In principle, I like the research question and the comparison above is probably the most you can make out from what is published. That said, it is the year 2022, capabilites and methodology have advanced enormously at least with those PM firms operating successfully in the commercial world markets. So it's the proverbial comparing apples and oranges on several dimensions to talk about how "prediction markets" (sic) perform for whatever. Different platform implementations have very different capabilities suited to very different tasks. Moreover, like any advanced tool, practical application of the more advanced PM platforms need a high degree of methodic knowhow on how to use their specific capabilities - based on real experience of what works and what does't.
OP's claim of inadequacy of EA London COVID measures lacks an objective "effectiveness" measure. It criticises a lack of clarity of the EA measures while lacking any clarity itself.
I am stressing this as this same problem applies to public policy in many countries. Australia is a severe case: its extremely harsh travel policy seems based on the premise that either the virus and its innumerable variant mutations will simply go away or that Australia can remain in perpetual lockdown without serious negative socioeconomic consequences on the medium and long term.
For a proper decision (even just at EA Lonon) we would need a collective forecast of the objectively measured number of participants who will be infected/severe cases/die at EA London with the current policy and conditional on the one proposed by OP. Step 2 would be a vote in full knowledge of the forecast consensus and distribution. Prediki Prediction Markt offers free use of its platform for such "effectiveness" purposes. While this would be an effort, it might be well worth it, as a showcase to the world (and Australia) on how to decide such matters objectively and "effectively".