This means that the R0 values that are currently estimated are specific to (a) Wuhan, and (b) (mostly) pre-intervention. The R0 is going to be different for different countries/regions and will change over time.
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Als antwoord op @K_G_Andersen
You're confusing R0 (the basic reproduction number, defined theoretically at time zero) with the reproduction number at time t (sometimes called the effective reproduction number).
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Als antwoord op @EvolveDotZoo
Yeah, I'm aware of the difference between the basic and effective reproduction number, but no, I'm still referring to R0 given that the virus is still spreading through a naive population and for R=R0x, we can largely ignore x (for now). This will of course change and R < R0.
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Als antwoord op @K_G_Andersen @EvolveDotZoo
2.5m after, herd-immunity matters. The observed epi is now an aggregated mix of epis happening at various stages & places. We now have parallel epis with very different durations. Also relevant: control keeps these spatially disaggregated, so homogenous assumptions collapse.
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Als antwoord op @LourencoJML @K_G_Andersen
Exactly. Across a large enough epidemic these heterogeneities even out such that comparing R0 among epidemics is a useful way of comparing transmissibilities (beta) and planning interventions. Right now, the R0 is very context sensitive. 1/2
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Which I think was Kristian’s point. So we all agree except on the semantics - I’d never phrase it as “R0 will vary through time”. 2/2
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Maybe Kristian meant that the R0 _estimates_ will vary through time. 100% agree with that.
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Als antwoord op @EvolveDotZoo @LourencoJML
Should have been more specific - no, I'm not saying that as an inherent property R0 will vary across time (that'd be R in a simple SEIR model). What I'm saying is that in a naive population where a virus e.g., moves from X1 to X2 and X2 has different env/response, R0 will change.
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And separately, yes, R0 *estimates* will vary (likely by a lot) as time goes on. My main point is that R0 isn't some magic number that can be attached to a particular pathogen - it all depends on context. E.g., R0(China) =! R0(UK) for the same virus.
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All that's likely to boil down to though is possible changes in contact structure. The other params that feed into R0 *should* be attached to a particular pathogen. With most cases in large urban centers, contact structure is likely similar so R0(China) may approx R0(UK)
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Of the main things influencing R0 - contact rate (k), probability of infection (b), and infectious period (d), all will vary based on population, environment, and detection/containment strategies - some more than others.
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I suppose, but since R0 is understood in absence of interventions, b and d should be mainly tied to pathogen unless major differences in host population (e.g., immune response, cross-immunity, etc)
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