Source avec lien : The Journal of Hospital Infection, Prépublication. 10.1016/j.jhin.2023.07.028
L’objectif de cette étude est d’examiner systématiquement les modèles de transmission du SRAS-CoV-2 dans les établissements de santé et résumer leurs contributions à la compréhension du COVID-19 nosocomial.
BACKGROUND: Since the onset of the COVID-19 pandemic, mathematical models have been widely used to inform public health recommendations regarding COVID-19 control in healthcare settings. OBJECTIVES: To systematically review SARS-CoV-2 transmission models in healthcare settings, and summarize their contributions to understanding nosocomial COVID-19. METHODS: Systematic search and review. DATA SOURCES: Published articles indexed in PubMed. STUDY ELIGIBILITY CRITERIA: Modelling studies describing dynamic inter-individual transmission of SARS-CoV-2 in healthcare settings, published by mid-February 2022. ASSESSMENT OF RISK OF BIAS: Not appropriate for modelling studies. METHODS OF DATA SYNTHESIS: Structured narrative review. RESULTS: Models have mostly focused on acute care and long-term care facilities in high-income countries. Models have quantified outbreak risk, showing great variation across settings and pandemic periods. Regarding surveillance, routine testing rather than symptom-based was highlighted as essential for COVID-19 prevention due to high rates of silent transmission. Surveillance impacts depended critically on testing frequency, diagnostic sensitivity, and turn-around time. Healthcare re-organization also proved to have large epidemiological impacts: beyond obvious benefits of isolating cases and limiting inter-individual contact, more complex strategies (staggered staff scheduling, immune-based cohorting) reduced infection risk. Finally, vaccination impact, while highly effective for limiting COVID-19 burden, varied substantially depending on assumed mechanistic impacts on infection acquisition, symptom onset and transmission. CONCLUSIONS: Modelling results form an extensive evidence base that may inform control strategies for future waves of SARS-CoV-2 and other viral respiratory pathogens. We propose new avenues for future models of healthcare-associated outbreaks, with the aim of enhancing their efficiency and contributions to decision-making.