Forecasting Covid-19 cases in the early goings

There was a lot of uncertainty in the beginning of the pandemic, so the forecasts varied across sources. There were also many forecasts. Youyang Gu provided on of those forecasts, and it predicted well. Ashlee Vance reporting for Bloomberg on the Covid-19 forecasting work of Youyang Gu:

The novel, sophisticated twist of Gu’s model came from his use of machine learning algorithms to hone his figures. After MIT, Gu spent a couple years working in the financial industry writing algorithms for high-frequency trading systems in which his forecasts had to be accurate if he wanted to keep his job. When it came to Covid, Gu kept comparing his predictions to the eventual reported death totals and constantly tuned his machine learning software so that it would lead to ever more precise prognostications. Even though the work required the same hours as a demanding full-time job, Gu volunteered his time and lived off his savings. He wanted his data to be seen as free of any conflicts of interest or political bias.

Reading this, it felt a little bit like cherry-picking the forecast that was best, but I don’t know enough to decide. It does seem to highlight though some of the limitations of larger organizations that don’t always have the best point of view.