Coronavirus: Have we been right to base our response on data models?
Throughout the COVID-19 pandemic, governments have persistently relied upon data modeling and forecasting, to guide policy responses, but at what cost?
Nina Schwalbe currently leads Spark Street Advisors, a think tank focused on strategy, policy and data analysis in public health. Nina has held numerous global health leadership positions including as Managing Director for Policy and Performance at Gavi, the vaccine alliance and Principal Advisor and acting Chief of Health at Unicef, overseeing their health programmes in over 150 countries. She also led the Policy team at Global Alliance for Tuberculosis Drug Development and directed global public health programmes for the Open Society Foundations.
Nina holds degrees from Harvard and Columbia Universities. She was appointed a lifetime member of the Council on Foreign Relations and serves as a Senior Fellow at the United Nations International Institute for Global Health and Chair of Gavi's evaluation advisory committee. She chairs Gavi’s Evaluation Advisory Committee and teaches on the faculty at the Heilbrunn Department of Population and Family Health at Columbia’s Mailman School of public health.
Throughout the COVID-19 pandemic, governments have persistently relied upon data modeling and forecasting, to guide policy responses, but at what cost?
A lack of adequate testing for COVID-19 means only a proportion of cases are being counted in official statistics - making it seem deadlier than it is.