Notice bibliographique
Résumé
When pneumonic plague struck Surat, Gujarat, India in 1994, thousands of people panicked and fled city. We were sitting in Ottawa watching CNN showing pictures of people fleeing, said Dr Ron St John, Director-General of Centre for Emergency Preparedness and Response at Public Health Agency of Canada, recalling how news media were first source of information on outbreak for public health officials, including those at WHO. The slow response to that outbreak and an Ebola outbreak in Kikwit in Democratic Republic of Congo following year led to panic and unnecessary deaths. We had no capacity to respond to outbreaks on our own, or even to deal with information coming in. All we had was a fax machine. The switchboards at WHO were completely overwhelmed, said Dr David Heymann, acting Assistant Director-General for Communicable Diseases and WHO Director-General's Representative for Pandemic Influenza. New techniques were clearly needed to respond to disease threats, such as pandemic influenza, that could kill millions. In 1996, then director-general, Dr Hiroshi Nakajima, asked Heymann to set up a new emerging infectious disease programme to deal with outbreaks. In age of real-time electronic media and television, journalists became a vital source of instant information that public health authorities could use to detect outbreaks, in addition to information from governments, nongovernmental organizations and health-care workers, said Dr Thomas Grein, Medical Officer, Alert and Response Operations at WHO. The question was: how to search through maze of thousands of reports filed by journalists every day? The answer came from Canada. St John linked up with Dr Rudi Nowak from Health Canada, Canadian health ministry, and they proposed development of a computerized system that would collect raw news feeds from international news agencies such as Agence France Presse, Associated Press and Reuters, and scan these feeds automatically to find news of disease outbreaks. Development work on software began in 1997 funded by a Canadian government grant of 800 000 Canadian dollars (US$ 500 000 at time). The news filtering system St John and Nowak developed, known as Global Public Health Intelligence Network (GPHIN, pronounced G-finn), went live in 1999 and scanned news feeds in English and French. We were astounded at how much information we could get, said St John, adding that system collects thousands of reports everyday. But information had to be verified, and incorrect information discarded. Nowak came to WHO in Geneva for two years to work with Heymann, Dr Guenael Rodier, Special Adviser for Communicable Diseases to Regional Director, WHO Regional Office for Europe, and Dr Mike Ryan, Director of Department of Epidemic and Pandemic Alert and Response, in establishing a team that would be responsible for verification. Every weekday morning at 9am about 20 members of that team meet in Strategic Health Operations Centre, nicknamed the SHOC room, at WHO's headquarters, to discuss outbreak reports that have come in and which ones need to be verified, by contacting WHO country offices, which, in turn, contact their host governments. The reports are also analysed by relevant crisis centres set up at WHO's regional offices. Ryan and his team set up Global Outbreak Alert and Response Network of 126 institutions across globe. Its experts can be despatched to field, where they work together with WHO staff from regional offices and headquarters to stem any outbreaks. Before WHO and other subscribers receive reports from GPHIN, these have been screened by a team of eight public health specialists in Canada. The SHOC was opened in May 2004 with funding from United States. After death of WHO's Director-General Dr LEE Jong-wook in May 2006, it was renamed JW Lee Centre for Strategic Health Operations. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».