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1.
Leora I. Horwitz; Tanayott Thaweethai; Shari B. Brosnahan; Mine S. Cicek; Megan L. Fitzgerald; Jason D. Goldman; Rachel Hess; S. L. Hodder; Vanessa L. Jacoby; Michael R. Jordan; Jerry A. Krishnan; Adeyinka O. Laiyemo; Torri D. Metz; Lauren Nichols; Rachel E. Patzer; Anisha Sekar; Nora G. Singer; Lauren E. Stiles; Barbara S. Taylor; Shifa Ahmed; Heather A. Algren; Khamal Anglin; Lisa Aponte-Soto; Hassan Ashktorab; Ingrid V. Bassett; Brahmchetna Bedi; Nahid Bhadelia; Christian Bime; Marie-Abele C. Bind; Lora J. Black; Andra L. Blomkalns; Hassan Brim; Mario Castro; James Chan; Alexander W. Charney; Benjamin K. Chen; Li Qing Chen; Peter Chen; David Chestek; Lori B. Chibnik; Dominic C. Chow; Helen Y. Chu; Rebecca G. Clifton; Shelby Collins; Maged M. Costantine; Sushma K. Cribbs; Steven G. Deeks; John D. Dickinson; Sarah E. Donohue; Matthew S. Durstenfeld; Ivette F. Emery; Kristine M. Erlandson; Julio C. Facelli; Rachael Farah-Abraham; Aloke V. Finn; Melinda S. Fischer; Valerie J. Flaherman; Judes Fleurimont; Vivian Fonseca; Emily J. Gallagher; Jennifer C. Gander; Maria Laura Gennaro; Kelly S. Gibson; Minjoung Go; Steven N. Goodman; Joey P. Granger; Frank L. Greenway; John W. Hafner; Jenny E. Han; Michelle S. Harkins; Kristine S.P. Hauser; James R. Heath; Carla R. Hernandez; On Ho; Matthew K. Hoffman; Susan E. Hoover; Carol R. Horowitz; Harvey Hsu; Priscilla Y. Hsue; Brenna L. Hughes; Prasanna Jagannathan; Judith A. James; Janice John; Sarah Jolley; S. E. Judd; Joy J. Juskowich; Diane G. Kanjilal; Elizabeth W. Karlson; Stuart D. Katz; J. Daniel Kelly; Sara W. Kelly; Arthur Y. Kim; John P. Kirwan; Kenneth S. Knox; Andre Kumar; Michelle F. Lamendola-Essel; Margaret Lanca; Joyce K. Lee-lannotti; R. Craig Lefebvre; Bruce D. Levy; Janet Y. Lin; Brian P. Logarbo Jr.; Jennifer K. Logue; Michele T. Longo; Carlos A. Luciano; Karen Lutrick; Shahdi K. Malakooti; Gail Mallett; Gabrielle Maranga; Jai G. Marathe; Vincent C. Marconi; Gailen D. Marshall; Christopher F. Martin; Jeffrey N. Martin; Heidi T. May; Grace A. McComsey; Dylan McDonald; Hector Mendez-Figueroa; Lucio Miele; Murray A. Mittleman; Sindhu Mohandas; Christian Mouchati; Janet M. Mullington; Girish N Nadkarni; Erica R. Nahin; Robert B. Neuman; Lisa T. Newman; Amber Nguyen; Janko Z. Nikolich; Igho Ofotokun; Princess U. Ogbogu; Anna Palatnik; Kristy T.S. Palomares; Tanyalak Parimon; Samuel Parry; Sairam Parthasarathy; Thomas F. Patterson; Ann Pearman; Michael J. Peluso; Priscilla Pemu; Christian M. Pettker; Beth A. Plunkett; Kristen Pogreba-Brown; Athena Poppas; J. Zachary Porterfield; John G. Quigley; Davin K. Quinn; Hengameh Raissy; Candida J. Rebello; Uma M. Reddy; Rebecca Reece; Harrison T. Reeder; Franz P. Rischard; Johana M. Rosas; Clifford J. Rosen; Nadine G. Rouphae; Dwight J. Rouse; Adam M. Ruff; Christina Saint Jean; Grecio J. Sandoval; Jorge L. Santana; Shannon M. Schlater; Frank C. Sciurba; Caitlin Selvaggi; Sudha Seshadri; Howard D. Sesso; Dimpy P. Shah; Eyal Shemesh; Zaki A. Sherif; Daniel J. Shinnick; Hyagriv N. Simhan; Upinder Singh; Amber Sowles; Vignesh Subbian; Jun Sun; Mehul S. Suthar; Larissa J. Teunis; John M. Thorp Jr.; Amberly Ticotsky; Alan T. N. Tita; Robin Tragus; Katherine R. Tuttle; Alfredo E. Urdaneta; P. J. Utz; Timothy M. VanWagoner; Andrew Vasey; Suzanne D. Vernon; Crystal Vidal; Tiffany Walker; Honorine D. Ward; David E. Warren; Ryan M. Weeks; Steven J. Weiner; Jordan C. Weyer; Jennifer L. Wheeler; Sidney W. Whiteheart; Zanthia Wiley; Natasha J. Williams; Juan P. Wisnivesky; John C. Wood; Lynn M. Yee; Natalie M. Young; Sokratis N. Zisis; Andrea S. Foulkes; - Recover Initiative.
medrxiv; 2023.
Preprint en Inglés | medRxiv | ID: ppzbmed-10.1101.2023.05.26.23290475

RESUMEN

Importance: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis. Methods: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged [≥]18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms. Discussion: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.


Asunto(s)
COVID-19 , Síndrome Respiratorio Agudo Grave
2.
Fractal and Fractional ; 6(8):410, 2022.
Artículo en Inglés | MDPI | ID: covidwho-1957259

RESUMEN

This study establishes a compartment model for the categorized COVID-19 risk area. In this model, the compartments represent administrative regions at different transmission risk levels instead of individuals in traditional epidemic models. The county-level regions are partitioned into High-risk (H), Medium-risk (M), and Low-risk (L) areas dynamically according to the current number of confirmed cases. These risk areas are communicable by the movement of individuals. An LMH model is established with ordinary differential equations (ODEs). The basic reproduction number R0 is derived for the transmission of risk areas to determine whether the pandemic is controlled. The stability of this LHM model is investigated by a Lyapunov function and Poincare–Bendixson theorem. We prove that the disease-free equilibrium (R0 < 1) is globally asymptotically stable and the disease will die out. The endemic equilibrium (R0 > 1) is locally and globally asymptotically stable, and the disease will become endemic. The numerical simulation and data analysis support the previous theoretical proofs. For the first time, the compartment model is applied to investigate the dynamics of the transmission of the COVID-19 risk area. This work should be of great value in the development of precision region-specific containment strategies.

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