38467250
pii: S0195-6701(24)00078-1
doi: 10.1016/j.jhin.2024.02.020
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None declared.

Auteurs

David R M Smith (DRM)

Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom. Electronic address: david.smith@ndph.ox.ac.uk.

Audrey Duval (A)

Epidemiology & Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris-Cité, Paris, France; Anti-Infective Evasion & Pharmacoepidemiology, Université Paris-Saclay, UVSQ, Inserm, CESP, Montigny-Le-Bretonneux, France; Laboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris, France.

Rebecca Grant (R)

Faculty of Medicine, University of Geneva, Geneva, Switzerland; Infection Control Programme & WHO Collaborating Centre on Infection Prevention and Control and Antimicrobial Resistance, Geneva University Hospitals, Geneva, Switzerland.

Mohamed Abbas (M)

Faculty of Medicine, University of Geneva, Geneva, Switzerland; Infection Control Programme & WHO Collaborating Centre on Infection Prevention and Control and Antimicrobial Resistance, Geneva University Hospitals, Geneva, Switzerland; MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom.

Stephan Harbarth (S)

Faculty of Medicine, University of Geneva, Geneva, Switzerland; Infection Control Programme & WHO Collaborating Centre on Infection Prevention and Control and Antimicrobial Resistance, Geneva University Hospitals, Geneva, Switzerland.

Lulla Opatowski (L)

Epidemiology & Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris-Cité, Paris, France; Anti-Infective Evasion & Pharmacoepidemiology, Université Paris-Saclay, UVSQ, Inserm, CESP, Montigny-Le-Bretonneux, France.

Laura Temime (L)

Laboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris, France.

Classifications MeSH