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A spatial interpretation of Australia's COVID-vulnerability
Dávid Karácsonyi1,2, Sigurd Dyrting1, Andrew Taylor1
1Northern Institute, Charles Darwin University Ellengowan Dr, Casuarina, Northern Territory, 0810, Australia.
International Journal of Disaster Risk Reduction : IJDRR
|October 31, 2022
Summary
The COVID-19 pandemic revealed social, demographic, and spatial vulnerabilities. A new model predicts risks using demographic and economic indicators, considering Australia
Area of Science:
- Disaster Sciences
- Public Health
- Sociology
Background:
- The COVID-19 pandemic highlighted systemic, demographic, and spatial vulnerabilities.
- Social vulnerability is defined as the risk of exposure to hazard impacts within societal structures.
- Understanding social vulnerability is crucial for effective disaster response and mitigation.
Purpose of the Study:
- To develop a risk prediction model for the COVID-19 pandemic based on social vulnerability.
- To identify and analyze demographic and economic vulnerabilities exacerbated by the pandemic and lockdowns.
- To explore the role of spatiality in pandemic disaster response, particularly in Australia.
Main Methods:
- Development of a risk prediction model using two composite indicators of social vulnerability.
- Analysis of demographic factors (aging, race) and economic impacts of lockdowns.
- Conceptualization of social vulnerability within the context of uneven spatial population distribution in Australia.
Main Results:
- The model integrates demographic and economic vulnerability indicators.
- Spatial factors, including isolation and connectivity, were identified as significant vulnerabilities.
- The study highlights the uneven impact of the pandemic across different spatial contexts in Australia.
Conclusions:
- Social vulnerability is a critical factor in understanding and managing pandemic crises.
- The developed model provides insights into predicting risks associated with demographic and economic factors.
- Spatial considerations are essential for a comprehensive approach to pandemic disaster science.
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