Tag Archives: risk mitigation

The Mysterious Mitigation Multiple

You will certainly have heard this statement:

“Investing in mitigation action to reduce disaster consequences shows benefits relative to costs multiplied by a factor of X — where X maybe four or seven, or some other number as high as 15.”

As most simply expressed in 2011 by Tom Rooney, U.S. Congressman for Florida’s 17th District “For every US$1 spent on mitigation, US$4 in post-storm cleanup and rebuilding is saved.” And you may have thought — I wonder how they calculated that? But then life is too busy to go into the details, and the statement — that investment in actions to reduce risk shows a fourfold (or sevenfold) reduction in the cost of disasters is very compelling. It implies you could go out and raise the height of a flood wall or strengthen your house and after a few years you would reap a reward in significantly reduced losses.

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Germanwings 9525: Why didn’t this happen before?

On the tenth anniversary of 9/11, I attended a commemorative meeting at the British Academy in London. A professor of international relations recounted how he watched the horrific scenes of destruction of the World Trade Center in the company of his five year-old daughter. She posed this intriguing question: why didn’t this happen before?

Just a few years before she was born, in December 1994, Algerian terrorists attempted to fly a hijacked plane into the Eiffel Tower. Fortunately, French commandos terminated the hijacking when the plane stopped for refueling. This was a near-miss. The American writer of counterfactual fiction, Philip Roth, observed in his book The Plot Against America that: “the terror of the unforeseen is what the science of history hides.” The destruction of the Eiffel Tower is not an event in terrorism history—just one of numerous ambitious plots that were foiled.

With the current state of historical and scientific knowledge, there are very few unknown hazard events that should take catastrophe risk analysts by surprise. Almost all either did happen before in some guise, or, taking a counterfactual view, might well have happened before. Take for example the great Japanese tsunami and magnitude 9 earthquake of four years ago. It is doubtful that this was the strongest historical earthquake to have struck Japan. The Sanriku Earthquake of 869 may merit this status, based on archaeological evidence of widespread tsunami deposits.

Disasters are rare, and preparedness depends crucially on knowledge of the past. Aviation is the safest mode of travel; there are very few crashes. However there are numerous near-misses, where one or more of the key flight parameters is dangerously close to the disaster threshold. There is a valuable learning curve associated with the lessons gained from such operational experience.

The direct action of the co-pilot in the tragic crash of Germanwings Flight 9525 on March 24, 2015 raises again the question: why didn’t this happen before? As recently as November 29, 2013, it did. A Mozambique Airlines plane flying from the Mozambican capital Maputo to Luanda in Angola crashed, killing 27 passengers and its six crew. The pilot locked himself in the cockpit keeping out the co-pilot. He ignored alarm signals and manually changed altitude levels.

Quite apart from this and other historical precedents for fatal crashes caused by direct pilot action, there must be many more near-misses, where timely intervention has inhibited direct action by pilots suffering from some psychological disorder. The reporting of incidents is a crucial part of aviation safety culture, so is advancing the learning curve. Analysis of such data would contribute to accident risk assessment and subsequent risk mitigation measures.

Measuring Disaster Risk for Global UN Goals

A dispiriting part of the aftermath of a disaster is hearing about the staggering number of deaths and seemingly insurmountable economic losses. Many of the disaster risk reduction programs that implement disaster prevention and preparedness capabilities are helping to create more resilient communities. These worthwhile programs require ongoing financing, and their success must be measured and evaluated to continue to justify the allocation of limited funds.

There are two global UN frameworks being renewed this year:

Both frameworks will run for 15 years. This is the first time explicit numerical targets have been set around disaster risk, and consequently, there is now a more pressing need to measure the progress of disaster risk reduction programs to ensure the goals are being achieved.

The most obvious way to measure the progress of a country’s disaster risk reduction would be to observe the number of deaths and economic losses from disasters.

However, as we have learned in the insurance industry in the early 1990s, this approach presents big problems around data sampling. A few years or even decades of catastrophe experience do not give a clear indication of the level of risk in a country or region because catastrophes have a huge and volatile range of outcomes. An evaluation that is purely based on observed deaths or losses can give a misleading impression of success or failure if countries or regions are either lucky in avoiding (or unlucky in experiencing) severe disaster events during the period measured.

A good example is the 2010 Haiti earthquake, which claimed more than 200,000 lives and cost more than $13 billion. Yet for more than 100 years prior to this devastating event, earthquakes in Haiti had claimed fewer than 10 lives.

Haiti shows that it is simply not possible to determine the true level of risk from 15 years of observations for a single country. Even looking at worldwide data, certain events dominate the disaster mortality data, and progress cannot be measured.

Global disaster-related mortality rate (per million global population), 1980–2013 (From Setting, measuring and monitoring targets for disaster risk reduction: recommendations for post-2015 international policy frameworks. Source: adapted from www.emdat.be)

A more reliable way to measure the progress of disaster risk reduction programs is to use a probabilistic methods, which rely on a far more extensive range of possibilities, simulating tens of thousands of catastrophic events. These can then be combined with data on exposures and vulnerabilities to output metrics of specific interest for disaster risk reduction, such as houses or lives lost. Such metrics can be used to:

  • Measure disaster risk in a village, city, or country and how it changes over time
  • Analyze the cost-benefit of mitigation measures:
    • For a region: For example, the average annual savings in lives due to a flood defense or earthquake early warning system
    • For a location: For example, choosing which building has the biggest reduction in risk if retrofitted
  • Quantify the impact of climate change and how these risks are expected to vary over time

In the long term, probabilistic catastrophe modeling will be an important way to ensure improved measurement and, therefore, management of disaster risk, particularly in countries and regions at greatest risk.

The immediate focus should be on educating government bodies and NGOs on the valuable use of probabilistic methods. For the 15 year frameworks which are being renewed this year, serious consideration should be given on how to implement a useful and practical probabilistic method of measuring progress in disaster risk reduction, for example by using hazard maps. See here for further recommendations: http://www.preventionweb.net/english/professional/publications/v.php?id=39649 

2015 is an important year for measuring disaster risk: let’s get involved.