Modelling influenza A(H1N1) 2009 epidemics using a randomnetwork in a distributed computing environment

Abstract

In this paper we propose the use of a random network model for simulating and understanding theepidemics of influenza A(H1N1). The proposed model is used to simulate the transmission process ofinfluenza A(H1N1) in a community region of Venezuela using distributed computing in order to accom-plish many realizations of the underlying random process. These large scale epidemic simulations haverecently become an important application of high-performance computing. The network model pro-posed performs better than the traditional epidemic model based on ordinary differential equationssince it adjusts better to the irregularity of the real world data. In addition, the network model allowsthe consideration of many possibilities regarding the spread of influenza at the population level. Theresults presented here show how well the SEIR model fits the data for the AH1N1 time series despitethe irregularity of the data and returns parameter values that are in good agreement with the medicaldata regarding AH1N1 influenza virus. This versatile network model approach may be applied to thesimulation of the transmission dynamics of several epidemics in human networks. In addition, the sim-ulation can provide useful information for the understanding, prediction and control of the transmissionof influenza A(H1N1) epidemics.