Interannual changes in the association between land use, abundance of <i>Culex quinquefasciatus</i> and <i>Culex tarsalis</i> (Diptera: Culicidae), and occurrence of arboviruses in Maricopa County, Arizona
Bibliographic record
Abstract
West Nile virus (WNV) (Orthoflavivirus nilense) and Saint Louis encephalitis virus (SLEV) (Orthoflavivirus louisense) are transmitted by Culex quinquefasciatus Say and Culex tarsalis Coquillett in Maricopa County, Arizona, where a significant increase in the number of WNV cases was reported in 2021. We used data collected between 2014 and 2021 from a network of CO2-baited surveillance traps to assess whether particular land use categories may have contributed to this rise in WNV cases. For each vector species and year, we estimated the association between the areas of each of 10 land use categories neighboring the traps and vector abundance or the odds of detecting WNV or SLEV in females from the traps. Across years, the percentage of traps detecting WNV in each vector was positively associated with the number of reported WNV human cases. Positive associations between areas of the land use categories Single-Family Residential, Industrial, and Golf Course and the odds of detecting WNV only occurred in 2021, indicating that a greater occurrence of WNV in vectors from within these land use categories may have contributed to the rise in WNV human cases in 2021. Areas of the land use categories Golf Course and Vacant were consistently negatively associated with Cx. quinquefasciatus abundance and the odds of detecting SLEV. Agriculture was consistently positively associated with Cx. tarsalis abundance and the odds of detecting SLEV. By identifying land use categories that may have mediated arbovirus transmission at landscape scale, our results provide valuable information for developing targeted vector control strategies.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".