What’s #CoEpi (@CoEpiApp) open source project been up to lately? A thread with some updates & frequently asked questions we’re seeing as there is growing awareness of the options of Bluetooth-based technology to support our fight against #COVID19 (+other transmissible illnesses).
If you’re not familiar with #CoEpi (@CoEpiApp), it’s an app for iOS and Android designed to use open source Bluetooth technology to anonymously log interactions with other devices and anonymously share symptoms to alert others.
How will this work?
First, #CoEpi@CoEpiApp does not have any user-identifiable information. No profile, no name, no username, no picture, etc. The app on the phone only has a randomly generated number that rotates every so often.
When the phone sees another device running a compatible app, it uses the first random number to create a second number that’s called a “temporary contact number” (or TCN). The second device logs this number locally - meaning on the phone itself.
If you don’t share symptoms, nothing leaves your phone. You’ll still benefit from using #CoEpi by receiving exposure alerts if you get exposed.
If you do choose to share a symptom report, the only thing that leaves your phone is the random number and the symptom report.
The #CoEpi app periodically pulls down symptom reports from the server. It only receives random numbers and associated symptoms. It uses the numbers it receives to regenerate TCN associated with symptoms, and compares the regenerated TCN with the local list seen by that phone.
If there’s a match (between the regenerated TCN and the TCN that the phone has previously seen), that exposure information is then revealed to the #CoEpi user, showing what symptoms they were potentially exposed to.
Note that this means #CoEpi (@CoEpiApp) is not doing traditional ‘contact tracing’. It’s doing Bluetooth-enabled anonymous exposure matching and alerting - based on symptom reports. We believe symptom reports are an important *leading* indicator of community transmission.
Contact tracing, while valuable & an essential public health strategy, is usually based off of confirmed #COVID19 tests, which may be limited due to supplies & other resources. Importantly, it’s also slowed down by delays between contagiousness, getting test, & receiving results.
(For more context on the timing implications of #COVID19 test strategies, @trvrb has an excellent thread with illustrations showing the timing and tight timelines to break chains of transmissions with testing and traditional contact tracing:
#CoEpi is designed to empower users, no matter what your situation is: whether you feel you must stay at home until #COVID19 vaccine becomes available, or you're nervous about going back to work, or if you’re an essential worker supporting our community today.
#CoEpi can be used by individuals & their family, friends, and coworkers. It can also be used successfully by other small communities - such as a workplace, residential community, etc. If you’re interested in exploring a pilot for an organization or workplace, please do reach out
#CoEpi is now in early beta testing for individuals - if you’d like to join the list and support our efforts by providing feedback, you can sign up here: forms.gle/MLeKz9nerPvX8f…. We’ll keep everyone posted as we move to wider stages of testing in the next few weeks.
We can also still use more native (iOS, Android) developers, backend or BLE expertise, etc - you can also indicate on the form (forms.gle/MLeKz9nerPvX8f…) if you have other skills & time to contribute to #CoEpi at #WeAreNotWaiting speed!
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1/ What if there was a tool to help identify who might have exocrine pancreatic insufficiency (EPI/PEI)?
EPI is a significant issue for many people with diabetes (likely more common than gastroparesis or celiac).
Here's how such a tool can help PWD👇🏼🧵
#ADASciSessions #ADA2024
2/ The Exocrine Pancreatic Insufficiency Symptom Score (EPI/PEI-SS) has 15 symptoms, rated by how frequent they are and how bothersome they are (aka severity).
n=324 ppl participated in a real-world survey.
n=118 were people with diabetes (PWD)!
#ADASciSessions #ADA2024
3/ Methods:
EPI/PEI-SS scores were analyzed and compared between PWD (n=118), with EPI (T1D: n=14; T2D: n=20) or without EPI (T1D: n=78; T2D: n=6), and people without diabetes (n=206) with and without EPI.
📣 Presentation of the primary outcome results from the CREATE Trial, which assessed open source automated insulin delivery (AID) compared to sensor-augmented pump therapy (SAPT) in adults & kids with T1D, at #ADA2022!
The CREATE trial aimed to study the efficacy and safety of an open source automated insulin delivery system, with a large scale, long term randomized controlled trial.
I just realized it's been 3 (!) years since I published my book on automated insulin delivery, with the goal of helping increased conversation and understanding of AID technology for people with diabetes, their loved ones, and healthcare providers!
I'm still very proud that it is available to read for free online, free to download a PDF (both of which have been done thousands of times each: ArtificialPancreasBook.com), or as an e-book, paperback, and now hardback copy. Proceeds from the purchased copies go to Life For A Child.
And, more recently, it has also been translated into French by the wonderful Dr. Mihaela Muresan and Olivier Legendre!
The French translation is available in Kindle, paperback, hardback, or free PDF download formats as well.
1/THREAD - my presentation is kicking off at #EASD2020 about open source automated insulin delivery.
(You can see a full version of my presentation here: bit.ly/DanaMLewisEASD…, or read the summary below!)
Note we should differentiate between open source (where the source of something is open), and DIY (do-it-yourself) implementations of open source code. Open source means it can be reviewed and used by individuals (thus, DIY or #DIYAPS) or by companies.
Poster 988-P at #ADA2020 by Jennifer Zabinsky, Haley Howell, Alireza Ghezavati, @DanaMLewis Andrew Nguyen, and Jenise Wong: “Do-It-Yourself Artificial Pancreas Systems Reduce Hyperglycemia Without Increasing Hypoglycemia”
This was a retrospective double cohort study that evaluated data from the @OpenAPS Data Commons (data ranged from 2017-2019) and compared it to conventional sensor-augmented pump (SAP) therapy from the @Tidepool_org Big Data Donation Project. #ADA2020
One month of CGM data (with more than 70% of the month spent using CGM), as long as they were >1 year of living with T1D, was used from the @OpenAPS Data Commons. People could be using any type of DIYAPS (OpenAPS, Loop, or AndroidAPS) and there were no age restrictions. #ADA2020
Poster 99-LB at #ADA2020 by @danamlewis, @azure_dominique, and Lance Kriegsfeld, “Multi-Timescale Interactions of Glucose and Insulin in Type 1 Diabetes Reveal Benefits of Hybrid Closed Loop Systems“
Background - Blood glucose and insulin exhibit coupled biological rhythms at multiple timescales, including hours (ultradian, UR) and the day (circadian, CR) in individuals without diabetes. But, biological rhythms in longitudinal data have not been mapped in T1D. #ADA2020
It is not known exactly how glucose and insulin rhythms compare between T1D and non-T1D, and whether rhythms are affected by type of therapy (Sensor Augmented Pump (SAP) or Hybrid Closed Loop (HCL)). #ADA2020