Key elements of infectious disease syndromic surveillance systems: A scoping review
Notice bibliographique
Résumé
IntroductionSyndromic surveillance is an alternative type of public healthsurveillance which utilises pre-diagnostic data sources to detectoutbreaks earlier than conventional (laboratory) surveillance andmonitor the progression of illnesses in populations. These systems areoften noted for their ability to detect a wider range of cases in under-reported illnesses, utilise existing data sources, and alert public healthauthorities of emerging crises. In addition, they are highly versatileand can be applied to a wide range of illnesses (communicable andnon-communicable) and environmental conditions. As a result, theirimplementation in public health practice is expanding rapidly. Thisscoping review aimed to identify all existing literature detailing thenecessary components in the defining, creating, implementing, andevaluating stages of human infectious disease syndromic surveillancesystems.MethodsA full scoping review protocol was developeda priori. Theresearch question posed for the review was “What are the essentialelements of a fully functional syndromic surveillance system forhuman infectious disease?” Five bibliographic databases (Pubmed,Scopus, CINAHL, Web of Science, ProQuest) and eleven websites(Google, Public Health Ontario, Public Health England, Public HealthAgency of Canada, Centers for Disease Control and Prevention,European Centre for Disease Prevention and Control, InternationalSociety for Disease Surveillance, Syndromic Surveillance Systems inEurope, Eurosurveillance, Kingston Frontenac, Lennox & AddingtonPublic Health (x2)) were searched for peer-reviewed, government,academic, conference, and book literature. A total of 1237 uniquecitations were identified from this search and uploaded into thescoping review softwareCovidence. The titles and abstracts werescreened for relevance to the subject material, resulting in 142documents for full-text screening. Following this step, 55 documentsremained for data extraction and inclusion in the scoping review. Twoindependent reviewers conducted each step.ResultsThe scoping review identified many essential elements in thedefining, creating, implementing, and evaluating of syndromicsurveillance systems. These included the defining of “syndromicsurveillance”, classification of syndromes, data quality andcompleteness, statistical methods, privacy and confidentialityissues, costs, operational challenges, management composition,collaboration with other public health agencies, and evaluationcriteria. Several benefits and limitations of the systems were alsoidentified, when comparing them to other public health surveillancemethods. Benefits included the timeliness of analyses and reporting,potential cost savings, complementing traditional surveillancemethods, high sensitivity, versatility, ability to perform short- andlong-term surveillance, non-specificity of the systems, ability to fillin gaps of under-reported illnesses, and the collaborations whichare fostered through its platform; limitations included the potentialresources and costs required, inability to replace traditional healthcareand surveillance methods, the false alerts which may occur, non-specificity of the systems, poor data quality and completeness, timelags in analyses, limited effectiveness at detecting smaller-scaleoutbreaks, and privacy issues with accessing data.ConclusionsOver the past decade, syndromic surveillance systems have becomean integral part of public health practice internationally. Their abilityto monitor a wide variety of illnesses and conditions, detect illnessesearlier than traditional surveillance methods, and be created usingexisting data sources make them a valuable public health tool.The results from this scoping review demonstrate the benefits andlimitations and overall role of the systems in public health practice.In addition, this study also shows that a complete set of key elementsare required in order to properly define, create, implement, andevaluate these systems to ensure their effectiveness and performance.
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 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 | 0,010 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| 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 ».