2013/10/06 by B. Morin, Benjamin R. Morin, Morin, Benjamin R.
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · #COVID-19 epidemiological studies #Evolution and Genetic Dynamics #FOS: Biological sciences #Mathematical and Theoretical Epidemiology and Ecology Models #Populations and Evolution (q-bio.PE) #q-bio.PE
paper · pdf · doi:10.48550/arxiv.1310.1648
arxiv created 2013/10/06 · openalex publication_date 2013/10/06 · arxiv updated 2013/10/08 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Variable individual response to epidemics may be found within many contexts in the study of infectious diseases (e.g., age structure or contact networks). There are situations where the variability, in terms of epidemiological parameter, cannot be neatly packaged along with other demographics of the population like spatial location or life stage. Transport equations are a novel method for handling this variability via a distributed parameter; where particular parameter values are possessed by various proportions of the population. Several authors (e.g., Kareva, Novozhilov, and Katriel) have studied such systems in a closed population setting (no births/immigrations or deaths/emigrations), but have cited restrictions to employing such methods when entry and removal of individuals is added to the population. This paper details, in the context of a simple susceptible-infectious-recovered (SIR) epidemic, how the method works in the closed population setting and gives conditions for initial, transient, and asymptotic results to be equivalent with the nondistributed case. Additionally, I show how the method may be applied to various forms of open SIR systems. Transport equations are used to transform an infinite dimensional system for the open population case into a finite dimensional system which is, at the very least, able to be numerically studied, a model with direct inheritance of the distributed parameter is shown to be qualitatively identical to the nondistributed case, and finally a model where disease results in sterilization is fully analyzed.