We were asked to model roadmap #step4 happening on 19th July with:
▶️ different vaccine effectiveness vs. Delta δ B.1.617.2
▶️ different transmission levels after step 4
This time, we ran *a lot* of model fits, shoutout @PushoverApp.
We fitted the transmissibility (TX) of δ relative to α given (central and optimistic) assumptions on vaccine effect 💉
We also produced model fits w/ combinations of:
🌘 waning immunity🌖
😣 severity of delta 🏥
We made some changes to our assumptions since last time, for example:
1⃣ updating vaccine effect against onward transmission (see nejm.org/doi/full/10.10…)
2⃣assuming a longer duration of immunity for waning scenarios (15% loss in 1 year, previously 6 months)
3⃣using age varying length of hospital stay estimates
4⃣updating case fatality ratios
5⃣using measured delays between 1st and 2nd vaccine doses
6⃣updating vaccine coverage
[full details in report]
We project implementing #roadmap step 4 with different sensitivities (reductions in protective behaviours e.g. mask wearing/self isolation, vaccine effect, vaccine uptake, waning immunity and severity of δ). Here is default #USP projecting low, mid and high changes in *mobility*
So, to the results:
1⃣We project COVID-19 transmission wave for all scenarios (severity of wave depends on assumptions)
3⃣Optimistic assumptions ▶️ lower levels of transmission
4⃣In all scenarios, we project lower burden on COVID-19 mortality than previous waves ⚕️❤️🩹
5⃣behavioural changes such as increased contact rates and relaxations in self-protective measures (mask wearing 😷 social distancing) have the biggest effect
6⃣scenarios with waning immunity lead to bigger waves of transmission
7⃣reduced vaccine efficacy leads to bigger waves of transmission
8⃣lower vaccine uptake (e.g. due to underestimating population sizes) leads to bigger waves of transmission
[flowers to cheer you up]
There are a lot of uncertainties about the dynamics we project over the next few months in England. The link between cases and severe outcomes (hospitalisations, deaths) has been *weakened*, but imo it is still important to be cautious and #getvaccinated if you are able to 💉💜
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 🧵 on our latest work looking at #step4 🪜👩💻 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 💉
To capture changes in behaviour (➡️ 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 🍀 We make low, medium and high assumptions to account for uncertainty... ⭐️
A lot of attention on our @cmmid_lshtm preprint on the SARS-CoV-2 VOC 202012/01. For some background, the precursor work on a (single-variant) model looking at tiered restrictions and lockdown in England was published last night: authors.elsevier.com/sd/article/S14… ✨PEER REVIEWED(!)✨ 1/9
We fitted a (single-variant) model of SARS-CoV-2 transmission to the first and second waves in England from March - October 2020, using a number of data sources across NHS England regions 2/9
We used mobility and contact survey data to assess the effects of regional tiered restrictions (Tiers 1, 2, 3) introduced in England in October 2020 (pictured), and the effects of the Welsh firebreak 🔥 Northern Irish circuit breaker 🔐 lockdowns 3/9