January 2023 CIC Webinar Recap

Editor's note:

The twenty-fourth in the series of COVID Information Commons (CIC) webinars which began in 2020 took place on January 31st, 2023. In this forum, leading COVID-19 scientists presented their current research on the global pandemic. 

Event moderators included Florence Hudson, Executive Director of the Northeast Big Data Innovation Hub at Columbia University and COVID Information Commons Principal Investigator (PI), Lauren Close, Operations & Communications Manager, and Emily Rothenberg, National Student Data Corps (NSDC) Program Coordinator. 

The researchers presented a range of topics, each touching on broader themes related to the COVID-19 pandemic. Three presentations spoke about the future of pandemic prevention efforts being spearheaded by the NSF Predictive Intelligence for Pandemic Prevention (PIPP)  initiative. Another presentation discussed the research being done on antibodies in human breast milk after COVID-19 infection. These research projects are funded by the National Science Foundation (NSF) and National Institutes of Health (NIH). 


The session started with a presentation from Mark Lurie from Brown University. Dr. Lurie discussed his research project, Mobility Analysis for Pandemic Prevention Strategies (MAPPS).This grant is funded by NSF Predictive Intelligence for Pandemic Prevention Phase 1. 

Lurie’s team, in concert with the Center for Mobility Analysis for Pandemic Prevention Strategies (MAPPS) at Brown University, has categorized, organized, and synthesized data on individual mobility and social mixing. The project will develop new tools for measuring social mobility and predicting future pandemics. All data will be organized and available for public use in an open database. 

A video of Mark’s presentation can be found on the CIC website.


Next, Peter Pirolli from the Florida Institute for Human & Machine Cognition, Inc. presented his research on Computational Theory of the Co-evolution of Pandemics, (Mis)information, and Human Mindsets and Behavior. This project was funded by NSF Behavioral and Cognitive Sciences (BCS). 

Pirolli’s presentation illustrated the importance of scientific research into human behavior to predict people’s responses to information about pandemics and infectious disease. Individual mindsets can vary across subgroups, meaning that responses to policy and public messaging vary widely. Pirolli’s work uses computational theories and models to assess the interdependent evolution of infection, behavior, and information. Resulting research will support improved pandemic intelligence, prediction, explanation, and countermeasures.

A video of Peter’s video presentation can be found on the CIC website.


Next, Rebecca Powell from the Icahn School of Medicine at Mount Sinai presented their research on Comprehensive assessment of SARS-CoV-2-reactive antibodies in human milk to determine their potential as a COVID-19 therapeutic and as a means to prevent infection of breastfed babies. This project was funded by the NIH, National Institute of Allergy and Infectious Diseases. 

Powell’s research considered the therapeutic value of breastfeeding to prevent infant infection. Although COVID-19 pathology in children is believed to be relatively mild compared to adults, infection can lead to serious health outcomes for babies. One potential mechanism for protection of infants against COVID-19 is passive immunity provided through breastfeeding by a previously-infected mother. Potent SARS-CoV-2 antibody (Ab) responses may be effective in treating COVID-19 by providing secretory (s) IgA and sIgM Abs. Pilot data found 93% of breast milk samples obtained post-COVID-19 contain SARS-CoV-2-reactive sIgA Abs, indicating that human milk immunology may have important protective biological functions. 

A video of Rebecca’s video presentation can be found on the CIC website.


The webinar ended with a presentation from Jennifer Surtees from the University at Buffalo on her research: Center for Ecosystems Data Integration and Pandemic Early Warning Systems. This project was funded by the NSF Predictive Intelligence for Pandemic Prevention Phase 1 initiative.

Surtees’ NSF grant supports the design and implementation of next-generation environmental and clinical surveillance systems. These programs will monitor and track the emergence and transmission of new pathogens with pandemic potential, triggering early warning systems for health system leaders and stakeholders in New York state. The project team has established a center that reviews wastewater data to develop a baseline of pathogens in local communities in collaboration with the Erie County Department of Health. 

A video of Jennifer’s session can be found on the CIC website.



Following the presentations, Florence Hudson, Lauren Close, and Emily Rothenberg hosted a Q&A session where the audience engaged in a rich discussion with the researchers. These talks offered great insights into the impact of COVID-19 on health, education, and communities.

A recording of this event is available on the Northeast Big Data Innovation Hub’s YouTube Channel and the COVID Information Commons website. The COVID Information Commons is an NSF-funded project brought to you by the Big Data Innovation Hubs, led by the Northeast Big Data Innovation Hub at Columbia University. 

We look forward to welcoming you to the next CIC Lightning Talks webinar on April 24th, 2023!



January 31, 2023