Climate change and Trypanosoma cruzi transmission in North and central America
Bibliographic record
Abstract
Trypanosoma cruzi is a protozoan parasite that causes Chagas disease in humans. Transmission of T cruzi by triatomine vectors is dependent on diverse environmental and socioeconomic factors. Climate change, which is disrupting patterns of human habitation and land use, can affect the epidemiology of Chagas disease by influencing the distribution of vector and host species. We conducted a review using triatomine distribution as a proxy for T cruzi transmission in North America (Canada, Mexico, and the USA) and central America (Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, and Panama) and investigated the association of T cruzi transmission with climate change, identifying 12 relevant studies. Most studies (n=9) modelled the effect of the scenario of climate change on the distribution of relevant vector species and found that global warming could sometimes favour and sometimes hinder triatomine distribution. There is a need for more research in parasite biology and social sciences to further understand how climate change and socioeconomic factors can affect the epidemiology of this neglected tropical disease.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".