Stochastic modelling for pneumonia incidence: A conceptual framework

Abstract

Stochastic model is one of the tools that can be used to estimate the probability distribution of potential outcomes and it allows the random variation in one or more inputs over time. In order to understand more on the disease transmission, researchers used mathematical modeling. There are two types of mathematical modeling for infectious disease study that are deterministic and stochastic model. The deterministic model also known as a compartmental model where it gives the basic supporting structure for the study of transport between different systems. The stochastic models rely on possible variation in risk of disease, exposure and other factors. This model is used when these changes are important, for example in a small population. Stochastic model also considers random effect which mean that it takes into account an extra quantity of variance component which is estimable within the map and which can be regarded as a clear probabilistic structure. This is very different from deterministic model as deterministic model does not take into account random effect. In this paper, we will review some deterministic mathematical models that have been used by other researchers in studying the pneumonia disease which from these mathematical models we will use it later as a guidance to proposed stochastic mathematical model.