@BarnardResearch profile picture
Dr Rosanna C Barnard (she/her) @BarnardResearch

Research Fellow in Infectious Disease Modelling @cmmid_lshtm @LSHTM, previously @SussexUni 👩🏻‍💻 Mathematics PhD 🎲 Views my own 🏳️‍🌈📷⛰🚲🥑🌺

Joined August 2018
  • Tweets 404
  • Following 649
  • Followers 2,831
52 Photos and videos
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/s41467-0… Until I write a book on this (publishers/agents hmu😝), here is a 🦣🧵

11
35
121
Dr Rosanna C Barnard (she/her) retweeted
Dr Emma Hodcroft@firefoxx66
22 Sep 2022
What should we expect from #SARSCoV2 this autumn? I think it would be smart to prepare for both an increase in #COVID19 due to seasonal (behavioural) change & a new variant. As so many others have elegantly illustrated, new lineages of SC2 are sparking interest. 1/17
30
343
1,204
Dr Rosanna C Barnard (she/her) retweeted
Hunter Wapman@hneutr
21 Sep 2022
1/ New paper! nature.com/articles/s41586-0… with @_szhang @aaronclauset @DanLarremore. 🎓 We analyzed all 295K tenure-track faculty at US PhD-granting universities in 10,612 departments over 10 years to quantify hierarchy and dynamics in US faculty hiring and retention. 🦥 A summary:
36
1,008
3,173
Dr Rosanna C Barnard (she/her) retweeted
CMMID@cmmid_lshtm
13 Sep 2022
Join us for the 2022 @cmmid_lshtm Annual Lecture Dr Jessica Metcalf (@CJEMetcalf | @Princeton | @PrincetonEnviro) will address the topic "Landscapes of immunity: past & futures of infectious disease". 📅 18 October ⏲️ 16:00-17:30 BST 📍 Online 🔗 bit.ly/3D58lwz
12
44
Dr Rosanna C Barnard (she/her) retweeted
Nature Portfolio
@NaturePortfolio
19 Sep 2022
A SARS-CoV-2 model of transmission dynamics in England shows the biggest factors influencing virus transmission are waning immunity, social behaviour and seasonality, @BarnardResearch writes in the Nature Portfolio Health Community. go.nature.com/3DBrF50
9
24
Dr Rosanna C Barnard (she/her) retweeted
Gwen Knight@gmknght
2 Sep 2022
💫NEW JOB💫 I’m hiring a data scientist to work on questions around the drivers of antibiotic resistance. You’d be joining the great @cmmid_lshtm and @LSHTM_AMR at LSHTM as part of my team working on AMR questions using a variety of microbiological, modelling & economic tools.
7
66
104
Dr Rosanna C Barnard (she/her) retweeted
London School of Hygiene & Tropical Medicine
@LSHTM
2 Sep 2022
Want to learn more about how researchers analysed the fast-moving twists and turns of #COVID19? New blog by @BarnardResearch offers a glimpse behind the scenes of the work of our mathematical modellers to produce crucial evidence about the pandemic. 👇
CMMID@cmmid_lshtm
2 Sep 2022
📣 ICYMI 🔍 @BarnardResearch's #NaturePortfolioCommunities Behind the Paper blog introduces her recent research (with @_nickdavies, @markjit & John Edmunds) on modelling the key factors influencing #COVID19 transmission. ➡️ bit.ly/3q30JTI @NatureComms
1
9
16
Dr Rosanna C Barnard (she/her) retweeted
Nature Communications@NatureComms
31 Aug 2022
Modelling the medium-term dynamics of #SARSCoV2 transmission in England in the #Omicron era Future dynamics will depend greatly on assumptions about waning immunity @barnardresearch @_nickdavies @cmmid_lshtm @markjit @LSHTM go.nature.com/3Rsg0ZX
4
7
I wrote a #NaturePortfolioCommunities "Behind the Paper" blog post which provides a (hopefully accessible!) introduction to my recent @NatureComms paper w/ @_nickdavies @markjit @cmmid_lshtm & John Edmunds ⬇️ healthcommunity.nature.com/p… *bonus content included, details below* 🎁

3
15
32
The bonus content compares our model fit and central model projections for England (made in May 2022) to what happened in reality, using data up to August 2022 The model: 1⃣doesn't capture Omicron BA.5's increase from May 2⃣struggles to capture PCR prevalence, even for BA.2
Plots showing the aggregated model fit to data between March 2020 and May 2022, and the resulting basecase model projection between May and December 2022 for England. New data from May to August 2022, which was not used for the original model fitting, is shown in alternative colours as a comparison to model projections. (a) The number of COVID-19 hospital admissions per day. (b) The proportion of the population in England testing PCR-positive for SARS-CoV-2 between March 2020 and December 2022. In both plots, the vertical dashed line denotes the date at which model fitting processes were run to produce both the model fit and projection. This Figure has been adapted from Figure 4 in Barnard et al., available at: https://www.nature.com/articles/s41467-022-32404-y

ALT Plots showing the aggregated model fit to data between March 2020 and May 2022, and the resulting basecase model projection between May and December 2022 for England. New data from May to August 2022, which was not used for the original model fitting, is shown in alternative colours as a comparison to model projections. (a) The number of COVID-19 hospital admissions per day. (b) The proportion of the population in England testing PCR-positive for SARS-CoV-2 between March 2020 and December 2022. In both plots, the vertical dashed line denotes the date at which model fitting processes were run to produce both the model fit and projection. This Figure has been adapted from Figure 4 in Barnard et al., available at: https://www.nature.com/articles/s41467-022-32404-y

1
7
I know @chrischirp and others noted that predictive models like these are of limited use without capturing emerging variants (e.g. x.com/chrischirp/status/1562…), so it's nice to be able to show some of these limitations visually ⤴️

Prof. Christina Pagel - @chrischirp.bsky.social@chrischirp
24 Aug 2022
Replying to @chrischirp
With the rapid evolution of variants we've had this year, this unfortunately means that predictive infectious disease models are of limited use. What remains useful are insights of how big a role waning & behaviour can play. 3/3
1
1
4
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/s41467-0… Until I write a book on this (publishers/agents hmu😝), here is a 🦣🧵

11
35
121
more replies
In the acknowledgements section of the paper I thank @riverssteve @Lloyd_Chapman_ @ciaravmccarthy (friends / colleagues who supported me by, e.g., accompanying me on numerous seaside (t/w)alks, having faith in me when I didn't, & patiently listening to rants / problem solving 🥰)
1
3
One other honorary mention: my colleague @seabbs makes an excellent point about how difficult it is/was to crowbar research done in response to COVID-19 (or any other outbreak, FWIW) into traditional academic outputs (& sadly that was 100% my experience) x.com/seabbs/status/15620919…

Sam Abbott (@seabbs@fosstodon.org)@seabbs
23 Aug 2022
Replying to @seabbs
Note in the thread how ludicrously hard crowbarring response work into academic publications was. We should maybe reflect on that both for how we assess ECRs now and how we evaluate outputs from future outbreaks.
2
Dr Rosanna C Barnard (she/her) retweeted
Brian Uzzi@UzziLeadership
29 Aug 2022
Science teams made up of men and women produce papers that are more novel and highly cited than those of all-men or all-women teams. Read our findings @PNASNews w/ Yang Yang, Tanya Tian, Teresa Woodruff and @bfjo. @KelloggSchool @NICOatNU pnas.org/doi/10.1073/pnas.22…
Gender-diverse teams produce more novel and higher-impact scientific ideas

ALT Gender-diverse teams produce more novel and higher-impact scientific ideas

Figure 2 from PNAS publication

ALT Figure 2 from PNAS publication

8
180
651
Load more