Stochastic SIR Household Epidemic Model with Misclassification .

n this work, we developed a theoretical framework leading to misclassifi­ cation of the final size epidemic data for the stochastic SIR (Suscepti- ble-Infective-Removed), household epidemic model, with false negative and false positive misclassification probabilities. Maximum likelihood based algo­ rithm is then employed for its Inference. We then.analyzed and- compared<the estimates of the two dimensional model with- those of the three and four di­ mensional models associated with misclasslfied final size data over arrange of theoretical parameters, local and global Infection rates and corresponding proportion infected in the permissible region, away from it's boundaries and misclassification probabilities. The adequacies of the three models to the final size data are examined. The four and three-dimensional models are found to outperform the two dimensional model on misclassified final size data.