Tag Archives: RMS LifeRisks

The Coronavirus Outbreak: Part Two – Self-Isolation and Quarantine

The village of Eyam in Derbyshire, central England, was unlucky to discover that the pandemic, then raging 150 miles (226 kilometers) to the south in London, had arrived on its doorstep.  

The pandemic was the plague – the year was 1665. The disease had reached Eyam through the delivery of flea-ridden cloth from London to the local tailor, who would then made clothes for the villagers. The fleas carried the plague bacterium and the recipient of the cloth was the first to die.

Within three months another 41 villagers had perished. By spring 1666 a newly appointed rector proposed that, for the sake of other plague-free towns in the Peak District region, the village should self-isolate. A local Earl offered to guarantee food for the town (supplied on a rock at the edge of the village, paid with coins immersed in vinegar – see location below). In June 1666 the villagers reluctantly agreed. Over the summer the plague returned with a vengeance and there were five or six deaths each day. Eventually one third of the population died. But the nearby towns stayed plague free.

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The Coronavirus Outbreak: Part One – Modeling “Spotting”

Since 2017, in modeling the threat from wildfire on communities in California, the significant new RMS innovation has been in capturing the process of “spotting” (i.e. identifying new outbreaks of fire far from the fire-front). Strong dry winds bring swarms of glowing embers from a raging wildland fire, which can travel long distances. Should these embers settle on shingle roofs, wooden patios or a leaf-filled plastic gutter, a fire will start. Unchecked, the fire will consume a house.

In high-density housing suburbs, wind-driven fire can spread from building to building and consume a whole neighborhood – as happened in the city of Santa Rosa in 2017. And the only way to stop an outbreak is to intervene: to extinguish each ember-ignited fire before it can spread.

Modeling ember ignitions requires sampling the speed and direction of the wind and also anticipating what proportion of fire-starts get extinguished before they can spread. Still it only takes one unchecked fire to burn down the town.

This same process, in modeling “spotting”, is key to anticipating the spread of the new coronavirus into western Europe and North America.  

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The Art and Science of Loss Reserving

The recent allegations against General Electric (GE) read like a financial thriller: Bernie Madoff whistle-blower teams up with anonymous hedge fund to expose the alleged financial misdeeds of one of the most recognizable brands in American history.

But most people’s interest in this story ends abruptly when they hear about the crux of the allegations, which can be summarized in eight words: “… inadequate loss reserves for long term care (re)insurance.” This topic is esoteric at best, and sleep-inducing at worst. It’s impossible to spin into media clickbait. And it’s clear that media is struggling to describe exactly what Harry Markopolos, the whistle-blower, is alleging in his 175 page report

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