Prevention of pandemic influenza after mass gatherings – learning from Hajj
Bibliographic record
Abstract
Shortly after Hajj 2009 ended on 30 November, less than 100 pilgrims with confirmed pandemic influenza A H1N1 09, including five fatalities, had been reported by Saudi officials in the media.1 Since the elderly and others with influenza risk factors were discouraged from attending Hajj, this case fatality rate of 5% is inconsistent with that expected (less than 0.5%) and suggests there were many more undetected surviving cases. It is known from earlier pandemics that the ‘percentage of the recognised sick, who seek medical advice does not represent the total of the afflicted’.2 To date Saudi Arabia has the largest number of influenza A H1N1 09 cases (9355, 20% of all cases) and the third largest number of fatalities (81, 14% of all fatalities) reported from the World Health Organization (WHO) Eastern Mediterranean Region.3 Further, a Saudi hospital has claimed that about one-fifth of hospitalized patients had the influenza A H1N1 virus infection after returning from travel abroad,4 so publication of Hajj 2009 realtime influenza surveillance data (with PCR confirmation, if possible) by the Saudi Ministry of Health would be useful and welcome to inform global pandemic influenza control. A large number of pilgrims stay in Saudi Arabia for a month. If as few as 10 arrived with H1N1 09 influenza, and assuming a low basic reproduction number (R0) of 1.5, a serial interval of 3 days and a susceptible population,5 nearly 1000 cases will have occurred within that month. Up to 60% of Hajj pilgrims suffer symptoms of respiratory infection,6 and the attack rate of influenza among symptomatic pilgrims has been estimated as 10%,7 so that extrapolating for 2.5 million pilgrims attending this year's Hajj 150,000 cases of influenza would be expected. It is a tradition in Muslim communities that as well as pilgrims being visited by friends and relatives on arrival in Mecca, many travel after Hajj in the Middle East and Indian subcontinent, and recent returnees attend congregational prayers at mosques. These activities increase the risk of infections such as the influenza spreading among pilgrims' vulnerable contacts including the elderly and children. Also, Hajjis' travel and return coincided with the 2009 Christmas and New Year holiday period and associated overseas travel and contact in airplanes, airports and other sites. Useful recommendations for the prevention and control of influenza A H1N1 at Hajj 2009, published in both Science and the Lancet in mid-November,8,9 summarized the advice from an expert consultation undertaken by the Saudi Arabian Ministry of Health. These included good surveillance at Hajj by realtime electronic reporting, rapid laboratory confirmation via the healthcare system at Hajj, compliance with WHO advice, particularly that on the control of infectious diseases during mass gatherings and reporting of infection as required by the International Health Regulations 2005.10,11 The latter assumes surveillance in the country of origin to be adequate for recognizing and reporting post-Hajj infections. However, experience is of delay in recognizing Hajj-associated cases and outbreaks. It is less than a decade since the Hajj-associated worldwide outbreak of meningococcal W135 disease following Hajj 2000 when 87% (78/90) of the Hajj-associated cases in Europe were in contact with those who had returned from Hajj; there were 14 deaths which may have been avoided by quicker recognition of the association.12 Risk events for pandemic influenza A H1N1 09 include the continuing Umrah and other mass gatherings subsequent to and soon after Hajj 2009, such as the December UN conference on Climate Change expecting 15,000 delegates, world leaders and politicians in Copenhagen, the winter Olympics in Vancouver early in 2010, and the FIFA World Cup later in 2010. Post-event surveillance is just as important for these in the control of respiratory infections. Health services around the world need reminding of the importance and means of surveillance, which may need strengthening or construction. Therefore, we set out here recommendations for post-event surveillance, diagnosis and treatment: Vigilance and questioning about recent travel abroad, including attendance at Hajj or other mass gatherings; Reporting suspected cases locally and to WHO; Confirming H1N1 09 flu by PCR; Continuing preventive action: respiratory etiquette, mask use by symptomatic cases and their contacts, maintenance of hand hygiene, voluntary isolation of cases, antivirals for cases and for prophylaxis in vulnerable contacts, vaccination of unvaccinated Hajjis and their at risk contacts against seasonal and pandemic influenza, pneumococcal vaccination of at risk pilgrims; We also urge WHO to develop a post-event surveillance scheme and directive for immediate electronic reporting of travel-associated influenza and its complications, during the current pandemic influenza A H1N1 09 and in preparation for the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.006 |
| 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; both teacher heads agree on what is shown here.
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".