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Record W4400242806 · doi:10.1093/jtm/taae089

Epidemiology of travel-associated dengue from 2007 to 2022: A GeoSentinel analysis

2024· article· en· W4400242806 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Travel Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversity of Calgary
FundersCenters for Disease Control and PreventionAarhus UniversitetPublic Health AgencyUniversiteit van AmsterdamPublic Health Agency of CanadaInternational Society of Travel MedicineAarhus Universitetshospital
KeywordsDengue feverMedicineEpidemiologyEnvironmental healthVirologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Dengue is a leading cause of febrile illness among international travellers. We aimed to describe the epidemiology and clinical characteristics of imported dengue in returning travellers evaluated at GeoSentinel sites from 2007 to 2022. METHODS: We retrieved GeoSentinel records of dengue among travellers residing in non-endemic countries. We considered dengue confirmed when diagnosed by a positive dengue virus (DENV)-specific reverse-transcriptase polymerase chain reaction, positive NS-1 antigen and/or anti-DENV IgG seroconversion, and probable when diagnosed by single anti-DENV IgM or high-titre anti-DENV IgG detection. Severe dengue was defined as evidence of clinically significant plasma leakage or bleeding, organ failure, or shock, according to the 2009 World Health Organization guidance. Complicated dengue was defined as either severe dengue or dengue with presence of any warning sign. Analyses were descriptive. RESULTS: This analysis included 5958 travellers with confirmed (n = 4859; 81.6%) or probable (n = 1099; 18.4%) dengue. The median age was 33 years (range: <1-91); 3007 (50.5%) travellers were female. The median travel duration was 21 days (interquartile range [IQR]: 15-32). The median time between illness onset and GeoSentinel site visit was 7 days (IQR: 4-15). The most frequent reasons for travel were tourism (67.3%), visiting friends or relatives (12.2%) and business (11.0%). The most frequent regions of acquisition were South East Asia (50.4%), South Central Asia (14.9%), the Caribbean (10.9%) and South America (9.2%). Ninety-five (1.6%) travellers had complicated dengue, of whom 27 (0.5%) had severe dengue and one died. Of 2710 travellers with data available, 724 (26.7%) were hospitalized. The largest number of cases (n = 835) was reported in 2019. CONCLUSIONS: A broad range of international travellers should be aware of the risk of acquiring dengue and receive appropriate pre-travel counselling regarding preventive measures. Prospective cohort studies are needed to further elucidate dengue risk by destination and over time, as well as severe outcomes and prolonged morbidity (long dengue) due to travel-related dengue.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.388
Teacher spread0.332 · 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