Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".