Temporal and probabilistic forecasts of epidemic interventions
Boudreau, Mariah
Boudreau, Mariah
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Abstract
In this work, time-dependent probability generating functions (PGFs) model a stochastic branching process of disease spread over a network of contacts where public health interventions are introduced over time. We define a general transmissibility equation to account for varying contact patterns and percentage of the population immunized. The resulting framework showcases a temporal and probabilistic analysis of an intervention's impact on disease spread, which match continuous-time stochastic simulations. To aid decision makers, we define several metrics over which these forecasts can be compared. Our work provides a more detailed short-term forecast of disease spread and comparison of intervention strategies.
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Graduate
Date
2023-01-01