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Global prevalence and genotype distribution of hepatitis C virus infection in 2015: a modelling study
Sarah Blach, Stefan Zeuzem, Michael P. Manns, Ibrahim Altraif, Ann‐Sofi Duberg, David Handojo Muljono, Imam Waked, Seyed M Alavian, Mei–Hsuan Lee, Francesco Negro, Faisal Abaalkhail, Ahmed Ms Abdou, Maheeba Abdulla, Antoine Abou Rached, Inka Aho, Ulus Salih Akarca, Imad Ghazzawi, Saad Al Kaabi, Faryal Al Lawati, Khalid Al Namaani, Y. Al Serkal, Said A. Al‐Busafi, L. Al‐Dabal, Soo Aleman, Abdullah Alghamdi, Abdulrahman Aljumah, Hamad Eid Al‐Romaihi, Monique Andersson, Vic Arendt, Perttu Arkkila, Abdullah M. Assiri, Oidov Baatarkhuu, Abate Bane, Ziv Ben‐Ari, Colm Bergin, Fernando Bessone, Florian Bihl, Abdul Rahman Bizri, Martin Blachier, Antonio Javier Blasco, Carlos Eduardo Brandão‐Mello, Philip Bruggmann, Cheryl Brunton, Filipe Calinas, Henry Lik‐Yuen Chan, Asad Chaudhry, Hugo Cheinquer, Chien‐Jen Chen, Rong‐Nan Chien, Moon Seok Choi, Peer Brehm Christensen, Wan‐Long Chuang, Vladimir Chulanov, Laura Cisneros, Mette Rye Clausen, Matthew Cramp, Antonio Craxı̀, Esther A. Croes, Olav Dalgård, Jorge Daruich, Victor de Lédinghen, Gregory J. Dore, Manal H. El‐Sayed, Gül Ergör, Gamal Esmat, Chris Estes, Karolin Falconer, Elmoubasher Farag, Maria Lúcia Gomes Ferraz, Paulo Roberto Abrão Ferreira, Robert Flisiak, Soňa Fraňková, Ivane Gamkrelidze, Ed Gane, Javier García‐Samaniego, Amir Ghafoor Khan, Ilias Gountas, Adrian Goldis, Magnús Gottfreðsson, Jason Grebely, Michael Gschwantler, Mário Guimarães Pessôa, J. Gunter, Behzad Hajarizadeh, O. Hajelssedig, Saeed Hamid, Waseem Hamoudi, Angelos Hatzakis, Sayed Himatt, Harald Hofer, Irena Hrstić, Yee-Tak Hui, Béla Hunyady, Ramazan Idılman, Wasim Jafri, Rohani Jahis, Naveed Z. Janjua, Peter Jarčuška, Agita Jēruma, Jón G. Jónasson, Yasser Kamel, Jia‐Horng Kao, Sabahattin Kaymakoğlu, David Kershenobich, Jawad Khamis, Young Sam Kim, Loreta A. Kondili, Zaher Koutoubi, Mel Krajden, Henrik Krarup, Moon-sing Lai, Wim Laleman, Wai‐Cheung Lao, Daniel Lavanchy, Pablo Lázaro, Henri Leleu, Olufunmilayo Lesi, Laurentius A. Lesmana, Michael Li, Valentina Liakina, Young‐Suk Lim, Boris Lukšić, Adam Mahomed, Matti Maimets, Mihály Makara, Abraham O. Malu, Rui Tato Marinho, Paul Marotta, Stefan Mauss, Muhammad Sadik Memon, Maria Cássia Mendes Corrêa, Nahúm Méndez‐Sánchez, Shahin Merat, Ammal M. Metwally, Rosmawati Mohamed, Christophe Moreno, Fadi H. Mourad, Beat Müllhaupt, Kimberly Murphy, H. Nde, Richard Njouom, Diana Nonković, Suzanne Norris, Solomon Obekpa, Stephen Oguche, Sigurður Ólafsson, Marián Oltman, O. Omede, C. Omuemu, Ohene Opare‐Sem, Anne Øvrehus, Shirley Owusu‐Ofori, Tsendsuren Oyunsuren, George Papatheodoridis, K. Pasini, Kevork Peltekian, Richard Odame Phillips, Nikolay Pimenov, Hossein Poustchi, Nishi Prabdial‐Sing, Huma Qureshi, Alnoor Ramji, Devin Razavi‐Shearer, Kathryn Razavi‐Shearer, Berhane Redae, H. W. Reesink, Ezequiel Ridruejo, Lewis R. Roberts, Stuart K. Roberts, William Rosenberg, Françoise Roudot‐Thoraval, Stephen Ryder, Rifaat Safadi, Olga Sagalova, Riina Salupere, Faisal M. Sanai, J.F. Sánchez-Ávila, Vivek A. Saraswat, Rui Sarmento‐Castro, Christoph Sarrazin, Jonathan Schmelzer, Ivan Schréter, Carole Seguin‐Devaux, Samir R. Shah, Ala I. Sharara, Manik Sharma, A. Shevaldin, Gamal Shiha, William Sievert, Mark Sonderup, Kyriakos Souliotis, Danutė Speičienė, Jan Šperl, Peter Stärkel, Rudolf Stauber, Catherine Stedman, Daniel Struck, Tung‐Hung Su, Vana Sypsa, Soek-Siam Tan, Junko Tanaka, Alexander Thompson, Ieva Tolmane, Krzysztof Tomasiewicz, Jonas Valantinas, Pierre Van Damme, Ingo van Thiel, Hans Van Vlierberghe, Adriana Vince, Wolfgang Vogel, Heiner Wedemeyer, Nina Weis, Vincent Wai‐Sun Wong, César Yaghi, Ayman Yosry, Man‐Fung Yuen, Evy Yunihastuti, Aasim Yusuf, Eli Zuckerman, Homie Razavi
Bibliographic record
VenueThe Lancet. Gastroenterology & hepatology · 2016
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
FundersCliniques Universitaires Saint-LucBritish Columbia Centre for Disease ControlKwame Nkrumah University of Science and TechnologyMerck Sharp and DohmeFakultet Medicinskih Nauka, Univerziteta U KragujevcuMedical Research CouncilAbbott DiagnosticsTartu ÜlikoolUniversity of Cape TownUniversitas IndonesiaKementerian Kesihatan MalaysiaUniversidade de São PauloMonash UniversityUniversidad de Buenos AiresRigshospitaletInstituto Mexicano del Seguro SocialAalborg UniversitetshospitalTehran University of Medical Sciences and Health ServicesUniversiti MalayaUniversity of New South WalesKU LeuvenBundesministerium für GesundheitAriad PharmaceuticalsNational Taiwan University HospitalFakultas Kedokteran, Universitas IndonesiaAalborg UniversitetUniversity of UlsanCairo UniversityKing Saud UniversityIntercept PharmaceuticalsNational Taiwan UniversityInstitut National de la Santé et de la Recherche MédicaleUniversität WienUniversity of NottinghamHáskóli ÍslandsMinisterio de Economía y CompetitividadBristol-Myers SquibbHadassah Medical OrganizationCleveland ClinicCilagAnkara UniversitesiAin Shams UniversityUniversità degli Studi di PalermoDokuz Eylül ÜniversitesiNottingham University Hospitals NHS TrustUniversity College LondonAlexion PharmaceuticalsMedizinische Universität WienNational and Kapodistrian University of AthensKarolinska InstitutetBill and Melinda Gates FoundationFalk FoundationIstituto Superiore di SanitàGilead SciencesDalhousie UniversityGlaxoSmithKlineAkershus UniversitetssykehusTrimbos-instituutAmerican University of BeirutAlnylam PharmaceuticalsNational Institute for Health and Care Research
KeywordsGenotypeVirologyHepatitis C virusMedicineHepatitis CDistribution (mathematics)BiologyVirusGeneticsMathematics
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.017
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 head0.057
GPT teacher head0.372
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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 designSimulation or modeling
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
Citations2,032
Published2016
Admission routes1
Has abstractno