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

Tom Britton

In the current paper the focus has been on predicting the number of infected over time. Clearly, the burden on the health care system measured by hospitalized patients or case fatalities, are more relevant quantities. When predicting these quantities, an age-structured model is advantageous since the risk for severe symptoms and death increases with age. However, there is also high uncertainty in what fraction of all infected that will require health care at different levels, as well as the infection fatality risk f . For example, current estimates of f (not to be mixed up with case fatality risk, cfr) vary between 0.2% up to 1% (e.g. [13] , [12] ). Clearly, any prediction of the number of fatalities will be equipped with very large uncertainty due to uncertainty in f let alone all other uncertainties, and this big uncertainty is most often not acknowledged by instead picking just one published estimate of f .