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How mathematical models help us predict epidemics and weather

Thursday, July 2nd 2020, 7:00 pm - Understanding and predicting the effects of COVID-19 is perhaps the most important and difficult forecast of our time.

Predicting the future is our job and there is a lot going on underneath the hood to make that happen. Science and math are the foundations of our predictive power. In science, our “crystal ball” takes the form of a mathematical model, which uses numbers to describe the relationship between things, such as how air moves from high to low pressure creating the wind.

The idea is that if we know what's happening now and our model is a good approximation of reality, then we can predict the future. It sounds easy, but is really hard in practice. That’s the case not only in meteorology, but in other fields such as epidemiology.

The latest episode of our long-form series/podcast Viral Weather is an intriguing discussion of the parallels and differences between predicting the weather and forecasting the worst pandemic in over 100 years.

Being part of this episode was fascinating. It's an inside look at infectious disease epidemiology, and the work going on to predict what could happen next. Understanding and predicting the effects of COVID-19 is perhaps the most important and difficult forecast of our time.

Here are three key takeaways from the Viral Weather panel discussion between myself, Dr. Ashleigh Tuite (Epidemiologist, Mathematical Modeler and Assistant Professor at the University of Toronto), Kim Court (Director, Catastrophe Exposure Analysis at Northbridge Financial Corporation in Vancouver), and our host, Chris St. Clair:

  1. No mathematical model is perfect. A blend of models called an ensemble will often give a more accurate forecast of the weather or how a disease will spread.
  2. Meteorologists have a huge advantage in not having to predict human behaviour because it doesn’t influence the forecast. With epidemiology, people's behaviour is probably the biggest uncertainty in predicting the future.
  3. The math describing the spread of infectious disease is ‘relatively’ simple in comparison to the fluid dynamics that underpin meteorology. The devil for epidemiologists is having to make so many assumptions about unknowns: How infectious is the virus? How does it spread? How will governments and people react?

I found myself wanting to ask the obvious question: “What will happen next?” But I caught myself, knowing the internal eye-roll I do when asked the same question about the weather.

There isn’t one perfect answer to such a complex problem -- but modelling and expertise can give us a lot of insight. So the next time you're asking someone to predict the future -- whether that's your investment advisor or local meteorologist -- ask these questions: What is the most likely outcome? What scenarios are possible? What low probability outcome concerns you? What is your confidence in this forecast?

These questions won't get the short answer -- but they will get you the best answer.

Thumbnail courtesy: Markus Spiske (via Unsplash)

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