Estimating Exposure Risk to Guide Behaviour During the SARS-COV2 Pandemic - Smyth, Barry (Frontiers in Digital Health, 2021)
The end of 2020 proved to be a challenging time for many countries in Europe as the combination of winter weather, holiday celebrations, and the emergence of more transmissible variants of the virus conspired to create a perfect storm for virus transmission in Europe. At the same time lockdowns appeared to be less effective than they were earlier in the pandemic. In this paper we argue that one contributing factor is that existing ways of communicating risk – case numbers, test positivity rates, hospitalisations etc. – are difficult for individuals to translate into a level of personal risk, thereby limiting the ability of individuals to properly calibrate their own behaviour. We propose an new more direct measure of personal risk, exposure risk, to estimate the likelihood that an individual will come into contact with an infected person, and we argue that it can play an important role, alongside more conventional conventional statistics, to help translate complex epidemiological data into a simple measure to guide pandemic behaviour. We describe how exposure risk can be calculated using existing data and infection prediction models, and use it to evaluate and compare the exposure risk for 39 European countries.