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“There is an unhelpful tendency to regard superspreaders – and events where superspreading has occurred – as anomalies out of the ordinary. This contributes relatively little to our understanding of infectious dynamics and is bound to exacerbate the stigmatisation of individuals, as it has e.g. during the early years of AIDS, when much sensationalistic and unjustified blame was laid at the feet of early HIV patient Gaetan Dugas (on which see McKay, 2014). Rather, superspreading is one 'tail' of a distribution prominent mainly because it is noticeable – statistical models predict that there are generally an equal number of 'greatly inferior spreaders' who are particularly ineffective in spreading the illness.”
― Computational Modeling of Infectious Disease: With Applications in Python
― Computational Modeling of Infectious Disease: With Applications in Python
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