Abstract:  ?Agent-based modeling vs. Equation-based modeling of Endemic infections?

Submitted by Thomas Riggs, MD, MSc

Vaccine trials involving day-care centers where entire units are randomly assigned to vaccination vs. no vaccination are often used to assess transmission effects of vaccines.  To estimate statistical power in such trials, one needs a prior estimate of both prevalence and the probability distribution of the number infected within the unit.  Agent based modeling using Ascape was contrasted with equation based modeling using the Kolmogorov equations to estimate the prevalence of endemic infection levels in small transmission units.  Using the equation based approach and assuming constant values for the (i) outside force of infection, (2) the recovery time from infection and (3) the internal contact rate, the equilibrium values for prevalence and for the probability distribution of the number of infected within the unit were calculated.

An agent-based model based on keeping the same three parameters constant and matching prevalence levels and outside force to those of the equation-based models demonstrated that the probability distributions matched very closely for the two methods.  In the agent-based model, the three parameters were varied individually in a range that would cause mean prevalence to vary ( 5-10 % at the extreme parameter values.  When either the outside force of infection or the contact rate was randomly varied, the mean prevalence was the same and the probability distributions were unchanged compared with a constant value for these two parameters.  However, the same degree of change in the recovery time introduced a significant bias to decrease the mean prevalence.  Precise estimation of the recovery time appears to be more critical than estimation of the outside force of infection or the contact rate for modeling prevalence and distribution of outcome for small transmission units.