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There is increasing interest in superspreading for COVID-19, not least due to an excellent article by @kakape on the topic 1/9https://www.sciencemag.org/news/2020/05/why-do-some-covid-19-patients-infect-many-others-whereas-most-don-t-spread-virus-all …
Mathematically, we are interested in the variation of the number of secondary cases that are generated by one infected index case. This variation can be described by a negative binomial distribution using the dispersion parameter k. 2/9
Small values of k mean that only a few infected individuals contribute to most transmissions. Ebola, SARS and MERS have k values around 0.2. Assuming R0 = 2, this would result in 62% of cases not transmitting at all, while around 15% of cases cause 80% of transmissions. 3/9
High values of k mean steadier transmission without much superspreading. For example, k for influenza is thought to be around 1. Assuming R0 = 2, this would result in 33% of cases not transmitting at all, while around 40% of cases cause 80% of transmissions. 4/9
So what is k for COVID-19? In January, @JulRiou and I estimated a median k = 0.54. There was still considerably uncertainty and it remained unclear whether the transmission characteristics were more akin to SARS or influenza. 5/9 https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.4.2000058 …
A more recent study from @JustinLessler and colleagues using data from Shenzhen, China, estimated a similar k of 0.58. 6/9https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30287-5/fulltext …
Another study from @sbfunk, @AdamJKucharski and colleagues obtain a k around 0.1. https://wellcomeopenresearch.org/articles/5-67 A quick analysis of a published transmission cluster from Austria results in k = 0.16. 7/9 https://www.ages.at/service/service-presse/pressemeldungen/epidemiologische-abklaerung-am-beispiel-covid-19/ …
The value of k for COVID-19 remains unclear, and it will likely depend on social contact structures and environmental settings. I would argue that COVID-19 does transmit in a relatively steady and efficient way while also having the potential for superspreading. 8/9
Preventing these superspreading events from happening - and conducting thorough contact tracing should they happen - can play an important role in avoiding new flare ups of COVID-19. 9/9
Mr. Althaus, I understand very little of what you’re describing but your pursuit of these details is compelling. Thanks for your hard work in pursuit of the facts.
I know little about this, but is anything known about how much "detection" bias there is in the investigated/reported clusters? The clusters only represent a (convenience?) sample of all cases and there is a larger asymptomatic/presymptomic component? 1/
not sure of the direction of the bias, but the reported cluster sizes are self-exciting processes -> if you look you find more and if you don't look then you will not find much? Just a thought... probably someone of the publications have given this more thought... 2/ @sbfnk
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