Influence of Demography, Land Use, and Urban Form on West Nile Virus Risk and Human West Nile Virus Incidence in Ottawa, Canada
Bibliographic record
Abstract
Human infection by West Nile virus (WNV; family Flaviviridae), in some cases, develops into a deadly neuroinvasive disease. WNV risk is thought to be influenced by factors affecting the density of species that promote replication and transmission of the virus, namely peridomestic bird and mosquito species. Factors influencing contact between peridomestic bird and mosquito species and contact between infected mosquitoes and vulnerable human populations may also be important in determining WNV risk in an area. Several urban form and demographic factors, such as population density and the proportion of aged housing units, have been linked with increased WNV risk. Other factors, such as proportion of old-growth forest and wetlands, have been linked to decreased WNV risk. In this study, we aimed to test the effect of several demographic, land use, and urban form variables on WNV risk within neighborhoods of the city of Ottawa, Canada, based on the spatiotemporal clustering of infected mosquitoes and human WNV cases. We found a large positive effect of population density and proportion of aged housing units on WNV risk, using both entomological and epidemiological data. Interestingly, we found a large negative effect of proportion of natural areas in our epidemiological analysis, but not in our entomological analysis. Although our epidemiological data set was relatively small, these results suggest entomological surveillance results should be interpreted alongside other factors when investigating risk to humans. Our study is also one of the few to suggest an effect of demography, land use, and urban form on WNV risk in a Canadian urban center, using both entomological and epidemiological data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".