In a recent talk delivered at the Conference on Complex Systems (CCS2021), I got the opportunity to present our work on the risks of Covid-19 transmission in non-confined crowds.
The aim was to rank everyday-life situations involving non-confined crowds by the risks that they present, not so much for the individual (individual perspective) as in terms of their contribution to the spread of the epidemic (collective perspective). The hurdle to that endeavour is that contact tracing is (at the very best) uneasy, not to say impossible, in these conditions: Who knows the name of the pedestrian that has just come close to them on a busy street? Even contact-tracing apps do not recall such a short encounter. Accordingly, we overcame the hurdle by turning to simple models describing the propagation of respiratory droplets (in a coarse way) and coupling these models to field data which we collected in a variety of situations involving crowds.
Our main findings and all the details of the methodology that underlie them can be found in our recent publication in Safety Science.
