Efectividad de la limitación de la movilidad en la evolución de la pandemia por Covid-19
Notice bibliographique
Résumé
Introduction During the Covid-19 pandemic, non-pharmacological interventions (NPIs) aimed to minimise the spread of the virus as much as possible to avoid the most severe cases and the collapse of health systems. These measures included mobility restrictions in several countries, including Spain. Objective To assess the impact of mobility constraints on incidence, transmission, severe cases and mortality in the evolution of the Covid-19 pandemic. These constraints include: • Mandatory home confinement. • - Recommendation to stay at home. • - Perimeter closures for entry and/or exit from established areas. • - Restriction of night-time mobility (curfew). Methodology Systematic literature review, including documents from official bodies, systematic reviews and meta-analyses. The following reference databases were consulted until October 2021 (free and controlled language): Medline, EMBASE, Cochrane Library, TripDB, Epistemonikos, Royal college of London, COVID-end, COVID-19 Evidence Reviews, WHO, ECDC and CDC. Study selection and quality analysis were performed by two independent researchers. References were filtered firstly by title and abstract and secondly by full text in the Covidence tool using a priori inclusion and exclusion criteria. Synthesis of the results was done qualitatively. The quality of the included studies was assessed using the AMSTAR-II tool. Results The literature search identified 642 studies, of which 38 were excluded as duplicates. Of the 604 potentially relevant studies, 12 studies (10 systematic reviews and 2 official agency papers) were included in the analysis after filtering. One of the official agency papers was from the European Centre for Disease Prevention and Control (ECDC) and the other paper was from the Ontario Agency for Health Promotion and Protection (OHP). The result of the quality assessment with the AMSTAR-II tool of the included systematic reviews was: 3 reviews of moderate quality, 6 reviews of low quality and 1 review of critically low quality. The interventions analysed in the included studies were divided into 2 categories: the first category comprised mandatory home confinement, recommendation to stay at home and curfew, and the second category comprised perimeter blocking of entry and/or exit (local, cross-community, national or international). This division is because the included reviews analysed the measures of mandatory home confinement, advice to stay at home and curfew together without being able to carry out a disaggregated analysis. The included systematic reviews for the evaluation of home confinement, stay-at-home advice and curfew express a decrease in incidence levels, transmission and severe cases following the implementation of mobility limitation interventions compared to the no measure comparator. These conclusions are supported by the quantitative or qualitative results of the studies they include. All reviews also emphasise that to increase the effectiveness of these restrictions it is necessary to combine them with other public health measures. In the systematic reviews included for the assessment of entry and/or exit perimeter closure, most of the studies included in the reviews were found to be modelling studies based on mathematical models. All systematic reviews report a decrease in incidence, transmission and severe case levels following the implementation of travel restriction interventions. The great heterogeneity of travel restrictions applied, such as travel bans, border closures, passenger testing or screening, mandatory quarantine of travellers or optional recommendations for travellers to stay at home, makes data analysis and evaluation of interventions difficult. Conclusions Mobility restrictions in the development of the Covid-19 pandemic were one of the main NPI measures implemented. It can be concluded from the review that there is evidence for a positive impact of NPIs on the development of the COVID-19 pandemic. The heterogeneity of the data from the included studies and their low quality make it difficult to assess the effectiveness of mobility limitations in a disaggregated manner. Despite this, all the included reviews show a decrease in incidence, transmission, hospitalisations and deaths following the application of the measures under study. These measures are more effective when the restrictions were implemented earlier in the pandemic, were applied for a longer period and were more rigorous in their application.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,008 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».