Sustainable, integrated control of native vectors: The case of Chagas disease in Central America
Bibliographic record
Abstract
Despite successes in reducing transmission, Chagas disease (American trypanosomiasis) remains the greatest economic burden of any parasitic disease in Latin America afflicting mostly the poor and further contributing to poverty. We review a long-term (2001-2022), integrated Ecohealth approach that addresses sustainable development goals to reduce risk of Chagas transmission by the main native vector in Central America, Triatoma dimidiata , s.l. The basis of the Ecohealth intervention was the identification of the risk factors for house infestation, an understanding of and collaboration with local communities, and genetic and proteomic studies that revealed the epidemiology and mechanisms of the rapid reinfestation seen following insecticide application. We review the development of this approach from a pilot project in two Guatemalan villages, to an expanded initiative across three countries with vastly different ecology, cultures, and municipal organization, and finally development of a multi-institutional, large-scale project to develop a strategy to tackle the remaining hot spots in Central America. This integrated Ecohealth approach resulted in reduced risk of transmission as measured by a sustained decrease in house infestation without further use of insecticides, a reduction in vectors with human blood meals and the Chagas parasite, as well as other health and economic benefits. We discuss lessons learned and how this approach could be applied to other vector-borne diseases.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".