Genomic epidemiology reveals multiple introductions of Zika virus into the United States
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".