Spatial contagions, such as pandemics, opinion polarisation, infodemics, and civil unrest, exhibit nontrivial spatiotemporal patterns and dynamics driven by complex human behaviours and population mobility. Here we propose a concise generic framework to model different contagion types within a suitably defined contagion vulnerability space. This space comprises risk disposition, considered in terms of bounded risk aversion and adaptive responsiveness, and a generalised susceptibility acquisition. We show that resultant geospatial contagion configurations follow intricate Turing patterns observed in reaction-diffusion systems. Pattern formation is shown to be highly sensitive to changes in underlying vulnerability parameters. The identified critical regimes (tipping points) imply that slight changes in susceptibility acquisition and perceived local risks can significantly alter the population flow and resultant contagion patterns. We examine a case study of the COVID-19 pandemic in Australia, demonstrating that the observed geo-spatial pandemic spread generated Turing patterns in accordance with the proposed model. The paper describing the framework, model and results: Jamerlan, C. M. and Prokopenko M. 2024. Bounded risk disposition explains Turing patterns and tipping points during spatial contagions. R. Soc. Open Sci. 11: 240457. http://doi.org/10.1098/rsos.240457 Please cite this paper and references below when using the model.