Molecular prevalence of trypanosome infections in cattle and tsetse flies in the Maasai Steppe, northern Tanzania
Bibliographic record
Abstract
BACKGROUND: African trypanosomosis is a disease of public health and economic importance that poses a major threat to the livelihoods of people living in the Maasai Steppe, where there is a significant interaction between people, livestock and wildlife. The vulnerability of the Maasai people to the disease is enhanced by the interaction of their cattle, which act as vehicles for trypanosomes, and tsetse flies close to wildlife in protected areas. This study was aimed at identification of trypanosome infections circulating in cattle and tsetse flies in order to understand their distribution and prevalence in livestock/wildlife interface areas in the Maasai Steppe. METHODS: A total of 1002 cattle and 886 tsetse flies were sampled from June 2015 to February 2016 in five villages and PCR was conducted to amplify the internal transcribed spacer 1 (ITS1) from trypanosomes. All Trypanosoma brucei-positive samples were further tested for the presence of the serum resistance-associated (SRA) gene found in human-infective trypanosomes using the SRA-LAMP technique. RESULTS: The overall prevalence of trypanosome infections was 17.2% in cattle and 3.4% in tsetse flies. Using a nested PCR, prevalence and abundance of five trypanosome species, Trypanosoma vivax, T. brucei, T. simiae, T. theileri and T. congolense, were determined, which varied with season and location. The highest prevalence of the identified trypanosome species was recorded at the end of wet season with an exception of T. brucei which was high at the beginning of the wet season. No human-infective trypanosomes were detected in both cattle and tsetse fly DNA. CONCLUSIONS: This study confirms that seasonality and location have a significant contribution to the prevalence of trypanosome species in both mammalian and vector hosts. These results are important for designing of community-wide vector and disease control interventions and planning of sustainable regimes for reduction of the burden of trypanosomosis in endemic pastoral areas, such as the Maasai Steppe in northern Tanzania.
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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 | 0.000 |
| 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) | 0.001 | 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".