Disaster Preparedness Plan - Awareness
English: % of population aware of the key [specify the hazard] preparedness measures set out in the disaster preparedness plan
French: % de la population consciente des mesures de préparation au [spécifiez le danger] clés listées dans le plan de préparation aux catastrophes
Portuguese: % da população consciente das principais medidas de preparação para [especifique o risco] estabelecidas no plano de preparação para desastres
Czech: % obyvatelstva s povědomím o hlavních opatřeních v případě [určete daný hazard] stanovených plánem připravenosti
What is its purpose?
The indicator measures the extent to which the at-risk population is aware of the most important preparedness measures set out in the preparedness plan for a specific type of a hazard, such as floods or earthquake - a crucial pre-condition for the preparedness plan's effectiveness.
How to Collect and Analyse the Required Data
Determine the indicator's value by using the following methodology:
1) Together with the local stakeholders responsible for the preparedness plan's implementation, select a limited number (3-6) of the most important preparedness measures that every at-risk household should be aware of and follow.
2) Set the minimum number (or types) of preparedness measures the respondent must be aware of to be considered as having "appropriate awareness" (for example, to know "at least 3 out of 5 measures" or to know "the two most important and at least one additional measures").
3) Conduct qualitative household survey asking a representative sample of adult respondents: "What are the most important measures the local households should take to prepare themselves for [specify the hazard]?" After the respondent replies, keep probing: "Is there anything else the households should do to prepare themselves for [specify the hazard]?"
4) To calculate the indicator's value, divide the number of respondents aware of the minimum number (or types) of preparedness measures by the total number of interviewed respondents. Multiply the result by 100 to convert it to a percentage.
Disaggregate the data by gender, age groups and specific vulnerable groups.