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Record W2996923971 · doi:10.1371/journal.pone.0226781

Zoonotic Babesia: A scoping review of the global evidence

2019· review· en· W2996923971 on OpenAlexafffund
Kaitlin M. Young, Tricia Corrin, Barbara Wilhelm, Carl Uhland, Judy Greig, Mariola Mascarenhas, Lisa Waddell

Bibliographic record

VenuePLoS ONE · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsAlberta HealthCegep de Saint HyacinthePublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsBabesiosisBabesiaIxodes scapularisIxodesBiologyTick-borne diseaseLyme diseaseZoonosisTickVector (molecular biology)VirologyIxodidae

Abstract

fetched live from OpenAlex

BACKGROUND: Babesiosis is a parasitic vector-borne disease of increasing public health importance. Since the first human case was reported in 1957, zoonotic species have been reported on nearly every continent. Zoonotic Babesia is vectored by Ixodes ticks and is commonly transmitted in North America by Ixodes scapularis, the tick species responsible for transmitting the pathogens that also cause Lyme disease, Powassan virus, and anaplasmosis in humans. Predicted climate change is expected to impact the spread of vectors, which is likely to affect the distribution of vector-borne diseases including human babesiosis. METHODS: A scoping review has been executed to characterize the global evidence on zoonotic babesiosis. Articles were compiled through a comprehensive search of relevant bibliographic databases and targeted government websites. Two reviewers screened titles and abstracts for relevance and characterized full-text articles using a relevance screening and data characterization tool developed a priori. RESULTS: This review included 1394 articles relevant to human babesiosis and/or zoonotic Babesia species. The main zoonotic species were B. microti, B. divergens, B. duncani and B. venatorum. Articles described a variety of study designs used to study babesiosis in humans and/or zoonotic Babesia species in vectors, animal hosts, and in vitro cell cultures. Topics of study included: pathogenesis (680 articles), epidemiology (480), parasite characterization (243), diagnostic test accuracy (98), mitigation (94), treatment (65), transmission (54), surveillance (29), economic analysis (7), and societal knowledge (1). No articles reported predictive models investigating the impact of climate change on Babesia species. CONCLUSION: Knowledge gaps in the current evidence include research on the economic burden associated with babesiosis, societal knowledge studies, surveillance of Babesia species in vectors and animal hosts, and predictive models on the impact of climate change. The scoping review results describe the current knowledge and knowledge gaps on zoonotic Babesia which can be used to inform future policy and decision making.

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)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.027
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0270.026
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.127
GPT teacher head0.335
Teacher spread0.208 · 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 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

Citations88
Published2019
Admission routes2
Has abstractyes

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