I think this is attempting to answer the wrong question.Abstract Objective:Our objective is to demonstrate a method to estimate the probability of a laboratory confirmed COVID19 infection, hospitalization, and death arising from a contact with an individual of unknown infection status. Methods: We calculate the probability of a confirmed infection, hospitalization, and death resulting from a county-level person-contact using available data on current case incidence, secondary attack rates, infectious periods, asymptomatic infections, and ratios of confirmed infections to hospitalizations and fatalities. Results: Among US counties with populations greater than 500,000 people, during the week ending June 13,2020, the median estimate of the county level probability of a confirmed infection is 1 infection in 40,500 person contacts (Range: 10,100 to 586,000). For a 50 to 64 year-old individual, the median estimate of the county level probability of a hospitalization is 1 in 709,000 person contacts (Range: 177,000 to 10,200,000) and the median estimate of the county level probability of a fatality is 1 in 6,670,000 person contacts (Range 1,680,000 to 97,600.000). Conclusions and Relevance: Estimates of the individual probabilities of COVID19 infection, hospitalization and death vary widely but may not align with public risk perceptions. Systematically collected and publicly reported data on infection incidence by, for example, the setting of exposure, type of residence and occupation would allow more precise estimates of probabilities than possible with currently available public data. Calculation of secondary attack rates by setting and better measures of the prevalence of seropositivity would further improve those estimates.

Starting with the minimum of the infections, then with the 10% infection rate from an infectious contact, and assuming there's no clustering - so indeed, if the overall rate is 6/100k uniformly spread and people interact uniformly, and you have a 0.3% chance of death if infectious, then it is going to be very low.

I think the main problem is that it's missing the impact of cluster events and it's actually better to think what the chance is of being in a group with an infectious person.

Any views... It's being shared by the founder of the "Keep Britain Free" hashtag - who lives in Monaco