Evaluating the spatial ecology of anthrax in North America: examining epidemiological components across multiple geographic scales using a GIS-based approach
Bibliographic record
Abstract
This dissertation explores the spatial ecology and potential pathways of infection of anthrax, Bacillus anthracis, in North America. A multi-scale approach was used to evaluate the components required for disease agent survival in the environment, interactions with wildlife, and the potential role that vectors play in anthrax transmission. First, ecological niche modeling with the Genetic Algorithm for Rule-set Production (GARP) was used to predict the geographic distribution of anthrax in the continental U.S. using case data from outbreaks between 1957 and 2005. These results were then used to produce the first quantitative, continental scale predictions of anthrax in Mexico. At the meso-scale, the route of transmission in white-tailed deer is unknown, despite a large number of outbreaks in wild deer in Texas in recent years (2001 – 2005). To determine the interactions between deer and potential anthrax sources, two pilot studies were conducted on 1) the distribution of biting flies in relation to anthrax cases to evaluate the potential role of hematophagous flies as vectors, and 2) the summer home ranges of deer in relation to fly densities and carcass locations. The results of the GARP studies support the use of the technique for modeling the niche of this disease and suggest a central corridor of anthrax habitat from southwest Texas to the Canadian border, with disjunct areas in the Pacific Northwest and California. Mexico’s predicted areas were extensions of the Texas and California ranges. The deer study suggests that deer interactions with spores occur within a limited home range in Texas and long-distance movement of spores is unlikely by individual deer. Biting fly densities were highest in areas of known anthrax infection and lowest in areas where case-positive deer have not been identified, suggesting that flies may play a role in disease transmission, either through mechanical transmission or through increased nuisance that leads to immuno-suppression in deer. This dissertation presents the first continental-scale predictions for the geographic distribution of anthrax in the U.S. and Mexico. Additionally, this is the first known study to evaluate spatial patterns between known cases, fly densities, and animal movements.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".