The Centers for Disease Control and Prevention is monitoring a number of statistical or mathematical models to predict the spread of the COVID-19 pandemic.
One model, created by independent data scientist Youyang Gu, uses artificial intelligence and an epidemiological methodology called SEIS (susceptible, exposed, infectious, susceptible again) to make its predictions. The model tracks the number of infections and deaths on a national and state-by-state basis.
The accuracy of the Youyang Gu model (C19Pro) is compared to another used by the Institute for Health Metrics and Evaluation (IHME), an independent research center at the University of Washington. On April 30, the IHME model predicted 1,641 deaths in California, while the Gu model predicted 2,032 deaths. The actual number of deaths reported was 2,031. The IHME model does not measure factors such as mobility of the population or epidemiology, according to Gu.
Experts also say models can differ widely and represent a range of possibilities for officials to consider.
