Eastern Equine Encephalitis Virus in Mosquitoes and Their Role as Bridge
Bibliographic record
Abstract
Eastern equine encephalitis virus (EEEV) is maintained in an enzootic cycle involving Culiseta melanura mosquitoes and avian hosts. Other mosquito species that feed opportunistically on mammals have been incriminated as bridge vectors to humans and horses. To evaluate the capacity of these mosquitoes to acquire, replicate, and potentially transmit EEEV, we estimated the infection prevalence and virus titers in mosquitoes collected in Connecticut, USA, by cell culture, plaque titration, and quantitative reverse transcription–PCR. Cs. melanura mosquitoes were the predominant source of EEEV (83 [68%] of 122 virus isolations) and the only species to support consistently high virus titers required for effi cient transmission. Our fi ndings suggest that Cs. melanura mosquitoes are primary enzootic and epidemic vectors of EEEV in this region, which may explain the relative paucity of human cases. This study emphasizes the need for evaluating virus titers from fi eld-collected mosquitoes to help assess their role as vectors. During the past 6 years, eastern equine encephalitis virus (EEEV; family Togaviridae, genus Alphavirus) has reemerged in the northeastern United States and resulted in 26 human cases of infection and 9 deaths (ArboNET; Centers for Disease Control and Prevention, Atlanta, GA, USA). Virus transmission has intensified throughout this region, spread to locales where it had not been previously detected, and extended north into New Hampshire and Maine, USA, and Nova Scotia, Canada (1). Disease outbreaks caused by EEEV occur at irregular intervals when underlying ecologic conditions favor virus amplification and overflow into human and equine populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".