T
Tobias F. Rinke de Wit
Researcher at University of Amsterdam
Publications - 193
Citations - 19138
Tobias F. Rinke de Wit is an academic researcher from University of Amsterdam. The author has contributed to research in topics: Population & HIV drug resistance. The author has an hindex of 45, co-authored 172 publications receiving 14241 citations. Previous affiliations of Tobias F. Rinke de Wit include University of Alcalá & Foundation Center.
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"I wish to remain HIV negative": Pre-exposure prophylaxis adherence and persistence in transgender women and men who have sex with men in coastal Kenya.
Makobu Kimani,Elise M van der Elst,Oscar Chirro,Elizabeth Wahome,Fauz Ibrahim,Nana Mukuria,Tobias F. Rinke de Wit,Susan M. Graham,Don Operario,Eduard J. Sanders,Eduard J. Sanders +10 more
TL;DR: In this paper, the authors assessed PrEP adherence by measuring tenofovir-diphosphate (TFV-DP) levels and explore motives for PrEP persistence in TGW and MSM.
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Building capacity for the assessment of HIV drug resistance : Experiences from the pharmaccess African studies to evaluate resistance network
Raph L. Hamers,Elske Straatsma,Cissy Kityo,Carole L. Wallis,Wendy S. Stevens,Kim C. E. Sigaloff,Margaret Siwale,Francesca Conradie,Mariette E. Botes,Kishor Mandaliya,Maureen Wellington,Akin Osibogun,Michèle van Vugt,Tobias F. Rinke de Wit +13 more
TL;DR: The sustainability of the PASER network is challenged by funding limitations, constraints in human resources, a vulnerable general health infrastructure, and high cost and complexity of molecular diagnostic testing.
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Emergence of untreatable, multidrug-resistant HIV-1 in patients failing second-line therapy in Kenya.
Seth C Inzaule,Raph L. Hamers,Irene Mukui,Kennedy Were,Prestone Owiti,Daniel Kwaro,Tobias F. Rinke de Wit,Clement Zeh +7 more
TL;DR: Overall, one in four patients failing second-line ART have completely exhausted available antiretrovirals in Kenya, highlighting the need for increased access to third-line drugs.
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Dried blood spot technology for CD4+ T-cell counting
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An update to the HIV-TRePS system: the development of new computational models that do not require a genotype to predict HIV treatment outcomes
Andrew D. Revell,Dechao Wang,Robin Wood,Carl A. Morrow,Hugo Tempelman,Raph L. Hamers,Gerardo Alvarez-Uria,Adrian Streinu-Cercel,Luminita Ene,Annemarie M. J. Wensing,Peter Reiss,Ard van Sighem,Mark Nelson,Sean Emery,Julio S. G. Montaner,H. Clifford Lane,Brendan Larder,Ard I van Sighem,Julio Montaner,Richard Harrigan,Tobias F. Rinke de Wit,Kim C. E. Sigaloff,Brian K. Agan,Vincent Marconi,Scott Wegner,Wataru Sugiura,Maurizio Zazzi,José M. Gatell,Elisa de Lazzari,Brian Gazzard,Anton Pozniak,Sundhiya Mandalia,Lidia Ruiz,Bonaventura Clotet,Schlomo Staszewski,Carlo Torti,Cliff Lane,J A Metcalf,Maria-Jesus Perez-Elias,Andrew Carr,Richard Norris,Karl Hesse,Emanuel Vlahakis,Roos Barth,Gordana Dragovic,David A. Cooper,John D. Baxter,Laura Monno,Bonventura Clotet,Gaston Picchio,Marie-Pierre deBethune +50 more
TL;DR: The development of the latest computational models to predict the response to combination antiretroviral therapy without a genotype, for potential use in resource-limited settings where genotyping is not generally available are described.