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Zika virus outbreak in Suriname, a report based on laboratory surveillance data

2018· article· en· W2800670911 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePLoS Currents · 2018
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsOutbreakZika virusChikungunyaMedicineGeographyEnvironmental healthSocioeconomicsDemographyPediatricsVirologyVirus

Abstract

fetched live from OpenAlex

INTRODUCTION: Since the identification of ZIKV in Brazil in May 2015, the virus has spread extensively throughout the Americas. Cases of ZIKV infection have been reported in Suriname since October 2, 2015. METHODS: A laboratory-based surveillance system was quickly implemented according to previous experience with the emergence of chikungunya. General practitioners and public health centers located in different districts of Suriname were asked to send blood samples from suspicious cases to Academic Hospital for molecular diagnosis of Zika virus infection. We investigated Zika-related laboratory data collected during surveillance and response activities to provide the first outbreak report in Suriname in terms of time, location and person. RESULTS: A total of 791 molecularly confirmed cases were reported during a 48-week interval from October 2015 to August 2016. The majority of ZIKV-positive cases involved women between 20 and 39 years of age, reflecting concern about Zika infection during pregnancy. The outbreak peaked in mid-January and gradually spread from the district of Paramaribo to western coastal areas. DISCUSSION: This report provides a simple and comprehensive description of the outbreak in Suriname and demonstrates the utility of laboratory data to highlight the spatiotemporal dynamics of the outbreak in that country.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.047
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

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

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 head0.044
GPT teacher head0.329
Teacher spread0.285 · 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