Tick Control in a Connected World: Challenges, Solutions, and Public Policy from a United States Border Perspective
Bibliographic record
Abstract
Ticks are able to transmit the highest number of pathogen species of any blood-feeding arthropod and represent a growing threat to public health and agricultural systems worldwide. While there are numerous and varied causes and effects of changes to tick-borne disease (re)emergence, three primary challenges to tick control were identified in this review from a U.S. borders perspective. (1) Climate change is implicated in current and future alterations to geographic ranges and population densities of tick species, pathogens they can transmit, and their host and reservoir species, as highlighted by Ixodes scapularis and its expansion across southern Canada. (2) Modern technological advances have created an increasingly interconnected world, contributing to an increase in invasive tick species introductions through the increased speed and frequency of trade and travel. The introduction of the invasive Haemaphysalis longicornis in the eastern U.S. exemplifies the challenges with control in a highly interconnected world. (3) Lastly, while not a new challenge, differences in disease surveillance, control, and management strategies in bordering countries remains a critical challenge in managing ticks and tick-borne diseases. International inter-agency collaborations along the U.S.–Mexico border have been critical in control and mitigation of cattle fever ticks (Rhipicephalus spp.) and highlight the need for continued collaboration and research into integrated tick management strategies. These case studies were used to identify challenges and opportunities for tick control and mitigation efforts through a One Health framework.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".