Genomic epidemiology reveals multiple introductions of Zika virus into the United States
Notice bibliographique
Résumé
Genome sequencing of Zika virus samples from infected patients and Aedes aegypti mosquitoes in Florida shows that the virus was probably introduced into the United States on multiple occasions, and that the Caribbean is the most likely source. Three papers in this issue present a wealth of new Zika virus (ZIKV) genome sequences and further insights into the genetic epidemiology of ZIKV. Nathan Grubaugh et al. provide 39 new ZIKV genome sequences from infected patients and Aedes aegypti mosquitoes in Florida. Phylogenetic analysis suggests that the virus has been introduced on multiple separate occasions, probably linked to travel from the Caribbean. They find a low probability of long-term persistence of ZIKV transmission chains within Florida, suggesting that the potential for future ZIKV outbreaks there will depend on transmission dynamics in the Americas. Nuno Faria et al. and Hayden Metsky et al. reconstruct the spread of ZIKV in Brazil and the Americas. Faria et al. provide 54 new ZIKV genomes, several sequenced in real time in a mobile genomics laboratory. They trace the spatial origins and spread of ZIKV in Brazil and the Americas and date the timing of the international spread of ZIKV from Brazil. They find that northeast Brazil had a crucial role in the establishment of the epidemic and the spread of the virus within Brazil and the Americas. Metsky et al. generate 110 ZIKV genomes from clinical and mosquito samples from ten regions. They also see rapid expansion of the epidemic within Brazil and multiple introductions to other geographic areas. In agreement with Faria et al., they find that ZIKV circulated unobserved for many months before transmission was detected. Metsky et al. additionally describe ZIKV evolution and discuss how the accumulation of mutations might affect the performance of diagnostic tests in the future. Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital abnormalities1,2. In July 2016, mosquito-borne ZIKV transmission was reported in the continental United States; since then, hundreds of locally acquired infections have been reported in Florida3,4. To gain insights into the timing, source, and likely route(s) of ZIKV introduction, we tracked the virus from its first detection in Florida by sequencing ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least 4 introductions, but potentially as many as 40, contributed to the outbreak in Florida and that local transmission is likely to have started in the spring of 2016—several months before its initial detection. By analysing surveillance and genetic data, we show that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions were linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. Our study provides an understanding of how ZIKV initiates transmission in new regions.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 source (Gemma direct ou Codex distillé), 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 ».