The virus evolves: four public health priorities for reducing the evolutionary potential of SARS-CoV-2
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Notice bibliographique
Résumé
As scientists who study evolution, we are concerned about the threat posed to public health by evolving SARS-CoV-2 variants. We celebrate the start of vaccination campaigns, enabled by remarkable scientific achievements, but these advances are now at risk of being undermined by evolution. In particular, we emphasize that—unless we keep case numbers low—novel variants will continue to emerge, increasing the chances that some will evade vaccine-induced immunity. These dangerous consequences of SARS-CoV-2 evolution are looming, but rapid viral evolution is not inevitable. Fundamental principles of evolution provide clear guidelines for slowing down the evolutionary process. With these principles in mind and echoing the calls made by others (see the supplementary material for complete references and signatories), we urge policymakers to prioritize the following: One of the most well established truths of evolution is that adaptive change is more likely when populations are larger. This means that a drastic reduction in infections will not only reduce illness and save lives in the face of variants that are already present, but it will guard against the conditions that favor the evolution of new variants of concern, which may be more transmissible, more virulent, or more able to escape immunity (“escape variants”). The emergence and spread of escape variants is favored by transmission of the virus to and from people who are immunized (whether they have been immunized by natural infection or by vaccines). Although such transmission chains may be infrequent, they become more likely when case numbers are high in areas where vaccinations are being rolled out. Therefore, in order to limit the emergence and spread of escape variants as vaccination campaigns proceed, policy-makers should encourage vaccinated people to continue to adhere to mitigation measures (e.g., masks, physical distance, ventilation) while case numbers remain high. Genomic surveillance (regular sequencing of a representative sample of cases) is essential for identifying the emergence of new variants. Sharing these sequence data on public repositories as quickly as possible will enable rapid responses when new variants of concern are detected. Moreover, genomic data should be paired with patient metadata so that any variants that alter the disease characteristics can be identified. Concurrent with genomic surveillance, increased genotyping of samples from cases for known variants of concern (e.g., via RT-PCR, polymerase chain reaction, which can return test results very quickly) is needed for rapid detection so that targeted control efforts can be put in place around those cases. We all live on the same planet. Leaving the epidemic uncontrolled anywhere leaves the global population vulnerable to the evolution of variants that can escape immunity. Therefore, we support the scientific consensus calling for global coordination on both vaccination campaigns and genomic surveillance. We ask leaders to seize this window of opportunity; protect the health of citizens and economies by taking swift action to guard against the threat of ongoing viral evolution. Supplemental file with a list of society signatories and full references is available at BIOSCI online. Joint Public Policy Committee: The Society for the Study of Evolution and The American Society of Naturalists Co-signing scientific societies include the Society for the Study of Evolution, the American Society of Naturalists, the European Society for Evolutionary Biology, the American Institute for Biological Sciences, the Canadian Society for Ecology and Evolution, the Society of Systematic Biologists, the Indian Society of Evolutionary Biologists, the International Society for Behavioral Ecology, the Netherlands Society for Evolutionary Biology, the Chilean Society of Evolution, the European Society for Evolution and Development, and the Konrad Lorenz Institute for Evolution and Cognition Research.
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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 | 0,003 | 0,017 |
| 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 | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 découle