Rabies surveillance in the United States during 2021
Bibliographic record
Abstract
OBJECTIVE: To provide epidemiological information on the occurrence of animal and human rabies in the US during 2021 and summaries of 2021 rabies surveillance for Canada and Mexico. PROCEDURES: State and territorial public health departments and USDA Wildlife Services provided data on animals submitted for rabies testing in 2021. Data were analyzed temporally and geographically to assess trends in domestic animal and wildlife rabies cases. RESULTS: During 2021, 54 US jurisdictions reported 3,663 rabid animals, representing an 18.2% decrease from the 4,479 cases reported in 2020. Texas (n = 456 [12.4%]), Virginia (297 [8.1%]), Pennsylvania (287 [7.8%]), North Carolina (248 [6.8%]), New York (237 [6.5%]), California (220 [6.0%]), and New Jersey (201 [5.5%]) together accounted for > 50% of all animal rabies cases reported in 2021. Of the total reported rabid animals, 3,352 (91.5%) involved wildlife, with bats (n = 1,241 [33.9%]), raccoons (1,030 [28.1%]), skunks (691 [18.9%]), and foxes (314 [8.6%]) representing the primary hosts confirmed with rabies. Rabid cats (216 [5.9%]), cattle (40 [1.1%]), and dogs (36 [1.0%]) accounted for 94% of rabies cases involving domestic animals in 2021. Five human rabies deaths were reported in 2021. CLINICAL RELEVANCE: The number of animal rabies cases reported in the US decreased significantly during 2021; this is thought to be due to factors related to the COVID-19 pandemic.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".