Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches

por Fred S. Lu, Mohammad W. Hattab, Cesar Leonardo Clemente, Matthew Biggerstaff, Mauricio Santillana
Publicado 2019

Technology to advance infectious disease forecasting for outbreak management

por Dylan B. George, Wendy Taylor, Jeffrey Shaman, Caitlin Rivers, Brooke Paul, Tara O’Toole, Michael A. Johansson, Lynette Hirschman, Matthew Biggerstaff, Jason Asher, Nicholas G. Reich
Publicado 2019

Forecasting influenza activity using machine-learned mobility map

por Srinivasan Venkatramanan, Adam Sadilek, Arindam Fadikar, Christopher L. Barrett, Matthew Biggerstaff, Jiangzhuo Chen, Xerxes Dotiwalla, Paul Eastham, Bryant Gipson, Dave Higdon, Onur Kucuktunc, Allison Lieber, Bryan L. Lewis, Zane Reynolds, Anil K. Vullikanti, Lijing Wang, Madhav Marathe
Publicado 2021

Using “outbreak science” to strengthen the use of models during epidemics

por Caitlin Rivers, Jean-Paul Chretien, Steven Riley, Julie A. Pavlin, Alexandra Woodward, David Brett-Major, Irina Maljkovic Berry, Lindsay Morton, Richard G. Jarman, Matthew Biggerstaff, Michael A. Johansson, Nicholas G. Reich, Diane Meyer, Michael R. Snyder, Simon Pollett
Publicado 2019

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.

por Simon Pollett, Michael A Johansson, Nicholas G Reich, David Brett-Major, Sara Y Del Valle, Srinivasan Venkatramanan, Rachel Lowe, Travis Porco, Irina Maljkovic Berry, Alina Deshpande, Moritz U G Kraemer, David L Blazes, Wirichada Pan-Ngum, Alessandro Vespigiani, Suzanne E Mate, Sheetal P Silal, Sasikiran Kandula, Rachel Sippy, Talia M Quandelacy, Jeffrey J Morgan, Jacob Ball, Lindsay C Morton, Benjamin M Althouse, Julie Pavlin, Wilbert van Panhuis, Steven Riley, Matthew Biggerstaff, Cecile Viboud, Oliver Brady, Caitlin Rivers
Publicado 2021