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Record W2480643507 · doi:10.1017/s146625231600013x

Prevalence of tuberculosis, brucellosis and trypanosomiasis in cattle in Tanzania: a systematic review and meta-analysis

2016· review· en· W2480643507 on OpenAlexaff
Silvia Alonso, Ian R. Dohoo, Johanna F. Lindahl, Cristóbal Verdugo, Isaiah Akuku, Delia Grace

Bibliographic record

VenueAnimal Health Research Reviews · 2016
Typereview
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsHealth PEI
FundersAustralian Centre for International Agricultural Research
KeywordsBrucellosisBrucellaTanzaniaVeterinary medicineMeta-analysisTuberculosisMedicinePrevalenceBiologyMycobacterium tuberculosisEpidemiologyEnvironmental healthInternal medicinePathologyGeography

Abstract

fetched live from OpenAlex

A meta-analysis was performed to derive prevalence estimates for Brucella spp., Mycobacterium spp. and Trypanosoma spp. in cattle in Tanzania using data derived from a systematic review of zoonotic hazards in cattle production systems. Articles published before 2012 reporting prevalence and considered at least moderate in quality were included in the analysis. Results showed high heterogeneity between studies, with wide ranges in the reported prevalence: Brucella (0.3-60.8%), Mycobacterium (0.1-13.2%) and Trypanosoma (0.82-33.3%). Overall meta-analytic mean prevalence estimates were 8.2% (95% CI 6.5-10.2), 1.28% (95% CI 0.35-4.58) and 10.3% (95% CI 6.20-16.70) respectively, for Brucella spp., Mycobacterium spp. and Trypanosoma spp. Time and region were predictors of variability of Brucella spp. prevalence, while diagnostic test was a strong predictor of Mycobacterium spp. prevalence, with higher prevalence estimates given by skin tests compared with post-mortem inspection. None of the studied factors were associated with prevalence of Trypanosoma spp. The small sample sizes, range of study locations, study designs and diagnostics used, contributed to high variability among prevalence estimates. Larger and more robust prevalence studies are needed to adequately support risk assessment and management of animal and public health threats.

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 imitation

Not 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.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0280.003
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.556
GPT teacher head0.557
Teacher spread0.001 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2016
Admission routes1
Has abstractyes

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