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Record W2158081092 · doi:10.1017/s095026880500556x

The SARS outbreak in a general hospital in Tianjin, China – the case of super-spreader

2005· article· en· W2158081092 on OpenAlexaff
SH. X. WANG, Yinghua Li, Bingyang Sun, Shuangshung Zhang, Weijun Zhao, Maoti Wei, Kexin Chen, Xinrong Zhao, Z. L. Zhang, Murray Krahn, Angela M. Cheung, Peter Wang

Bibliographic record

VenueEpidemiology and Infection · 2005
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of TorontoMemorial University of NewfoundlandUniversity Health Network
FundersCenters for Disease Control and Prevention
KeywordsOutbreakCase fatality rateEpidemiologyAttack rateMedicineTransmission (telecommunications)Public healthDiseaseIndex casePediatricsEnvironmental healthEmergency medicineVirologyInternal medicinePathology

Abstract

fetched live from OpenAlex

Severe acute respiratory syndrome (SARS) is a newly emerged infectious disease with a high case-fatality rate and devastating socio-economic impact. In this report we summarized the results from an epidemiological investigation of a SARS outbreak in a hospital in Tianjin, between April and May 2003. We collected epidemiological and clinical data on 111 suspect and probable cases of SARS associated with the outbreak. Transmission chain and outbreak clusters were investigated. The outbreak was single sourced and had eight clusters. All SARS cases in the hospital were traced to a single patient who directly infected 33 people. The patients ranged from 16 to 82 years of age (mean age 38.5 years); 38.7% were men. The overall case fatality in the SARS outbreak was 11.7% (13/111). The outbreak lasted around 4 weeks after the index case was identified. SARS is a highly contagious condition associated with substantial case fatality; an outbreak can result from one patient in a relatively short period. However, stringent public health measures seemed to be effective in breaking the disease transmission chain.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.369
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2005
Admission routes1
Has abstractyes

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