Spring 2020 brought with it the arrival of the celebrity statistical model. As people tried to gauge how big a deal the novel coronavirus might be, they were pointed again and again to two forecasting systems: one built by Imperial College London, the other by the Institute for Health Metrics and Evaluation, or IHME, based in Seattle.
But the models yielded wildly divergent predictions. Imperial warned that the U.S. might see as many as 2 million Covid-19 deaths by the summer, while the IHME forecast just 60,000 deaths. Neither, it turned out, was very close. The U.S. ultimately reached about 160,000 deaths by the start of August.
The huge discrepancy in the forecasting figures that spring caught the attention of a young data scientist named Youyang Gu. The 26-year-old had a master’s degree in electrical engineering and computer science from the Massachusetts Institute of Technology and another degree in mathematics, but he had no formal training in a health-related area such as biology or epidemiology. Still, he thought his background dealing with data models could prove useful during the pandemic.
In mid-April, while he was living with his parents in Santa Clara, Calif., Gu spent a week building his own Covid death predictor and a website to display the morbid information. Before long, his model started producing more accurate results than those cooked up by institutions with hundreds of millions of dollars in funding and decades of experience.
Denne historien er fra March 01, 2021-utgaven av Bloomberg Businessweek.
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Denne historien er fra March 01, 2021-utgaven av Bloomberg Businessweek.
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