Infectious disease epidemiology is an important, complex, global societal problem. Currently, emerging challenges - climate change, political instability, urbanization, and others - threaten to slow recent progress in this area.
Epidemic science also motivates fundamental problems in computing, with broad impacts possible in social networks, cyber-security, web science, and public health policy.
We see a timely opportunity to simultaneously make fundamental advances in computing, data science, and artificial intelligence that will yield significant societal, health, and economic benefits.
Metrics of Success
- Develop new theoretical transdisciplinary frameworks (e.g. Socio-political epidemiology, ML-based exascale simulations, computational theory of spreading processes)
- Publish high-impact research articles
Impact Public Policy
- Develop and assess new, implementable strategies for controlling epidemic outbreaks
- Support real-time decisions and analysis during factual epidemics
- Develop and deploy Cyber-Environment for Real-Time Epidemic Science (CERTES) for epidemiological responders and policy makers
Inform Thought Leadership
- Organize annual meetings
- Organize DIMACS and SAMSI workshops
- Develop new education and training programs for next-generation epidemiologists