An initial investigation of the association between the SARS outbreak and weather: with the view of the environmental temperature and its variation
Bibliographic record
Abstract
OBJECTIVE: To understand the association between the SARS outbreak and the environmental temperature, and to provide a scientific basis for prevention and control measures against it. METHODS: The daily numbers of the probable SARS patients and the daily meteorological factors during the SARS outbreak period in Hong Kong, Guangzhou, Beijing, and Taiyuan were used in the data analysis. Ecological analysis was conducted to explore the association between the daily numbers of probable SARS patients and the environmental temperature and its variations. RESULTS: There was a significant correlation between the SARS cases and the environmental temperature seven days before the onset and the seven day time lag corresponds well with the known incubation period for SARS. The optimum environmental temperature associated with the SARS cases was between 16 degrees C to 28 degrees C, which may encourage virus growth. A sharp rise or decrease in the environmental temperature related to the cold spell led to an increase of the SARS cases because of the possible influence of the weather on the human immune system. This study provided some evidence that there is a higher possibility for SARS to reoccur in spring than that in autumn and winter. CONCLUSION: Current knowledge based on case studies of the SARS outbreak in the four cities suggested that the SARS outbreaks were significantly associated with the temperature and its variations. However, because the fallacy and the uncontrolled confounding effects might have biased the results, the possibility of other meteorological factors having an affect on the SARS outbreaks deserves further investigation.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".