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PIPP Phase I: Predicting Emergence in Multidisciplinary Pandemic Tipping-points (PREEMPT)

PIPP Phase I: Computational Foundations for Bio-social Modeling of Unseen Pandemics

EVO Games Plus International Training Network

PIPP Phase I: Predicting Emergence in Multidisciplinary Pandemic Tipping-points (PREEMPT)

PIPP Phase I: Computational Foundations for Bio-social Modeling of Unseen Pandemics

EVO Games Plus International Training Network

Folder: Partner Networks

PIPP Phase I: Predicting Emergence in Multidisciplinary Pandemic Tipping-points (PREEMPT)

PIPP Phase I: Computational Foundations for Bio-social Modeling of Unseen Pandemics

EVO Games Plus International Training Network

Folder: Publications

Fahim Tasneema Azad

Oct 23

Written By K. Selcuk Candan

Computer Science, Ph.D. Student at Arizona State University

K. Selcuk Candan

Javier Anton Redondo

Center for Assured and Scalable Data Engineering (CASCADE) @ Arizona State University, USA

School of Public Health @ Georgia State University, USA

Kyoto University, Japan

University of Nagasaki, Japan

The PanCommunity project is funded by

NSF CNS#2125246SCC-IRG JST: PanCommunity: Leveraging Data and Models for Understanding and Improving Community Response in Pandemics
NSF DEB#2026797
RAPID: RTEM: Rapid Testing as Multi-fidelity Data Collection for Epidemic Modeling
NSF CMMI/CDSE#1610282 DataStorm: A Data Enabled System for End-to-End Disaster Planning and Response