Dr Rosanna C Barnard (she/her) Profile picture
Jul 12, 2021 11 tweets 8 min read Read on X
An updated 🧵 on our latest report modelling #step4 of the #roadmap on 19th July 2021 🛣️🪜 with @_nickdavies @markjit & John Edmunds @cmmid_lshtm 👩‍💻 (published today) ... #storytime with pictures 📒📷 gov.uk/government/pub…
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

We used the same #agestructured #compartmental #deterministic model as before An image showing the compartments and transitions between di
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 🏥 A screenshot showing the Pushover app with lots of notificat
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] A figure with two panels showing vaccine coverage in England
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* A figure showing Google Community Mobility data in England b
So, to the results:

1⃣We project COVID-19 transmission wave for all scenarios (severity of wave depends on assumptions)

2⃣Pessimistic assumptions ▶️ hospital admissions, beds occupied could exceed winter 2020/2021 levels

3⃣Optimistic assumptions ▶️ lower levels of transmission Figures showing projections of COVID-19 transmission in Engl
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 Model projections of COVID-19 transmission between July and
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] A photograph of a vase of flowers including peonies.
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 💉💜 A photograph of a kitten's paw
Huge thanks to all of my team @_nickdavies @markjit John Edmunds and @cmmid_lshtm colleagues, as well as others on SPI-M e.g. @GrahamMedley 👨‍🔬👩‍🔬 You can read the other reports from @imperialcollege and @warwickuni @JuniperConsort1 gov.uk/government/pub…

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Dr Rosanna C Barnard (she/her)

Dr Rosanna C Barnard (she/her) Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @BarnardResearch

Aug 23, 2022
My research (with @_nickdavies @cmmid_lshtm @markjit & John Edmunds) is published in @NatureComms 🥳

This is the culmination of many months of work (my funding from @Epipose)🍾🎉

nature.com/articles/s4146…

Until I write a book on this (publishers/agents hmu😝), here is a 🦣🧵
The code to reproduce this work is available at: github.com/rosannaclaireb… 🛠️⚙️🧩🏗️

This implementation of 'covidm' builds on work by @_nickdavies (the OG creator) in the early #COVID days

Since joining @LSHTM in July 2020, I have developed covidm with @_nickdavies

👩‍💻👩‍🔧👩‍🎨👩‍💼👩‍🔬
Early 2020 discussions @cmmid_lshtm led @_nickdavies to build #covidm

CMMID members @LSHTM (e.g. @rozeggo, John Edmunds, & @adamjkucharski) contributed to these discussions

Many other colleagues contributed to model development (e.g. @cap1024 @Lloyd_Chapman_ @KevinvZandvoort)
Read 29 tweets
Dec 11, 2021
The B.1.1.529 SARS-CoV-2 variant was first reported on 24th November 2021, and 2 days later @WHO designated it #Omicron. Since then we (me @_nickdavies @cap1024 @markjit and John Edmunds) have worked to understand potential consequences for England. 🧵 [cmmid.github.io/topics/covid19…] Figure 1 from the paper linked in the tweet. This figure has
First, what do we know about Omicron?

1⃣ it has a large number of mutations (see covdb.stanford.edu/page/mutation-…)
2⃣ there is evidence from South Africa (s/out @SACEMAdirector and team) of an increased reinfection risk associated with the emergence of Omicron: An image showing the mutations within the genome of the Omic
3⃣ Omicron neutralisation studies are emerging (~5 so far this week). These suggest a drop in neutralisation for Omicron
4⃣ @UKHSA vaccine effectiveness data suggests a significant reduction for dose 2 Omicron compared to Delta ()
Read 18 tweets
Jun 14, 2021
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 A photograph of the West pier and Brighton beach with low ti
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 💉 An illustration of the age-structured compartmental transmis
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... ⭐️ Figures showing google mobility data between January 2020 an
Read 11 tweets
Dec 24, 2020
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 Image
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 Image
Read 9 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(