Plenary at #SER2022 with @zeynep re aspects of human behavior that were not adequately incorporated into pandemic response. This is a very dense talk w/o slides so livetweet is a bit bumpy... but talk was super interesting so I did my best. For example, because of stigma, it doesn't make sense/isn't possible to have effective rules that only sick people wear masks.

Plenary from @michaelmina_lab at #SER2022.
Testing is not just a medical tool! Most of the discussion of testing is focused on medical diagnostics but testing is a public health tool. We need to start thinking/evaluating testing as a population health tool. Applications of tests for public health? test to isolate; test to exit isolation; test to enter/stay; test to go; contact tracing. Medical testing is for patient; testing for public health is for others.

Dr. @MadhavThambiset From Mechanisms to Medicines: realizing the DREAM of an AD Cure
Today's @melodem_group talk! Outline:
1. why we've failed to find cures for AD.
2. Establishing a pipeline for id'ing drug targets w/ systems biology (APOE-signature, PREVENT AD based on candidate drugs in mouse models, and the DREAM study, real world analyses of pharmacotherapies)

Capstone of @UCSF_Epibiostat Sampling Knowledge Hub series with @EpidByDesign talking about generalizability and transportability in research. Two issues in interpreting an intent-to-treat estimate as a public health. 1. Internal vs external validity (difference between the study sample and people in general) and 2. Exposures vs population interventions (not everyone in real world will take up intervention).

Thread about @manlyepic & my @jamaneuro commentary re one especially shameful aspect of the FDA approval of #aduhelm. Before working w/ @manlyepic on this, I knew it was bad, but I didn’t know how bad. doi:10.1001/jamaneurol.2021.3404 1/27 In @Biogen’s FDA filing, only 0.6% (ie 19 people) of 3285 trial participants identified as Black, 3% as Hispanic, 0.03% (1 person) American Indian or Alaska Native, and 0.03% as Native Hawaiian or Pacific Islander. Of 9% identified as Asian, 94% were recruited in Asia. 2/n

Really excited for Dr. Patrick Ball of @hrdag's talk. His background is quantitative analysis for evaluating human rights violations, e.g., for truth commissions. @UCSF_Epibiostat #SamplingKnowledgeHub #epitwitter This guy's incredible. Silicon valley background- made software to help people safely document human rights violations. Started in 1991, when a grad student at @UMich soc and demography. Struggled after seeing what was happening in Guatemala and El Salvador- many crimes.

Rohit Vashish from @UCSF_BCHSIt presenting at @UCSF_Epibiostat department meeting about using electronic health record (EHR) data to emulate target trials to understand treatment effects for chronic disease management, example with type II diabetes Beautiful explanation of the data gap: there is just no way to have good head-to-head RCTs of all the important medication decisions for all of the important potential outcomes (retinopathy, acute CVD event, etc). We must use "real world data", e.g. EHR data.

Department meetings at @UCSF_Epibiostat have become surprisingly fabulous. Every meeting a thoughtful covid update from George Rutherford. +Today new faculty member @Jean_J_Feng jeanfeng.com re fair machine learning algorithms in medical care. She thinks of ML apps along 2 dimensions: severity of healthcare situation (low=apple watch for Afib) (high=viz.ai contact to id stroke in process) and along significance of the information provided (low=apple watch) (high=idx-DR diabetic retinopathy).

I hope everyone reads the results in this paper but ignores the conclusions, since conclusions do not seem to reflect the results Batty et al: bmj.com/content/368/bm… @PWGTennant @epi_kerrykeyes @EpiEllie @EpidByDesign @MarcusMunafo @MikaKivimaki 1/n Their question is super important: can we generalize from highly selected samples (HSS) eg UK Biobank (UK) to populations? HSS are much cheaper than representative samples (and in general, high response rates are expensive to achieve), but … 2/n.

Dr Julia Adler-Milstein re turning digital fumes into fresh air (ie useful evidence for clinical care & system design) at @UCSF_Epibiostat seminar. Super cool new Center for Clinical Informatics and Improvement Research. medicine.ucsf.edu/cliir @CliirUcsf 1/n Digital transformation: requires constant evolution & improving tools we use, which is achieved by observing how users interact w/ & use tools. In health care, we're still in early stages of this work-need to move into an era where we adopt continuous test/refine cycle.

So excited for @sherrirose long-awaited workshop on computational health economics & outcomes. @UCSF_Epibiostat #epitwitter She leads by calling for value of interdisciplinary research. Need both strong theory & practical/relevant for practice. Sometimes theoretical ideal and practicability are in conflict. Callout for articles on methods grounded in real problems for journal @biostatistics.