Computational modelling of spatial contagion dynamics: epidemics, infodemics and socio-economic turbulence
Access status:
Open Access
Type
ThesisThesis type
Doctor of PhilosophyAuthor/s
Jamerlan, Ma ChristinaAbstract
Contagions, ranging from epidemics to infodemics and socio-economic turbulence, are often studied in isolation despite exhibiting analogous spatiotemporal transmission dynamics. In this thesis, we develop a unifying multi-city framework for modelling spatial contagions, integrating ...
See moreContagions, ranging from epidemics to infodemics and socio-economic turbulence, are often studied in isolation despite exhibiting analogous spatiotemporal transmission dynamics. In this thesis, we develop a unifying multi-city framework for modelling spatial contagions, integrating contagion dynamics, risk disposition, population mobility, and resource distribution. By extending classical multi-city epidemic models, we introduce dynamically adaptive risk-driven mobility flows and examine how population mobility, susceptibility acquisition, risk disposition and effectiveness of distributed resources jointly shape contagion severity and resultant spatial patterns across multiple contagion types. Our results show that small changes in risk disposition or resource effectiveness parameters can lead to substantial shifts in contagion dynamics, revealing phase transitions and tipping points in resultant contagion patterns. We introduce a novel metric, the average cluster intensity, to quantify mean contagion cluster intensity and measure emergent phenomena, such as shield immunity. In some contagion types, altruistic interactions between inoculated and affected individuals reduce overall contagion severity and fragment spatial spread. This shielding effect is most pronounced in socio-economic turbulence, moderate in epidemics, limited in social myth spreading, and not observed in polarisation dynamics. Our case studies using Australian data on COVID-19 incidence, crime records, conflict exposure during protests, and real estate activity confirm that Turing-like patterns are observed empirically in concordance with our model's predictions. Overall, this thesis provides a robust framework for understanding how risk disposition, susceptibility, mobility, and resource distribution collectively drive spatial contagion dynamics. Findings may guide policymakers in designing interventions, allocating resources, and mitigating contagion impacts across diverse societal domains.
See less
See moreContagions, ranging from epidemics to infodemics and socio-economic turbulence, are often studied in isolation despite exhibiting analogous spatiotemporal transmission dynamics. In this thesis, we develop a unifying multi-city framework for modelling spatial contagions, integrating contagion dynamics, risk disposition, population mobility, and resource distribution. By extending classical multi-city epidemic models, we introduce dynamically adaptive risk-driven mobility flows and examine how population mobility, susceptibility acquisition, risk disposition and effectiveness of distributed resources jointly shape contagion severity and resultant spatial patterns across multiple contagion types. Our results show that small changes in risk disposition or resource effectiveness parameters can lead to substantial shifts in contagion dynamics, revealing phase transitions and tipping points in resultant contagion patterns. We introduce a novel metric, the average cluster intensity, to quantify mean contagion cluster intensity and measure emergent phenomena, such as shield immunity. In some contagion types, altruistic interactions between inoculated and affected individuals reduce overall contagion severity and fragment spatial spread. This shielding effect is most pronounced in socio-economic turbulence, moderate in epidemics, limited in social myth spreading, and not observed in polarisation dynamics. Our case studies using Australian data on COVID-19 incidence, crime records, conflict exposure during protests, and real estate activity confirm that Turing-like patterns are observed empirically in concordance with our model's predictions. Overall, this thesis provides a robust framework for understanding how risk disposition, susceptibility, mobility, and resource distribution collectively drive spatial contagion dynamics. Findings may guide policymakers in designing interventions, allocating resources, and mitigating contagion impacts across diverse societal domains.
See less
Date
2026Rights statement
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
Faculty of Engineering, School of Computer ScienceAwarding institution
The University of SydneyShare