Part 1 - Understanding risk |
Risk can be described and expressed in a number of ways. One standard method is to count all the people exposed to a particular risk and divide this number by the number of people who have actually experienced the hazard over a defined time span. If the number of people who travel by train in any one year is ten million and ten people are killed on average each year, then the annual risk of being killed in train travel is one in one million. These simplified quantifications of risk raise more questions than they solve. Is the risk spread equally over the ten million people or are some people more at risk than others? Did some special type of failure cause all 10 deaths? Are longer trips more hazardous than shorter trips?
Not all risks define the people exposed to them as clearly as train travel. When trying to quantify risks to the population from, for example, chemical release from an industrial plant, the risk is obviously highest for those who live nearest, and less for those who live further away. If 20 people required hospital attention from a particular chemical release, then to quantify the risk from a similar event in the future, that 20 should be divided by the total population exposed - but where should the line be drawn to define the population exposed? Five kilometers from the plant? A hundred? The whole country? Similarly with risk assessment from natural hazards, the definition of the population exposed affects the assessment of that risk. There is no one standard way of defining the population exposed to a risk, so statistical expressions of risk need to be carefully defined and explained for them to be useful.
Figure 1 - Probability of an individual dying in any one year^{5}
Smoking 10 cigarettes a day |
One in 200 |
All natural causes, age 40 |
One in 850 |
Any kind of violence or poisoning |
One in 3,300 |
Influenza |
One in 5,000 |
Accident on the road (driving in Europe) |
One in 8,000 |
Leukemia |
One in 12,500 |
Earthquake, living in Iran |
One in 23,000 |
Playing field sports |
One in 25,000 |
Accident at home |
One in 26,000 |
Accident at work |
One in 43,500 |
Floods, living in Bangladesh |
One in 50,000 |
Radiation working in radiation industry |
One in 57,000 |
Homicide living in Europe |
One in 100,000 |
Floods, living in Northern China |
One in 100,000 |
Accident on railway (travelling in Europe) |
One in 500,000 |
Earthquake, living in California |
One in 2,000,000 |
Hit by lightning |
One in 10,000,000 |
Wind storm, Northern Europe |
One in 10,000,000 |
Gross levels of risk, taking the number of deaths from that cause, divided by some estimate of the population exposed can give the type of approximate ranking of probability of death to an individual by different causes, as shown in figure 1. This gives some idea of how disaster risk to an individual compares with other risks, and how disaster risk may vary from place to place. The probability of being killed in an earthquake in Iran during any one year for example, is obtained from the total number killed by earthquakes in Iran this century (120,000), divided by 90 years. This gives an average of 1,300 people killed annually. The population of Iran (currently 55 million) averaged over the past ninety years is less than 30 million, so the average probability of being killed in an earthquake is given as one in 23,000.^{6} Of course not everyone in Iran is equally at risk. Some parts of Iran are more seismic than others, so those living in the seismic zones are more at risk. Those living in poorer quality houses are more at risk than people who live in strong seismically-resistant houses. But to define the exact seismic zones and the exact number of people in houses of different seismic resistance requires much more detailed analysis. Some of these types of analysis are described in examples given later in this module.