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Wyszukujesz frazę ""Riley, Pete"" wg kryterium: Autor

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    Tytuł:
    COVID-19: On the Disparity in Outcomes Between Military and Civilian Populations.
    Autorzy:
    Riley P; Predictive Science Inc., San Diego, CA 92121, USA.
    Ben-Nun M; Predictive Science Inc., San Diego, CA 92121, USA.
    Turtle J; Predictive Science Inc., San Diego, CA 92121, USA.
    Bacon D; Leidos Inc., Tysons, VA 22182, USA.
    Owens AN; Defense Threat Reduction Agency (DTRA) Reachback, Fort Belvoir, VA 22060-6201, USA.
    Riley S; Department of Infectious Disease Epidemiology, School of Public Health, Imperial College, London, SW7 2BX, UK.
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    Źródło:
    Military medicine [Mil Med] 2023 Jan 04; Vol. 188 (1-2), pp. 311-315.
    Typ publikacji:
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
    MeSH Terms:
    COVID-19*/epidemiology
    Military Personnel*
    Humans
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
    Tytuł:
    Consistent pattern of epidemic slowing across many geographies led to longer, flatter initial waves of the COVID-19 pandemic.
    Autorzy:
    Ben-Nun M; Predictive Science Inc., San Diego California United States of America.
    Riley P; Predictive Science Inc., San Diego California United States of America.
    Turtle J; Predictive Science Inc., San Diego California United States of America.
    Riley S; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
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    Źródło:
    PLoS computational biology [PLoS Comput Biol] 2022 Aug 15; Vol. 18 (8), pp. e1010375. Date of Electronic Publication: 2022 Aug 15 (Print Publication: 2022).
    Typ publikacji:
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.
    MeSH Terms:
    COVID-19*/epidemiology
    Pandemics*
    Forecasting ; Government ; Humans ; Seasons
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
    Tytuł:
    COVID-19 deaths: Which explanatory variables matter the most?
    Autorzy:
    Riley P; Predictive Science Inc., San Diego, California, United States of America.
    Riley A; Predictive Science Inc., San Diego, California, United States of America.
    Turtle J; Predictive Science Inc., San Diego, California, United States of America.
    Ben-Nun M; Predictive Science Inc., San Diego, California, United States of America.
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    Źródło:
    PloS one [PLoS One] 2022 Apr 21; Vol. 17 (4), pp. e0266330. Date of Electronic Publication: 2022 Apr 21 (Print Publication: 2022).
    Typ publikacji:
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
    MeSH Terms:
    COVID-19*/epidemiology
    Humans ; Pandemics ; Physical Distancing ; Population Density ; SARS-CoV-2 ; United States/epidemiology
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
    Tytuł:
    Accurate influenza forecasts using type-specific incidence data for small geographic units.
    Autorzy:
    Turtle J; Infectious Disease Group, Predictive Science Inc., San Diego, California, United States.
    Riley P; Infectious Disease Group, Predictive Science Inc., San Diego, California, United States.
    Ben-Nun M; Infectious Disease Group, Predictive Science Inc., San Diego, California, United States.
    Riley S; Infectious Disease Group, Predictive Science Inc., San Diego, California, United States.; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, United Kingdom.
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    Źródło:
    PLoS computational biology [PLoS Comput Biol] 2021 Jul 29; Vol. 17 (7), pp. e1009230. Date of Electronic Publication: 2021 Jul 29 (Print Publication: 2021).
    Typ publikacji:
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
    MeSH Terms:
    Forecasting/*methods
    Influenza, Human/*epidemiology
    Centers for Disease Control and Prevention, U.S. ; Computational Biology ; Epidemiological Monitoring ; Geography ; Humans ; Incidence ; Influenza, Human/diagnosis ; Models, Statistical ; Point-of-Care Testing/statistics & numerical data ; Public Health ; Seasons ; Software ; Time Factors ; United States/epidemiology
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknieSzczegóły
    Tytuł:
    Forecasting national and regional influenza-like illness for the USA.
    Autorzy:
    Ben-Nun M; Predictive Science Inc., San Diego, CA, USA.
    Riley P; Predictive Science Inc., San Diego, CA, USA.
    Turtle J; Predictive Science Inc., San Diego, CA, USA.
    Bacon DP; Leidos, McLean, VA, USA.
    Riley S; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, UK.
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    Źródło:
    PLoS computational biology [PLoS Comput Biol] 2019 May 23; Vol. 15 (5), pp. e1007013. Date of Electronic Publication: 2019 May 23 (Print Publication: 2019).
    Typ publikacji:
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
    MeSH Terms:
    Epidemics*/statistics & numerical data
    Forecasting/*methods
    Influenza, Human/*epidemiology
    Centers for Disease Control and Prevention, U.S. ; Computational Biology ; Humans ; Humidity ; Markov Chains ; Models, Biological ; Models, Statistical ; Monte Carlo Method ; Prospective Studies ; Retrospective Studies ; Seasons ; United States/epidemiology
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
    Tytuł:
    Collaborative efforts to forecast seasonal influenza in the United States, 2015-2016.
    Autorzy:
    McGowan CJ; Epidemiology and Prevention Branch, Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Biggerstaff M; Epidemiology and Prevention Branch, Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. .
    Johansson M; Dengue Branch, Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
    Apfeldorf KM; Arete Associates, Northridge, California, USA.
    Ben-Nun M; Predictive Science, Inc., San Diego, California, USA.
    Brooks L; Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
    Convertino M; Division of Media and Network Technologies and Division of Frontier Science, Graduate School of Information Science and Technology, Gi-CoRE Station for Big Data & Cybersecurity, Hokkaido University, Sapporo, Japan.; Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
    Erraguntla M; Knowledge Based Systems, Inc., College Station, Texas, USA.
    Farrow DC; Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
    Freeze J; Knowledge Based Systems, Inc., College Station, Texas, USA.
    Ghosh S; Discovery Analytics Center, Virginia Tech University, Arlington, Virginia, USA.
    Hyun S; Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
    Kandula S; Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA.
    Lega J; Department of Mathematics, University of Arizona, Tucson, Arizona, USA.
    Liu Y; Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
    Michaud N; Department of Statistics, University of California, Berkeley, Berkeley, California, USA.
    Morita H; Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA.
    Niemi J; Department of Statistics, Iowa State University, Ames, Iowa, USA.
    Ramakrishnan N; Discovery Analytics Center, Virginia Tech University, Arlington, Virginia, USA.
    Ray EL; Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, Massachusetts, USA.
    Reich NG; Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, Amherst, Massachusetts, USA.
    Riley P; Predictive Science, Inc., San Diego, California, USA.
    Shaman J; Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA.
    Tibshirani R; Department of Statistics and Data Science, Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
    Vespignani A; Northeastern University, Boston, Massachusetts, USA.
    Zhang Q; Northeastern University, Boston, Massachusetts, USA.
    Reed C; Epidemiology and Prevention Branch, Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
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    Corporate Authors:
    Influenza Forecasting Working Group
    Źródło:
    Scientific reports [Sci Rep] 2019 Jan 24; Vol. 9 (1), pp. 683. Date of Electronic Publication: 2019 Jan 24.
    Typ publikacji:
    Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
    MeSH Terms:
    Models, Statistical*
    Influenza, Human/*epidemiology
    Centers for Disease Control and Prevention, U.S. ; Disease Outbreaks ; Humans ; Influenza, Human/mortality ; Morbidity ; Seasons ; United States/epidemiology
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
    Tytuł:
    Intra-Weekly Variations of Influenza-Like Illness in Military Populations.
    Autorzy:
    Riley P; Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121.
    Cost AA; Armed Forces Health Surveillance Center, 11800 Tech Road, Suite 220, Silver Spring, MD 20910.
    Riley S; Predictive Science Inc., 9990 Mesa Rim Road, Suite 170, San Diego, CA 92121.
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    Źródło:
    Military medicine [Mil Med] 2016 Apr; Vol. 181 (4), pp. 364-8.
    Typ publikacji:
    Journal Article
    MeSH Terms:
    Ambulatory Care Facilities/*statistics & numerical data
    Emergency Service, Hospital/*statistics & numerical data
    Influenza, Human/*epidemiology
    Military Personnel/*statistics & numerical data
    Population Surveillance/*methods
    Forecasting ; Humans ; Incidence ; Military Medicine ; Time Factors ; United States/epidemiology
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknieSzczegóły
    Tytuł:
    Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations.
    Autorzy:
    Riley P; Predictive Science Inc., San Diego, California, United States of America.
    Ben-Nun M; Predictive Science Inc., San Diego, California, United States of America.
    Linker JA; Predictive Science Inc., San Diego, California, United States of America.
    Cost AA; Armed Forces Health Surveillance Center, Silver Spring, Maryland, United States of America.
    Sanchez JL; Armed Forces Health Surveillance Center, Silver Spring, Maryland, United States of America.
    George D; Biomedical Advanced Research and Development Authority (BARDA), Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS), Washington, D.C., United States of America.
    Bacon DP; Leidos, McLean, Virginia, United States of America.
    Riley S; Predictive Science Inc., San Diego, California, United States of America; MRC Centre for Outbreak Analysis and Modelling, Imperial College London, United Kingdom.
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    Źródło:
    PLoS computational biology [PLoS Comput Biol] 2015 Sep 24; Vol. 11 (9), pp. e1004392. Date of Electronic Publication: 2015 Sep 24 (Print Publication: 2015).
    Typ publikacji:
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
    MeSH Terms:
    Databases, Factual*
    Influenza, Human*/epidemiology
    Influenza, Human*/transmission
    Models, Biological*
    Pandemics*/prevention & control
    Pandemics*/statistics & numerical data
    Computational Biology/*methods
    Humans
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknieSzczegóły
    Tytuł:
    Multiple estimates of transmissibility for the 2009 influenza pandemic based on influenza-like-illness data from small US military populations.
    Autorzy:
    Riley P; Predictive Science Inc., San Diego, California, USA. pete@predsci.com
    Ben-Nun M
    Armenta R
    Linker JA
    Eick AA
    Sanchez JL
    George D
    Bacon DP
    Riley S
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    Źródło:
    PLoS computational biology [PLoS Comput Biol] 2013; Vol. 9 (5), pp. e1003064. Date of Electronic Publication: 2013 May 16.
    Typ publikacji:
    Journal Article; Research Support, Non-U.S. Gov't
    MeSH Terms:
    Influenza, Human*/epidemiology
    Influenza, Human*/transmission
    Models, Biological*
    Models, Statistical*
    Pandemics*
    Military Personnel/*statistics & numerical data
    Computational Biology/methods ; Humans ; Incidence ; United States/epidemiology
    Czasopismo naukowe
    Pełny tekst  Link otwiera się w nowym oknieSzczegóły
      Wyświetlanie 1-10 z 10

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