Responding to avian influenza A <scp>H5N1</scp> detection on a hospital property in Maine—An interdisciplinary approach
Bibliographic record
Abstract
BACKGROUND: The risk of infection with avian influenza A viruses currently circulating in wild and domestic birds in the Americas is considered low for the general public; however, detections in humans have been reported and warning signs of increased zoonotic potential have been identified. In December 2022, two Canada geese residing on the grounds of an urban hospital in Maine tested positive for influenza A H5N1 clade 2.3.4.4b. AIMS: Given the opportunity for exposure to staff and hospital visitors through potentially infected faeces on the property, public health authorities determined mitigation efforts were needed to prevent the spread of disease. The ensuing response relied on collaboration between the public health and animal health agencies to guide the hospital through efforts in preventing possible zoonotic transmission to humans. MATERIALS AND METHODS: Mitigation efforts included staff communication and education, environmental cleaning and disinfection, enhanced illness surveillance among staff and patients, and exposure and source reduction. RESULTS: No human H5N1 cases were identified, and no additional detections in birds on the property occurred. Hospital staff identified barriers to preparedness resulting from a lack of understanding of avian influenza A viruses and transmission prevention methods, including avian influenza risk in resident wild bird populations and proper wildlife management methods. CONCLUSION: As this virus continues to circulate at the animal-human interface, this event and resulting response highlights the need for influenza A H5N1 risk awareness and guidance for facilities and groups not traditionally involved in avian influenza responses.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".