Antibiotic Resistance Increases with Local Temperature
Why this work is in the frame
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Bibliographic record
Abstract
Antibiotic resistance is considered as one of our greatest emerging public health threats. Current understanding of the factors governing spread of antibiotic-resistant organisms and mechanisms among populations is limited. We explored the roles of local temperature, population density, and additional factors on the distribution of antibiotic resistance across the United States, using a database of regional antibiotic resistance that incorporates over 1.6 million bacterial pathogens from human clinical isolates over the years 2013–2015. We identified that increasing local temperature as well as population density were associated with increasing antibiotic resistance in common pathogens. An increase in temperature of 10oC was associated with increases in antibiotic resistance of 4.2%, 2.2%, and 3.6% for the common pathogens Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. The effect of temperature on antibiotic resistance was robust across almost all classes of antibiotics and pathogens and strengthened over time. These findings suggest that current forecasts of the burden of antibiotic resistance could be significant underestimates in the face of a growing population and warming planet. Antibiotic resistance increases with increasing temperature. (A) A heatmap of mean normalized antibiotic resistance for E. coli for all antibiotics across the USA. (B) A heatmap of 30-year average minimum temperature (oC) across the USA. All authors: No reported disclosures.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it