Dear Member of Congress: The Infectious Diseases Society of America (IDSA) and HIV Medicine Association (HIVMA) are deeply grateful for the longstanding bipartisan support from Congress for the National Institutes of Health (NIH). We want to inform you of current and likely impacts of delays and changes in funding policies and procedures for NIH grants. Our concerns relate to the following areas within NIH: • Massive reduction in notice of funding opportunities • Delays in funding processes and inadequate capacity to administer grants • Increase in forward funding of multiyear awards in year one • Delays and potential lapses in funding for large clinical trial networks and clinical trial units Lack of transparency around permitted international collaborative partners for research projects • Disproportionate impact of grant terminations on vulnerable populations, especially women and people of color

U.S. infectious disease research is on the brink. Without immediate action from Congress, much of it will cease to exist within a year.

For example👇

1️⃣ No collaborative RFAs posted for >1 year (normal: many / year).
2️⃣ No foreign collaborators allowed on grants.

🧪🪦 www.idsociety.org/globalassets...

Using electronic health records to assess the relationship between colonization pressure and nosocomial pathogen acquisition - Nature Communications Hospitalised patients are at risk of acquiring infections, and the risk increases when there is a higher prevalence among ward co-occupants, known as colonisation pressure. Here, the authors built an ...

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🎉 Our paper on colonization pressure (CP) and nosocomial pathogen acquisition is out in Nature Communications! Lots of surprising findings.

www.nature.com/articles/s41...

🚨 My lab is hiring! @ucirvine.bsky.social Seeking full-time data scientists & machine learning engineers.

We apply LLMs and AI tools to clinical data, rapidly scaling up epidemiological analyses and models of sepsis, hospital-acquired infections, and more. tpaklab.org #MedSky #IDsky 🧪 1/x

Machine Learning Operations Engineer in Irvine, California | University of California, Irvine Careers Home is hiring a Machine Learning Operations Engineer in Irvine, California. Review all of the job details and apply today!

If you are experienced in managing Python, R, and/or SQL software projects; use data science and ML best practices; love research on infectious diseases; and want to join a growing computational lab based in SoCal...

➡️ Apply today! jobs.uci.edu/careers-home...

#EpiSky #SciSky #MedSky #IDSky 🧪 2/x

🚨 My lab is hiring! @ucirvine.bsky.social Seeking full-time data scientists & machine learning engineers.

We apply LLMs and AI tools to clinical data, rapidly scaling up epidemiological analyses and models of sepsis, hospital-acquired infections, and more. tpaklab.org #MedSky #IDsky 🧪 1/x

ID fellow Alejandro De La Hoz Gomez, MD, of Mass General Brigham shares three things people don’t realize about a career in infectious diseases. #WhyILoveID

I'll try to TL;DR the debate lol (although its not a short TL;DR).

ATS CAP guidelines say give antibiotics for CAP with +virus in severe CAP, non-severe hospitalized CAP, and outpatient CAP with comorbidities, but don't give antibiotics for non-comorbid outpatient CAP

I've been using #ClaudeCode for #research #informatics—cohort building, debugging pipelines, genomics in #AllofUs. Before any of that was useful, I had to set things up right.

The setup isn't complicated, but it matters. Here's how I do it:
1/

The last part abt how measles disrupts immunity vs other infections is, imo, underappreciated (& mechanism was recently clarified). It's part of why measles vaccination was seen to help beyond just reducing measles complications - not getting measles reduces severity of subsequent infections too.

🚨 New pre-print! 🚨 In the largest study of its kind to-date, we investigate the ecological and evolutionary mechanisms driving within-patient evolution of antimicrobial resistance (AMR). Read here:
www.biorxiv.org/content/10.6... , and follow along with this thread, discussing our findings (1/21)

Clinical Trials Affected by Research Grant Terminations at the National Institutes of Health This cross-sectional study summarizes the number of trials with terminated grants from the National Institutes of Health (NIH) and calculates the proportion of affected trials among those with previou...

Clinical trials affected by NIH grant terminations

"Approximately 1 in 30 trials and more than 74 000 trial participants were affected ... Affected trials disproportionately studied infectious diseases, prevention, and behavioral interventions" #MedSky #IDSky jamanetwork.com/journals/jam...

What I'm Reading:
Curiosity, a 1B-parameter model built on Epic Cosmos.

It's genuinely interesting: zero-shot outputs rivaled supervised baselines across 78 real-world tasks, and the scaling laws (α=0.52) mirror NLP. Cool to see how information scales across domains.

arxiv.org/abs/2508.12104

1/

Rise of anti-science rhetoric has fundamentally changed the relationship between doctors and patients “The rise of anti-science and anti-vaccine rhetoric has fundamentally changed the relationship between clinicians and patients.”

Rise of anti-science rhetoric has fundamentally changed the relationship between doctors and patients www.statnews.com/2025/12/10/a... by @krutikakuppalli.bsky.social
via @statnews.com

#HHS #FDA #CDC #publichealth #vaccines #science #MedSky

Infectious Diseases Society of America (IDSA) Position Statement: Why IDSA Did Not Endorse the Community-Acquired Pneumonia Guidelines 2025 Update The Infectious Diseases Society of America (IDSA) did not endorse updated community-acquired pneumonia guidelines because they recommend antibiotics for pa

A @idsainfo.bsky.social position statement in @cidjournal.bsky.social describing why the society backed out of ATS CAP guidelines.

[In viral pneumonia] “briefly withholding antibiotics for patients with nonsevere illness to clarify the diagnosis is safe”

#IDSky

academic.oup.com/cid/advance-...

Today I am very proud to announce the release of the Antibiotic Resistance Microbiology Dataset - Mass General Brigham (ARMD-MGB; physionet.org/content/armd...) , as part of an NIH-funded collaboration led by Jonathan Chen at Stanford. (1/6)

When plotting, LLMs see what they expect to see - Posit Data science agents need to accurately read plots even when the content contradicts their expectations. Our testing shows today's LLMs still struggle here.

To be effective, data science agents need to be able to read plots reliably. @sara-altman.bsky.social and I wrote about some concerning findings on LLMs' ability to interpret plots when the content contradicts their expectations on the @posit.co blog.

posit.co/blog/introdu...

Gave my 1st talk in NL: how to make multicenter data analysis with patient data actually work.

tl;dr: common data models (global interoperability) + LLMs (data harmonization, mapping, future-proofing) + federated learning (privacy)

Let me know what you think!

drive.google.com/file/d/1N3yk...

Heatmaps show symptom co-occurrence and infection sources. Panel A charts 30 signs/symptoms (skin, cardiopulmonary, gastrointestinal, dizziness, constitutional), with red indicating high co-occurrence. Panel B links infection sources to symptoms via ICD-10-CM codes.

An #LLM extracted signs and symptoms for patients with sepsis with similar accuracy to humans, and identified 7 syndromes differentially correlating with multidrug-resistant infection risk and mortality. ja.ma/47onWVE

Syndromic Analysis of Sepsis Cohorts Using Large Language Models This cohort study compares the performance of a large language model against manual medical record review for extracting presenting signs and symptoms data from hospital admission notes and uses these...

Maybe AI Knows Something That We Do Not!
🆕💫 Cohort study
LLM accurately extracted presenting signs & symptoms from admission notes that clustered into syndromes differentially correlated with infection sources, MDR infections, and mortality #IDsky
jamanetwork.com/journals/jam...

Opinion | We Can Stop Deadly Hospital Outbreaks -- So Why Aren't We? Genomic surveillance can help contain local and nationwide threats

My new piece in @medpagetoday.com

We Can Stop Deadly Hospital Outbreaks - So Why Aren't We?

Genomic surveillance can prevent outbreaks from spreading, save lives, and costs.

So what’s holding it back from being implemented in hospitals?

#IDSky

www.medpagetoday.com/opinion/seco...

#IDsky #Medsky 🧪🦠

New preprint from our lab by Rangachar Srinivasa et al:

We WGS 4 major respiratory viruses in 3 hospitals (RSV, influenza, rhinovirus, HMPV) & found silent transmission happening under the radar

Genomics uncovered hidden spread, complex transmission chains #IDSky
📄: www.medrxiv.org/content/10.1...

How many hospitalized patients need care in the ICU? How many of them survive? What interventions do they receive there?

These are some of the questions I had two years ago while trying to write the "background" section for my masters thesis. But I couldn't find the answers... they did not exist.

The amount of green on this level of evidence guiding antifungal treatment duration demonstrates nicely the research knowledge gap in this field!

#IDSky #ClinMicro #AMR @drneilstone.bsky.social

ondering how this year’s measles outbreaks compare to previous years? This chart shows that 2025 (dark purple) is already about 4x higher than this time last year (light purple), which was itself a sharp increase over 2023. The trend is alarming. Prevention—including vaccination—is critical.

Agree that individual vs population-level goals often get conflated, to ASPs’ detriment

But even for #2, even at an individual level, a decision of which MDROs to prevent pivots on colonization burden, pathogenicity, and ∆ harm once MDR

This still puts Staph aureus and PsA near the top of the list

OK but then to keep going with this…

Staph aureus is just one of thousands of bacteria species in people’s noses, should we base our whole GPC coverage on it?

ID - Return to Basics:

This was the 1st reported case of an adult immunocompetent host who survived measles complicated by ARDS. A 36 yo female ED nurse, unvaccinated, who was exposed to a patient w active measles in October 1989. Ten days later, she developed measles

Your AI can't see gorillas – A comparison of LLMs' ability to perform exploratory data analysis

chiraaggohel.com/posts/llms-e...

Clever tricks with token sampling can guide a "reasoning" LLM like Deepseek's R1 (and the many new models it is already inspiring) into <think>'ing longer, and thereby producing more accurate output

There is a lot more juice to squeeze from these kinds of models.

timkellogg.me/blog/2025/02...