Determinant factors for malaria transmission on the coast of Oaxaca State, the main residual transmission focus in Mexico
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate the influence of demographic, socioeconomic and ecological factors in malaria transmission in the most important residual transmission focus in Mexico, located in the state of Oaxaca. MATERIAL AND METHODS: The extension of the focus was determined by a spatial and time analysis of the distribution of malaria cases in the state between 1998 and 1999 using a Geographical Information System. A malaria transmission intensity index (MTII) was constructed based on the total number of cases during the study period and the duration and frequency of transmission outbreaks within the villages. The relationship between local determinants and malaria transmission intensity was investigated using multinomial and ordered logistic models. RESULTS: The distribution of villages according to their MTII was: 325 high, 341 medium, 142 low and 717 with no transmission. Localities of high MTII were associated with areas having a tropical climate with summer rains and low water evaporation. Most high MTII villages were located in elevations between 200 and 500 m above sea level, in the area around Pochutla City. The amount of temporary streams in the neighborhood of localities had a highly significant positive association with the MTII. Distance to roads was only significant in the high malaria MTII stratum. CONCLUSIONS: The main factors determining malaria transmission in the focus are related to good conditions for the breeding of mosquito vectors. The existence of short-range population movements around Pochutla, the main economically active city in the area, indicates the necessity to implement a system of epidemiological surveillance to halt the dispersion of new outbreaks.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".