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We propose a newstochastic model of infectious disease propagation. This model tracks individual outcomes, but does so without needing to create connectivity graphs for all members of the population. This makes the model scalable to much larger populations than traditional agent-based models have been able to cope with, while preserving the impact of variability during the critical early stages of...
Epidemic modeling is dominated by systems models—so-called SIR models—that describe the spatio-temporal and network dynamics of disease outbreaks. Reed-Frost, discrete-time, stochastic transmission-chain models have also been important; but, increasingly, epidemiological modelers are turning to agent-based (ABM) approaches that permit the inclusion of individual-specific characters, which may relate...
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