A1.5 Risk assessment
The objective of risk assessment is to distinguish between very high and low risks so that priorities for risk management can be established.
Once potential hazards and their sources and events have been identified, the level of risk associated with each hazard or event needs to be estimated. Not all hazards will require the same degree of attention, and risk estimation assists in directing attention and resources to those hazards that are most threatening.
In some instances, an initial screening-level risk assessment may be useful to identify broad issues and show where to focus efforts for a more detailed assessment.
Summary of actions
Define a consistent approach to be used for risk assessment.
Evaluate the major sources of uncertainty associated with each hazard and hazardous event and consider actions to reduce uncertainty.
Determine significant risks and establish and document priorities for risk management (based on assessment of maximum and residual risk).
Periodically review and update the risk assessment.
An example of an approach to estimating the level of risk is provided in Tables A1.4, A1.5 and A1.6. These tables have been adapted from AS/NZS 4360:1999 Risk Management and can be modified to meet the needs of an organisation.
Using these tables to guide a risk assessment will quickly reveal the need to define the level of detail required and format to be used for classifying events. Events may arise along a continuum from commonly recurring incidents of minor consequence to rarer incidents with more serious consequences. In some cases, variations of the same type of event can appear at both ends of the spectrum. For example, ‘loss of disinfectant residual in the distribution system’ can have distinctly different meanings. A slight reduction or a loss in parts of a system may be fairly common and have limited health consequences; a total loss of disinfection should be rare but could have potentially severe consequences. There is no set of rules to be followed in using these tables; rather, they are offered as a general guide for the development of a consistent methodology that will be relevant for the water system under study.
Chapter 5 introduces the use of quantitative microbial risk assessment (QMRA) which investigates the likelihood of disease along a risk pathway from the point at which pathogen concentration is quantified (e.g. in a water source) to the receptor (e.g. a consumer of drinking water). QMRA involves quantifying each component of the exposure pathway, together with the estimated health outcome. The outcome of a QMRA is a quantitative assessment of risk and is most applicable for answering quantitative questions such as: “What is safe?” and “How much treatment is required to achieve safety?”. Figure A3.1 in Appendix 3 provides an overview of the QMRA process.
Table A1.4 Qualitative measures of likelihood
A
Almost certain
Is expected to occur in most circumstances
B
Likely
Will probably occur in most circumstances
C
Possible
Might occur or should occur at some time
D
Unlikely
Could occur at some time
E
Rare
May occur only in exceptional circumstances
Table A1.5 Qualitative measures of consequence or impact
1
Insignificant
Insignificant impact, little disruption to normal operation, low increase in normal operation costs
2
Minor
Minor impact for small population, some manageable operation disruption, some increase in operating costs
3
Moderate
Minor impact for large population, significant modification to normal operation but manageable, operation costs increased, increased monitoring
4
Major
Major impact for small population, systems significantly compromised and abnormal operation if at all, high level of monitoring required
5
Catastrophic
Major impact for large population, complete failure of systems
Table A1.6 Qualitative risk analysis matrix — level of risk
A (almost certain)
Moderate
High
Very high
Very high
Very high
B (likely)
Moderate
High
High
Very high
Very high
C (possible)
Low
Moderate
High
Very high
Very high
D (unlikely)
Low
Low
Moderate
High
Very high
E (rare)
Low
Low
Moderate
High
High
Based on the assessment of risk, priorities for risk management should be determined. Maximum risk in the absence of preventive measures should first be determined to identify high-priority risks and provide an indication of worst-case scenarios in the event of failures. Residual risk, determined in conjunction with evaluation of existing preventive measures, should also be assessed to provide information on the effectiveness of existing strategies and the need for improvements.
Uncertainty
The outcome of hazard identification and risk assessment will depend on the level of uncertainty associated with each parameter. Evaluating the major sources and types of uncertainty associated with the hazards can assist in understanding the limitations of the hazard identification and risk assessment as well as how these limitations can be reduced.
Hazard identification and risk assessment need to explicitly consider the sources and types of uncertainty.
Uncertainty can be broadly classified into two types: variability and knowledge uncertainty. By documenting the major sources of variability and knowledge uncertainty that arise for all risks, insights can be gained into the appropriate actions for reducing the role of uncertainty.
Variability represents the true differences that can occur in the specific values of parameters that contribute to a risk — for example, contaminant concentrations over time and space, flows and number of people exposed. Variability contributes to uncertainty because it usually cannot be described completely, due to incomplete or insufficient monitoring data, and there is no single correct answer that will cover all circumstances. For example, the mean temperature over a defined period of time will not represent the high and low extremes and these may be more important depending on what we are seeking to know. Because there is variability in temperature, a decision will need to be made on which value or values to use from the available data, and this choice will carry with it some uncertainty.
Knowledge uncertainty represents an inadequate state of knowledge that exists in the values of parameters measured. Knowledge uncertainty may be reflected in a lack of assurance that methods are accurately measuring what is intended or in a lack of understanding of how a process works. For example, in using methods to count Cryptosporidium oocysts, there may be a degree of uncertainty that the particles being counted are truly Cryptosporidium oocysts. Alternatively, while there may be confidence that the method for counting oocysts is accurate, further uncertainty exists about what the measurement means because it is not known if the oocysts are viable and, if viable, whether they are infective.
There is value in being able to distinguish the relative impacts of variability and knowledge uncertainty. Variability cannot be reduced by more accurate measurement. However, by characterising variability more fully, the nature of a hazard (and thereby the dimensions of the risk) can be better understood. Understanding how variability contributes to uncertainty may lead to actions to change a system to reduce its variability (e.g. increasing reservoir storage times to minimise fluctuations in water quality).
In contrast to variability, knowledge uncertainty can be reduced by better measurement and research. The increased understanding from reducing knowledge uncertainty can provide greater assurance that the preventive measures being considered will achieve their intended purpose. This requirement supports the need for a research capability within the water industry.
Last updated
