 So thank you so much for your participation. I'm very, very happy to have you involved. As a quick reminder, we have a listserv that we'd love to get you involved in so we can have regular conversations outside of these meetings as well. We also have a chat channel through rocket.chat that we'd love to have you participate in as well. With that said, I'm gonna hand over to Erica. Erica. Great, thank you, Rich. Thanks everyone for joining us again today for our special topic meeting on COVID-19. We have a really exciting speaker for you today. So I'm gonna go through a couple housekeeping items and then get right to that presentation. We also have to do a quick update of our subgroups. So let's try to keep that really quick so we can get to the bulk of the meeting. So just to remind you, this meeting is being recorded. Also, I have to show you the Linux Foundation Anti-Trust Policy. We've pretty much all seen this before. It's basically just saying be a good person. You can read over that. And then next, is there anyone on the call that would like to introduce themselves that's new? Please unmute yourself and tell us where you're located and what your interests are in blockchain and healthcare specifically. Is there anyone that would like to introduce themselves? Sure, this is David Pitt. I'm new to the SIG. Oh, hi, David. Where are you located? I'm located in Kansas City. I'm with Keyhole Software. Also, I believe from Keyhole Software, Maddie Slack and Zach Gardner have also joined. We're interested in hyperledger blockchain and also healthcare applications as we do work in that space quite a bit. Wonderful. Thank you so much for joining with the team. That's terrific. Anyone else? Hey, good morning, everybody. This is Markey Allen. Hi, Markey. How are you? Washington, D.C., how are you guys? Good, how are you doing? Get to have you on the call. Yeah, absolutely. Oh, yeah, I have more to say. Sorry, didn't mean to cut you off. I'm with Clinical Squared. We're a HIT consulting solutions developer and software developer company. And we're building crazy things on blockchain that make the world taste better. So really excited to connect with some of the people in the SIG and spread the love and get some more knowledge and share some information along the way. Wonderful. Thank you so much for joining today. I don't. Anyone else? All right, I just wanted to point out we also have our HCC membership directory up on the screen. It's a great place to connect with other members and you can put your information, your company in here. And it's great for networking. So I'd highly recommend you do that. And you can let Rich know or create a Linux Foundation ID to get on there. So, and with that, we will do our subgroup updates starting with the patient subgroup. Is Dennis on the call? Hi, everybody. Hi, Erika, how are you doing? Good, how are you, Dennis? It's getting a bit colder again in Switzerland. But under these conditions with a pandemic, we are doing very, very well. From our sites, we had our last meeting last week. And we developed the further part of the patient recruitment on the solitude. And we want to also integrate protocol builders together with the e-consent part on the solitude part of our proof of concept. And anybody who wants to join us in the call, very much welcome. Our meeting call is every weekly. The next week of this call week, this next Monday, we welcome anybody with domain knowledge in clinical trials and in blockchain technology or any interest to improve his expertise in both domains. You are very much welcome. Thank you so much, Dennis. If anyone wants to reach out to Dennis on that, let us know. And next, we have the pairs. The group is Ravish on the line. Yeah, Rika. Hi, Ravish. How are you? Good. How are you doing? Good. Do you want to have a quick update on the pairs, that group? Sure, sure, sure. So just a quick information. We meet every other Friday. So our next meeting is next Friday from 1 to 2 PM Eastern time zone. And last week, just a quick update from the last week, we started looking at hyperledger fabric. And we are trying to use a Joget low-code platform, which has a plug-in for hyperledger to be able to build applications. I did get a chance to go through the integration. And we were doing some hands-on last week. I know some of the folks were not able to join. So we plan to kind of reset and redo that next week as well. The idea is to leverage this knowledge to start building a POC on the prescription management that we have. And Erika, maybe next time I can give an overview of the use case that we are working on right now. Yeah, that'd be wonderful. So if you can put me on the agenda, I will be glad to cover that. But anyone and everyone is welcome to join our meeting. It is at an exciting time wherein we are deciding what tools we are going to be picking up to build this use case. And we have also reached out to one of the payers who is interested in joining the effort for the POC for kind of a validation as well. So I think we are at a good exciting times. And I'm looking forward for anyone else who wants to join from payer standpoint and overall prescription management if you have any expertise in that domain. I would love for anyone to join. The goal is going to be in the next few meetings, start putting together an end-to-end use case in a prototype working end-to-end. So that's what the focus is going to be. Wonderful. And Ravish, I'd love to come to that, too, being a pharmacist and having a background in prescription management. I would be happy to join the meeting as well. Excellent. Yeah. And so thank you for that update. You're welcome. And then is Stephen on the call from the Health Care Interoperability Subgroup? I don't see him on the call. I don't know. Do we have any members from the subgroup that would want to sort of give us an update? OK. Good. And just a reminder to please mute. If you're not speaking, I'll go ahead and mute everyone. I'm going to mute everyone. So if you need to speak, please unmute. OK. And then Rich, do you want to give us an update on the Wiki redesign team? Yeah, so we have, in addition to subgroups, we, of course, which, and really the subgroups for the Special Interest Group, are really where people have an opportunity to do real work that's focused around specific topics. And as Erica called out, we have three separate subgroups, one for payer, patient, and then, of course, the Health Care Interop subgroup. As well, we have ad hoc teams, which are really intended to be more shorter term, intending to focus on very specific issues that relate to more operations of this organization. We have the Wiki redesign team, which is sort of an ongoing team of folks that sort of phase in and phase out. And we're always looking for folks who are experts with the Confluence Wiki program, which is what we use here in Hyperledger. So always interested to have you join that team. We're always looking for great ways to improve the experience for membership here. So feel free to contact me if you have an interest in doing any work with Confluence. And we'd be thrilled to have you. Thank you. Great. Thank you, Rich. And then I'll give an update on the use case team. We had rescheduled our meeting for a couple weeks from now. This group has a few different use cases that we're developing showing how Hyperledger and blockchain technologies can be used in use cases like supply chain and provider credentialing. And payer is another one, patient records as well. So we've got about five people in the group. But if anyone's interested in joining, we're just creating documents, kind of short documents for the industry to kind of get a high level overview of how blockchain technologies can be applied to these different use cases. So if you're interested and you have any expertise, or even if you don't, we're really just doing, basing these on research more than anything, on primary literature, and things that are already out there. So it's really open to anybody, especially if you are a clinician or in these different industries and have a background, we would love to have you join us. So please let me know if you're interested. Erica, just a quick thing. I will try to send out the information to you. And it's available on our wiki as well, if you go to the pairs of group. The use case that I was talking about regarding the pharmacy management, I think it might be something that you want to look at as well. Great. Yeah, I would love to. And if I can't, I'll connect with you directly offline too after the meeting and get some more information. Yeah. So with that, we're going to move on to our special topic. We've been doing these for, I think this was our fourth one. And we've had speakers discussing things from all over the world, from Switzerland, Mexico, Africa, India, on topics related to battling the COVID-19 virus with regard to supply chain, connecting people in services. We had one on identity and also provider credentialing to get some of these health care providers credentialed more quickly. So we've had a lot of great topics around COVID-19 and blockchain technologies. And today, we are very honored to have Dr. Wendy Charles, the chief scientific officer at Borscht IQ, who's going to be talking about some of the challenges and opportunities around COVID-19 research from a public health surveillance standpoint and how blockchain technologies can be applied. And I want to give her as much time as possible. So Wendy, if you're ready, I'll stop sharing and you can take over. Does that sound good? That sounds great. OK, I'm going to stop sharing. Let me know if you have any problems. OK, let's see. I don't know if it's sharing. I'm going to stop. I can see. Yeah, I saw your screen. OK. I don't now, but I just did. There we go. Yeah, it's great now. All right, do you see the full slide view now? I do. OK, perfect. All right, thank you for that. All right, thank you very much for inviting me to speak today. I'm Wendy Charles. And as Erica mentioned, I'm the Chief Scientific Officer for Brist IQ. And that's a blockchain platform provider that specializes in health care. I'm pleased to see so many friends on the call. And we'll be presenting material about blockchain and COVID-19 research and development. So today, during this session, I will provide a brief primer of the challenges with COVID-19 research, discuss strategies for proposing blockchain-based solutions. And I'm going to give examples of digital contact tracing, provide an update about research foundry, and we'll have some questions and answers. Now, to maximize the educational value for you, I'll cover a lot of material. And I'll speak quickly. And it's likely that I'll answer your questions in later slides. So therefore, please continue to mute yourself and hold your verbal questions until the end. Feel free to post your written questions in the chat. And if we don't have sufficient time to address all your questions, I can always provide written answers to remaining questions in a follow-up email. And as Erica noted, please, you can download a PDF of this presentation from the Health Care SIG Wiki page. So before I get started, I'd like to offer the following disclaimers, starting with my assertion that these are my opinions and observations and do not necessarily represent the views of my employer, Brist IQ, the Linux Foundation Hyperledger Efforts or the Hyperledger Healthcare Special Interest Group. Next, I am a scientist with 28 years of clinical research experience, but I don't work as an epidemiologist. So my discussions of epidemiology to describe COVID-19 are based on academic training of epidemiology instead of real-world experience. I'm sure that health care providers on the calls such as Jonathan Holt could provide deeper insight about real-world applications. I try to include as many international efforts when describing COVID-19 management, but I focus the most content on what I know US efforts and specifically the state of Colorado for granular details. And last, my perspectives bring together my work for a blockchain company, my years of conducting clinical research and my experiences with evaluating health care technologies, health information technologies for and within health care settings. So let's start by discussing challenges in COVID-19 epidemiology research. So I've now interacted with dozens of blockchain programmers who focus only on describing what their technology can do but don't actually measure it. There are a number of blockchain-based products being rushed to market that really need to conduct research if they want to have any credibility. I'll first focus on some of the research on COVID-19 disease spread. And my goal is for our product developers to understand what certain terms mean and how to incorporate research concepts when considering that health care clients make evidence-based decisions. So when you create evidence or come across evidence in a peer-reviewed publication, it's important to understand which types of evidence have more credibility. I'm showing two different lists of evidence and I'm kind of combining them in my description. At the very bottom, which is not actually evidence, is intuition, a hunch or belief. And a hunch is not evidence even if you are the president of the United States. Next, anecdotal evidence means that you're describing observations or medical test results from one or a few patients. And then collectively moving up, as research design and methodology becomes more controlled and sophisticated, the results have more respect and credibility. At the very highest level, evidence is a meta-analysis. And for those of you unfamiliar with this concept, what you do is you take the data from many high-quality studies to determine large-scale trends. And if you look at this graph on the right side, you'll see specific data points, dots for standardized study findings adjusted so that they are all on the same scale, often like a Z score for those of you who've taken statistics. The bars coming out of each data point show the spread of scores within a study, also standardized so that they're all on the same scale. Now, while it would be ideal to conduct meta-analyses on COVID-19 studies, there just hasn't been enough time yet anyway to conduct enough high-quality studies to make solid conclusions in a meta-analysis. But we predict that this is common. A popular type of epidemiology study that's somewhere in the middle of quality of evidence is called a case control study. And a case control study provides the odds of developing disease based on exposure. And I'd like you to look at the methodology in the colored boxes on the left side of the slide over here. Now, to distinguish between cases and controls, you must have the ability to clearly define and differentiate between people who have the disease and people who do not. And for each of these categories, you should have a clear delineation of those who were exposed to a disease and those who were not exposed or had... An exposure is not just exposure to the pathogen. Exposure can also mean having a pre-existing condition like diabetes or hypertension. Now, why is this type of research so hard with COVID-19? Because the incubation period is so long, it's very difficult to know for certain if you've been exposed or how somebody might have been exposed. And also, there aren't clear ways to distinguish between those who have the disease and those who don't. And I'll explain more about what I mean when I say that. So, of course, we're aware that people can have COVID-19 symptoms without showing... Have COVID-19 without showing obvious symptoms. But to create a definitive diagnosis, scientists had to develop laboratory tests to detect COVID-19. And developing diagnostic tests is much more challenging than you may think. Here's a grid to show how to determine the quality of tests. And diagnostic tests, for any matter, but including COVID, need sensitivity, which is the degree to which a test correctly identifies someone who has the disease. Specificity, which is the degree to which a test correctly excludes someone who doesn't have the disease. Validity, which asks, is the test measuring what we think it does? And reliability, do we get the same results when repeating the test? And to get these statistics, the new test is measured against a gold standard, which is a test with high validity and reliability. It's well-respected in industry. But do we have a true gold standard for COVID-19? I don't know. Remember the early problems with the tests developed by the US Centers for Disease Control, the CDC? Recently, a physician at Denver Health, which is an academic medical center in Denver, which is where I used to work, said during virtual grand rounds that the hospital acquired 20 different COVID-19 tests. And the test results didn't always agree. So, which test do you believe? It takes a lot of testing called validation studies to get sufficient information to use the test to make diagnoses with confidence. So once you diagnose someone with COVID-19, how do you enter all that information in the patient's health record? So at the time that COVID-19 started to spread, there were no diagnostic codes. This chart shows a sampling of ICD-10 standard diagnostic codes, while not shown there are also new LOINC codes to enter COVID-19 laboratory tests. And when creating a COVID-19 blockchain solution for healthcare, just be aware of the appropriate diagnostic codes. Now, we've also been creating projections based on models produced by epidemiologists. And there are some absolutely amazing epidemiologists working on this crisis. So why did the models seem to be so different? As George Box has said, all models are wrong, but some are useful. So first and foremost, there's a need to create models of the disease and possible outcomes. And this allows epidemiologists to create targets for intervention. What you see here is a model created by the state epidemiology team in Colorado. And I just wanted to emphasize I have so much respect for this team. And in fact, the governor of Colorado, Jared Polis, really listens to these scientists and wants to be briefed twice a day. This is a model produced by the Colorado state epidemiologist that shows projections of need for ICU beds based on different levels of social distancing. You can see that there's a different projected peak of ICU need based on different levels of social distancing. Now, on the right is a model produced by the Institute for Health Metrics and Evaluation. Why do these models look so different? But models are sophisticated, longitudinal regression analyses where many factors have to be entered as assumptions. So the most common assumption is the degree to which people are successful with social distancing. But when you use different assumptions, you get different models. At the end of March, when there was enough data about COVID-19 cases in Colorado, the state epidemiologists were able to create estimates of some of the factors to refine their models. And as you can see in the estimates of the proportion of individuals who self-isolated, identifying symptomatic cases and the effectiveness of social distancing, it was challenging to control people's behaviors. Now, this data is from the end of March and I haven't seen yet data from April, but we would expect that there would be more efforts to improve social distancing. This is a map from Tuesday that shows mobility of our cell phones using GPS data. This graph doesn't show social distancing but uses a traditional grading scale of A through F to show how well we are reducing non-essential trips and reducing encounters. And the mobility statistics can also be broken down by county within state. And these grades take into account a number of factors with some examples on the left side of the screen here. And all of these factors together create a composite. And there are several grades, there are also overall grades for mobility reduction by county. And I noted that the county that I live in or Apojo County was the only county in Colorado to receive an overall grade of F. Yeah. Epidemiology models can also include community vulnerability and this graph shows a rating severity of outcomes to healthcare, retail and other socioeconomic measures if infected with COVID-19. And maps have specific purposes and may or may not explain phenomena outside of their intended purpose. So for the example of comparing vulnerability to mobility maps for the state of Colorado, I didn't see any patterns that would suggest that counties engaged in less or more mobility if they were more vulnerable. And there are just so many, there are many other types of epidemiology maps too, such as density maps and heat maps. And I won't go into the other types of maps, but be aware that there are many mechanisms by which epidemiologists can create visual representations of disease. Now all these models are used to determine risk and the concern is that there could be, maybe will be, a second peak of COVID-19 cases if social measures, distancing measures are relaxed. So after studying all these important epidemiology research measures and models for COVID-19, how do we return to normal? Boy, that's a good question. This is a sampling of steps that I found across different states and these are ideal areas to target to assist with interventions. The technology approach that we're starting to learn about involves contact tracing and monitoring and I will focus on contact tracing when given examples. So to get back to normal, how can blockchain help? But as I mentioned earlier, so many blockchain innovators are focusing on describing the cool features of their technology, but they often lose sight of the value proposition, the need for evidence and creating solid messaging for their product to be successful. Now in this section of the presentation, I'll go through each of these steps individually with explanations and recommendations. To put the steps into context, I mentioned that I'm using the example of digital contact tracing. I chose to talk about digital contact tracing as the example because it's both timely and pertinent to the stage of COVID-19 management. And as another disclaimer, I am not trained in contact tracing, my knowledge is academic. So of greatest interest to this audience, there are blockchain-based contact tracing apps being developed for COVID-19. And I also wanted to share, I'm not advocating for or against development of contact tracing technologies, but I hope that the steps for product rollout seem more pertinent when we're talking about something we've all heard about. So I'm gonna go back and forth between blockchain-based rollout steps and contact tracing examples. And when you see the image of wireless rings in the upper left-hand corner, you'll know that I'm talking about contact tracing as an example. So when we talk about digital contact tracing, it's also important to differentiate between the digital contact tracing tools used for public health case management and those used for proximity tracking of citizens with COVID-19. I will be focusing on proximity tracking. And proximity tracking is defined by the CDC as tools that use Bluetooth or GPS to track an individual's exposure to cases used in addition to contact tracing tools. And please also note, when you see the abbreviation PHA on some of the upcoming slides, this stands for Public Health Agency or Public Health Authority. As of Tuesday, 53 different proximity contact tracing apps were available in 29 countries. But we don't even know how many more apps are in development. I listed as many blockchain-based solutions that I could find, but you might be aware of more and I'd be happy to learn about more. The blockchain-based apps will be competing with non-blockchain-based apps and these apps are all in production, they've all been used and the Apple Google app is scheduled for release today, May 1st. So if you have an iPhone or an Android operating system, the Apple Google technology will soon be on your phone. So it seems worthwhile to talk about the plan and guidelines published by Google. Now, I'm not involved in Apple or Google technology so if anyone in attendance was part of the development, I welcome your additional input at the end of the presentation. So I thought the first thing that was interesting is that Apple and Google insist on referring to this as exposure notification instead of proximity tracking. I guess that sounds less intrusive. The plan is that digital contact tracing capabilities will be built into the iPhone and Android phone operating systems and that public health agencies can use APIs which are application programming interfaces to build apps, to integrate with that software to use information for health purposes. Google published guidelines that specify that data will only be used by public health authorities for COVID-19 pandemic management that the software doesn't collect personally identifiable information or user location and that if you have a list of people you've been in contact with that information doesn't leave your phone and that contact tracing feature will stop when the pandemic is over and in order to enable this technology to work you have to specifically opt in on your phone. You have to enable the Bluetooth feature and you have to explicitly give permission for it to start proximity tracking. So here's exactly how it's planned to work as published by Google and I thought this was interesting and worthwhile to share. So I'm gonna read the text from these Google images because the font's pretty small. So first, Alice and Bob meet each other for the first time and have a 10 minute conversation. Their phones exchange anonymous identifier beacons which change frequently. Bob is positively diagnosed for COVID-19 and enters the test result in an app from a public health authority. With Bob's consent, his phone uploads the last 14 days of keys for his broadcast beacons to the cloud. And there's a little side note that says apps can only get more information via user consent. Next, Alice continues her day unaware that she has been near a potentially contagious person. Alice's phone periodically downloads the broadcast beacon keys of everyone who has tested positive for COVID-19 in her region. A match is found with Bob's anonymous identifier beacons. And there's a little side note that says anonymous identifier keys are downloaded periodically. Alice sees a notification on her phone that reads alert. You have recently been exposed to someone who has tested positive for COVID-19. Tap for more information. And when tapping, Alice's phone receives a notification with information about what to do next. Additional information is provided by the health authority app or website. So while the Apple Google guidelines insist that they will not collect identifiable information, each jurisdiction may choose to capture additional information about its residents. This is a graphic from the Wall Street Journal and it shows differences among different jurisdictions about the type of information that they have collected for contact tracing. Not shown on this graphic, I thought it was particularly interesting that South Korea not only collected information from people's phones, but also from their credit card purchases and street-based camera surveillance to help establish their resident location and proximity. As we as blockchain evangelists, it's important that we're very clear then about why we would use blockchain in any technology solution. And don't be like this cartoon. This cartoon says, my team has created a very innovative solution, but we're still looking for a problem to go with it. But as you're aware, blockchain must be addressing a need not looking for a need. And as a critical temp, first perform some intel about what's already being done and create a clear vision for how your product can add value. I use this chart. Actually, I use this chart at least once a week. This was created by the World Economic Forum last year, lead author Sheila Warren. And this helps me carefully consider, first, the key dimensions of blockchain that are needed, the capabilities within these dimensions and value drivers that are critical components in the value proposition. In getting back to our example of proximity tracking, I just came up with a few examples of the potential capabilities that blockchain could use to enhance data privacy and security. And while I won't go through it in this presentation, the next step in your value proposition would be to describe the value drivers as they are applied to the targeted situation. And the capabilities and value drivers should apply to both short-term and long-term needs. And you probably see, there's been a lot published about COVID-19 lately, especially we have been attentive to that in the blockchain community. And there have been some really interesting blockchain-based solutions proposed in the last month for COVID-19. And one of them, for example, is the stated need for patients to have more control over their medical records. Well, that is valid. But how is that actionable? You know, if a proposal is not actionable right now, it may or not be practical to address COVID-19. And similarly, if a proposal doesn't have long-term benefit or applicability, it may be passed over for one that does. So if you're designing a COVID-19 technology, consider building in a flexibility that it could provide value in action right now, but be sustainable and provide value for the next public health disruption. Next step, make a list of all the stakeholders involved in any proposal and what their interests may be. Now, from your value drivers, graph the message targeted to each specific group of stakeholders. And I describe this as the what's in it for me message. For the Digital Proximity Tracking App, it seems like all of these stakeholders would apply to some degree. And your design and goals, consider whether you have assembled the knowledge and expertise required. And the US Center for Disease Control, the CDC, reminds us that contact tracing is a specialized skill and it requires people with training, supervision, and access to social and medical support. And also any team working on contact tracing should really have an understanding of medical terms and patient confidentiality. So next, what kind of research do you plan to conduct on your proposed technology? Remember, you really should collect substantial data to show that your technology functions in a manner consistent with your intended purpose and especially for your marketing materials. This type of data collection is called validation studies. And this type of information is not very high on the evidence scale, but it would be ideal to collect more controlled studies. It'd be great if there were clinical outcomes as well. For me, after having worked in healthcare environments for nearly my entire career, I wanna emphasize that healthcare organizations make data-driven decisions. And while you may be focused on cool features, the decision makers are rarely distracted by the shiny objects. As my former colleague, the Chief Information Security Officer at Denver Health used to say, I don't care if you tell me that your product is a hundred times better than what I'm currently doing. Show me the evidence. And those of you who know me well know that I am like a broken record advocating compliance by design. So it's important to note early in the process about all the potential regulations that may be involved in your product for the intended environment. So for example, if your product will be used in a covered entity and will store or process protected health information, you have to design it to be compliant with the HIPAA security rule. And in general, many potential regulations could apply and you have to do your homework and build in the compliance features. It's really difficult. Some people even would suggest that it's impossible to retrofit the regulations into a completed technology. Now when designing proximity tracking tools, be aware that a number of health and privacy regulations could apply. And it's important to note that the CDC has created a set of guidelines of minimum criteria that a tool should have to be acceptable for use of the public health agency. And this is just the kind of information you have to know in order to build into your product early in the design process. Now when designing a new product to be used by healthcare or a public health organization, the approval processes are also typically more complicated. So first, as you are aware, we may need a few to several meanings to just to explain what blockchain is. Next, remember that these organizations must find solutions aligned with CDC criteria or the Office of the National Coordinator of Health Information Technology for interoperability requirements. And the vendor selection process could be lengthy and preference may also be given to companies that have a history of success working with public health agencies or can demonstrate compatibility or interoperability with existing systems. So therefore just make sure that you understand these organizations processes and you plan carefully for the review and approval process. If you thought that the vendor approval process was complicated, just wait till you get to implementation. I was trained and I use a 21 step method for implementing health information technology. And I use that method when implementing a global safety database for pharmacovigilance. And it really helped me to create realistic strategy and messaging. And the same approach really applies when using blockchain as a health information technology. I'll talk briefly about three considerations, buy-in workflow and technology integration as applied to the proximity tracking solutions. So for implementation buy-in, remember that it's necessary to get buy-in from every single stakeholder group. But let's just focus on citizens or residents. So would enough of them trust how the data will be used? Well, think about like for Google. Google has been so transparent about how it has used your and sold your data in the past. Would enough people get tested if there's fear that they would be tracked and that their COVID positive status results would be reported anonymously to everyone they came in contact with for the past 14 days? Let's say that citizens understand the importance of testing and contact tracing, but would they take that extra step of turning on the Bluetooth and explicitly opt into this technology? And would enough people use exactly the same technology for it to be effective? A study out of Oxford was published last week and found that through modeling that 80% of smartphone users, which is 56% of the entire United Kingdom population would have to opt in to exactly the same proximity tracking software for there to be enough data to be effective. It is true that modest benefits could be taken from lower usage, but it's not ideal. The best evidence about software downloads comes from Singapore, where the government strongly encouraged all residents to download one single proximity tracking app called Trace Together. But even after strong government support for one app, only 12 to 20% of the population downloaded the app. Moving on to workflow, any new technology must have a logical fit in an organization's workflow. And while workflows could be modified, humans, as you were aware, are very resistant to change. So ideally, a new technology would have minimal disruption. So what you're seeing here is the example of a workflow used for contact tracing in South Korea. And this is where the proximity tracking technology fits into the workflow. And as you can see, the workflow is described in detail and the technology fit into the existing workflow. That's the last implementation consideration. Integration involves careful consideration of how a new technology can work with existing systems. And those of us who have worked in with health information technology know how healthcare organizations use equipment or systems for as long as they possibly can, even if it can't run the latest software. Well, Apple and Google discovered that 2.5 billion people have the same approach. And let's go through these limitations. Of course, not all adults have cell phones. And which segment of the population is less likely to have a cell phone? That would be the older adults who are most vulnerable to COVID-19. How about smartphones? In 2019, the Pew Research Center determined that only 78% of US adults have smartphones. And in Denver, the penetration rate is a little higher at 84%. But even those with smartphones, Apple and Google, for example, discovered that their proximity tracking software only works in smartphones that have fairly recent Bluetooth chips. So that even excludes my iPhone. Next, the proximity tracking software has to run constantly in order to transmit the identifier beacons. And this process uses a lot of resources which drains the battery. And last, the software can be pretty sophisticated and includes encryption, which means that it could be regulated by export control laws. And that may be one of the, maybe a reason or one of the reasons why Apple and Google cannot use their proximity tracking software in China in certain other countries. So in addition to technology availability, there are many privacy concerns about using proximity tracking. And first, even though these apps claim that their exposure notifications are anonymous, I mean, it's not kidding ourselves, about the reasonable prospect of figuring out the sources of some COVID exposure. Next, as of two days ago, the New York Times reported that only 25% of proximity tracking apps provided privacy policies. Next, apps that use GPS for proximity tracking are not very accurate at all. And those that use Bluetooth still have limited ranges and capabilities. We already discussed concerns about security and trust and data uses and has proven to be a legitimate concern about proximity tracking. So as an example of that, in India, the Android version of the Erogya Setu app leaked users latitude and longitude to a YouTube server where data were accessible. And Google, as you're familiar with YouTube, said that Erogya Setu app appears to have sent the location data inadvertently. And the problem has since been corrected, but a lot of information about individual users was leaked. And as the final concern, some people view proximity tracking as the same unauthorized surveillance about their whereabouts, which can be subject to abuse. And as an example from South Korea, the proximity tracking app revealed that, this is for a specific example, on the morning of March 28th, anonymous patient 15 in Mapo had arrived at the airport where she initially tested negative at a screening checkpoint after visiting the United States. In Seoul, she had visited a cosmetic store, a fried chicken joint, a hair salon, a post office, and multiple convenience stores and restaurants before testing positive on March 29th. On that popular Facebook post, a group about COVID-19, someone wrote a post announcing her for being so irresponsible. They wrote, just die alone. That's a lot of information and a lot of concern. Now, some people think blockchain could solve the problems of security and privacy, but blockchain does introduce its own set of vulnerabilities and no system is impervious to hacking, greed, or human error. So even though we have great confidence in blockchain's capabilities, we should assess blockchains, values, and vulnerabilities as accurately as possible to maintain credibility. And as the last consideration about developing a new product, how will you ensure sustainability? Now, some governments have intervened in the market of proximity tracking apps to make them mandatory or strongly encourage use of a single app. But then what happens at the end of the pandemic? Also, what policies need to be put in place? How do you obtain and maintain funding for ongoing testing and maintenance? And there's more to maintain, hence the need for flexibility to maintain long-term needs. So as key points to remember, when you're developing a new blockchain-based solution, it requires tremendous first understanding of the market. And I would also add human behavior and ethical consensus privacy, knowledge of current best practices and regulations, data collection to create evidence, risk assessments, especially for the loss of confidentiality and plans for mitigation, and solid implementation strategies and messaging. We are all in this together. And in the interest of time, I'm just gonna go to the last slide, but we invite you to sign up for Research Foundry, which is a humanitarian, non-revenue generating blockchain environment to advance research, prepare for future public health needs and promote collaborations. And it's totally free. There's no cost for anyone ever. It's not a free trial. It's accessible to everyone. You can test a blockchain platform. And in the interest of time, I'm just gonna let you know where it is. And now I am receptive to any of your questions. Wendy, that was a great presentation. That's awesome. And I think the researchfoundry.com will be a good place to use for testing. So if I create a KESA solution, I can use a framework there or services to test it. Is that correct? Absolutely. The technology is, the base platform technology is technically proprietary, but it is interoperable and layers really nicely with Hyperledger and other blockchain platforms. And there's no risk to try it. Excellent. One other thing, I'll say that the presentation was fantastic actually. You've covered a whole lot of different domains in this presentation and you nailed all of them at a very solid level, which is really, really hard to do. So you're not just in healthcare, you're not in IT, you're not just in blockchain, you're sort of all over the place and you really covered all of those well. The one thing that occurs to me, there was one slide you showed, which had to do with the differences across showing the different features for contact tracing across different countries, right? What would have been interesting is to take that one slide and lay it against what was there observed in section rates to see the differences. That particular slide related against what were the actually observed in section rates across those countries based on, in a sense, the data collected, is there any correlation between the two? That would be... Yeah, that'd be really interesting. Yeah, I haven't seen that, but it would be ideal to put that together. Thank you so much. Oh, thanks, Jim. I appreciate your kind words. So, were there any questions in the chat? Hi, Wendy, it's Erica. That was awesome. Thank you for such a informative and interesting presentation. I learned a lot. I'm looking through the chat here. We've got just some comments on here about Facebook, maybe sending consent contracts the next few days. I don't see any other questions. Oh, slides are going to be available. Slides are available on the Wiki for our agenda here. And I'm sure we can get those out to you if you don't have access. So, that was one of the questions. Thank you so much. And I'll go ahead and take back over the screen if no one else has any other questions. Okay, thanks again, Wendy. That was amazing. I can't say enough. I learned so much about all the challenges that we have with COVID-19 research. It seems like we have a lot to learn and Research Foundry is such a great idea and platform for everyone to collaborate risk-free. So, I love that. And I love that BursaQ is doing that. It's wonderful. Oh, thank you. Thank you so much for having, for coming today. And we've got about four minutes. Before I, I do want to touch just here. I'm not going to go through all of this, but here's some of the status of funding from around the world. And you can go ahead and read through that. It looks like there's GrantStation for Global. There's a Canadian rapid research funding opportunity. And then there's also some other status and funding support in the US down below here. And you feel free to look into those through the NIH, the NCI, and COVID Help for Families, which is to help matchmaking for those offering help and those seeking help. That's not a blockchain solution. It's just extra information there. And then the UC Davis Office of Research actually has a directory of funding opportunities if you're interested. You can check that out. And Rich, did you have any other comments before we start to close that? Yeah, no. So thank you, Wendrick, for that. That was a great presentation. And it's really great to get that multifaceted approach to viewing this from a very rigorous scientific point of view. And I think that's gonna be really helpful for a lot of us on the call here that are looking for ways to develop and spin up their solutions in the context of a very rigorous healthcare context, which we have to have. Otherwise, we would fail, I mean, in short. I mean, our healthcare environment has to be done to very high academic standards in order for us to succeed. So this is a great resource, and thanks for that, I appreciate it. Yeah, so Erica just sort of went through some of the opportunities that are really funding related for those of us that are in smaller businesses primarily. A lot of the work that we do, trying to spin up these sorts of solutions require some level of funding. So if you don't get the funding through your larger organization, these are opportunities for you to sort of dig in and seek government funding either here through the US or globally. We continue the sort of the special meeting topics around the COVID virus. This was our fourth. We'll likely continue this again in two weeks. We meet every two weeks at the same time, at the same location. And so coming up May 15th is our next meeting. So two weeks from today, Friday, we'll continue to have this discussion. And it's great to have everyone on the call and we really look forward to having you join us in two weeks. And in the meantime, please engage with the Hyperledger Healthcare SIG community. We have, again, a couple of ways to do so. One way is by way of our listserv. So if you're not engaged with that and signed up, get involved and you'll get regular emails and you'll have an opportunity to converse with other members as well as our Raka Chat channel. And so all those resources are available through our Wiki page. And if you have any questions, feel free to contact either myself or Erica. And with that said, thanks everyone, appreciate it. I think we are adjourned. Thanks all. Thank you, everyone. Thank you, Wendy. Thank you. Thank you, everyone.