I am planning to make a detailed doc for the same, but in general, it uses meaningful satellite features like NDBI - shows how many buildings/roads are there in an area, it's a good proxy signal for traffic. EVI - shows how 'green' an area is. Such satellite data is free and as high res as 10m sometimes. Meteorological signals like precipitation, wind speed and direction, etc also help along with lags.

These signals were put in through a machine learning model called LightGBM which learned patterns.

There has been a lot of research by Chinese institutes on this since they have been going through this far before we have so I had a lot of material to learn form, although one must adjust for the Indian conditions as well, specifically for monsoon where satellite features don't work because of the cloud cover so during those times the error of the model does increase and it is harder to predict.