Estimating the Final Epidemic Size for COVID-19 Outbreak using Improved Epidemiological Models

Rajesh Ranjan

We first show validity and limitation of these models by taking the data for Hubei and Hunan in China. Predictions using all these models are made using part of the available data and then are compared with actual data. Figure 4 shows these results. It may be noticed that if the data included for modeling come only from the acceleration region (exponential growth part) of the curve, the predictions of eventual epidemic size are very different from the actual numbers. Further, predictions by different models differ from one another in such cases. This highlights the convergence issue in estimation of modeling parameters. The predictions improve when part of the flattened curve is also included for the estimation of parameters in the model. The predictions by models SIR and SEIQRDP are very close to each other. The logistic model consistently underpredicts the final epidemic size.