If one had the time, enough knowledge and funds, you could look at data
from each colony as an individual, managing risks by accounting for
varying degrees of infection, vulnerability, genetics, management
history, and treat accordingly. In bees, and in humans, controlling a
disease by avoiding any contact with a potential parasite seems fairly
difficult. For bees, quarantines and eradications have not worked very
well. Both bees and humans have evolved good protective systems which
are the first line of defense against any agent. Humans, when healthy,
have a marvelously well tuned immune system. Bees, lacking such a fine
tuned machinery, have instead evolved mostly behavioral social
immunity.
The messy data in the U.S. actually may allow for the most compelling
analysis of the effect of various factors, assuming there is good
information on all possible factors for each county or other
geographical area through time. The more time passes, the more robust
the data should be. A mega-analysis could look at cases and deaths
(as the dependent variable), through time, with all kinds of numerical
(e.g. time since the first case detected, rate of testing, daily
temperature) and categorical groupings (e.g. masks vs. no masks,
restaurants open vs. closed) coded as independent variables. The
effect of any single factor should pop up clearly if it was of any
value. Uniform and rigorously followed mitigation guidelines, if they
did exist in other countries, would contribute little to figuring out
an effect. What would a reference point (control?) be to assess an
improvement?
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