Severe Acute Respiratory Syndrome: Overview With an Emphasis on the Toronto Experience
Bibliographic record
Abstract
OBJECTIVE: To provide an overview of the severe acute respiratory syndrome (SARS) outbreak in Toronto, Ontario, which experienced the largest outbreak outside Asia, and to review what has been learned during the past year. DATA SOURCES: MEDLINE search of all studies related to SARS, including review of the Centers for Disease Control and Prevention, World Health Organization (WHO), and Health Canada Web sites. DATA SYNTHESIS: During the SARS outbreak in Toronto, 438 people had been diagnosed as having suspected or probable SARS and 44 people died. Elderly people and those with comorbid illnesses were at greatest risk of complications or death. Transmission was via direct contact with respiratory secretions. The use of gloves, gowns, N95 masks, and eye protection was effective in preventing transmission. No transmission occurred before symptom onset or after recovery. Serologic tests suggest that antibodies may not appear until 28 days after illness onset. Molecular tests give their greatest yield during the second week of illness. The value of ribavirin treatment remains questionable. The combination of interferon plus corticosteroids appears to be better than corticosteroids alone. Postmortem examination revealed pulmonary edema and evidence of diffuse alveolar damage. Very few morphological changes were noted in other organs despite the presence of viral RNA as detected by polymerase chain reaction. CONCLUSION: On July 5, 2003, the WHO declared that the SARS outbreak was over. Since then, new cases of SARS have been reported in Asia. With global travel, the disease can rapidly spread throughout the world. Therefore, we must remain vigilant to prevent another pandemic.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".