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Your search keyword '"Meyers, Lauren Ancel"' showing total 17 results
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17 results on '"Meyers, Lauren Ancel"'

1. Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures

Author

Yang, Haoxiang, primary, Sürer, Özge, additional, Duque, Daniel, additional, Morton, David P., additional, Singh, Bismark, additional, Fox, Spencer J., additional, Pasco, Remy, additional, Pierce, Kelly, additional, Rathouz, Paul, additional, Valencia, Victoria, additional, Du, Zhanwei, additional, Pignone, Michael, additional, Escott, Mark E., additional, Adler, Stephen I., additional, Johnston, S. Claiborne, additional, and Meyers, Lauren Ancel, additional

Published
2021
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7. Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge

Author

Biggerstaff, Matthew, Alper, David, Dredze, Mark, Fox, Spencer, Fung, Isaac Chun Hai, Hickmann, Kyle S., Lewis, Bryan, Rosenfeld, Roni, Shaman, Jeffrey, Tsou, Ming Hsiang, Velardi, Paola, Vespignani, Alessandro, Finelli, Lyn, Chandra, Priyadarshini, Kaup, Hemchandra, Krishnan, Ramesh, Madhavan, Satish, Markar, Ashirwad, Pashley, Bryanne, Paul, Michael, Meyers, Lauren Ancel, Eggo, Rosalind, Henderson, Jette, Ramakrishnan, Anurekha, Scott, James, Singh, Bismark, Srinivasan, Ravi, Bakach, Iurii, Hao, Yi, Schaible, Braydon J., Sexton, Jessica K., Del Valle, Sara Y., Deshpande, Alina, Fairchild, Geoffrey, Generous, Nicholas, Priedhorsky, Reid, Hickman, Kyle S., Hyman, James M., Brooks, Logan, Farrow, David, Hyun, Sangwon, Tibshirani, Ryan J., Yang, Wan, Allen, Christopher, Aslam, Anoshã, Nagel, Anna, Stilo, Giovanni, Basagni, Stefano, Zhang, Qian, Perra, Nicola, Chakraborty, Prithwish, Butler, Patrick, Khadivi, Pejman, Ramakrishnan, Naren, Chen, Jiangzhuo, Barrett, Chris, Bisset, Keith, Eubank, Stephen, Anil Kumar, V. S., Laskowski, Kathy, Lum, Kristian, Marathe, Madhav, Aman, Susan, Brownstein, John S., Goldstein, Ed, Lipsitch, Marc, Mekaru, Sumiko R., Nsoesie, Elaine O., Gesualdo, Francesco, Tozzi, Alberto E., Broniatowski, David, Karspeck, Alicia, Tse, Zion Tsz Ho, Ying, Yuchen, Gambhir, Manoj, and Scarpino, Sam

Subjects
0301 basic medicine, Veterinary medicine, Influenza season, Models, Biological, 03 medical and health sciences, 0302 clinical medicine, Public health surveillance, Models, Centers for Disease Control and Prevention (U.S.), Influenza, Human, Influenza prevention, Expert evaluation, Humans, Medicine, Public Health Surveillance, Research article, National level, 030212 general & internal medicine, Duration (project management), health care economics and organizations, Models, Statistical, business.industry, Modeling, social sciences, Statistical, Biological, Disease control, United States, Influenza, 3. Good health, 030104 developmental biology, Infectious Diseases, Forecasting, Prediction, Seasons, Human, Centers for Disease Control and Prevention, U.S, business, Research Article, Demography
Abstract

Background Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013–14 Unites States influenza season. Methods Challenge contestants were asked to forecast the start, peak, and intensity of the 2013–2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013–March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1669-x) contains supplementary material, which is available to authorized users.

Published
2016
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9. Assessing real-time Zika risk in the United States

Author

Castro, Lauren A., primary, Fox, Spencer J., additional, Chen, Xi, additional, Liu, Kai, additional, Bellan, Steven E., additional, Dimitrov, Nedialko B., additional, Galvani, Alison P., additional, and Meyers, Lauren Ancel, additional

Published
2017
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10. Enhancing disease surveillance with novel data streams: challenges and opportunities

Author

Althouse, Benjamin M, primary, Scarpino, Samuel V, additional, Meyers, Lauren Ancel, additional, Ayers, John W, additional, Bargsten, Marisa, additional, Baumbach, Joan, additional, Brownstein, John S, additional, Castro, Lauren, additional, Clapham, Hannah, additional, Cummings, Derek AT, additional, Del Valle, Sara, additional, Eubank, Stephen, additional, Fairchild, Geoffrey, additional, Finelli, Lyn, additional, Generous, Nicholas, additional, George, Dylan, additional, Harper, David R, additional, Hébert-Dufresne, Laurent, additional, Johansson, Michael A, additional, Konty, Kevin, additional, Lipsitch, Marc, additional, Milinovich, Gabriel, additional, Miller, Joseph D, additional, Nsoesie, Elaine O, additional, Olson, Donald R, additional, Paul, Michael, additional, Polgreen, Philip M, additional, Priedhorsky, Reid, additional, Read, Jonathan M, additional, Rodríguez-Barraquer, Isabel, additional, Smith, Derek J, additional, Stefansen, Christian, additional, Swerdlow, David L, additional, Thompson, Deborah, additional, Vespignani, Alessandro, additional, and Wesolowski, Amy, additional

Published
2015
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14. Vaccination against 2009 pandemic H1N1 in a population dynamical model of Vancouver, Canada: timing is everything

Author

Conway, Jessica M, primary, Tuite, Ashleigh R, additional, Fisman, David N, additional, Hupert, Nathaniel, additional, Meza, Rafael, additional, Davoudi, Bahman, additional, English, Krista, additional, van den Driessche, P, additional, Brauer, Fred, additional, Ma, Junling, additional, Meyers, Lauren Ancel, additional, Smieja, Marek, additional, Greer, Amy, additional, Skowronski, Danuta M, additional, Buckeridge, David L, additional, Kwong, Jeffrey C, additional, Wu, Jianhong, additional, Moghadas, Seyed M, additional, Coombs, Daniel, additional, Brunham, Robert C, additional, and Pourbohloul, Babak, additional

Published
2011
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