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This paper studies a novel approach for approximating the behavior ofcompartmental spreading processes. In contrast to prior work, the methodsdeveloped describe a dynamics which bound the exact moment dynamics, withoutexplicitly requiring a priori knowledge of non-negative (or non-positive)covariance between pairs of system variables. Moreover, we provide systemswhich provide both upper- and lower- bounds on the process moments. We thenshow that when system variables are shown to be non-negatively (ornon-positively) correlated for all time in the system's evolution, we mayleverage the knowledge to create better approximating systems. We then applythe technique to several previously studied compartmental spreading processes,and compare the bounding systems' performance to the standard approximationsstudied in prior literature.

Deterministic Bounding Systems for Stochastic Compartmental Spreading Processes