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Enregistrement W2889326365 · doi:10.14745/ccdr.v40i12a07

The challenges of sustaining measles elimination in Canada

2014· article· en· W2889326365 sur OpenAlexaffvenueabout
NS Crowcroft

Notice bibliographique

RevueCanada Communicable Disease Report · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueVirology and Viral Diseases
Établissements canadiensPublic Health OntarioUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMeaslesVirologyPolitical scienceMedicineVaccination

Résumé

récupéré en direct d'OpenAlex

Recent importations of measles into Canada have not generally led to large outbreaks, indicating that measles is well controlled in Canada.Isolated large outbreaks that have occurred remind us of the need to remain vigilant.Measles presents particular challenges because it is the most infectious disease known, it thrives among those who do not access the child health system for one reason or another, and we do not always have the information we need to identify and target communities with low immunization coverage.Outbreaks typically arise from Canadians who travel and are exposed to measles abroad.Controlling sporadic outbreaks arising from importations is time and resource intensive, which makes immunization for Canadians travelling outside the region of the Americas (where measles has been eliminated) a priority.To prevent importations of measles into Canada altogether requires other countries and regions of the world to make progress in eliminating measles.Recent importations of measles into Canada are actually a reminder of the amazing success of immunization in eliminating this disease.This is because, with a few notable exceptions, the majority of importations have either not led to further cases or have caused only small outbreaks, indicating that, overall, measles is currently well controlled in Canada (1).The size of outbreaks (including cases that have no onward transmission) can be used to estimate level of control through calculation of the effective reproduction number (Re), defined as the average number of people actually infected by each case during a specified time period in a population that has some level of immunity (2).Provinces such as Ontario, in which a single case is defined as an outbreak, can calculate Re.Analysis of data from 13 outbreaks in 2009-12 revealed an estimated Re of 0.52, well below the epidemic threshold of Re = 1 (3).Recent outbreaks of measles in Canada have included typical cases characterized by fever, cough and a maculopapular rash.Patients have been hospitalized, but fortunately there have been no deaths.In 2011, 10 measles deaths occurred in France during a year when epidemics of measles exploded across Europe, with over 30,000 cases reported to the European Centre for Disease Control (4, 5).Following repeated importations from the 2011 epidemic in Europe, Quebec had the largest outbreak of measles of any country in North, Central or South America since 2001, reaching a total of 776 cases between 2011 and 2012.This threatened the elimination status of the whole region (6).The main cause of the outbreak was a level of immunization coverage lower than what was needed for elimination (6), an example of why jurisdictions cannot be complacent and why they need high-quality data on coverage, down to district level and in all age groups, to identify areas at risk and take effective action when gaps in immunity are identified.We know that gaps in immunity exist in communities that reject immunization or in areas where coverage is just not high enough.Questions that arise about the exact level of immunization coverage and population immunity cannot be answered in the absence of a vaccine registry or sero-surveillance.The fact that three-quarters of cases in 2013 were unimmunized may indicate that coverage is lower than we think, since we would expect most cases to be vaccinated if coverage were high.Measles presents a particular challenge because it is the most infectious disease known, with a basic reproduction number of around 17 (meaning that in a fully susceptible population, each infected person would, on average, infect 17 others).Population immunity above 95% is therefore needed for elimination (7).Allowing for vaccine failures, this means our system has to reach 97% two-dose coverage to sustain elimination, a https://doi.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,121
Score d'incertitude au seuil0,881

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,010
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0140,003
Communication savante0,0070,002
Science ouverte0,0050,005
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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 Opus0,017
Tête enseignante GPT0,246
Écart entre enseignants0,229 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations3
Publié2014
Routes d'admission3
Résumé présentoui

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