HLTH 6200 Week 6 Hazard Risk Matrix Example

A Risk Matrix for Five County Hazards and the Definitions That Make Its Ordering Defensible

Student Name

Walden University

HLTH 6200: Risk Assessment, Preparedness, and Disaster Mitigation

Instructor Name

Month Day, Year

A Risk Matrix for Five County Hazards and the Definitions That Make Its Ordering Defensible

Purpose

This matrix brings together likelihood and consequence for five hazards on the county's list: riverine flooding, extreme heat, winter storms, tornadoes and failure of the upstream dam. Its purpose is an ordering the county could act on. The matrix itself is a small table; its value lies in the definitions underneath, which determine where each hazard falls. Those definitions are stated before the matrix so that anyone who disagrees with a placement can point to the definition responsible. The jurisdiction is a teaching composite, and its numbers are illustrative.

Likelihood Bands

Likelihood is expressed as the annual chance of an event of the severity described in each hazard's profile. Five bands are used: rare, less than 1% per year; unlikely, 1% to 5%; possible, 5% to 20%; likely, 20% to 50%; and almost certain, more than 50%. Major riverine flooding, with a central estimate near 4% a year and a band of about 1% to 11%, falls in unlikely, and its band reaches into possible. A dangerous heat wave, defined as three or more consecutive days with heat index above the local warning threshold, has occurred in about one year in three recently and falls in likely. A winter storm closing roads county-wide for two or more days is likely. A tornado of moderate or greater strength in the county is possible. Failure of the upstream dam is rare.

Consequence Levels

Consequence is rated in each of the three categories from the consequence estimate, using four levels defined in Table 1. A hazard's overall consequence level is the highest level it reaches in any category. That rule is deliberately conservative: a hazard with severe consequences for continuity of services is not averaged down because its property losses are modest.

Table 1

Consequence Level Definitions by Category

The Matrix

Table 2 places each hazard, with its category ratings shown so the overall level can be checked.

Table 2

Risk Matrix Placement for Five County Hazards (Composite County)

Risk levels follow the grid set for this matrix: severe consequences are high risk at unlikely or above and medium at rare; major consequences are high risk at likely or above and medium at possible.

The Ordering and How Ties Are Broken

Three hazards share the high level, so the matrix alone does not order them. Ties are broken by two stated rules. First, a hazard whose likelihood band reaches a higher band ranks above one whose band does not, because the estimate may be low. Second, among the remainder, life safety consequence ranks above continuity, and continuity above property. Applying those rules gives this order: riverine flooding first, because its likelihood band reaches possible and its continuity consequence is severe; extreme heat second, because its major consequence falls on life safety; winter storms third, because their major consequence falls on continuity; tornadoes fourth; and dam failure fifth, with a flag explained below.

What the Matrix Hides

Risk matrices have known weaknesses. They can assign the same rating to risks that differ greatly in expected loss, compress wide ranges into a few categories and, in some cases, order risks incorrectly (Cox, 2008). This matrix shows those weaknesses in the dam failure row: a catastrophic but rare event lands at medium, alongside a tornado, though the two are nothing alike. To guard against that, the paper keeps the category ratings visible beside each placement, rather than reporting only the colored cell, and flags dam failure for separate attention because its consequences would be severe in every category. A decision maker reading only the risk level column would miss that; one reading the whole table would not.

How Sensitive the Ordering Is

Two changes in assumptions would alter the ordering. If the flood likelihood estimate were taken from the low end of its band, flooding would remain in unlikely and stay high risk because of its severe continuity consequence, so its place is robust. If the heat definition required five consecutive days instead of three, heat would drop to possible and fall to medium, below winter storms. That sensitivity matters because the county has little local data on heat events, so the heat placement rests on a definition chosen by the planner rather than on a long record. The paper flags it for review once better surveillance data exist.

The combining rule also matters. If overall consequence were the average of the three categories rather than the highest, flooding would fall from severe to major, and winter storms and heat would tie with it. The conservative rule was chosen because averaging would hide the severe continuity consequence of a flood, the very information decision makers most need.

What the Ordering Is For

The ordering guides where mitigation analysis begins, not what the county must fund. Federal guidance for hazard assessment asks jurisdictions to describe risks in ways that support capability targets and planning decisions (Federal Emergency Management Agency, 2018), and an ordering with stated definitions does that. The next weeks examine mitigation options for the top-ranked hazard, riverine flooding, and return to the others in the priority memo at the end of the term. In the classic formulation, risk is a set of scenarios, each paired with a probability and an outcome (Kaplan & Garrick, 1981), and the matrix is only a compressed view of that fuller picture.

References

Cox, L. A. (2008). What's wrong with risk matrices? Risk Analysis, 28(2), 497-512. https://doi.org/10.1111/j.1539-6924.2008.01030.x

Federal Emergency Management Agency. (2018). Threat and hazard identification and risk assessment (THIRA) and stakeholder preparedness review (SPR) guide: Comprehensive Preparedness Guide (CPG) 201 (3rd ed.).

Kaplan, S., & Garrick, B. J. (1981). On the quantitative definition of risk. Risk Analysis, 1(1), 11-27. https://doi.org/10.1111/j.1539-6924.1981.tb01350.x