Rats and the COVID-19 pandemic: Early data on the global emergence of rats in response to social distancing
Bibliographic record
Abstract
Abstract Following widespread closures of food-related businesses due to efforts to curtail the spread of SARS-CoV-2, public health authorities reported increased sightings of rats in close vicinity of people. Because rats vector a number of pathogens transmissible to people, changes in their behavior has consequences for human health risks. To determine the extent of how stay-at-home measures influenced patterns of rat sightings we: 1) examined the number of rat-related public service requests before and during the period of lockdown in New York City (NYC) and Tokyo, Japan; 2) examined reports made in proximity to closed food service establishments in NYC; and 3) surveyed pest control companies in the United States, Canada, Japan, and Poland. During the month following lockdown, the overall number of reports decreased by 30% in NYC, while increasing 24% in Tokyo. However, new hotspots of 311 calls were observed in proximity of closed food service establishments in NYC; and there was a consistent positive association between kernel density estimates of food service establishments and location of 311 calls ( r = 0.33 to 0.45). Similarly, more reports were observed in the restaurant-dense eastern side of Tokyo. Changes in clientele for pest control companies varied geographically, with 37% of pest-management companies surveyed in North America reporting 50-100% of their post-lockdown rat-related requests coming from new clients. In Warsaw, where there are no clusters of restaurants in densely-populated areas, there were no changes. In Tokyo, there were no changes in clients. We conclude that changes in public service calls are region-specific and localized, with increases in rat sightings more likely near restaurant-dense regions. Pest control companies surveyed in North America either lost much of their business or shifted clientele from old to new locations. We discuss possible mitigation measures including ramping up pest control during re-opening of food-related establishments and the need for citywide rodent surveillance and disease monitoring.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| 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".