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Is there safety in numbers? The effect of cattle herding on biting risk from tsetse flies

2007· article· en· W2090376189 on OpenAlexafffund
Stephen J. Torr, Anne Prior, Paul J. Wilson, Steven R. Schofield

Bibliographic record

VenueMedical and Veterinary Entomology · 2007
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsTrent University
FundersDepartment for International DevelopmentTrent University
KeywordsHerdBiologyHerdingBitingLivestockVeterinary medicineVector (molecular biology)EcologyZoologyGeographyForestry

Abstract

fetched live from OpenAlex

In sub-Saharan Africa, tsetse (Glossina spp.) transmit species of Trypanosoma which threaten 45-50 million cattle with trypanosomiasis. These livestock are subject to various herding practices which may affect biting rates on individual cattle and hence the probability of infection. In Zimbabwe, studies were made of the effect of herd size and composition on individual biting rates by capturing tsetse as they approached and departed from groups of one to 12 cattle. Flies were captured using a ring of electrocuting nets and bloodmeals were analysed using DNA markers to identify which individual cattle were bitten. Increasing the size of a herd from one to 12 adults increased the mean number of tsetse visiting the herd four-fold and the mean feeding probability from 54% to 71%; the increased probability with larger herds was probably a result of fewer flies per host, which, in turn, reduced the hosts' defensive behaviour. For adults and juveniles in groups of four to eight cattle, > 89% of bloodmeals were from the adults, even when these comprised just 13% of the herd. For groups comprising two oxen, four cows/heifers and two calves, a grouping that reflects the typical composition of communal herds in Zimbabwe, approximately 80% of bloodmeals were from the oxen. Simple models of entomological inoculation rates suggest that cattle herding practices may reduce individual trypanosomiasis risk by up to 90%. These results have several epidemiological and practical implications. First, the gregarious nature of hosts needs to be considered in estimating entomological inoculation rates. Secondly, heterogeneities in biting rates on different cattle may help to explain why disease prevalence is frequently lower in younger/smaller cattle. Thirdly, the cost and effectiveness of tsetse control using insecticide-treated cattle may be improved by treating older/larger hosts within a herd. In general, the patterns observed with tsetse appear to apply to other genera of cattle-feeding Diptera (Stomoxys, Anopheles, Tabanidae) and thus may be important for the development of strategies for controlling other diseases affecting livestock.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.025
GPT teacher head0.355
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations37
Published2007
Admission routes2
Has abstractyes

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