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Record W2967901999 · doi:10.1093/jtm/taz063

Ebola virus outbreak in North Kivu and Ituri provinces, Democratic Republic of Congo, and the potential for further transmission through commercial air travel

2019· article· en· W2967901999 on OpenAlexaff
Ashleigh R. Tuite, Alexander Watts, Kamran Khan, Isaac I. Bogoch

Bibliographic record

VenueJournal of Travel Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health NetworkSt. Michael's HospitalBlueDot (Canada)Public Health Ontario
Fundersnot available
KeywordsMedicineOutbreakTransmission (telecommunications)VirologyEbola virusDisease transmission2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)Environmental healthSocioeconomicsDiseaseTelecommunicationsInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The 2018-2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces, Democratic Republic of Congo (DRC), continues to spread. The recent discovery of cases in Uganda and in Goma, a major city in the eastern DRC, raises concern for potential EVD transmission in distant locales via commercial air travel. METHODS: We examined air travel patterns from the affected region with itinerary-level data from the International Air Transport Association for the year 2018 between July and October, inclusive. We focused on three scenarios: (i) travel from Beni airport, (ii) travel from Beni, Goma and Bunia airports and (iii) travel from Beni, Goma and Bunia, and Kigali airports. We evaluated country-level Infectious Disease Vulnerability Index (IDVI) scores for traveller destinations. RESULTS: There were 2255 commercial air passengers departing from Beni Airport during the specified time frame, all with domestic destinations, and 55% of which were to Goma. A total of 29 777 passengers travelled from Beni, Bunia and Goma airports during this time frame, with most travel (94.6%) departing from Goma Airport. A total of 72.4% of passengers' final destination from these three airports were within the DRC, primarily to Kinshasa. There were 166 281 outbound passengers from Beni, Bunia, Goma and Kigali airports with the majority (82.1%) of passengers departing from Kigali. The most frequent destinations from these airports were Nairobi, Kinshasa and Entebbe. Eight of the 10 destinations with greatest passenger volumes are to countries with IDVI scores less than 0.4. CONCLUSION: There is little commercial airline connectivity from the current EVD-affected area; however, larger cities in DRC and throughout East Africa should be aware of the low potential for EVD importation through this route. Most countries at greatest risk for EVD importation have limited capacity to manage these cases.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.206
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.019
GPT teacher head0.301
Teacher spread0.282 · 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

Citations27
Published2019
Admission routes1
Has abstractyes

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