Effects of minimum epidemic and population sizes on a global epidemic in simulations of final size data
Abstract
The stochastic SIR household epidemic model is well discussed in [2], [3] and [4]. The work of [1] also proposed maximum likelihood based algorithm for its inference by assuming independence of epidemic in each household, contrary to the dependency assumption in [4].
Using simulations, we examined the need for an appropriate choice of cut-o between small and large epidemics often referred to as minimum epidemic size, using rejection sampling, for a global infection to occur and then compared the estimates of the model parameters over a range of theoretical parameters, LambdaL and lambdaG with corresponding z in [0; 1]:
We found that with large population size, appropriate choice of the minimum epidemic size and lambdG not 0, facilitate the occurrence of a global epidemic.
Thus, given these scenarios, the adequacy of the model fitness to the final size epidemic data is then realised.
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References
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