The spatio‐temporal distribution of a rodent reservoir host of cutaneous leishmaniasis
Bibliographic record
Abstract
Summary 1. The rodent Psammomys obesus is the main reservoir host for Leishmania major, the causative agent of cutaneous leishmaniasis in Tunisia, much of North Africa and mid‐western Asia. An understanding of the population dynamics of this rodent is essential to establish a preventive control strategy based on the early prediction of rodent outbreaks. 2. The study of P. obesus dynamics at a regional scale requires index‐based sampling. Rodent numbers were monitored twice per year at the beginning and end of the breeding season, using transects around the Sidi Bouzid region in central Tunisia. 3. Two different types of dynamics occurred in two drainage basins. Rodents living in the northern basin were at low density and those living in the southern basin were at high density. 4. At the scale of a plot, occupied burrows were generally associated with the presence of three Chenopodiaceae: Arthrocnemum glaucum, Salsola tetrandra and Suæda fruticosa, rarely in monospecific formations. However, in dry periods, occupied burrows drifted to A. glaucum formation linked with high moisture and salinity of the soil (χ2 MacNemar = 6·26). 5. The risk of a P. obesus outbreak can be assessed by a simultaneous knowledge of flooding regimes in the drainage basins, the distribution of halophytic plant formations, and the progressive movements of the rodents as drying out proceeds. The transect indices of rodents are easily repeatable, economical and would be applicable in other developing countries where cutaneous leishmaniasis occurs. 6. This work illustrates that simple ecological methods can assist the assessment of spatial and temporal components of epidemiological risk such as the proximity between rodent colonies and human habitats at the time of 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 | 0.001 | 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) | 0.002 | 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".