A deterministic epidemic model for the emergence of COVID-19 in China

Meng Wang; Jingtao Qi

The study provides a deterministic mathematical model to analyse and predict characteristics of an infectious disease spreading in an extremely large population with strong prevention and control measures. The model depends purely on statistic data of categorised epidemic cases reported in public. We apply the model to the emergence of COVID-19 in China. Although the model is not yet perfect, it is effective, robust and consistent as long as there is no sudden change in control measures. Comparing with the classic SIR model, we extract the basic reproduction number, R 0 , and make predictions on the time when the effective reproduction number will become less than one and on the total number of confirmed cases in the end. Our study indicates that it is essential to take effective control measures as early as possible for curbing an infectious disease and it is important to report epidemic data precisely and timely for epidemiological modelling. In the era of globalisation, an infectious disease can spread as far as any individual can reach on the earth, that makes the whole world population to be susceptible. As COVID-19 has spread around the world, we anticipate our method can be adapted in modelling the spread and help public health authorities make policy decisions.