Methodological challenges in the translation of data and evidence into policy during COVID-19

Date: Friday 21 May 2021, 4.00PM
Other Event (non-RSS)


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A virtual event, hosted by The JBC-Turing-RSS Laboratory.

Introduced by Dr Johanna Hutchinson, Director of Data and Data Science at the Joint Biosecurity Centre, and by Professor Peter Diggle, Technical Director of the Turing-RSS Laboratory.

Albert Icksang Ko is Professor of Epidemiology and Medicine and Department Chair of Microbial Diseases at the Yale Schools of Public Health and Medicine

Click HERE for full information and to register

 

In this visiting lecture, Professor Ko will discuss the challenges in developing data-driven policy during the COVID-19 pandemic.

He will draw on his experience as lead scientific advisor to the US state of Connecticut and discuss the barriers to framing policy questions that can be addressed by data and evidence, to obtaining actionable data during an emergency response, and to communicating evidence to decision makers.

Finally, he will use the example of post-licensure vaccine effectiveness studies during the current COVID-19 resurgence in Brazil to illustrate the gaps between data collection, analytic methods and policy and identify lessons learned for present and future health challenges.

 

Professor Albert Ko

Department Chair and Professor of Epidemiology (Microbial Diseases) and of Medicine (Infectious Diseases) at Yale School of Medicine

Professor Peter Diggle

Distinguished Professor, CHICAS, Lancaster University and Steering Group Mentor, RSS COVID-19 Taskforce