Mistry, Avinaba2023-11-022023-11-022022-12Thesis 11261https://unbscholar.lib.unb.ca/handle/1882/37522Analysis, prediction and decision support for contagion spread and its associated risk with Ordinary Differential Equation models proved to be challenging in terms of incorporating the underlying heterogeneity of emergent spatio-temporal contact networks of the moving objects. These models reduce the granularity and scope of analysis of possible pharmacological and non-pharmacological intervention measures. To address these limitations, we propose to aggregate population level dynamics by modelling individual-level interactions. To that end, first we introduce an individual level agent-based stochastic contagion simulation modelling framework as a possible solution for adapting to rapidly changing parameters of a contagion including SARS-CoV-2. Second, we propose a spatio-temporal index to extract contact networks from distributed real-world mobility data stores. The framework has been implemented declaratively in R and functionally in Julia and the spatio-temporal index in Python. We conduct thorough experimental evaluation to show the viability and applicability of the proposed approaches.xvii, 132electronicenhttp://purl.org/coar/access_right/c_abf2Biomathematics.Contagious distributions.Computer simulation.master thesisRay, SuprioSeahra, Sanjeev(OCoLC)1426853109Computer Science