ClientCity of Gold Coast
Gold Coast City Council needed to identify and describe vulnerable communities within Gold Coast City for the purpose of targeting specialised approaches to support people as part of disaster preparation.
By incorporating multiple demographic information at SA2 level to describe "vulnerability" (such as homelessness, disability, low income households, older lone persons etc), we were able to give council decision makers a clear idea as to where their most vulnerable populations reside and how factors of vulnerability differ geographically.
Our work provided a clear guide to the unique vulnerability profile of different areas, allowing Council to confidently establish a targeted disaster management plan.
Gold Coast City Council engaged .id to find out more about their vulnerable communities. Their goal was to highlight areas that might be particularly vulnerable in times of disaster and understand where they may need to target specialised approaches to support people in preparing for, and in times of, disaster. Defining these communities required .id’s extensive demographic expertise and knowledge of available datasets. By interrogating these datasets, we could tell them where vulnerable communities are located and how different vulnerability indicators are spatially distributed.
Prior to commencing analysis, we identified which demographic indicators would be best used to describe vulnerability within a community. Once the indicators were established, information was obtained at Statistical Area 2 (SA2) level, which roughly related to suburbs. With the available information, analysis was done to assess where each vulnerability indicator is most prominent. As more indicators were examined, we began to see patterns emerging and some parts of Gold Coast City would appear as vulnerable multiple times.
Some of the data which was used to develop a view of vulnerability in Gold Coast City was:
- Homeless population
- People aged 65+
- Lone person households & lone person households aged 65+
- People with a disability
- Disengaged youth
- People in low income households
- People with poor English proficiency
- People with no internet access at home and/or no motor vehicle at household
- Visitors away from home staying in area on Census night.
A full demographic picture of vulnerable communities was developed and assessed. This allowed for us to pinpoint which SA2s/suburbs were most vulnerable, which ones featured as vulnerable in multiple datasets and which ones had specific challenges which made them vulnerable. The same areas tend to appear as hotspots for vulnerable populations across many measures. There were three main groups:
- High density areas with high visitor population
- Medium-high density, lower socioeconomic areas with many renters and culturally diverse populations
- Retirement communities
Any strategies to support vulnerable populations will need to focus on these specific areas.