RT @LSHTM_GHECO: 🇹🇭 New study from @LSHTM members & collaborators is the first economic evaluation of next-gen flu vaccines in Thailand. 💉….

We won an Innovation Award for our project: "Unveiling the Sex-Specific Impact on Antimicrobial Resistance (AMR): A Bayesian Hierarchical Model Approach Using Vivli Data”. Great team work with @gmknght @mert0248 @ckim0509 and Alastair Clements! . @LSHTM_AMR @cmmid_lshtm.

RT @cmmid_lshtm: 💉 For our annual lecture, we’re delighted to welcome Prof Matt Keeling for his talk on the deployment & roll-out of COVID-….

RT @gmknght: Just writing a job description for a RA/RF post I'll soon be advertising: an exciting opportunity to work on drug resistant #T….

RT @gmknght: Happy to say that this now out in @PLOSMedicine! Thanks to @N_R_Waterlow @bugwonk @JVRobotham & reviewers. We're now working….

Stefan was one of my PhD supervisors - highly recommend working with him! ☺️.

RT @gmknght: Looking for a PhD on #AMR? want to get your teeth into a tricky public health problem? .Then consider my project with @catmoor….

Fun to win a prize with a great team!😃. We looked at MIC values across ages, sex, bug-drugs and much more to see what the implications could be for infection routes. Conclusion: Many interesting trends + MIC data is underused!. See our report:

Thanks to co-authors @bugwonk, @JVRobotham and @gmknght and @ECDC_EU for data access. But of course biggest thanks to all the individuals at country-level who contributed to this dataset and made the analysis possible. (6/6).

We highlight the need for a better grasp of variation in AMR by demographics. Our #1 conclusion: AGE MATTERS! And sex somewhat too!.Collecting, publishing and analysing AMR data within countries and across demographic factors will help us understand AMR and its development. (5/6).

The shape and magnitude of the trends vary by bac-antibiotic combination, with some showing increasing resistance with age, some decreasing, and some u- or n-shaped trends. (Fig: MRSA, with anonymised countries on the x-axis, colour indicates sex). (4/6)

We investigate further using statistical modelling techniques, and show that the demographic trends vary by country and sub-nationally. (Fig shows trends for MRSA across 3 anonymised European countries, points = country-level data, lines/ribbons = model fit by lab) (3/6)

We use EARSNET bloodstream infection data to look by different bac-antibiotic combo's, age and sex, and find strong demographic differences! (Fig shows e.g for 6 antibiotics for Acinetobacter and Pseudomonas where x is age and we fit separate lines for data from ♂️ and ♀️) (2/6)

Do you think age and sex matter for antimicrobial resistance (AMR)?. They do! 🦠🧒🧓. However, it’s not usually considered. Most analyses only look at country-level trends but we explored the patterns by age revealing some interesting patterns… (1/6).

Thanks to co-authors @mert0248, Edwin van Leeuwen, @VetSree, @markjit and @rozeggo! . Also for a fuller understanding of the cost-effectiveness of such vaccines check out our other paper, answering similar questions in a completely different setting!

And additionally be highly cost-effective! . We therefore add to the evidence for investing in the development and roll-out of nextgen flu vaccines!

New paper: The potential cost-effectiveness of next generation influenza vaccines in England and Wales: A modelling analysis! . Our paper shows that nextgen flu vaccines may greatly reduce the impact of flu on the population of England & Wales .

RT @cmmid_lshtm: Next week! . 👋to @CarolineTrott13 who will discuss the use of modelling to inform decision-making on vaccine policy and ep….

RT @cmmid_lshtm: 👋In this month's early career researcher spotlight we get to know @N_R_Waterlow & her work with colleagues @LSHTM. Naomi….

Take a look at the preprint for more details and discussion! Thanks to all co-authors and the PHIRST study, especially Cheryl Cohen and @StfnFlsch.