SARS-CoV-2: How Science has Advanced in the Era of the COVID-19 Pandemic
Notice bibliographique
Résumé
Background : The SARS-CoV-2 (Severe Acute Respiratory Syndrom Corona Virus) virus causes COVID-19 (Corona Virus Disease) disease, which was first diagnosed in late December 2019 among a few people with unknown respiratory illness in Wuhan city, Hubei province, China. Presumably this virus jumped from a natural host to human, and that occurred in one of the open food markets in Wuhan city, spreading very quickly to neighbouring provinces, neighbouring countries and eventually different continents. The World Health Organization declared the outbreak a Public Health Emergency of International Concern on 30 January 2020 and a pandemic on 11 March 2020. As of writing, this virus has infected close to 185 million people and killed over 3.97 million people globally. People from all colours and tribes have fallen victim to this virus and the world is struggling to restore pre-pandemic life, which seems far away. While this virus hijacked the freedom of human beings in so many ways, on the other hand SARS CoV-2 also forced us to invent new skills and technology not only to defeat it but also to propel ourselves forward. For instance, diagnostic tests for SARS CoV-2 became available in weeks instead of years, vaccines were produced using newer as well as traditional technology from scratch in a matter of months rather than 10-14 years, a variety of online platforms were adopted and widely used in the past year. While the speed at which science progressed has reached new dimensions, we have experienced many unintended consequences as well since we were forced to focus on SARS CoV-2. In this article a brief update on the history, origin, characteristics of this virus, its epidemiology, transmission, laboratory diagnoses, whole genome sequencing will be given, highlighting the scientific gains driven by the pandemic such as the development of new drugs and repurposing of old drugs, vaccines, prevention measures and infection control.
 Methodology : Title, abstract and text of relevant scientific articles were retireved from PubMed, Goole Scholar and WHO websites from 1974 to 2021.
 Conclusion : Finally, unintended consequences, post COVID-19 issues, myths and superstitions and adoption of technological development and new innovations will be discussed.
 IAHS Medical Journal Vol 4(2), June 2021; 63-73
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 | 0,022 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».