In Russia, for example, “data-based” estimates have suggested that the true death count may be twice as high as the official count, and in India the assessed gap is even larger. In fact, in many countries there is uncertainty about the most basic issue-how many people died as a result of COVID-19 infection. The ability to rapidly obtain high quality data and to analyze it, in a timely manner, cannot be taken for granted. But in any case, a volatile reality as manifested in crisis times requires a well-founded and robust approach for data-driven decision making. Depending on the state of emergency, tools being used and depth of analysis will vary. In Israel, infections waned following a tight lockdown, but returned to much higher levels several months after most restrictions were removed.Īs a pandemic unfolds, new dilemmas arise.
For example, Britain adopted tight lockdowns only after a limited social distancing campaign was accompanied by heavy infection and burden of disease. Countries veered from one policy to another. In reality, specific policy choices varied widely, from the airtight seal in New Zealand to the lockdowns in Europe and the laisse faire attitude of Brazil. Specifically, decision makers should seek actionable information coming from robust and rigorous analysis of accurate and relevant data. Ideally, such policy decisions should be based on properly analyzed data and subject knowledge. Faced with a crisis at a scale not experienced in the last century, policy makers were required to make difficult decisions on a daily basis. The COVID-19 pandemic posed significant challenges to the health, economic and social systems around the globe. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making. The meeting was designed to provide a forum for exchange of views on the profession’s role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making.
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