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An updated 𧡠on our latest report modelling #step4 of the #roadmap on 19th July 2021 π£οΈπͺ with @_nickdavies @markjit & John Edmunds @cmmid_lshtm π©βπ» (published today) ... #storytime with pictures ππ· gov.uk/government/pubβ¦
We were asked to model roadmap #step4 happening on 19th July with:
βΆοΈ different vaccine effectiveness vs. Delta Ξ΄ B.1.617.2
βΆοΈ different transmission levels after step 4
We used the same #agestructured #compartmental #deterministic model as before
βΆοΈ different vaccine effectiveness vs. Delta Ξ΄ B.1.617.2
βΆοΈ different transmission levels after step 4
We used the same #agestructured #compartmental #deterministic model as before
This time, we ran *a lot* of model fits, shoutout @PushoverApp.
We fitted the transmissibility (TX) of Ξ΄ relative to Ξ± given (central and optimistic) assumptions on vaccine effect π
We also produced model fits w/ combinations of:
π waning immunityπ
π£ severity of delta π₯
We fitted the transmissibility (TX) of Ξ΄ relative to Ξ± given (central and optimistic) assumptions on vaccine effect π
We also produced model fits w/ combinations of:
π waning immunityπ
π£ severity of delta π₯
It's been a busy few days/weeks/months modelling steps 2, 3 and 4 of the #roadmap out of lockdown in England, with my #ateam @_nickdavies @markjit and John Edmunds. A 𧡠on our latest work looking at #step4 πͺπ©βπ» and a #photodump of some nice things I saw along the way
We project the dynamics of #SARSCoV2 transmission in England using an #agestructured #transmission #model which divides the population into vaccine states and disease states. The model has compartments for three #COVID19 variants (OG, #alpha and #delta) and 2 two-dose vaccines π
To capture changes in behaviour (β‘οΈ the amount people mix in the model), we use historic #mobilitydata and make assumptions about what might happen to mobility when policies are implemented, e.g. #step4 π We make low, medium and high assumptions to account for uncertainty... βοΈ
