Lessons from COVID-19: Data, Trust, and Decision-Making in Times of Crisis

The COVID-19 pandemic posed an unprecedented challenge to health systems, economies, and societies, requiring decision-makers to act under conditions of uncertainty, time pressure, and incomplete information. This lecture will discuss key lessons that can be drawn from Israel’s experience in responding to the pandemic, with a focus on the role of data, models, statistical thinking, and interdisciplinary collaboration in shaping public policy.The lecture will examine how information collected during the pandemic informed decision-making under rapidly changing conditions. Alongside the successes, we will discuss the challenges that emerged: data quality and availability, gaps in access to information, communication between experts and decision-makers, and the need to build public trust around data-driven decisions. One central lesson is that preparedness for a crisis does not begin during the crisis itself, but during routine periods: by building data infrastructures, establishing ongoing channels of collaboration between experts and government ministries, and developing a shared language between science, policy, and the public. The aim of the lecture is to offer a forward-looking perspective on how the lessons of COVID-19 can be used to better prepare for future crises in health, climate, security, and society.