We show that relaxing the assumption of homogeneity in the modelling code released by Flaxman et al (Nature) to allow for individual variation in susceptibility or connectivity gives a model that has better fit to the data and more accurate 14-day forward prediction of mortality.
Allowing for heterogeneity in 11 European countries reduces estimate of "counterfactual" deaths that would have occurred if there had been no interventions from 3.2 million to 262,000, explaining most of the slowing and reversal of COVID-19 mortality by build-up of herd immunity.
The estimate of the herd immunity threshold depends on the value specified for the infection fatality ratio (IFR): a value of 0.3% for the IFR gives 15% for the average herd immunity threshold over the 11 European study countries.
The release of the modelling code and dataset used by Flaxman et al is a valuable contribution to transparent evaluation of infectious disease modelling.
You can follow @mgmgomes1.
Tip: mention @twtextapp on a Twitter thread with the keyword “unroll” to get a link to it.

Latest Threads Unrolled: