You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
It's also possible to define a likelihood for multi-type branching process for age-stratified data (Kucharski et al, PLOS Comp Biol, 2015, which is particularly relevant if the population introducing the infection is very different to that driving human-to-human transmission (e.g. older individuals more likely to be index cases for MERS-CoV).
If multi-type inference not a priority, it may be worth considering a multi-type simulation process for age-stratified social mixing data in meantime (currently implemented as simulate.data() in above repo.
The text was updated successfully, but these errors were encountered:
It's also possible to define a likelihood for multi-type branching process for age-stratified data (Kucharski et al, PLOS Comp Biol, 2015, which is particularly relevant if the population introducing the infection is very different to that driving human-to-human transmission (e.g. older individuals more likely to be index cases for MERS-CoV).
There's a (not particularly tidy) implementation here: https://github.com/adamkucharski/subcritical_chains, which could also be combined with
socialmixr
.If multi-type inference not a priority, it may be worth considering a multi-type simulation process for age-stratified social mixing data in meantime (currently implemented as
simulate.data()
in above repo.The text was updated successfully, but these errors were encountered: