Ebola, Statistics, and What Pandemic Science Can Teach Markets

About this episode

The episode discusses the challenges of modeling pandemic risk in markets, featuring insights from Dr. Ben Swallow on Ebola and statistical methods.

The Democratic Republic of Congo is in the middle of its 17th Ebola outbreak since 1976 and the WHO has declared a public health emergency of international concern. There are no approved vaccines. No approved treatments. Hundreds of suspected cases emerged before the outbreak was even confirmed. And the surveillance infrastructure needed to track it is operating in an active conflict zone. For reinsurers and ILS investors, pandemic risk has always been the peril that's hardest to model, hardest to price, and hardest to transfer. The triggers don't work and the data is noisy.. And the market has largely walked away from the problem since COVID. My guest today has spent his career working on exactly that problem from the science side. Dr. Ben Swallow is a lecturer in statistics at the University of St. Andrews, where he works at the intersection of Bayesian inference, uncertainty quantification, and epidemic modeling. He co-led the uncertainty quantification effort for the Scottish government during COVID. He's worked on Ebola outbreak analysis in West Africa. And he's currently part of the Isaac Newton Institute's program on pandemic preparedness. Subscribe to Risk Market News

People in this episode

Host: Risk Market News

Guest: Dr. Ben Swallow

Topics covered

• Ebola
• pandemic science
• market risk
• epidemic modeling
• statistical analysis

Keywords

• Ebola
• pandemic risk
• statistical modeling
• Bayesian inference
• epidemic preparedness

Mentioned in this episode

Organizations: University of St. Andrews, WHO, Scottish government, Isaac Newton Institute

Places: Democratic Republic of Congo

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