COVID-19 Contact Tracing Strategies During the First Wave of the Pandemic: Systematic Review of Published Studies
Notice bibliographique
Résumé
BACKGROUND: Contact tracing (CT) represented one of the core activities for the prevention and control of COVID-19 in the early phase of the pandemic. Several guidance documents were developed by international public health agencies and national authorities on the organization of COVID-19 CT activities. While most research on CT focused on the use digital tools or relied on modelling techniques to estimate the efficacy of interventions, poor evidence is available on the real-world implementation of CT strategies and on the organizational models adopted during the initial phase of the emergency to set up CT activities. OBJECTIVE: We aimed to provide a comprehensive picture of the organizational aspects of CT activities during the first wave of the pandemic through the systematic identification and description of CT strategies used in different settings during the period from March to June 2020. METHODS: A systematic review of published studies describing organizational models of COVID-19 CT strategies developed in real-world settings was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. PubMed, Embase, and Cochrane Library were searched. Studies not providing a description of the organizational aspects of CT strategies and studies reporting or modelling theoretical strategies or focusing on the description of digital technologies' properties were excluded. Quality of reporting was assessed by using the Template for Intervention Description and Replication Checklist for Population Health and Policy. We developed a narrative synthesis, using a conceptual framework to map the extracted studies broken down by target population. RESULTS: We retrieved a total of 1638 studies, of which 17 were included in the narrative synthesis; 7 studies targeted the general population and 10 studies described CT activities carried out in specific population subgroups. Our review identified some common elements across studies used to develop CT activities, including decentralization of CT activities, involvement of trained nonpublic health resources (eg, university students or civil servants), use of informatics tools for CT management, interagency collaboration, and community engagement. CT strategies implemented in the workplace envisaged a strong collaboration with occupational health services. Outreach activities were shown to increase CT efficiency in susceptible groups, such as people experiencing homelessness. Data on the effectiveness of CT strategies are scarce, with only few studies reporting on key performance indicators. CONCLUSIONS: Despite the lack of systematically collected data on CT effectiveness, our findings can provide some indication for the future planning and development of CT strategies for infectious disease control, mainly in terms of coordination mechanisms and the use of human and technical resources needed for the rapid development of CT activities. Further research on the organizational models of CT strategies during the COVID-19 pandemic would be required to contribute to a more robust evidence-making process.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,001 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».