Angus Lamond and Michael Levitt discussed their approaches to analysing COVID-19 data during the pandemic. Angus shared his experience analysing data from the Diamond Princess cruise ship, which helped him estimate the total level of the catastrophe. Levitt emphasized the importance of believing data and identifying problems with data collection, rather than assuming exponential growth. He also presented data from a European website showing that COVID-19 mortality rates are higher among older populations, with 50% of COVID-related deaths occurring among those over 85.
Speaker:
🎙️ Michael Levitt, Professor of Biophysics at Stanford Medicine
EMBL Scientific Advisory Committee (SAC) Member, 1983-1988
Nobel Prize in Chemistry (2013)
Summary:
0:00 Analyzing Data During the COVID-19 Pandemic
• Michael Levitt shares his analysis of COVID-19 data, highlighting a familiar flattening curve observed in China and New Zealand.
• Despite initial concerns, Chinese COVID-19 data is surprisingly accurate, showing consistent patterns globally.
• Analysis includes extrapolating total catastrophe levels from Diamond Princess data, considering infection rates and population density.
6:00 COVID-19 Mortality Rates and Age Distribution
• Discussion on COVID-19 deaths in Wuhan and Europe, noting similarities in mortality rates.
EuroMOMO database shows excess deaths in Europe, with a peak in 2020 due to COVID-19.
• Mortality rates by age group: Half of the deaths are in individuals over 85, with only 8% in those under 65.
• Michael Levitt emphasises the importance of platforms like Twitter for sharing data and ideas, despite its limitations, and encourages ongoing discussion at @MLevitt_NP2013