As the COVID-19 pandemic continues to escalate in the United States and in many locations around the world, countless questions remain about next steps for mitigation and response. How will various mitigation methods affect the spread? How will those change as the pandemic progresses or regresses?
What can current “hot spots” learn from locations that have successfully managed the pandemic so far? Researchers from the University of Virginia’s Biocomplexity Institute are diligently working to answer these and numerous other questions related to COVID-19 thanks in part to new grant funding from the U.S. National Science Foundation (NSF).
Through its Rapid Response Research (RAPID) funding mechanism, the NSF recently awarded the Biocomplexity Institute four grants totaling more than $280,000 for ongoing work related to COVID-19. The NSF RAPID grants are designated for “non-medical, non-clinical-care research that can be used immediately to explore how to model and understand the spread of COVID-19, to inform and educate the public about the science of virus transmission and prevention, and to encourage the development of processes and actions to address this global challenge.”
The Biocomplexity Institute has been at the forefront of epidemiological modeling to track the COVID-19 pandemic since early 2020. Institute researchers have developed a suite of COVID-19 Epidemic Response Resources to support healthcare systems and policy makers in making informed decisions for effective interventions and resource allocation. They have partneredwith several U.S. and state government agencies to support informed decision-making including the Centers for Disease Control and Prevention (CDC), the U.S. Department of Defense (DOD), and the Virginia Department of Health, among many others.
The NSF RAPID grants will support the Institute’s ongoing research work related to COVID-19, specifically for the following four projects:
- COVID-19 Response Support: Building Synthetic Multi-Scale Networks – Led by Principal Investigator Madhav Marathe, director of the Biocomplexity Institute’s Network Systems Science and Advanced Computing (NSSAC) division,and Co-Principal Investigators Henning Mortveit and Srinivasan Venkatramanan, Institute researchers were awarded funding totaling more than $173,000 to build synthetic networks for developing accurate models of COVID-19 spread and intervention analysis. Using three different approaches, researchers will study spread and associated response at the community, subnational, national, and global levels. The data will be available to the global scientific community immediately through the NSF-funded CINES portal and other open repositories.
- Using Phylodynamics and Line Lists for Adaptive COVID-19 Monitoring – Led by Principal Investigator Anil Vullikanti, professor in the Institute’s NSSAC division and UVA’s School of Engineering and Applied Science, Institute researchers were awarded a $50,000 grant to study data-driven methods of improving COVID-19 surveillance with more targeted testing and intervention. The research team will develop processes, models, and actions to address the pandemic and understand its spread. “Efficient tracking of COVID-19 cases is crucial to controlling its spread, but is challenging due to the complexity of factors involved in transmission and the prevalence of missing data,” Vullikanti said. “This research project seeks to develop tools from data analytics to improve surveillance and make critical strides toward more successful tracking methodology.”
Aside from their application to the COVID-19 pandemic, Institute researchers believe the tools can be useful for other infectious disease and network settings, such as viral marketing and cyber security. The research team also includes Principal Investigator B. Aditya Prakash from Georgia Tech.
- Improving Computational Epidemiology with Higher Fidelity Models of Human Behavior – This project, led by Principal Investigator Mark Orr, research associate professor in the Institute’s NSSAC division, will research computational models of human response at the micro level (e.g. geographical regions, social groups, households, and individuals) to non-pharmaceutical epidemic interventions (NPIs), such as social distancing. The models will ultimately generate data that can be applied to a more broad-based macro level to guide health and government officials with decision-making about NPI response and interventions. “Human behavior is central to the dynamics of COVID-19,” Orr said. “We’re trying to understand how to leverage cognitive science, psychology, and artificial intelligence (AI) to build models of human behavior in the COVID-19 context.”
As part of a larger grant awarded to lead organization Institute for Human and Machine Cognition (IHMC), the NSF awarded the Biocomplexity Institute more than $32,000 in funding to provide statistical analysis support, natural language processing analytics, literature reviews, and manuscript development for the project.
- Transfer Learning Techniques for Better Response to COVID-19 in the United States – Led by Principal Investigator Madhav Marathe and Co-Principal Investigators Jiangzhuo Chen, Bryan Lewis, and Srinivasan Venkatramanan, Institute researchers received a $25,000 grant for research work focused on developing metapopulations and aggregate models for Wuhan, China, with newly available data. Using the concept of transfer learning in artificial intelligence (AI), the team is aiming to understand: how the lessons from Wuhan can be transferred to other regions; whether the Wuhan epidemic will resume once the restrictions are lifted; and whether COVID-19 will become an endemic disease due to the specific biological properties of the virus and the development of strong herd immunity and advanced therapeutics.
The project builds on the recently awarded $10 million NSF collaborative grant for “Expeditions in Computing: Global Pervasive Computational Epidemiology,” to revolutionize real-time epidemiology. The research team also includes Martin Blaser, Director of the Center for Advanced Biotechnology and Medicine at Rutgers University, and Simon Levin, Distinguished University Professor in Ecology and Evolutionary Biology at Princeton University.
“As the COVID-19 pandemic continues its escalation in the United States and elsewhere around the world, it is clear that there is much more work the scientific community can do to support healthcare systems and government agencies with mitigation and response,” Marathe said. “We are grateful to the NSF for the RAPID grant funding that enables the Biocomplexity Institute to continue our epidemiological modeling work related to COVID-19 and expand our research into new areas that we hope will lead to greater understanding and ultimately control of the spread.”
Marathe adds, “I am proud of the contributions our research team has made thus far in helping policy makers as well as the general public use science to make wise decisions, and through our ongoing commitment to research, I am hopeful we will continue to have a strong impact toward curtailing the spread of this disease.”
For more information about the Biocomplexity Institute’s work supporting the COVID-19 response effort as well as other major epidemics since 2005, visit https://biocomplexity.virginia.edu/covid19.