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Record W3007638478 · doi:10.1371/journal.pntd.0007858

Human myiasis in Ecuador

2020· review· en· W3007638478 on OpenAlexaff
Manuel Calvopiña, Esteban Ortiz‐Prado, Byron Castañeda, Isabel Cueva, Richar Rodríguez‐Hidalgo, Philip J. Cooper

Bibliographic record

VenuePLoS neglected tropical diseases · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMyiasisBiologyZoologyMedicineEcologyLarva

Abstract

fetched live from OpenAlex

We review epidemiological and clinical data on human myiasis from Ecuador, based on data from the Ministry of Public Health (MPH) and a review of the available literature for clinical cases. The larvae of four flies, Dermatobia hominis, Cochliomyia hominivorax, Sarcophaga haemorrhoidalis, and Lucilia eximia, were identified as the causative agents in 39 reported clinical cases. The obligate D. hominis, causing furuncular lesions, caused 17 (43.5%) cases distributed along the tropical Pacific coast and the Amazon regions. The facultative C. hominivorax was identified in 15 (38%) clinical cases, infesting wound and cavitary lesions including orbital, nasal, aural and vaginal, and occurred in both subtropical and Andean regions. C. hominivorax was also identified in a nosocomial hospital-acquired wound. Single infestations were reported for S. haemorrhoidalis and L. eximia. Of the 39 clinical cases, 8 (21%) occurred in tourists. Ivermectin, when it became available, was used to treat furuncular, wound, and cavitary lesions successfully. MPH data for 2013-2015 registered 2,187 cases of which 54% were reported in men; 46% occurred in the tropical Pacific coast, 30% in the temperate Andes, 24% in the tropical Amazon, and 0.2% in the Galapagos Islands. The highest annual incidence was reported in the Amazon (23 cases/100,000 population), followed by Coast (5.1/100,000) and Andes (4.7/100,000). Human myiasis is a neglected and understudied ectoparasitic infestation, being endemic in both temperate and tropical regions of Ecuador. Improved education and awareness among populations living in, visitors to, and health personnel working in high-risk regions, is required for improved epidemiological surveillance, prevention, and correct diagnosis and treatment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.282
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations40
Published2020
Admission routes1
Has abstractyes

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