Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Evan L. Ray"'
Publikováno v:
Emerging Infectious Diseases, Vol 30, Iss 9, Pp 1967-1969 (2024)
On the basis of historical influenza and COVID-19 forecasts, we found that more than 3 forecast models are needed to ensure robust ensemble accuracy. Additional models can improve ensemble performance, but with diminishing accuracy returns. This unde
Externí odkaz:
https://doaj.org/article/7631b230d0f94d5fa073de0a73aa80b4
Autor:
Sarabeth M. Mathis, Alexander E. Webber, Tomás M. León, Erin L. Murray, Monica Sun, Lauren A. White, Logan C. Brooks, Alden Green, Addison J. Hu, Roni Rosenfeld, Dmitry Shemetov, Ryan J. Tibshirani, Daniel J. McDonald, Sasikiran Kandula, Sen Pei, Rami Yaari, Teresa K. Yamana, Jeffrey Shaman, Pulak Agarwal, Srikar Balusu, Gautham Gururajan, Harshavardhan Kamarthi, B. Aditya Prakash, Rishi Raman, Zhiyuan Zhao, Alexander Rodríguez, Akilan Meiyappan, Shalina Omar, Prasith Baccam, Heidi L. Gurung, Brad T. Suchoski, Steve A. Stage, Marco Ajelli, Allisandra G. Kummer, Maria Litvinova, Paulo C. Ventura, Spencer Wadsworth, Jarad Niemi, Erica Carcelen, Alison L. Hill, Sara L. Loo, Clifton D. McKee, Koji Sato, Claire Smith, Shaun Truelove, Sung-mok Jung, Joseph C. Lemaitre, Justin Lessler, Thomas McAndrew, Wenxuan Ye, Nikos Bosse, William S. Hlavacek, Yen Ting Lin, Abhishek Mallela, Graham C. Gibson, Ye Chen, Shelby M. Lamm, Jaechoul Lee, Richard G. Posner, Amanda C. Perofsky, Cécile Viboud, Leonardo Clemente, Fred Lu, Austin G. Meyer, Mauricio Santillana, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Michal Ben-Nun, Pete Riley, James Turtle, Chis Hulme-Lowe, Shakeel Jessa, V. P. Nagraj, Stephen D. Turner, Desiree Williams, Avranil Basu, John M. Drake, Spencer J. Fox, Ehsan Suez, Monica G. Cojocaru, Edward W. Thommes, Estee Y. Cramer, Aaron Gerding, Ariane Stark, Evan L. Ray, Nicholas G. Reich, Li Shandross, Nutcha Wattanachit, Yijin Wang, Martha W. Zorn, Majd Al Aawar, Ajitesh Srivastava, Lauren A. Meyers, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan L. Lewis, Madhav Marathe, Srinivasan Venkatramanan, Patrick Butler, Andrew Farabow, Naren Ramakrishnan, Nikhil Muralidhar, Carrie Reed, Matthew Biggerstaff, Rebecca K. Borchering
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predi
Externí odkaz:
https://doaj.org/article/b22341a399b644b886f816887477dc5b
Publikováno v:
Epidemics, Vol 45, Iss , Pp 100728- (2023)
Identifying data streams that can consistently improve the accuracy of epidemiological forecasting models is challenging. Using models designed to predict daily state-level hospital admissions due to COVID-19 in California and Massachusetts, we inves
Externí odkaz:
https://doaj.org/article/5d9022409f6a4684920dac4ada89ca9e
Autor:
Karen M. Holcomb, Sarabeth Mathis, J. Erin Staples, Marc Fischer, Christopher M. Barker, Charles B. Beard, Randall J. Nett, Alexander C. Keyel, Matteo Marcantonio, Marissa L. Childs, Morgan E. Gorris, Ilia Rochlin, Marco Hamins-Puértolas, Evan L. Ray, Johnny A. Uelmen, Nicholas DeFelice, Andrew S. Freedman, Brandon D. Hollingsworth, Praachi Das, Dave Osthus, John M. Humphreys, Nicole Nova, Erin A. Mordecai, Lee W. Cohnstaedt, Devin Kirk, Laura D. Kramer, Mallory J. Harris, Morgan P. Kain, Emily M. X. Reed, Michael A. Johansson
Publikováno v:
Parasites & Vectors, Vol 16, Iss 1, Pp 1-13 (2023)
Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting
Externí odkaz:
https://doaj.org/article/2ee21ea30b4a49b5a774c7a9b548f0c6
Autor:
Estee Y. Cramer, Yuxin Huang, Yijin Wang, Evan L. Ray, Matthew Cornell, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Aaron Gerding, Katie House, Dasuni Jayawardena, Abdul Hannan Kanji, Ayush Khandelwal, Khoa Le, Vidhi Mody, Vrushti Mody, Jarad Niemi, Ariane Stark, Apurv Shah, Nutcha Wattanchit, Martha W. Zorn, Nicholas G. Reich, US COVID-19 Forecast Hub Consortium
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-15 (2022)
Abstract Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Preven
Externí odkaz:
https://doaj.org/article/300e02be0bde4c32adf9ae19db234dca
Publikováno v:
Scientific Data, Vol 8, Iss 1, Pp 1-11 (2021)
Abstract Forecasting has emerged as an important component of informed, data-driven decision-making in a wide array of fields. We introduce a new data model for probabilistic predictions that encompasses a wide range of forecasting settings. This fra
Externí odkaz:
https://doaj.org/article/be7aeb3e86c243b7b92bcddfd06f1baa
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 2, p e1008618 (2021)
For practical reasons, many forecasts of case, hospitalization, and death counts in the context of the current Coronavirus Disease 2019 (COVID-19) pandemic are issued in the form of central predictive intervals at various levels. This is also the cas
Externí odkaz:
https://doaj.org/article/ca7ae5c7d221495d83bd6ed87855f369
Autor:
Nicholas G, Reich, Justin, Lessler, Sebastian, Funk, Cecile, Viboud, Alessandro, Vespignani, Ryan J, Tibshirani, Katriona, Shea, Melanie, Schienle, Michael C, Runge, Roni, Rosenfeld, Evan L, Ray, Rene, Niehus, Helen C, Johnson, Michael A, Johansson, Harry, Hochheiser, Lauren, Gardner, Johannes, Bracher, Rebecca K, Borchering, Matthew, Biggerstaff
Publikováno v:
Am J Public Health
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bea4ad8b68697e80ad52dce6b42ccf8b
https://doi.org/10.2105/ajph.2022.306831
https://doi.org/10.2105/ajph.2022.306831
Publikováno v:
medRxiv
Identifying data streams that can consistently improve the accuracy of epidemiological forecasting models is challenging. Using models designed to predict daily state-level hospital admissions due to COVID-19 in California and Massachusetts, we inves
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d12e4f808af55f8afe4f7b5e410731c
https://europepmc.org/articles/PMC10029058/
https://europepmc.org/articles/PMC10029058/
Autor:
Karen M. Holcomb, Sarabeth Mathis, J. Erin Staples, Marc Fischer, Christopher M. Barker, Charles B. Beard, Randall J. Nett, Alexander C. Keyel, Matteo Marcantonio, Marissa L. Childs, Morgan E. Gorris, Ilia Rochlin, Marco Hamins-Puértolas, Evan L. Ray, Johnny A. Uelmen, Nicholas DeFelice, Andrew S. Freedman, Brandon D. Hollingsworth, Praachi Das, Dave Osthus, John M. Humphreys, Nicole Nova, Erin A. Mordecai, Lee W. Cohnstaedt, Devin Kirk, Laura D. Kramer, Mallory J. Harris, Morgan P. Kain, Emily M. X. Reed, Michael A. Johansson
Publikováno v:
Parasites & Vectors. 16
Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74e196995e0a679ed533a52e143733a2
https://doi.org/10.1186/s13071-022-05630-y
https://doi.org/10.1186/s13071-022-05630-y