Increased risk of endemic mosquito-borne diseases in Canada due to climate change
Bibliographic record
Abstract
There are currently over 80 species of mosquito endemic in Canada-although only a few of these carry pathogens that can cause disease in humans. West Nile virus, Eastern equine encephalitis virus and the California serogroup viruses (including the Jamestown Canyon and snowshoe hare viruses) are mosquito-borne viruses that have been found to cause human infections in North America, including in Canada. Over the last 20 years, the incidence of most of these endemic mosquito-borne diseases (MBD) has increased approximately 10% in Canada, due in large part to climate change. It is anticipated that both the mosquito lifecycle and virus transmission patterns will be affected by climate change, resulting in an increase in both the range and local abundance of several important mosquito species. Laboratory studies and mathematical modelling suggest that increased ambient temperatures, changes in precipitation and extreme weather events associated with climate change will likely continue to drive mosquito vector and MBD range expansion, increasing the duration of transmission seasons and leading to MBD-related epidemics. Furthermore, Canada's endemic MBDs have complex transmission cycles, involving multiple reservoir hosts (birds and mammals), multiple pathogens and multiple mosquito species-all of which may be sensitive to climate and other environmental changes, and making forecasting of potential emerging trends difficult. These expected climate-induced changes in mosquitoes and MBDs underline the need for continued (and expanded) surveillance and research to ensure timely and accurate evaluation of the risks to the public health of Canadians.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".