Acute respiratory tract infection symptoms and the uptake of dual influenza and pneumococcal vaccines among Hajj pilgrims
Bibliographic record
Abstract
BACKGROUND: Hajj pilgrims are encouraged to take influenza and pneumococcal vaccines prior to their travel to safeguard against acute respiratory tract infections (ARTIs). It is unclear whether dual immunisation with influenza and pneumococcal vaccines have had any impact on ARTI symptoms. To this end, we have examined the data of the last several years to assess whether combined influenza and pneumococcal vaccination has affected the rate of ARTI symptoms among Hajj pilgrims. MATERIALS AND METHODS: Hajj pilgrims from United Kingdom, Australia, Saudi Arabia and Qatar who attended the congregation between 2005 and 2015 were included in this study. Data from surveillance studies or clinical trials involving Hajj pilgrims were used. In this analysis we have made use of the raw data to construct a trend line graph with the prevalence of combined cough and fever (as a proxy for ARTI) against the uptake of combined influenza and pneumococcal vaccines, and to estimate the relative risk (RR) of ARTI with 95% confidence interval (95% CI). RESULTS: Data of a pooled sample of 9350 pilgrims, aged 0.5-90 years with a male to female ratio of 1.1, were analysed. Although vaccination uptake did not rise significantly over the years, there was also no observed meaningful benefit of combined vaccination (RR = 1.1; 95% CI 0.8-1.4), the rates of ARTI symptoms demonstrated a decline over the last several years. The findings of this analysis highlight that the prevalence of 'cough and fever' among Hajj pilgrims is on decline but the uptake of combined influenza and pneumococcal vaccines remains unchanged over years, and the decline can not be attributed to dual influenza and pneumococcal vaccination. CONCLUSIONS: Acute respiratory tract infections among Hajj pilgrims are decreasing, it is unclear if the reduction is due to vaccine uptake, but the data and analysis have some limitations.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".