Mosquitoes Know No Borders: Surveillance of Potential Introduction of Aedes Species in Southern Québec, Canada
Bibliographic record
Abstract
Current climatic conditions limit the distribution of Aedes (Stegomyia) albopictus (Skuse, Diptera: Culicidae) in the north, but predictive climate models suggest this species could establish itself in southern Canada by 2040. A vector of chikungunya, dengue, yellow fever, Zika and West Nile viruses, the Ae. Albopictus has been detected in Windsor, Ontario since 2016. Given the potential public health implications, and knowing that Aedes spp. can easily be introduced by ground transportation, this study aimed to determine if specimens could be detected, using an adequate methodology, in southern Québec. Mosquitoes were sampled in 2016 and 2017 along the main roads connecting Canada and the U.S., using Biogent traps (Sentinel-2, Gravide Aedes traps) and ovitraps. Overall, 24 mosquito spp. were captured, excluding Ae. Albopictus, but detecting one Aedes (Stegomyia) aegypti (Skuse) specimen (laid eggs). The most frequent species among captured adults were Ochlerotatus triseriatus, Culex pipiens complex, and Ochlerotatus japonicus (31.0%, 26.0%, and 17.3%, respectively). The present study adds to the increasing number of studies reporting on the range expansions of these mosquito species, and suggests that ongoing monitoring, using multiple capture techniques targeting a wide range of species, may provide useful information to public health with respect to the growing risk of emerging mosquito-borne diseases in southern Canada.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".