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Enregistrement W3163175611 · doi:10.1101/2021.05.17.21257315

Impact of non-pharmaceutical interventions on SARS-CoV-2 outbreaks in English care homes: a modelling study

2021· preprint· en· W3163175611 sur OpenAlexfundaboutno aff
Alicia Roselló, Rosanna C. Barnard, David R. Smith, Stephanie Evans, Fiona Grimm, Nicholas G. Davies, Sarah R Deeny, Gwenan M. Knight, W. John Edmunds

Notice bibliographique

RevuemedRxiv · 2021
Typepreprint
Langueen
DomaineMathematics
ThématiqueCOVID-19 epidemiological studies
Établissements canadiensnon disponible
Organismes subventionnairesEuropean and Developing Countries Clinical Trials PartnershipResearch EnglandMedical Research CouncilWellcome TrustAgence Nationale de la RechercheEuropean CommissionWorld Health OrganizationForeign, Commonwealth and Development OfficeUK Research and InnovationCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchNational Institute for Health Research Health Protection Research UnitBill and Melinda Gates Foundation
Mots-clésOutbreakIsolation (microbiology)Psychological interventionMedicineInfection controlPopulationEnvironmental healthHealth careFamily medicineNursingIntensive care medicineVirology

Résumé

récupéré en direct d'OpenAlex

Abstract Background COVID-19 outbreaks are still occurring in English care homes despite the non-pharmaceutical interventions (NPIs) in place. Methods We developed a stochastic compartmental model to simulate the spread of SARS-CoV-2 within an English care home. We quantified the outbreak risk under the NPIs already in place, the role of community prevalence in driving outbreaks, and the relative contribution of all importation routes into the care home. We also considered the potential impact of additional control measures, namely: increasing staff and resident testing frequency, using lateral flow antigen testing (LFD) tests instead of PCR, enhancing infection prevention and control (IPC), increasing the proportion of residents isolated, shortening the delay to isolation, improving the effectiveness of isolation, restricting visitors and limiting staff to working in one care home. Findings The model suggests that importation of SARS-CoV-2 by staff, from the community, is the main driver of outbreaks, that importation by visitors or from hospitals is rare, and that the past testing strategy (monthly testing of residents and daily testing of staff by PCR) likely provides negligible benefit in preventing outbreaks. Daily staff testing by LFD was 39% (95% 18-55%) effective in preventing outbreaks at 30 days compared to no testing. Interpretation Increasing the frequency of testing in staff and enhancing IPC are important to preventing importations to the care home. Further work is needed to understand the impact of vaccination in this population, which is likely to be very effective in preventing outbreaks. Funding The National Institute for Health Research, European Union Horizon 2020, Canadian Institutes of Health Research, French National Research Agency, UK Medical Research Council. The World Health Organisation funded the development of the COS-LTCF Shiny application. Research in Context Evidence before this study Care homes have been identified as being at increased risk of COVID-19 outbreaks, and a number of modelling studies have considered the transmission dynamics of SARS-CoV-2 in this setting. We searched the PubMed database and bioRxiv and medRxiv’s COVID-19 SARS-CoV-2 preprints for English-language articles on the 11th May 2021, with the search terms (“COVID-19” OR “SARS-CoV-2” OR “coronavirus”) AND (“care home” OR “LTCF” OR “long term care facility” OR “nursing home”) AND (“model”). In addition to these searches, we identified articles relevant to this work through informal networks. These searches returned 87 studies, of which 12 explicitly modelled SARS-CoV-2 transmission within care homes and explored the effectiveness of non-pharmaceutical interventions in these settings. These studies employed a number of modelling approaches (agent-based and compartmental models) and considered various strategies for mitigating epidemic spread within care homes. Only one of these studies modelled care homes in England, but didn’t consider individual care homes as separate entities (transmission between residents in separate facilities was equally likely as within one facility) and only modelled one intervention within the care home: the effect of restricting visitors. Another study modelled a different type of long-term care facility, a rehabilitation facility in France. Other studies modelled care homes in Canada, Scotland, and the US. These modelled care homes were larger than the average English care home. Only one study included importation of SARS-CoV-2 to care homes from hospitals through resident hospitalisation. Added value of this study We developed a stochastic compartmental model describing the transmission dynamics of SARS-CoV-2 within English care homes. This study is the first to assess the relative importance of all SARS-CoV-2 importation routes to care homes (including resident hospitalisation) and to quantify the impact of a range of non-pharmaceutical interventions against SARS-CoV-2 particularly for English care homes. We found that community prevalence, through staff importations, was the main driver of outbreaks in care homes at 30 days, not importation from hospital visits nor by visitors. In line with this, we found daily testing of staff to be the most effective testing strategy in preventing outbreaks. We show the previous testing strategy (PCR testing residents once every 28 days and staff once a week) to be ineffective in preventing outbreaks and suggest that more frequent testing of staff is required. Restricting visitors bore little effect on the probability of an outbreak occurring by day 30. Interventions focusing on decreasing the transmission of SARS-CoV-2 in the care home were the most effective in reducing the frequency of outbreaks. We provide a Shiny application for users to explore alternative care home characteristics, outbreak characteristics and interventions. Implications of all the available evidence Preventing the importation of SARS-CoV-2 to care homes from the community through staff is key to preventing outbreaks. Infection prevention and control (IPC) measures targeting transmission within the care home and frequent testing of staff, ideally daily, are the most effective strategies considered. Many care homes in England are currently unable to meet the additional workload daily testing would entail, therefore additional support should be considered to enable these measures. Allowing visitors should be considered given their general positive contribution to residents’ physical and mental health and likely negligible contribution to outbreaks.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,159
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,002
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,417
Tête enseignante GPT0,524
Écart entre enseignants0,107 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2021
Routes d'admission2
Résumé présentoui

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