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Basic estimation-prediction techniques for Covid-19, and a prediction for Stockholm

Britton, T.

2020-04-17 infectious diseases
10.1101/2020.04.15.20066050 medRxiv
Show abstract

Predicting future infections for covid-19 is essential in planning healthcare system as well as deciding on relaxed or strengthened preventive measures. Here a quick and simple estimation-prediction method for an urban area is presented, a method which only uses the observed initial doubling time and R0, and prediction is performed without or with preventive measures put in place. The method is applied to the urban area of Stockholm, and predictions indicate that the peak of infections happened in mid-April and infections start settling towards end of May.

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The top 6 journals account for 50% of the predicted probability mass.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.