Hello dear forum members,
I am seeking your feedback on the question that I have limited knowledge about (i.e., stochastic modeling).
Say, I am working with a variant of standard epidemiological compartment model -- SEIR (Susceptible --> Exposed --> Infected --> Recovered):
In my analysis I focus on the role of within- and between-county mobility in prediction of the new infections. Therefore, I add two components to this (deterministic) model: (1) within-county mobility parameter, denoted as rho, which pre-multiplies betas in E and I equations, and also (2) between-county mobility flows using origin-destination (OD) patterns. Building on prior research and available data science centered publications, I arrive at the following model for the newly exposed people:
where rho(jt) denotes the within-county mobility index. x(kt) denotes the proportion of infected population at county j at time t. m(jk) is the number of people traveling from county k to county j in one unit of time. To express the population flow, I use M by M OD-matrix where M is the number of locations in the simulated area.
My question is: What would be a plausible approach to "convert" this model to a stochastic one?
Your feedback and guidance would be greatly appreciated.
I am seeking your feedback on the question that I have limited knowledge about (i.e., stochastic modeling).
Say, I am working with a variant of standard epidemiological compartment model -- SEIR (Susceptible --> Exposed --> Infected --> Recovered):
In my analysis I focus on the role of within- and between-county mobility in prediction of the new infections. Therefore, I add two components to this (deterministic) model: (1) within-county mobility parameter, denoted as rho, which pre-multiplies betas in E and I equations, and also (2) between-county mobility flows using origin-destination (OD) patterns. Building on prior research and available data science centered publications, I arrive at the following model for the newly exposed people:
where rho(jt) denotes the within-county mobility index. x(kt) denotes the proportion of infected population at county j at time t. m(jk) is the number of people traveling from county k to county j in one unit of time. To express the population flow, I use M by M OD-matrix where M is the number of locations in the simulated area.
My question is: What would be a plausible approach to "convert" this model to a stochastic one?
Your feedback and guidance would be greatly appreciated.
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