The Western Cape of South Africa is a dynamic province that is disaster-prone, in particular the vulnerable urban communities in and around its environs. Such communities are more vulnerable to wildfire, flooding, drought, pandemic and other natural and human-made disasters because of poverty and, consequently, poor living conditions such as overcrowding and non-understanding of community resilience. The inability of these communities to understand community resilience and withstand adversities affects the sustainability of initiatives to develop them. This study aims to identify the mechanisms influencing the level of understanding of community resilience in a vulnerable community and to contribute to the understanding of community resilience to disaster risk. Fieldwork was conducted in an informal settlement in the Western Cape. The research study was conducted in two cycles of data collection and analysis (cycle 1 and cycle 2). Data in the form of observation notes, document analysis and interviews were analysed using grounded theory principles. Ten inter-related variables or mechanisms emerged from the analysis. The theoretical model consists of four reinforcing (R) feedback loops (R1, R2, R3 and R4), respectively, which explain how the understanding of community resilience in the informal settlement maps on to the relative achievement systems archetype. Negative reinforcing behaviour would explain the lack of understanding of community resilience, while positive reinforcing behaviour indicates how an understanding of community resilience develops. In addition, the variable with the leverage to improve the mechanisms influencing the understanding of community resilience was found to be the ‘level of public education and public awareness’ of community resilience. The theory of how these variables behave in context was represented as a qualitative system dynamics model.

Onyeagoziri, O.J., Shaw, C. & Ryan, T., 2021, 'A system dynamics approach for understanding community resilience to disaster risk', Jàmbá: Journal of Disaster Risk Studies 13(1), a1037. https://doi.org/10.4102/jamba.v13i1.1037