Marc Lipsitch, Professor in the Departments of Epidemiology and Immunology and Infectious Diseases at Harvard University, and Director of the Center for Communicable Diseases and Dynamics joins hosts Drs. Dylan George and Caitlin Rivers as they consider data analytics, public health interventions, disease modeling, and the need for the public health community to be at the fore to help implement, design, and execute strategies to manage the COVID-19 response. References: Center for Communicable Disease Dynamics

In this episode of the B.Next Outbreak Analytics & Forecasting Series, Dr. Dylan George sits down with Sean Byrnes, CEO of Outlier.AI, (an In-Q-Tel portfolio company) in a discussion about looking for insights – changes, indicators – from the bottom up rather than asking questions from the top down. Outlier produces a coronavirus tracker, a daily report on Outlier’s findings in the pandemic data. The company is focused on helping organizations identify unexpected changes within their critical business data. References: www.outlier.ai

In this episode of the B.Next Outbreak Analytics & Forecasting series, Drs. Dylan George and Caitlin Rivers are joined by Nita Madhav, CEO of Metabiota, an In-Q-Tel portfolio company working to make the world more resilient to epidemics. The trio explore Metabiota’s use of data to understand and report epidemic preparedness levels across nearly 200 countries, epidemiological modeling to understand disease spread, and a fear index revealing economic impact from coronavirus. References: www.metabiota.com

Data plus analytics (with human intelligence) will yield better informed decision making. Join Dr. Tom Frieden, former Director of the Centers for Disease Control and Prevention and former Commissioner of the New York City Health Department, and now President and CEO of Resolve to Save Lives, an initiative of Vital Strategies, and series hosts Drs. Dylan George and Caitlin Rivers as they explore what data should be collected and analyzed to enable an appropriate public health response to novel coronavirus and other public health challenges.   References: Resolve to Save Lives

Modeling is vital to understanding disease spread and optimal interventions. In this episode of the B.Next Outbreak Analytics & Forecasting series, Dr. Marita Zimmermann, Affiliate Assistant Professor and Research Economist at the Institute for Disease Modeling, discusses with Dr. Dylan George the need for modeling and how it’s used to understand which people are at risk for COVID-19 and determine public health interventions to minimize their risk.   References: Institute for Disease Modeling COVID-19 Reports

In this episode of the B.Next Outbreak Analytics & Forecasting series, Drs. Dylan George and Caitlin Rivers are joined by Dr. Nick Reich, one of the leading researchers who is building operational forecasting capabilities in collaboration with public health agencies. Listen in as they discuss the need for better quantity and quality data to have more high-resolution, real-time data to enable better modeling and guide response efforts, and the development of the CDC COVID-19 Forecasting Hub.    References: COVID-19 Forecast Hub Reich Lab Technology to advance infectious disease forecasting for outbreak management

Today, weather forecasters can spot the development of a tropical storm and use models to help determine its path and strength, which is incredibly important to protect those in its path. In episode four of the B.Next Outbreak Analytics & Forecasting series, Drs. Dylan George and Caitlin Rivers explain why the world needs a disease forecasting center now more than ever, and how it could work to inform decision making among government, policy makers, the public health community, and more to minimize disease spread.   References: How to Forecast Outbreaks and Pandemics

Episode three of the B.Next Outbreak Analytics & Forecasting series features Dr. Steven Riley from Imperial College of London, with Drs. Dylan George and Caitlin Rivers exploring the importance of the infection mortality rate, the value, and need for the public health community to embrace data and use it better.   References: Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions Factors that make an infectious disease outbreak controllable

Episode two of the B.Next Outbreak Analytics & Forecasting series features Dr. Dylan George discussing simulated forecasting in infectious disease with Dr. Jeff Shaman, professor at Columbia University and director of the Climate and Health program at the Mailman School of Public Health. Analyzing the past to develop models may be able to inform the trajectory of infectious disease activity in the near-term future and allows for public health officials to consider real-world intervention strategies to help mitigate the spread of disease.                                                                                                                                                        References: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2) Differential Effects of Intervention Timing on COVID-19 Spread in the United States

In the era of COVID-19, you’ve likely heard the terms outbreak analytics and forecasting being used more frequently. This episode kicks off a special B.Next series that will investigate outbreak analytics and forecasting, how it’s being used to help with pandemic response efforts, and what’s needed to improve these capabilities. Dr. Dylan George, Vice President at IQT’s B.Next, and Dr. Caitlin Rivers, Assistant Professor at the Johns Hopkins Bloomberg School of Public Health and Center of Health Security, lead today’s discussion to provide an overview of how outbreak analytics are useful and critical tools in understanding the risks of the pandemic and how to best mitigate them.   References: Modernizing and Expanding Outbreak Science to Support Better Decision Making During Public Health Crises: Lessons for COVID-19 and Beyond Towards Epidemic Prediction: Federal Efforts and Opportunities in Outbreak Modeling