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Exaggerated risk of transmission of COVID-19 by fomites thelancet.com/journals/lanin…
Yes, lab studies use amounts of virus that may not reflect "real-life situations". Some of the reality beneath this is that cell culture struggles to detect infectious virus at what might be *truly* real-life levels. Yes, lab studies have always been perfect world experiments
But without these expts, we may get a false sense of the role of surfaces (and airborne transmission in which we can also find an infectious virus in aged aerosols for 3h during which the viral load drops from 10^3.5 to 10^2.7 TCID50)
nejm.org/doi/full/10.10…
We could try and do some animal work here (house susceptible animal in a cage previously occupied by infected animals?) to address the surfaces question at an organism level rather than cell culture level.
On aerosols, we don't have more than observation in humans. We can infect African green monkey's via aerosolised MERS-CoV and see a dose-response using much more "real-life" doses. But what does "real life mean?
europepmc.org/article/ppr/pp… [preprint, USAMRIID]
Unhelpfully, the author of the ⬆ opinion doesn't attempt to define any "real-life" relevant viral loads.
Helpfully, one of the papers mentioned did help here. The NEJM paper by van Doremalen et al above noted the inoculum used had RNA levels that *were* in the same load range
as those found in actual patient samples. So, perhaps those aerosol data are a little more real-life after all.
Regardless of specifics, we do seem to agree that susceptible people sharing proximity and time (crowds, poorer airflow) are more likely to be infected.
Whether droplets, droplet nuclei, the surfaces they all impact on, or a combination of each affected by environment and circumstance (most likely!), a precautionary principle still says hand hygiene, distance and PPE will all lower risk of transmission.
Maybe the boffins could focus on getting us all some useful data on surfaces, aerosols and masks now and leave further pronouncements and opinions for a bit?
At the end of the day, we're not reviewing new data.
We're rehashing reviews of old data.
We need new data.
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