OVERVIEW

This meeting is the culmination of 3 years of workshops, panel discussions, podcast interviews, and research presentations. The Research Roadmap shared is the distillation of the experiences and suggestions of over 1300 people and consists of ten recommendations split into 5 areas:

• Importance of Corporate-Government-Academic Partnerships and Multidisciplinary Collaboration
• Advanced Computing and AI
• Data and Computing Infrastructure
• Tools and Methods
• Societal Impacts

AGENDA

Each session (outside of the keynote) covers one of the above areas and involves a moderator guiding discussion on each of the recommendations in these areas.

10:00-11:00am ET: [Keynote] Developing Routines for Uncertainty: Preparing for the Next Pandemic

Moderators: Simon Levin, Princeton
Jessica Metcalf, Princeton

11:15-12:00pm ET: Importance of Corporate-Government-Academic Partnerships and Multidisciplinary Collaboration (3 recommendations)

Moderators: Madhav Marathe, UVA

12:15-1:00pm ET: Advanced Computing and AI (1 recommendation)

Moderator: Anil Vullikanti, UVA

1:00-1:45pm ET: Data and Computing Infrastructure (3 recommendations)

Moderators: Li Xiong, Emory

2:00-2:45pm ET: Tools and Methods (2 recommendations)

Moderators: Anil Vullikanti, UVA

2:45-3:30pm ET: Societal Impacts (1 recommendation)

Moderators: Madhav Marathe, UVA

10am ET: Developing Routines for Uncertainty: Preparing for the Next Pandemic

Moderator: Simon Levin, Princeton

C. Jessica Metcalf, Princeton

Jessica Metcalf is an Associate Professor of Ecology, Evolutionary Biology & Public Affairs, and is a demographer with broad interests in evolutionary ecology, infectious disease dynamics and public policy. She completed her PhD at Imperial College on the evolutionary demography of monocarpic perennials. Her post-doctoral research was conducted at various institutions. She studied the evolution of senescence at the Max Planck Institute of Demographic Research, the inference of tree demographic parameters at Duke University, and infectious disease dynamics at Pennsylvania State University and Princeton University.

Metcalf’s teaching focuses on a course titled Epidemiology: An Ecological and Evolutionary Perspective. Her course aims to communicate both an understanding of the core principles of epidemiology (ranging from classical study designs to core analytical techniques) and a broader perspective into the fundamental drivers of health outcomes (ranging from ecological drivers of the spread of infectious disease to the evolutionary determinants of profiles of late age mortality).

Program Committee

OVERVIEW

There will be four focus areas:

• Modeling Behavioral Components of Epidemic Dynamics for Public Health Policy
• Scenario Modeling: What worked and what didn't? 
• Global Perspectives on Modeling to Support Pandemic Decision Making
• Supporting Public Health Decision Makers at Various Levels in the United States

AGENDA

Each session will feature keynote talks followed by a panel discussion.

January 25 // 10:00-11:45am ET: Modeling Behavioral Components of Epidemic Dynamics for Public Health Policy

Moderators: Don Burke, UPitt & Juliet Pulliam, SACEMA
Sebastian Funk, LSHTM
Joshua Epstein, NYU
Paul Slovic, U Oregon

January 25 // 2-3:45pm ET: Scenario Modeling: What worked and what didn't?

Moderator: Jeff Shaman, Columbia U
Celia Quinn, NYC DoHMH
Jason Asher, CDC CFA
Sarah Cobey, U Chicago
Amit Huppert, Tel Aviv U

January 26 // 10:00-11:45am ET: Global Perspectives on Modeling to Support Pandemic Decision Making 

Moderators: Juliet Pulliam, SACEMA & Lone Simonsen, Roskilde U
Julia Gog, Cambridge U
Viggo Andreasen, Roskilde U
Thumbi Mwangi, U Nairobi
Joseph Wu, Hong Kong U

January 26 // 2-3:45pm ET: Data modeling challenges & opportunities

Moderators: Simon Levin, Princeton U & Madhav Marathe, UVA
Eili Klein, JHU & Kenneth Bellian, Jensen Partners
Lauren Meyers, UTA & Mark Escott, Austin EMS
Bryan Lewis, UVA & Justin Crow, VDH

Day 1, January 25th, 10am ET: Modeling Behavioral Components of Epidemic Dynamics for Public Health Policy

Moderator: Don Burke, UPitt & Juliet Pulliam, SACEMA

Sebastian Funk, LSHTM

Challenges in Modeling Behavior (slides found here)

Sebastian Funk from the London School of Hygiene & Tropical Medicine. His main interest is in using computational models in combination with infectious disease data in order to better understand and predict infectious disease dynamics. This includes developing and evaluating methods for short-term forecasting, testing the predictive value of additional data sources on pathogen biology and human behaviour, and doing all of this in order to inform public health decision-making. He strongly believes that science should be done openly and that there is great value in developing methods as tools that can be used by others.

Joshua Epstein & Jeewoen Shin, NYU

Joshua Epstein is a Professor of Epidemiology at the NYU School of Global Public Health, and founding Director of the NYU Agent-Based Modeling Laboratory. His research interest has been modeling complex social dynamics using mathematical and computational methods, notably the method of Agent-Based Modeling in which he is a recognized pioneer. He has applied this method to the study of infectious diseases like Ebola, pandemic influenza, and smallpox, vector-borne diseases like zika, urban disaster preparedness, contagious violence, the evolution of norms, economic dynamics, computational archaeology, and the emergence of social classes, among many other topics.

Paul Slovic, U Oregon

The Psychology of Risk & Decision-Making: Some Implications for Modeling

As one of the world's leading researchers on risk and decision-making, Paul Slovic from the University of Oregon has provided invaluable insights into some of the most important parts of being human—how humans evaluate risk and make decisions when it counts. Paul studies judgment and decision processes with an emphasis on decision-making under conditions of risk. His work examines fundamental issues such as the influence of affect on judgments and decisions. He also studies the factors that underlie perceptions of risk and attempts to assess the importance of these perceptions for the management of risk in society. His most recent research examines psychological factors contributing to apathy toward genocide, politicized violence, and decision-making pertaining to nuclear war. His work on the phenomenon of "psychic numbing" also shows the way to better comprehend the costs of human tragedy and become more compassionate ourselves. 

Day 1, January 25th, 2pm ET: Scenario Modeling: What worked and what didn't?

Moderators: Jeff Shaman, Columbia U

Celia Quinn, NYC DoHMH

Celia Quinn is the Deputy Commissioner for Disease Control, New York City Dept. of Health. She is a Commander in the US Public Health Service and completed her medical degree and Master of Public Health at the Mount Sinai School of Medicine. Since 2014 she has served as a Career Epidemiology Field Officer assigned to the NYC Health Department. Celia has served in vital leadership roles in recent emergencies that the Department has responded to, including Ebola and Zika. During the Department’s COVID-19 response, she has served in multiple roles, and is currently the Deputy Incident Commander, overseeing clinical, epidemiological, and laboratory science elements of the response.

Jason Asher, CDC CFA

Jason Asher is the director of the Predict Division in the Center for Forecasting and Outbreak Analytics (CFA) of the CDC. He has a distinguished career in mathematical modeling, conceptualizing, and constructing novel methods for forecasting and evaluating mitigations during federal emergency responses to a variety of disease outbreaks. There are multiple modeling tools in use today at CDC and the Administration for Strategic Preparedness and Response (ASPR) that are based on initial prototypes he developed. Since January 2020, Dr. Asher’s team has been devoted nearly full-time to the COVID-19 pandemic response. He collaborated with CDC to define standard modeling parameters and assumptions that were used early in the pandemic to scope the potential scale of impact in the United States.

Sarah Cobey, U Chicago

Sarah Cobey is a Professor in the Dept. of Ecology and Evolution at the University of Chicago. She studies the ecology and evolution of pathogens, including how ecological and evolutionary processes can influence each other, and how pathogens compete in the complex environment of the host immune system. More recently, Sarah's focus has expanded to include the related dynamics of the host immune response. She is the principal investigator at Cobey Lab, where research is tailored to study how the host adaptive immune response coevolves with pathogens, especially in ways relevant to vaccine design and pathogen diversity. The work is computational and done in close collaboration with immunologists and epidemiologists. 

Amit Huppert, Tel Aviv U

Amit Huppert is a Senior Lecturer at the School of Public Health, Tel Aviv University. He is interested in the interactions between environmental factors and the spread of infectious diseases. He uses a combination of mathematical modeling and data analysis to understand how different environmental factors - such as climate, demography, and habitat - affect the spatiotemporal spread of infectious diseases. He has been studying diseases that are directly transmitted (influenza, pneumonia), childhood infections (measles, mumps), vector-borne (leishmaniasis, malaria), sexual transmission (HPV), and enteric diseases (polio, shigella). He also combines laboratory experiments and statistical models to better estimate parameters for the use of mathematical models. An important goal of his research is to translate the academic findings and knowledge into policy setting and improve decision-making processes.

Day 2, January 26th, 10am ET: Global Perspectives on Modeling to Support Pandemic Decision Making

Moderators: Juliet Pulliam, SACEMA & Lone Simonsen, Roskilde U

Julia Gog, Cambridge U

Julia Gog is the Professor of Mathematical Biology, at DAMTP, Faculty of Mathematics at the University of Cambridge, and the David N. Moore Fellow in mathematics at Queens’ College Cambridge. Julia’s research is on the spread and evolution of infectious diseases, particularly influenza. Julia contributed to the scientific advice to the UK government during the COVID-19 emergency, as a member of the modelling group SPI-M, and as a participant of SAGE. Julia is co-lead of the JUNIPER consortium which brings together epidemiological research across several UK universities.

Viggo Andreasen, Roskilde U

Viggo Andreasen is an associate professor of mathematical epidemiology at Roskilde University and a founding member of the Pandemix group. For 30 years in the pre-COVID era, he studied the evolution of viral diseases and in particular influenza drift and pandemics. During the COVID pandemic, he served on the Danish covid-advisory board (referencegruppen) and advised the National Health Board on testing strategies and other aspects of pandemic control. In addition, he has been active in the Danish COVID debate. He has published 15+ essays on the Danish COVID situation and strategy, has given 300+ interviews on national TV and radio plus a similar number of interviews in newspapers.

Thumbi Mwangi, U Nairobi

Thumbi Mwangi is a veterinarian and infectious disease epidemiologist from Kenya. He co-directs the Center for Epidemiological Modelling and Analysis at the University of Nairobi and holds the positions of Associate Professor at the Washington State University Paul G Allen School for Global Health and Chancellors fellow at the University of Edinburgh. His research is focused on the prevention and control of infectious diseases with specific programs on neglected tropical diseases including rabies elimination, brucellosis, Rift Valley fever, and MERS-CoV among other zoonoses. He serves as a co-chair of the United Against Rabies Forum working group on the effective use of vaccines, medicines, tools, and technologies for rabies elimination, and the chair of the technical committee on COVID-19 modelling that guides the Kenyan government on responses to the COVID-19 pandemic.

Joseph Wu, Hong Kong U

Joseph Wu specializes in mathematical and statistical modelling of diseases. His research aims are: (i) to develop practical analytics and strategies for disease control and prevention; and (ii) to translate his research into policies and practice. He has worked on COVID-19, seasonal and pandemic influenza, hand-foot-and-mouth diseases, HPV, MERS, yellow fever, cervical cancer, colorectal cancer, and breast cancer. He earned his PhD (Operations Research) and BS (Chemical Engineering) from MIT. Joe is the managing director of the Laboratory of Data Discovery for Health (D24H). His research program in D24H aims to develop AI technology and tools for global and personal health protection, with a particular focus on vaccine hesitancy and epidemic nowcasting/forecasting. He is the director of (i) HKU's first Massive Open Online Courseware (MOOC) Epidemics which has had more than 50,000 people enrolled since its first launch in 2014; and (ii) the Croucher Summer Course Vaccinology for Public Health and Clinical Practice in the 21st Century. He is co-editor-in-chief of Epidemics and an associate editor of PLOS Computational Biology and PLOS Neglected Tropical Diseases. He is a member of the WHO Advisory Committee on Immunization and Vaccines-related Implementation Research (IVIR-AC). He is a member of the MIT SOLVE Challenge Leadership Group and an SME advisor of MIT HK Innovation Node. He is a Fellow of the UK Faculty of Public Health.

Day 2, January 26th, 2pm ET: Data modeling challenges & opportunities

Eili Klein, JHU & Kenneth Bellian, Jensen Partners

Eili Klein is an Associate Professor of Emergency Medicine at Johns Hopkins University and a senior fellow at the One Health Trust.  His research focuses on the role of individuals in the spread of infectious diseases. This area of research sits at the nexus of economics and epidemiology and is premised on the idea of incorporating incentives for healthy behavior and attendant behavioral responses into an epidemiological context to better understand how diseases are transmitted. 

Kenneth Bellian is the Principal and Chief of Clinical Strategy at Jensen Partners. He provides clients with a physician-executive perspective and a deep understanding of the complex challenges that exist in healthcare, as well as the opportunities which avail themselves to deliver disruptive solutions. Alongside many impactful projects, he was embedded with MPH on their pandemic response strategy.

Lauren Meyers, UTA & Mark Escott, Austin EMS

Lauren Meyers is a Professor in the Departments of Integrative Biology and Statistics & Data Sciences, and Director of the University of Texas COVID-19 Modeling Consortium. She has been a pioneer in the field of network epidemiology and the application of machine learning to improve outbreak detection, forecasting, and control. Professor Meyers leads an interdisciplinary team of scientists, engineers, and public health experts in uncovering the social and biological drivers of epidemics and building practical tools for the CDC and other global health agencies to track and mitigate emerging viral threats. 

During the height of the pandemic, she worked closely with Mark Escott, the Chief Medical Officer and EMS System Medical Director for the City of Austin and Travis County, the Texas Department of Public Safety, and the Texas Division of Emergency Management. He also served as Interim Medical Director and Health Authority for Austin Public Health. He has academic appointments as a Clinical Assistant Professor in the Division of Emergency Medicine at the University of Texas at Austin Dell Medical School and as a Senior Lecturer in Medicine and Public Health at Flinders University in Adelaide, Australia. Dr. Escott currently serves as the Immediate Past Chair of the Section of EMS and Prehospital Medicine of the American College of Emergency Physicians. 

Bryan Lewis, UVA & Justin Crow, VDH

Bryan Lewis is a Research Associate Professor at the Biocomplexity Institute, UVA. Dr. Bryan Lewis has spent the past two decades crafting, analyzing, and communicating the results of computational epidemiological models to policymakers and the scientific community.  He was lucky to cut his teeth as a PhD student at Virginia Tech in the MIDAS project and was involved in planning for a hypothetical influenza pandemic and then the very real response to the actual 2009 pandemic. In the years that followed he worked to develop new modeling techniques and supported federal responses to the Ebola outbreak in West Africa as well as myriad other pandemic threats and emerging diseases around the world (MERS, Cholera, Zika, etc.).  During the COVID-19 pandemic, he helped lead a team to support the Commonwealth of Virginia and the federal response through a variety of modeling and forecasting efforts as well as many many ad-hoc analyses.

After leading Virginia's forecasting and modeling work during the COVID-19 response, Justin Crow launched the Foresight and Analytics unit in the Virginia Department of Health, Office of Emergency Preparedness in April and now leads the unit full-time. He has performed public health research and analysis for the Commonwealth for over 12 years, including as Deputy Director of the Virginia Healthcare Workforce Data Center and Director of VDH’s Division of Social Epidemiology. He has worked in forecasting for over eight years, beginning as a volunteer "Superforecaster" with the Good Judgment Project in 2014.

Program Committee

OVERVIEW

There will be four focus areas:

• Vaccine acceptance and opportunity: the roles of hesitancy, global sharing, and behavioral response in VPD immunization coverage
• Destabilization and VPDs: operational disruption, health system resilience, and the impact of COVID-19 
• Epidemiological and immunological factors in VPDs
• Data and modeling challenges and opportunities in the pandemic and post-pandemic era

AGENDA

Each session will feature keynote talks followed by a panel discussion.

June 7 // 10:00-11:40am ET: Vaccine acceptance & opportunity

Moderator: Rosalind Eggo, LSHTM
Neil Johnson, GWU
Kerrigan McCarthy, NICD
Daniel Salmon, JHU

June 7 // 11:50-12:50pm ET: Keynote

Moderators: Rosalind Eggo, LSHTM and Anil Vullikanti, BI/UVA
Heidi Larson, LSHTM

June 7 // 1:30-3:10pm ET: Destabilization & VPDs

Moderator: Anil Vullikanti, BI/UVA
Carolina Danovaro, WHO
Bhargavi Rao, LSHTM/MSF
Anton Camacho, MSF

June 8 // 10:00-11:40am ET: Epidemiological & immunological factors

Moderators: Yang Liu, LSHTM and Anil Vullikanti, BI/UVA
Jessica Metcalf, Princeton
Deirdre Hollingsworth, Oxford
Ben Lopman, Emory

June 8 // 11:50-12:50pm ET: Keynote

Moderator: Stephen Eubank, BI/UVA
Raji Tajudeen, Africa CDC

June 8 // 1:30-3:10pm ET: Data modeling challenges & opportunities

Moderators: Jonathan Mosser, IHME/UW and Stephen Eubank, BI/UVA
Danil Mikhailov, data.org
Matt Ferrari, PSU
Michael Johansson, CDC

Day 1, June 7th, 10am ET: Vaccine Acceptance & Opportunity

Moderator: Rosalind Eggo, LSHTM

Neil Johnson, GWU

How extremes meet the mainstream - and a solution at scale

Neil Johnson is a professor of physics at GW and heads up a new initiative in Complexity and Data Science which combines cross-disciplinary fundamental research with data science to attack complex real-world problems. His research interests lie in the broad area of Complex Systems and ‘many-body’ out-of-equilibrium systems of collections of objects, ranging from crowds of particles to crowds of people and from environments as distinct as quantum information processing in nanostructures through to the online world of collective behavior on social media.

He is a Fellow of the American Physical Society (APS) and is the recipient of the 2018 Burton Award from the APS. He received his BA/MA from St. John's College, Cambridge, University of Cambridge and his PhD as a Kennedy Scholar from Harvard University. He was a Research Fellow at the University of Cambridge, and later a Professor of Physics at the University of Oxford until 2007, having joined the faculty in 1992. Following a period as Professor of Physics at the University of Miami, he was appointed Professor of Physics at George Washington University in 2018. He presented the Royal Institution Christmas Lectures "Arrows of Time" on BBC TV in 1999. He has more than 300 published research papers across a variety of research topics and has supervised the doctoral theses of more than 25 students. His published books include Financial Market Complexity published by Oxford University Press and Simply Complexity: A Clear Guide to Complexity Theory published by Oneworld Publications. He co-founded and co-directed CABDyN (Complex Agent-Based Dynamical Systems) which is Oxford University's interdisciplinary research center in Complexity Science, and an Oxford University interdisciplinary research center in financial complexity (OCCF).

Kerrigan McCarthy, NICD

Kerrigan McCarthy is a medical doctor who specialised in the laboratory diagnosis of infectious disease. She has spent her professional life supporting public health responses and health system strengthening for communicable diseases.

Her experience includes providing clinical care for persons living with HIV (Nazareth House, Johannesburg), implementation and support for TB/HIV integration and infection prevention and control (Wits HIV Research Institute), and evaluation of new TB diagnostic tests (Aurum Institute). Since 2015 she has worked at the NICD supporting national government responses to communicable disease outbreaks including the listeriosis outbreak in 2017-2018.

Most recently, she has provided technical support for COVID-related public health responses at national and provincial level. Kerrigan has been actively involved in the Anglican Church for a number of years. She serves as a lay minister at St Thomas in Linden and obtained a MPhil (Theology) from St Augustine’s college, Linden in 2012. Kerrigan serves the needs of inner city migrants and refugees living with HIV through supporting the work of the Sr Mura Foundation. Most importantly, she is a mother of two vibrant young adults who are pursuing their own careers to make the world a better place!

Daniel Salmon, JHU

Vaccine Hesitancy Beyond COVID-19

Dr. Salmon’s primary research and practice interest is optimizing the prevention of childhood infectious diseases through the use of vaccines. He is broadly trained in vaccinology, with an emphasis in epidemiology, behavioral epidemiology, and health policy. Dr. Salmon’s focus has been on post-licensure vaccine safety, determining the individual and community risks of vaccine refusal, understanding factors that impact vaccine acceptance, evaluating and improving state laws providing exemptions to school immunization requirements, developing systems and science in vaccine safety, and effective vaccine risk communication. Dr. Salmon has considerable experience developing surveillance systems, using surveillance data for epidemiological studies, and measuring immunization coverage through a variety of approaches. Dr. Salmon has worked with state and federal and global public health authorities to strengthen immunization programs and pandemic planning.

Day 1, June 7th, 11:50am ET: Keynote

Moderators: Rosalind Eggo, LSHTM and Anil Vullikanti, BI/UVA

Heidi Larson, LSHTM

Heidi J. Larson, PhD, is Professor of Anthropology, Risk and Decision Science and is the Founding Director of the Vaccine Confidence Project at the London School of Hygiene & Tropical Medicine. She is also Clinical Professor of Health Metrics Sciences, University of Washington, Seattle, USA, and Guest Professor at the University of Antwerp, Belgium.

Dr. Larson previously headed Global Immunisation Communication at UNICEF, chaired GAVI’s Advocacy Task Force, and served on the WHO SAGE Working Group on vaccine hesitancy. The VCP is a WHO Centre of Excellence on addressing Vaccine Hesitancy.

Professor Larson’s research focuses on the analysis of social and political factors that can affect uptake of health interventions and influence policies. Her particular interest is on risk and rumour management from clinical trials to delivery – and building public trust.  She served on the FDA Medical Countermeasure (MCM) Emergency Communication Expert Working Group, and is currently Principal Investigator for a global study on acceptance of vaccination during pregnancy; an EU-funded (EBODAC) project on the deployment, acceptance and compliance of an Ebola vaccine trial in Sierra Leone; and a global study on Public Sentiments and Emotions Around Current and Potential Measures to Contain and Treat COVID-19.

Day 1, June 7th, 1:30pm ET: Destabilization & VPDs

Moderator: Anil Vullikanti, BI/UVA

Carolina Danovaro, WHO

Dr. Danovaro works with the Strategic [Immunization] Information Group at the World Health Organization (WHO). She focuses mainly on the analysis and interpretation of global immunization data, supporting improved immunization monitoring in countries and the development of methodologies and processes to improve routine immunization monitoring and data quality. Between 2004 and 2015, Dr. Danovaro was responsible for immunization data quality and strategic information at the Pan American Health Organization (PAHO) in Washington DC. During her time at PAHO, she led an initiative to improve immunization data quality and to guide Member States in the planning, development and implementation of Electronic Immunization Registries. Before joining PAHO, Carolina worked at the International Vaccine Institute (IVI), on typhoid and cholera vaccine demonstrations projects in Asia and before that she was a fellow at the National Immunization Program at the US Centers for Disease Control and Prevention (CDC). Dr. Danovaro holds a medical degree from the Pontificia Universidad Católica of Chile and a Masters in Epidemiology from the London School of Hygiene and Tropical Medicine.

Bhargavi Rao, LSHTM/MSF

Operational Reflections: VPDs in Humanitarian Settings

I recently joined LSHTM after 8 years working at Médecins Sans Frontières (Operational Centre Amsterdam), including leading the Emerging and Infectious Diseases portfolio, dividing my time between COVID-19, malaria and other infectious diseases outbreaks.  I have worked in humanitarian responses across multiple contexts, and am a public health clinician with a PhD in infectious disease epidemiology.  

In my new role, I am looking forward to developing a programme of research on malaria and infectious disease control in public health crises and complex emergencies, with a particular interest in community level interventions, as well as investigating early-warning systems and resilience (linking disease, climate and conflict). In addition I will be contributing to the development of the Health in Humanitarian Crises MSc.  

To keep connected to the operational front-line, I'll be continuing in a part-time role as a malaria/infectious diseases specialist at MSF as well as retain an honorary clinical position with Public Health England.

Anton Camacho, MSF

Impact of COVID-19 Pandemic on VPDs: and MSF Perspective

I am a mathematical modeller in epidemiology. My work involves the development and the analysis of mathematical models to investigate the mechanisms underlying the epidemiological dynamics of infectious diseases. I am currently funded by an MRC Career Development Award in Biostatistics, and I am affiliated with the Centre for the Mathematical Modelling of Infectious Diseases at the London School.

I completed my PhD in Mathematical Biology in 2011, under the supervision of Bernard Cazelles and Amaury Lambert at the Eco-Evolutionary Mathematics lab in Paris. I contributed to the field of theoretical approaches to understand the epidemiology, immunology and evolution of influenza. More broadly, I am interested in interdisciplinary research, at the edge of mathematics, biology and computer sciences, in order to address public-health issues.

Day 2, June 8th, 10am ET: Epidemiological & immunological factors

Moderators: Yang Liu, LSHTM and Anil Vullikanti, BI/UVA

Jessica Metcalf, Princeton

Jessica Metcalf is an Associate Professor of Ecology, Evolutionary Biology & Public Affairs, and is a demographer with broad interests in evolutionary ecology, infectious disease dynamics and public policy. She completed her PhD at Imperial College on the evolutionary demography of monocarpic perennials. Her post-doctoral research was conducted at various institutions. She studied the evolution of senescence at the Max Planck Institute of Demographic Research, the inference of tree demographic parameters at Duke University, and infectious disease dynamics at Pennsylvania State University and Princeton University.

Metcalf’s teaching focuses on a course titled Epidemiology: An Ecological and Evolutionary Perspective. Her course aims to communicate both an understanding of the core principles of epidemiology (ranging from classical study designs to core analytical techniques) and a broader perspective into the fundamental drivers of health outcomes (ranging from ecological drivers of the spread of infectious disease to the evolutionary determinants of profiles of late age mortality).

Deirdre Hollingsworth, Oxford

Deirdre is an infectious disease epidemiologist who uses mathematical models and statistical analyses to study the evolution and transmission dynamics of infectious diseases with the aim of informing the design of more effective control interventions. She is particularly interested in neglected tropical diseases, a group of diseases which cause suffering amongst the poorest populations of the world. She leads the NTD Modelling Consortium, an international network of neglected tropical disease modellers. 

Her research foci are lymphatic filariasis, visceral leishmaniasis and a group of intestinal worms (soil transmitted helminths or STHs) which affect a large number of children and adults in low income settings. She has ongoing interests in the transmission and evolution of HIV in both Africa and European/North American settings as well as malaria and influenza.

Ben Lopman, Emory University

Human Contact and the Future of Endemic Infections

I am an infectious disease epidemiologist with a research focus on vaccines and enteric viruses. Our team conducts research globally and in the United States. Our research is targeted at diarrheal diseases, and, specifically rotavirus and norovirus. We use a range of approaches including field studies, statistical analysis and dynamic mathematical modeling to conduct policy-relevant public health research.

Day 2, June 8th, 11:50am ET: Keynote

Moderator: Stephen Eubank, BI/UVA

Raji Tajudeen, Africa CDC

Raji Tajudeen MD is a Medical Doctor with postgraduate qualifications in Pediatrics and Public Health. He is a Fellow of the West African College of Physicians and African Public Health Leaders Fellow of the Chatham House Royal Institute of International Affairs, UK. He has over 20 years of experience in Child Health and Public Health of which 16 years is at senior level. He has worked in different settings in the developing world; Nigeria, Saudi Arabia, Liberia, Guinea, Sierra Leone and Ethiopia. Additionally, Taj has strong experience working on programmes and projects for different international organizations. Further, he has academic and working knowledge of Health System Management, Health System
Strengthening, Health Diplomacy, Maternal and Child Health, and Health in Humanitarian Emergencies.

He is currently the Head of Public Health Institutes and Research of Africa Centres for Disease Control and Prevention (Africa CDC). He coordinates the establishment and strengthening of National Public Health Institutes across the 55 African Union Member States. He oversees the establishment of the five Africa CDC Regional Collaborating Centers. He coordinates the Africa CDC Institute for Workforce Development and oversees the continental public health research agenda. Taj heads the healthcare preparedness and countermeasures section of the Africa CDC COVID-19 response. He co-chairs the case management technical working group of the Africa Taskforce on COVID-19. Taj has publications in Medical journals and has co-authored a chapter in a medical textbook.

Day 2, June 8th, 1:30pm ET: Data modeling challenges & opportunities

Moderators: Jonathan Mosser, IHME/UW and Stephen Eubank, BI/UVA

Danil Mikhailov, data.org

Danil Mikhailov, Ph.D. is the Executive Director of data.org. He has over 20 years of experience setting up multiple start-ups and leading work across a range of diverse sectors, always investigating and innovating in the space where technology, culture, and society converge. Prior to data.org, Danil was at The Wellcome Trust, where he founded and directed the Wellcome Data Labs, an interdisciplinary team of data scientists, software developers, and social scientists, creating open-source data tools supporting Wellcome’s mission. While at Wellcome, Danil coordinated the data and data science aspects of the Trust’s Covid-19 pandemic response. Before joining The Wellcome Trust, Danil founded and chaired the Digital Strategy Forum for Science, Art, and Culture, in the United Kingdom. 

Danil strongly believes in the power of interdisciplinarity and, in addition to his tech expertise, he brings a social sciences and humanities perspective to his work. Danil holds a Ph.D. in Sociology and Communications from the University of Brunel, an MA in Philosophy, from Birkbeck, University of London, an MA in Chinese Studies, from SOAS, University of London, and a BSc in IT & Business Management, University of York.

Matt Ferrari, PSU

Rethinking Diagnostics for Public Healths

Matthew Ferrari is Director of the Center for Infectious Disease Dynamics; Huck Career Development Professor; and Professor of Biology at Penn State. Ferrari received his PhD in Ecology from Penn State in 2006. He received his Masters in Statistics in 2002 and in Fisheries and Wildlife Management from Montana State University in 1999, and a BA in Biology from Colby College in 1996.

His research focusses on the application of mathematical models and quantitative epidemiology to guide vaccination policy for childhood infections. For over a decade he has worked with the World Health Organization, the US-Centers for Disease Control and Prevention, and Doctors Without Borders on vaccination planning and outbreak response for measles around the world.

Ferrari was a sabbatical fellow at Epicentre/Medecins Sans Frontieres in 2018-19 and currently serves as a technical advisor to the SAGE Measles and Rubella Working Group at the World Health Organization. He joined Penn State as a faculty member in 2010.

Michael Johansson, CDC

Michael Johansson is a Biologist with the CDC. He serves as a CDC Liaison to the Infectious Disease Modeling and Analytics Initiative, conducts COVID-19 modeling work, and coordinates with the new Center for Forecasting and Analytics. He is also part of the National Center for Emerging and Zoonotic Infectious Diseases (NCEZID) and the Division of Vector-Borne Diseases (DVDB).

Program Committee

OVERVIEW

There will be four focus areas:

• Fostering and promoting effective epidemiology for decision makers
• Three levels of emerging architecture: node level, machine level, large-scale sensor systems
• Data considerations within HPC
• Expanding community's use of HPC

AGENDA

Each session will feature keynote talks followed by a panel discussion.

March 30 11-12:30pm ET: Effective Epidemiology for Decision Makers

Moderator: Madhav Marathe, UVA
Alex Vespignani, Northeastern
Rajesh Sundaresan, IISc
Nick Reich, U Mass

March 30 2-3:30pm ET: Expanding HPC Use

Moderator: John Towns, UIUC
Katriona Shea, Penn State
Fred Streitz, CDC/LLNL
Shawn Brown, PSC

March 31 11-12:30pm ET: Data Considerations

Moderator: Venkat Vishwanath, ANL
Kirk Jordan, IBM
Phil Blood, PSC
B. Aditya Prakash, GA Tech

March 31 2-3:30pm ET: Emerging Architectures

Moderator: Laxmi Parida, IBM
Andy Hock, Cerebras
Rick Stevens, ANL
Bud Mishra, NYU

Day 1, March 30, 11am EDT: Effective epidemiology for decision makers

Moderator: Madhav Marathe, UVA

Alessandro Vespignani, Northeastern

Alessandro Vespignani research activity is focused on the study of “techno-social” systems, where infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. In this context we aim at understanding how the very same elements assembled in large numbers can give rise – according to the various forces and elements at play – to different macroscopic and dynamical behaviors, opening the path to quantitative computational approaches and forecasting power.

The main research lines pursued at the moment are:
* Develop analytical and computational models for the co-evolution and interdependence of large-scale social, technological and biological networks.
* Modeling contagion processes in structured populations.
* Developing predictive computational tools for the analysis of the spatial spread of emerging diseases.
* Analyze the dynamics and evolution of information and social networks.
* Model the adaptive behavior of social systems.

Prof. Vespignani has a joint appointment between the College of Science, the College of Computer and Information Science, and the Bouvé College of Health Sciences.

Rajesh Sundaresan, IISc

Rajesh Sundaresan is Professor at the Indian Institute of Science. His research interests are in communication, computation, and control over networks. For some recent COVID-19 modelling and epidemiological work, please visit his webpage: https://ece.iisc.ac.in/~rajeshs

Before joining the Indian Institute of Science as Professor, Rajesh worked as Visiting Faculty in Toulouse Mathematics Institute, Universite Paul Sabatier October 2015 as Visiting Scholar, Coordinated Science Laboratory, University of Illinois at Urbana-Champaign August 2012 – July 2013, Visiting Faculty, Summer of 2007 and Senior Staff Engineer/Manager 2005 at Qualcomm Inc. Currently he is the Dean of the Division of EECS (Electrical, Electronics, and Computer Sciences) since August 2021. Rajesh did his Ph.D., (1999) and M.A. (1996) in Electrical Engineering from Princeton University. He got his B.Tech. (1994) in Electronics from Indian Institute of Technology, Madras.

Nick Reich, UMass

Nick is a Professor of Biostatistics at UMass. He received his PhD in Biostatistics from Johns Hopkins, where he also did his post-doctoral training in infectious disease epidemiology. The Reich Lab focuses on developing statistical methods and tools for data arising from infectious disease settings. In 2019, they were designated as a CDC-funded Influenza Forecasting Center of Excellence.
They use statistics, data science, and epidemiology to gain a better understanding of the complexities of infectious disease dynamics. Their work has been featured in the New York Times, FiveThirtyEight, the Economist, and the Boston Globe, and on National Public Radio and PBS NewsHour.

With active funded projects from the NIH and CDC, the Lab is involved in independent and collaborative research efforts. Collaborators include the Influenza Division at the US CDC, the Dengue Branch of the CDC in Puerto Rico, the Infectious Disease Dynamics Working Group and Center for Health Security at Johns Hopkins, the Thai Ministry of Public Health and National Electronics and Computer Technology Center (NECTEC), the New York City Department of Health and Mental Hygiene, the Children's Hospital Colorado, and the Veterans Health Administration branches in New York City and Iowa City. 

Day 1, March 30, 2pm EDT: Expanding HPC use in the research community

Moderator: John Towns, UIUC

Katriona Shea, Penn State

Katriona Shea is a Professor of Biology and Alumni Professor in the Biological Sciences at Penn State University. She has a B.A. in Physics from New College, Oxford, and a Ph.D. in Theoretical Population Ecology from Imperial College, University of London. 

Shea's primary research interest is in the use of ecological theory in population management. She addresses issues in invasion ecology, epidemiology, conservation and harvesting. An in-depth ecological understanding is essential for successful management, and this research focus allows her to ask important ecological questions for species of special concern. For example, she addresses the ecological factors that make certain species successful invaders of specific communities. At the same time, she examines the ways in which we can manipulate these factors to achieve management goals. Her research focuses on population management in a variety of ways, including quantitative theoretical studies of real systems, purely theoretical studies that inform practical approaches, and collaborative empirical work. 

Fred Streitz, CDC/LLNL

As Chief Computational Scientist at Lawrence Livermore National Laboratory (LLNL), Fred Streitz leads efforts to develop HPC applications that push the limits of leadership-class computational capability to address forefront scientific problems. He has twice led multidisciplinary/multi-institutional teams that were awarded a Gordon Bell Prize for significant achievement in supercomputing (and his teams have been finalists twice more).

His current focus is as a Senior Advisor at the Centers for Disease Control and Prevention (CDC), on a detail assignment from LLNL. In this role, Fred will help coordinate the development and deployment of computational and analytical capability at the Center for Forecasting and Outbreak Analytics at CDC.

Prior to this assignment, Fred was at Department of Energy HQ to help define and instantiate the Artificial Intelligence and Technology Office (AITO), which was successfully launched in September 2019. After the creation of the office, he remained on as Science Advisor until his re-assignment in 2022.

Dr. Streitz is a member of the White House National AI Research Resource Task Force and serves as the Associate Editor for the International Journal of High Performance Computing Applications. Prior to joining Lawrence Livermore National Laboratory in the Physical and Life Sciences Directorate in 1999, Fred held positions as a National Research Council Fellow at the Naval Research Laboratory and an Assistant Professor at Auburn University.
Fred earned an M.A. and Ph.D. in Physics from Johns Hopkins University and a B.S. in Physics from Harvey Mudd College. He is a Fellow of the American Physical Society.

Shawn Brown, PSC

Dr. Brown joined the team in 2019 as the Director of the Pittsburgh Supercomputing Center. He has over 25 years of experience in developing software to support the use of high-performance computing for research in areas such as chemistry, bioinformatics, and public health. In addition to directing the center, his research interests are:
1. How agent-based modeling and other computational techniques can be used to provide decision support in public health and chronic disease
2. Building of highly convergent collaborative neuroinformatics platforms for open data sharing and computation
3. Synthetic Ecosystems for representing cohort and cross-sectional data for modeling and open data sharing

Prior, he was the Associate Director of Research Software Development at the McGill Centre for Integrative Neuroscience, the Director of Public Health Applications at the Pittsburgh Supercomputing Center, Assistant Professor of Biostatistics at the University of Pittsburgh Graduate School of Public Health, and Research Associate at Q-Chem, Inc. He received his PhD from the University of Georgia in 2001 in Theoretical Chemistry and has authored over 100 peer-reviewed publications.

Day 2, March 31, 11am EDT: Data considerations

Moderator: Venkat Vishwanath, ANL

Kirk Jordan, IBM

Dr. Kirk E. Jordan is an IBM Distinguished Engineer, an IBM Executive position in IBM Research Division's Data Centric Solutions in IBM T.J. Watson Research Center and is the Chief Science Officer for IBM Research United Kingdom (UK). In the UK, he established the IBM Research presence at Science and Technologies Facilities Council's (STFC) Darebury Laboratory in collaboration with the STFC Hartree Centre focusing on data centric cognitive computing.  He has vast experience in high performance and parallel computing.

The Data Centric Solutions  group is addressing the challenges involved in achieving Petascale and Exascale performance on IBM's very high end system platforms, running real workflows and workloads to obtain significant results in science, engineering, business and social policy, and partnering and collaborating with key IBM clients on the most challenging applications and workloads on these large systems. Dr. Jordan oversees development of applications for IBM's advanced computing architectures, investigates and develops concepts for new areas of growth involving high performance computing (HPC), and provides leadership in high-end computing, data centric cognitive computing and simulation in such areas as computational fluid dynamics, systems biology and high-end visualization. At IBM, he held several positions promoting HPC and high performance visualization, including leading technical efforts in the Deep Computing organization within IBM's Systems and Technology Group, managing IBM's University Relations SUR (Shared University Research) Program and leading IBM's Healthcare and Life Sciences Strategic Relationships and Institutes of Innovation Programs. He is a member of the IBM Academy of Technology.

In addition to his IBM responsibilities, Jordan is able to maintain his visibility as a computational applied mathematician in the high-performance computing community. He is a Fellow of SIAM (Society for Industrial and Applied Mathematics) and of AAAS (American Association for the Advancement of Science). He is active on national and international committees on science and high-performance computing issues and has received several awards for his work on supercomputers. His main research interests lie in the efficient use of advanced architecture computers for simulation and modeling especially in the area of systems biology and physical phenomena. He has authored numerous papers on performance analysis of advanced computer architectures and investigated methods that exploit these architectures. Areas he has published include interactive visualization on parallel computers, parallel domain decomposition for reservoir/groundwater simulation, turbulent convection flows, parallel spectral methods, multigrid techniques, wave propagation, systems biology and tumor modeling.

Phil Blood, PSC

As Senior Director of Research, Phil directs PSC’s research and research support teams, including Biomedical Applications, AI & Big Data, and User Support for Scientific Applications. Phil also leads the Anton project at PSC, co-directs the National Center for Genome Analysis Support (NCGAS), and serves as co-PI of XSEDE. In these roles, Phil works closely with PSC’s leadership team to accomplish our mission to apply advanced computing to enable discoveries that benefit the world.

B. Aditya Prakash, GA Tech

B. Aditya Prakash is an Associate Professor in the College of Computing at the Georgia Institute of Technology (“Georgia Tech”). He received a Ph.D. from the Computer Science Department at Carnegie Mellon University in 2012, and a B.Tech (in CS) from the Indian Institute of Technology (IIT) -- Bombay in 2007. He has published one book, more than 80 papers in major venues, holds two U.S. patents and has given several tutorials at leading conferences. His work has also received multiple best-of-conference, best paper and travel awards.

His research interests include Data Science, Machine Learning and AI, with emphasis on big-data problems in large real-world networks and time-series, with applications to computational epidemiology/public health, urban computing, security and the Web. Tools developed by his group have been in use in many places including ORNL and Walmart. He has received several awards such as Facebook Faculty Awards (2015 and 2021), the NSF CAREER award and was named as one of ‘AI Ten to Watch’ by IEEE. His work has also won awards in multiple data science challenges (e.g the Catalyst COVID19 Symptom Challenge) and been highlighted by several media outlets/popular press like FiveThirtyEight.com. He is also a member of the infectious diseases modeling MIDAS network and core-faculty at the Center for Machine Learning (ML@GT) and the Institute for Data Engineering and Science (IDEaS) at Georgia Tech.

Day 2, March 31, 2pm EDT: Emerging architectures

Moderator: Laxmi Parida, IBM

Andy Hock, Cerebras

Andy Hock is VP of Product Management at Cerebras Systems, an AI hardware startup out to accelerate deep learning and change compute forever.

He has 13 years of experience in product management, technical program management, and enterprise business development; over 20 years of experience in research, algorithm development, and data analysis for image processing. 7 years experience in applied machine learning / AI.

Before Cerebras, Andy was Product Manager lead for Data and Analytics for Terra Bella at Google, where he led the development of machine learning-powered data products from satellite imagery. Earlier, he was Senior Director for Advanced Technology Programs at Skybox Imaging (which became Terra Bella following acquisition by Google in 2014), and before that was a Senior Program Manager and Senior Scientist at Arete Associates. He has a Ph.D. in Geophysics and Space Physics from the University of California, Los Angeles, and a B.A. in Astronomy-Physics from Colgate University.

Rick Stevens, ANL

Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences.

Stevens has been at Argonne since 1982, and has served as director of the Mathematics and Computer Science Division and also as Acting Associate Laboratory Director for Physical, Biological and Computing Sciences. He is currently leader of Argonne’s Exascale Computing Initiative, and a Professor of Computer Science at the University of Chicago Physical Sciences Collegiate Division. From 2000-2004, Stevens served as Director of the National Science Foundation’s TeraGrid Project and from 1997-2001 as Chief Architect for the National Computational Science Alliance.

Stevens is interested in the development of innovative tools and techniques that enable computational scientists to solve important large-scale problems effectively on advanced scientific computers. Specifically, his research focuses on three principal areas: advanced collaboration and visualization environments, high-performance computer architectures (including Grids) and computational problems in the life sciences. In addition to his research work, Stevens teaches courses on computer architecture, collaboration technology, virtual reality, parallel computing and computational science.

Bud Mishra, NYU

Bud Mishra is a professor of computer science and mathematics at NYU's Courant Institute of Mathematical Sciences, professor of human genetics at Mt Sinai School of Medicine, and a professor of cell biology at NYU School of Medicine. Bud has a degree in Sciences from Utkal University, in Electronics and Communication Engineering from Indian Institute of Technology (IIT), Kharagpur, and MS and PhD degrees in Computer Science from Carnegie-Mellon University. Bud is also a visiting scholar at CSHL's Center for Quantitative Biology. From 2001-04, he was a professor at the Watson School of Biological Sciences, Cold Spring Harbor Lab (CSHL) and from 2003-2006, a Visiting Professor at Tata Institute of Fundamental Research (TIFR).

Bud is an IIT, Kharagpur Distinguished Alumnus, NYSTAR Distinguished Professor, AAAS Fellow (engineering: robotics, hardware verification and computational biology), IEEE fellow (robotics and automation) and a fellow of the ACM (computational biology and symbolic computation).

His other research activities, outside of computational and systems biology, take place in the newly created Laboratory for Entrepreneurship in Data Sciences (LEDS) focusing on challenges from Finance, Advertising and Ad Technology, Philanthropy, Biomedicine and Engineering. Somewhat immodestly (and with apologies to Albert Arnold "Al" Gore), the laboratory aims to reinvent the Internet of the future.

Program Committee

John Towns, Arvind Ramanathan, Madhav Marathe, Laxmi Parida

 RP2: 2nd ANNUAL NSF RAPID PI MEETING

December 8-9, 2021

It has been just over a year since the PREPARE (Pandemic Research for Preparedness and Resilience virtual organization was created, and we’re intent on building a community focused on pandemic preparedness and resilience. As we work to maximize the collaborative synergies of the outstanding research completed through the NSF RAPID grant program, we’re excited to offer you this opportunity to present your work, learn from your colleagues, and seek collaborative opportunities at RP2: PREPARE 2nd Annual RAPID PI Meeting.

Watch all sessions on YouTube!

• Day 1
  • Opening remarks 
  • Epidemiology and Public Health 1 lightning round
  • Infodemiology, Social Networks, and Scientific Communication mini-lightning round 
  • Keynote: Simon Levin, Princeton University (Link to selected works cited)
  • Education, Training, & Workforce Development mini-lightning round 
  • Computational Biology and Bioinformatics lightning round
• Day 2
  • Keynote: Amira Roess, George Mason University 
  • Surveillance and Contact Tracing/Privacy/Computing and Data Infrastructure lightning round
  • Epidemiology and Public Health 2 lightning round
  • Social, Behavioral, Economic, and Governance lightning round 
  • Future directions

Link to Poster Sessions - coming soon! 

Keynote Speakers

Day 1: Simon Levin, Princeton University

COVID-19 and Challenges to the Classical Theory of Epidemics

The standard theory of infectious diseases, tracing back to the work of Kermack and McKendrick nearly a century ago, has been a triumph of mathematical biology, a rare marriage of theory and application. Yet the limitations of its most simple representations, which has always been known, have been laid bare in dealing with COVID-19, sparking a spate of extensions of the basic theory to deal more effectively with aspects of viral evolution, asymptotic stages, heterogeneity of various kinds, the ambiguities of notions of herd immunity, the role of social behaviors and other features. This lecture will address some progress in addressing these, and open challenges in expanding the mathematical theory.

Simon A. Levin is the James S. McDonnell Distinguished University Professor in Ecology and Evolutionary Biology at Princeton University and the Director of the Center for BioComplexity in the Princeton Environmental Institute. His research examines the structure and functioning of ecosystems, the dynamics of disease, and the coupling of ecological and socioeconomic systems. Levin is a Fellow of the American Academy of Arts and Sciences and the American Association for the Advancement of Science, a Member of the National Academy of Sciences and the American Philosophical Society, and a Foreign Member of the Istituto Veneto di Scienze, Lettere ed Arti, and the Istituto Lombardo (Milan). He has over 500 publications and is the editor of the Encyclopedia of Biodiversity and the Princeton Guide to Ecology. Levin’s awards include: the Heineken Prize for Environmental Sciences, Kyoto Prize in Basic Sciences, Margalef Prize for Ecology, the Ecological Society of America’s MacArthur and Eminent Ecologist Awards, the Luca Pacioli Prize (Ca’Foscari University of Venice), the Tyler Prize for Environmental Achievement, and the National Medal of Science.

Day 2: Amira Roess, George Mason University

The practicalities of multiple disciplinary research: lessons from COVID-19

Emerging zoonotic infectious diseases have long been recognized for their potential to lead to catastrophic morbidity and mortality, to disrupt global economies and to shape history. Pronouncements of the need to develop multi-disciplinary research programs to address this challenge have been made for over 40 years and yet the movement towards meaningful multi-disciplinary research has proceeded at a glacial pace until recently. In this talk we will review the history of zoonotic diseases, coronavirus pandemics and the current state of public health preparedness and responses.  We will discuss COVID-19 research and practice challenges that might just only be addressed using multiple disciplinary approaches.

Dr. Roess is a professor of Global Health and Epidemiology at George Mason University's College of Health and Human Services. Her expertise is in infectious diseases epidemiology. Dr. Roess leads several longitudinal studies including on the emergence and transmission of MERS-CoV (with support from the US National Science Foundation) and the development of COVID-19 in the first year of life (with support from NIH). She is also working on a number of other COVID-19 projects, including examining infection disparities and use of mHealth (especially apps) to enhance surveillance and contact tracing. Dr. Roess holds a PhD in global disease epidemiology and control from Johns Hopkins University. Prior to joining academia, Dr. Roess served as an Epidemic Intelligence Service (EIS) officer at the CDC.

Program Committee

Andreas Züfle, Li Xiong, Anil Vullikanti, and Beth Redbird

OVERVIEW

There will be four focus areas:

• Misinformation
• Equity and health disparities
• Governance and economic aspect
• Behavioral modeling

AGENDA

Each synchronous session will feature keynote talks followed by a panel discussion.

Day 1, June 24, 11am EDT: Governance and Economic Aspects

 The Politics of Pandemic Othering and Trust: COVID-19 in Historical Perspective // Kim Yi Dionne, UC Riverside

Abstract: In a global politics characterized by racialized inequality, pandemics such as COVID-19 exacerbate the marginalization of already oppressed groups. Published research on previous pandemics historicize what we call pandemic othering and blame, and we enumerate some of the consequences for politics, policy, and public health. We draw on lessons from smallpox outbreaks, the third bubonic plague, the 1918 influenza pandemic, and more recent pandemics, such as HIV/AIDS, SARS, and Ebola to show that COVID-19 continues a long history of othering and blame during disease outbreaks. These earlier pandemics also offer insights into the role of trust in pandemic response and highlight the obstacles posed by racialized marginalization in generating the trust necessary to collectively combat infectious disease outbreaks.

Bio: Kim Yi Dionne (@dadakim) is an Associate Professor of Political Science at UC Riverside. Her research examines health interventions, politics, and public opinion—primarily in African countries. Her book, Doomed Interventions: The Failure of a Global Response to AIDS in Africa (Cambridge University Press), drew significantly on her research during a Fulbright Fellowship to Malawi.

Title // Bryan Lewis, Biocomplexity Institute, UVA

Abstract: 

Bio: Bryan Lewis is a research associate professor in the Network Systems Science and Advanced Computing division. His research has focused on understanding the transmission dynamics of infectious diseases within specific populations through both analysis and simulation. Lewis is a computational epidemiologist with more than 15 years of experience in crafting, analyzing, and interpreting the results of models in the context of real public health problems.

Day 1, June 24, 2pm EDT: Equity and Health Disparities

The Role of Behavior, Mobility, and Social-Network Structure on COVID-19 Epidemics // Sam Scarpino, Northeastern

Abstract: The COVID-19 pandemic has upended our societies and re-shaped the way we go about our day-to-day lives—from how we work and interact to the way we buy groceries and attend school. Leveraging global data sets that represent billions of people, I will present a series of studies exploring how our behavior, mobility patterns, and social networks have altered and been altered by COVID-19 and the non-pharmaceutical interventions implemented to control its spread. Building on these studies, I will discuss work by Global.health, a new collaborative network of researchers, technologists, and public health experts that has developed and built an open access platform for collecting, storing, securing, and sharing anonymized, individual-level COVID-19 data. Currently, our data includes almost 30M individual-level cases from 160 countries, which are tagged with up to 40 fields of meta-data. Writing for The New York Times Magazine, Steven Johnson said the data captured by Global.health, "may well be the single most accurate portrait of the virus’s spread through the human population in existence."

Bio: Samuel V. Scarpino, PhD is an Assistant Professor in the Network Science Institute at Northeastern University and holds academic appointments in Physics, Health Sciences, the Khoury College of Computer Sciences, the Global Resilience Institute, and the Roux Institute. At Northeastern University, he directs the Emergent Epidemics Lab and is a Co-founder of Global.health. Scarpino has 10+ years of experience translating research into decision support and data science/ML tools across diverse sectors from public health and clinical medicine to real estate and energy. From 2017 to 2020, he was Chief Strategy Officer and head of data science at Dharma Platform–a social impact–technology startup. Scarpino has nearly 100 publications in academic journals and books. His expert commentaries on science and technology have appeared in publications such as: Nature, Science, PNAS, and Nature Physics. His research has been covered by the New York Times, Wired, the Boston Globe, NPR, VICE News, National Geographic, and numerous other venues. For his contributions to complex systems science, he was made a Fellow of the ISI Foundation in 2017, an External Faculty member of the Santa Fe Institute in 2020, and an External Faculty member of the Vermont Complex Systems Center in 2021.

Virginia’s COVID-19 Health Equity (Applied) Research Agenda // Justin Crow, VDH

Abstract: Several factors converged in 2020 to bring health equity into the spotlight in Virginia. In September 2019, Governor Ralph S. Northam appointed Dr. Janice Underwood to serve the Commonwealth, as the nation’s first cabinet-level Chief Diversity Officer. Disparities in infections, outcomes, and access to resources such as tests and personal protective equipment emerged early in the COVID-19 pandemic. Similarly, economic fallout from the pandemic and the response hit minority and low-income communities hardest. Over the summer, Richmond and its monuments to the Confederacy became a flashpoint in nationwide protests in response to the murder of George Floyd, highlighting the systemic and historical inequities driving these disparities. Finally, in February of 2021, the Virginia General Assembly passed a resolution declaring racism a public health crisis. The Office of Health Equity, a relatively small office in the Virginia Department of Health focused on data and applied research, played a key role in responding to these crises. Additionally, health equity became a central focus of Federal funding, providing additional resources to meet the challenges of COVID-19 and other emerging public health threats. In this presentation I describe how the Division of Social Epidemiology took an applied research approach during the pandemic, developed a COVID-19 Health Equity Research Agenda to understand the equity impacts of the pandemic and its response, and is building an equity-focused research infrastructure to address current and future public health crises. 

Bio: Justin Crow is the Director of the Division of Social Epidemiology in the Office of Health Equity of the Virginia Department of Health.  Prior to joining the Office of Health Equity, Justin served as the Deputy Director for the Virginia Healthcare Workforce Data Center and the Deputy Executive Director for the Board of Health Professions, both with the Virginia Department of Health Professions.  Justin earned his Master in Public Administration from Virginia Commonwealth University and his baccalaureate degree from the University of Mary Washington. 

Policing COVID-19 in Queensland, Australia // Katie Hail-Jares, Griffith

Abstract: ​In March 2020, shortly after the first confirmed COVID-19 case, the state of Queensland-- and many other jurisdictions around Australia-- expanded police powers in an effort to reduce the spread of the virus. This expansion of police powers was unprecedented, including powers to both stop and fine individuals who violated the public health directives (e.g. staying inside; wearing a mask; etc.) as well as created interstate border forces. Throughout the year, the Queensland Police Service regularly put out press releases about their COVID activities. A content analysis of 580 press releases published online between March 2020-August 2020 revealed that 45 mentioned COVID-19. The largest proportion reported on infringements. Looking more closely at these infringements notices, I suggest that public health citations were used to target people who were deemed socially undesirable, such as sex workers, people who were houseless, and gang members. The role of racism and xenophobia in issuing these infringements is also discussed.

Bio: Katie Hail-Jares (@khailjares) is a lecturer in the School of Criminology and Criminal Justice at Griffith University. She is an epidemiological criminologist who is interested in how criminalising behaviour can impact the health of people and their communities. She is the lead editor of Challenging Perspectives on Street-Based Sex Work (Temple University Press), where her chapter discussed the intersection of gentrification, policing, and trans sex work in Washington, DC. 

Day 2, June 25, 11am EDT: Misinformation

Socially Influence Campaigns: The Coordination of Events Using Bots and Misinformation // Kathleen Carley, CMU

Abstract: As the pandemic swept through the physical world a disinfodemic swept through the digital world. Misinformation was used to malign individuals, create havoc in civil society, repress minority groups, attack foreign powers, create confusion and so forth.  The role of bots, hate-speech and misinformation and how they are used together in influence campaigns is described. This is illustrated using information from the pandemic, various elections, and revolutions with particular emphasis on the re-open campaigns and conspiracy theories.   Recent advances in social cybersecurity are described and limitations of current theories and technologies are identified.

Bio: Dr. Carley is a Professor of Computer Science in the Institute for Software Research, IEEE Fellow, and Director of the Center for Computational Analysis of Social and Organizational Systems (CASOS) and Director of the center for Informed DEmocracy And Social‐cybersecurity (IDeaS) of the Center for at Carnegie Mellon University. She joined Carnegie Mellon in 1984 as Assistant Professor Sociology and Information Systems. In 1990 she became Associate Professor of Sociology and Organizations, in 1998 Professor of Sociology, Organizations, and Information Technology, and in 2002, attained her current role as Professor of Computation, Organization, and Society. She is also the CEO of Carley Technologies Inc. aka Netanomics. Dr. Carley’s research combines cognitive science, sociology, and computer science to address complex social and organizational issues. Her most notable research contribution was the establishment of Dynamic Network Analysis (DNA) – and the associated theory and methodology for examining large high‐dimensional time variant networks. Her research on DNA has resulted in tools for analyzing large‐scale dynamic networks and various multi‐agent simulation systems. She has led the development of tools for extracting sentiment, social and semantic networks, and cues from textual data (AutoMap & NetMapper), simulating epidemiological models (BioWar), and simulating changes in beliefs and practice given information campaigns (Construct). Her ORA system is one of the premier network analysis and visualization technologies supporting reasoning about geo‐spatial and dynamic high‐dimensional network data. It includes special features for handling small and big data, social media data, and network dynamics. It is used worldwide. Illustrative projects include assessment of fake news and social cyber‐security threats, IRS outreach, impact of NextGen on airline re‐rerouting, counterterrorism modeling, counter‐narcotics modeling, health analytics, social media analytics of elections, and social media based assessment of crises such as Benghazi, Darfur, the Arab Spring, COVID‐19.

Slides available here.

Do they really believe this? Motivations for spreading misinformation and reactions to interventions // Jennifer Golbeck, UMD

Abstract: Why do people share misinformation online and what can we do about it are questions driving many research efforts as we emerge from a year that has been astonishing in both the volume and negative impact of the bad information that has been shared. This talk will integrate a slew of new studies that seek to understand the people and motivations that drive the spread of misinformation and the efficacy of various interventions. Many of these results are consistent and go against conventional wisdom. This talk will bring up new questions raised by this work and suggest policy that may be effective to stop harmful misinformation spread.

Bio: Jennifer Golbeck is a Professor in the College of Information Studies at the University of Maryland, College Park. Her research focuses on artificial intelligence and social media, privacy, malicious online behavior, and trust on the web. She received an AB in Economics and an SB and SM in Computer Science at the University of Chicago, and a Ph.D. in Computer Science from the University of Maryland, College Park.

Slides available here.

Lessons from the COVID States Project // David Lazer, Northeastern

Abstract: I will discuss lessons drawn from the COVID States Project with respect to our understanding of the mechanism of dissemination of misinformation on social media, the impact of misinformation on behaviors/attitudes. The essential takeaways: we have a better understanding of online sharing behavior than exposure; well established methods to examine misbeliefs; but a relatively poor understanding of the relationship between exposure with beliefs and behaviors (like, the decision whether to get vaccinated). A key conclusion is that we need a large-scale, multi-platform approach to understanding the relationship between online behaviors (including and especially exposure) and offline attitudes and behaviors.

Bio: David Lazer is University Distinguished Professor of Political Science and Computer Sciences, Northeastern University, elected Fellow of the National Academy of Public Administration, and visiting scholar at the Institute for Quantitative Social Science at Harvard. His scholarship focuses on computational social science and social networks, with a particular focus on misinformation and political communication. He is co-lead of the COVID states project, which has charted public opinion in all 50 states through the pandemic.

Day 2, June 25, 2pm EDT: Behavioral Modeling

Cognitive Modeling of the Behavioral Effectiveness of Non-Pharmaceutical Interventions // Christian Lebiere, CMU

Abstract: Until the advent of vaccines and effective therapies, non-pharmaceutical interventions (NPIs) such as social distancing and mask wearing are the primary means to control the spread of epidemics. However, NPI mandates are difficult to enforce and largely depend upon the cooperation of the public. Models often make rough assumptions about what percentage of the population behave accordingly in order to estimate the effectiveness of NPIs. However, evidence suggests that behavioral changes vary according to context, are susceptible to personal experiences as well as messaging in mass and social media, and often precede the introduction of mandates. We develop cognitive models of behavioral response to NPIs to better estimate their impact on the course of epidemics. Our cognitive models reflect the cumulative effect of social media messaging, continuously adapt behavior to the rise and fall of the infection counts, and display divergent behavior resulting from distinct attitude clusters. Future work on extending our models to related issues such as vaccine hesitancy and integrating our cognitive models with epidemiological models is discussed.

Bio: Christian Lebiere is a Research Faculty in the Psychology Department at Carnegie Mellon University, having received his Ph.D. from the CMU School of Computer Science.  During his graduate career, he studied connectionist models and was the co-developer of the Cascade-Correlation neural network learning algorithm.  Since 1991, he has worked on the development of the ACT-R cognitive architecture and its applications to artificial intelligence, human-computer interaction, decision-making, intelligent agents, cognitive robotics, network science, and human-machine teaming.  He has recently been involved in defining the Common Model of Cognition, an effort to consolidate and formalize the scientific progress resulting from the 40-year research program in cognitive architectures.

What have we learned about COVID-19 conspiracies as barriers to controlling the pandemic in the US? // Dan Romer, Penn

Abstract: Conspiracies about the pandemic proliferated early in the pandemic and were associated with reduced willingness to engage in social distancing, mask wearing, and intentions to vaccinate. I review research conducted by the Annenberg Public Policy Center using a three-wave panel of 883 respondents from March to November 2020 that assessed conspiratorial thinking and specific COVID conspiratorial beliefs, perceived threats of the disease, fears of vaccination, and reliance on different media information sources as predictors of preventive action and trust in national health authorities, such as the CDC. Findings show that belief in conspiracies has undermined preventive action by different segments of the population, but that conservative media and its users were particularly prone to acceptance of conspiracies, producing a type of “echo chamber” that insulated its users from more mainstream media that supported preventive action. The findings show that wide-ranging exposure to mainstream US media is insufficient to counter the role of politically conservative echo chambers that undermined the consensus needed to confront a major public health emergency such as the COVID-19 pandemic.

Bio: Dan Romer is a psychologist and the research director of the Annenberg Public Policy Center of the University of Pennsylvania, where he conducts policy relevant research on social and individual influences on young people’s health and development. His research focuses on the role of the media, peers, and parents in combination with developmental differences as influences on public health outcomes, such as substance use, unintentional and intentional injury, and mental well-being. With the advent of the pandemic, he has focused on social and personality factors that impede effective decision making for preventing the spread of the coronavirus.

The Impact of informational and persuasive communications on behavior relevant to pandemics // Dolores Albarracin, UIUC

Abstract: In this talk, I describe various considerations about how to model the impact of communications and behavioral interventions on epidemics. During the first part of my talk, I review a spectrum that goes from informational communications to the impact of policy and discuss the likely effect of these programs across the board. I then take a more nuanced approach and distinguish formation from change of behavioral patterns, discuss the need to model delayed effects of communications, and review the likely impact of communications and interventions in interaction with recipients’ behavioral responses to those programs. I conclude by summarizing an agenda of questions to investigate to better model pandemics.

Bio: Dr. Dolores Albarracín, Ph.D. is currently a Professor of Psychology and Business Administration at the University of Illinois at Urbana-Champaign, Beginning July 1, 2021, she will be the Alexandra Heyman Nash University professor at the University of Pennsylvania. Trained in social and clinical psychology, she directs the Social Action Lab and the Health Social Media and Technology Group, where she studies social cognition and action, communication, misinformation, as well as attitudinal and behavioral change.  She applies her theoretical contributions to the domains of HIV, substance use, vaccines, and COVID-19.  Dr. Albarracín received her Ph.D. in Psychology from the University of Illinois at Urbana Champaign, and was previously a tenured professor at the University of Florida and at the University of Pennsylvania.  Her publications include 6 books and about 180 journal articles and book chapters.  She has been editor-in-chief of Psychological Bulletin (2014-2020) and received awards for Outstanding Mid-Career Contributions to the Psychology of Attitudes and Social Influence from the Attitudes Interest Group in the Society of Personality and Social Psychology and Outstanding Contributions to Social psychology from the Society of Personality and Social Psychology, as well as an Avant Garde Award from the National Interest of Drug Abuse. Her research is funded by the National Institutes of Health and the National Science Foundation.

 Networks all around: Social contact patterns and what they can tell us about COVID-19 control and interventions // Dina Mistry, Twitter

Abstract: 

Bio: Dina Mistry is a networks and data scientist at Twitter and formerly an infectious disease modeler at the Institute for Disease Modeling, a division of The Bill & Melinda Gates Foundation. Her work has focused on the questions of who we interact with in the physical world, data driven methods of modeling those diverse contact networks to integrate in infectious disease models, and how social mixing patterns and disease awareness change our understanding of disease spreading dynamics. She received a B.Sc. in Physics & Astronomy from the University of Toronto, and an M.Sc. and Ph.D. in Physics from Northeastern University.

Program Committee

OVERVIEW

The goal of the workshop is to bring together the pandemic research community, discuss the challenges and opportunities associated with access, creation, and maintenance of data and computing resources for pandemic research, and foster collaborations for future research.  The workshop will feature speakers from academia, industry, and government to share their perspectives as data providers, data consumers (domain researchers, health agencies/operations), and data researchers (infrastructure, privacy, security, and ethics).  

Together, we will examine questions including but not limited to the following.  The expected outcome is a better understanding from the community and a workshop report that contributes to the research roadmap of PREPARE.  

• What data can be collected? What are the hurdles to collect the data?
• What data can be shared? What are the hurdles to share the data?  
• What data is most useful?  What are the hurdles to access the data? 
• What technology/infrastructure has worked well, and what is still needed? 
• What policy/operational mechanisms have worked well, and what are still needed?
• What are the key differences (if any) and issues for supporting research use and operational use of the data for decision making?
• What are the key privacy, security, and ethical issues for access and use of the data? 

AGENDA

Each synchronous session (1~1.5 hours) will feature keynote talks followed by a mini-panel. Asynchronous discussion sessions will continue on YouTube after the synchronous sessions.

Day 1, May 12, 11am EDT: Mobility, Search, and Social Network Data

Public Health @ Google // Evgeniy Gabrilovich, Google Health

Abstract: In this talk we will discuss the use of anonymized and aggregated online signals to improve public health.

Bio: Dr. Evgeniy Gabrilovich is a research director at Google Health where he leads the Public & Environmental Health team. Prior to joining Google in 2012, he was a director of research and head of the natural language processing and information retrieval group at Yahoo! Research. Evgeniy is an IEEE Fellow and ACM Distinguished Scientist. He is a recipient of the 2014 IJCAI-JAIR Best Paper Prize and the 2010 Karen Sparck Jones Award for his contributions to natural language processing and information retrieval. Evgeniy has served as a technical program chair for WSDM 2021, WWW 2017, and WSDM 2015. He earned his PhD in computer science from the Technion - Israel Institute of Technology. He also graduated (with extra credit) from the Executive MD training program at Harvard Medical School.

The i-sense response to COVID-19 surveillance using Web search // Ingemar Cox, Vasileios Lampos, University College London

Abstract: Established in 2013, i-sense is a large, multi-institutional, multi-disciplinary research collaboration to develop early warning sensing systems for infectious diseases. One focus of this work has been in digital epidemiology, with a particular emphasis on influenza surveillance. Our work has encompassed disease surveillance at mass gathering, measuring the effectiveness of vaccination programs, and estimating the serial attack rate and serial interval of influenza. Our national influenza surveillance estimates are incorporated into Public Health England’s (PHE) weekly influenza surveillance reports beginning in 2017. In 2020, PHE initially requested that we modify this surveillance methodology to support national COVID-19 surveillance. Later, PHE requested information at a subnational level to identify regional anomalies in COVID-19 prevalence. This talk will describe the solutions we developed, the technical, legal, and ethical issues we needed to address, and reflects on what needs to be done to facilitate a better to response to a future pandemic.

Bio: Ingemar J. Cox is currently a Professor in the Department of Computer Science at University College London (UCL). He is also a Professor in the Department of Computer Science at the University of Copenhagen. He is Head of the Future Media Group at UCL and a deputy director of a £15M EPSRC Interdisciplinary Research Collaboration on "Early Warning Sensor Systems for Infectious Diseases", called i-sense. He is a Fellow of the ACM, IEEE, the IET (formerly IEE), and the British Computer Society. He has been a recipient of a Royal Society Wolfson Fellowship (2002-2007), a 2015 IEEE Signal Processing Society Sustained Impact Paper Award, and the Tony Kent Strix Prize for contributions to information retrieval (2019).

Facebook Data for Good // Alex Dow, Facebook

Abstract: Since 2016, the Facebook Data for Good program has leveraged Facebook data and technology to empower NGOs and researchers for social impact while protecting user privacy. In this talk, I’ll describe several Data for Good offerings related to disease prevention and the Covid19 pandemic, and I’ll discuss how we approach privacy, security, efficacy, and access.

Bio: Alex Dow - I lead the Interaction Science team at Facebook, which is part of the Computational Social Science and Core Data Science groups. We study people’s interactions on and with Facebook products and what effect those products have on them, their relationships, and their community. We leverage this understanding to design new and better products and guide the larger product teams. Our research includes topics such as technology use and well-being, crisis informatics, data for social good, information diffusion, and the structure of online prosocial and antisocial behavior. We also develop the methodologies and technologies that power Facebook Data for Good, a program focused on empowering partners with privacy-preserving data products that strengthen communities and make progress on social issues. I received my PhD in computer science from UCLA, where I did research in artificial intelligence and heuristic search algorithms.

Day 1, May 12, 2pm EDT: Contact Tracing, Syndromic Surveillance, and Social Media

Developing and Deploying Digital Contact Tracing: Lessons learned // Marcel Salathé, EPFL

Bio: Marcel Salathé is a digital epidemiologist working at the interface of health and computer science. He obtained his PhD at ETH Zurich and spent two years as a postdoc in Stanford before joining the faculty at Penn State University in 2010 at the Center for Infectious Disease Dynamics. In 2014, he spent half a year at Stanford as visiting assistant professor. In the summer of 2015, he became an Associate Professor at EPFL where he heads the Digital Epidemiology Lab at the Campus Biotech in Geneva. In 2016, he founded the EPFL Extension School, whose mission is to provide high quality online education in digital technology, and where he is the Academic Director.

Digital Epidemiology and the COVID-19 Pandemic // John Brownstein, Harvard University and Boston Children’s Hospital

Abstract: “Digital Epidemiology and the COVID-19 Pandemic” will address the surveillance, control, and prevention of disease; the development and application of data mining; and citizen science to public health in relation to his work with the COVID-19 pandemic

Bio: John Brownstein, PhD is Professor of Biomedical Informatics at Harvard Medical School and is the Chief Innovation Officer of Boston Children’s Hospital. He directs the Computational Epidemiology Lab and the Innovation and Digital Health Accelerator both at Boston Children’s. He was trained as an epidemiologist at Yale University. Dr. Brownstein is also co-founder of digital health companies Epidemico and Circulation and an ABC News Medical Contributor.

Mobility Networks for Modeling the Spread of COVID-19: Explaining infection rates and informing reopening strategies // Jure Leskovec, Stanford University

Abstract: In this talk I will demonstrate how fine-grained epidemiological modeling of the spread of Coronavirus -- predicting who gets infected at which locations -- can aid the development of policy responses that account for heterogeneous risks of different locations as well as the disparities in infections among different demographic groups. We use U.S. cell phone data to capture the hourly movements of millions of people and model the spread of Coronavirus from among a population of nearly 100 million people in 10 of the largest U.S. metropolitan areas. We show that even a relatively simple epidemiological model can accurately capture the case trajectory despite dramatic changes in population behavior due to the virus. We also estimate the impacts of fine-grained reopening plans: we predict that a small minority of superspreader locations account for a large majority of infections, and that reopening some locations (like restaurants) pose especially large risks. We also explain why infection rates among disadvantaged racial and socioeconomic groups are higher. Overall, our model supports fine-grained analyses that can inform more effective and equitable policy responses to the Coronavirus.

Bio: I am Associate Professor of Computer Science at Stanford University, and investigator at Chan Zuckerberg Biohub. My general research area is applied machine learning for large interconnected systems focusing on modeling complex, richly-labeled relational structures, graphs, and networks for systems at all scales, from interactions of proteins in a cell to interactions between humans in a society. Applications include commonsense reasoning, recommender systems, computational social science, and computational biology with an emphasis on drug discovery.

Day 2, May 13, 11am EDT: Clinical and Epidemiological Data

Improving Pandemic Response: Employing Mathematical Modeling to Confront COVID-19 // Matt Biggerstaff, CDC

Abstract: Modeling has been integral to the COVID-19 response. This talk will review how CDC utilized epidemiological and laboratory data to inform public health decision making and policy development throughout the COVID-19 response, including the use of modeling to improve situational awareness, to synthesize and assess epidemiological characteristics that were important for understanding the use and impact of mitigation measures, and to inform the evidence base for mitigation strategies.

Bio: Dr. Matt Biggerstaff has been with CDC since 2006 and an epidemiologist with the Influenza Division since 2009. In this role, he leads CDC influenza forecasting and modeling activities and works to understand and evaluate how forecasting and mathematical modeling can complement influenza surveillance and inform seasonal and pandemic influenza public health actions. He has also led and supported CDC’s and U.S. government’s interagency modeling and forecasting response to the COVID-19 pandemic since January 2020.

COVID-19: Data Requirements for Clinical and Logistical Modeling // Nathaniel Hupert, Weill Cornell Medicine

Abstract: Reviewing clinically- and operationally-oriented modeling efforts from the earliest days of the COVID-19 outbreak, this talk will highlight important lingering gaps in epidemiological data streams and analysis that may hinder clinical “sense-making,” and therefore may hamper improved responses, for COVID-19 and future pandemics.

Bio: Dr. Hupert is a physician and researcher at Weill Cornell Medical College and Cornell University whose work has focused on public health emergency response logistics, including the COVID-19 pandemic. He currently serves as the translation and policy lead for the Oxford- and Cornell based COVID-19 International Modeling (CoMo) Consortium (https://como.bmj.com). He served for 10 years as Senior Medical Advisor in the US Centers for Disease Control (CDC) Division of Preparedness and Emerging Infections, and was also both a Medical Advisor for the US Hospital Preparedness Program and member of the Scientific Advisory Board of the US National Institute of Health’s Modeling of Infectious Disease Agent Study (MIDAS). He practices internal medicine as a hospitalist at New York City’s Lower Manhattan Hospital, and trained at the University of Pittsburgh and Harvard Medical School.

Day 2, May 13, 2pm EDT: Data Curation and Data Sharing

Clinical Data Network for COVID-19 // Lucila Ohno-Machado, University of California San Diego

Abstract: Data curation and harmonization are critical in observational studies based on Electronic Health Records (EHRs). I will describe how we developed a large clinical data research network based on EHRs from 14 health systems in the US and abroad, including more than 60 million patients, to answer COVID-19 questions. The Reliable Response Data Discovery (R2D2) clinical data network encountered issues related to different mappings to a Common Data Model, as well as other harmonization challenges that were overcome by active participation of data analysts from the various health systems. We used a federated model that protects the privacy of patients, while allowing for the development and evaluation of multivariate predictive models.

Differential Privacy and Pandemic Research // Salil Vadhan, Harvard University

Abstract:  Differential privacy is a framework for enabling statistical analysis of sensitive data while providing strong guarantees of privacy to the individuals represented in the data.  Since its introduction 15 years ago by Dwork, McSherry, Nissim, and Smith, differential privacy has developed a rich mathematical theory and has seen large-scale deployments by the US Census Bureau and technology companies like Google, Apple, and Microsoft.   

In this talk, I will give an introduction to the basic concepts of differential privacy and discuss the state of its transition to practice, including OpenDP, a new community effort to develop trustworthy open-source software for using differential privacy.  I will also share thoughts on the ways in which differential privacy can (and already does) help enable data sharing in support of pandemic research.

Bio: Salil Vadhan is the Vicky Joseph Professor of Computer Science and Applied Mathematics at the Harvard John A. Paulson School of Engineering & Applied Sciences.  Vadhan’s research in theoretical computer science spans computational complexity, cryptography, and data privacy.  Since 2012, he has led the Harvard Privacy Tools Project, a multi-institution research effort on data privacy that brings together computer science, law, social science, and statistics.  Together with Gary King, he directs OpenDP, a new open-source software project around differential privacy. His honors include a Harvard College Professorship, a Simons Investigator Award, and a Guggenheim Fellowship.

Program Committee

Speakers

Summary Report available here

Poster Session Master List (note that posters are sorted based on the name of the first author)

Posters and lightning talks

Keynote Speaker - Professor Sir Roy Anderson FRS FMedSci "Where do people acquire SARS-CoV-2 infection and the challenges in creating herd immunity by mass vaccination"

Watch Sir Roy's complete talk on YouTube 

Sir Roy's slides available here

Opening remarks by Dr. Margaret Martonosi, NSF Assistant Director for CISE and by Dr. Gurdip Singh, NSF Division Director of CNS, can be viewed on our YouTube channel

Program Committee: