 Okay, hi everyone, I'm Laura Kergan and welcome and thanks for coming today And thanks as always to Laila Catelier for hosting and making sure things run smoothly with these events But mostly for her energetic engagement with our research and all the projects that come out of GSAP. So thanks Laila We're introducing you today to a project that we've just launched mapping a new politics of care It's an interactive map as well as a longer-term project which uncovers the geographies of community Vulnerability in the US in the context of COVID Next slide we're proposing the contours For a community health core of one million workers to address both the long-standing Inequalities embedded in the social and political landscape of the US and the immediate needs produced by the pandemic next slide We've all been staring at this election map and many of us went back to TV for a few days and all watched the experts Gathered new data to explain the geography of our elections county by county Across the USA in urban suburban and rural categories as well as the racialized and socialized categories of how we voted Next slide Here's Georgia again. Here we are visualizing vulnerability in four different ways county by county this time on our map and you will learn About each vulnerability later in our presentation, but just so you know what the acronyms stand for FBI is social vulnerability index and YPLL is years of potential life lost. Next slide. COVID affects each of our communities differently vulnerabilities that predate the pandemic and have fueled its uneven and opportunistic effects across the United States. It was not hard to try to it was not hard to try to take our data back to the election map. So here you can see some provisional things county by county highest and lowest in terms of our several vulnerabilities. There's no direct pattern here. But lots of room for further research. So you can see, you know, there's no pattern really between the Biden and Trump voters, but then might be once we look at it across the whole country. This project began by a provocative article I read by Greg Consolvis from the Yale Law School from the Yale School of Public Health and Amy Kepchinsky from the Yale Law School. The article was called the new politics of care and in it they said we must build a better future, not just to climb out of the rubble of this pandemic brush ourselves off and start up in the same place we found ourselves in January 2020. The United States is sicker now with COVID-19 but we've been sick for a long while in many other ways. So long story short, we decided to work together. And so together now this map proposes a new jobs program, a program to get millions of Americans to care for each other. Quoting them again, shoring up the foundations of US healthcare by valuing care itself isn't just the first step towards a more rapid effective response to health threats in the future. It will also move us towards a new politics of care that starts from the ground up in places we live, work and socialize. A politics that builds power among caregivers as an act of caring becomes publicly recognized and compensated for the productive work that it is. Done right and without the racialized and gendered exclusions that characterize the WPA, these jobs can be a source of power for those who have never been fully allowed a voice in our democracy. So what we're showing to today is the result of our collaboration, which has expanded to include our amazing team. We've asked each collaborator to present a very short version of what they contributed to most strongly. Jia Zhang will go first and she's a Mellon associate research scholar at the Center for Spatial Research. Darryl Broly is the assistant director of the Center for Spatial Research. Tommy Thornhill is a research assistant at the Yale School of Public Health. Suzanne Illoglu is a post-doctoral research assistant at the Yale, associate at the Yale School of Public Health. After they've presented, Greg and I will talk about how the specialization of this concept has helped in conceptualizing further what tasks a community health core might take on. In the second panel is the work of the CSR students who work together with us over the summer, guided by the same provocation, a new politics of care. They zoomed in much closer on specific topics and places to further our research. We'll keep adding to these case studies on our map in the coming year. I will introduce the students just before the second panel starts. But before we start, I want to thank Greg for this generous collaboration, his dedication to scholarship and research on the one hand and an activism on the other hand is a model for us all. So over to Jia. Hi, I'm going to be walking you through the map we created for this project. So our map has three different views, vulnerabilities, allocations and comparisons. The first view you see here of vulnerabilities allows us to show you how counties have prioritized according to the seven metrics we have identified and incorporated into our map. This is a map of counties in South Carolina. The yellow parts show the highest percentile rankings in terms of social vulnerability index or the most vulnerable when we use the SDI metric. Next slide. When we use the total number of COVID cases in the last 14 days as our metric for vulnerability, we see that Greenville County now has come up to the top. Next. The next tab in our map shows a map view of community health worker allocations. This view shows how one million community health workers will be distributed according to each metric we use. Here's where workers would be allocated if we again use SDI as the metric. Next. And here for the total COVID cases. Well, Next. The last view of the map is called comparisons. It allows us to compare the differences between each of these seven metrics using the number of community health workers assigned as the gauge. Here we're comparing between the two metrics we last saw in the previous slides SDI and total COVID cases. We can see that in some counties such as Allendale County. Next. And Greenville County. These particular metrics we use make a huge difference in the number of workers that would be assigned. Well, in next, while in Florence County, these particular metrics do not make a huge difference. And then here we'll go into more detail about what each of these seven metrics mean. The first SDI as Laura explained stands for social vulnerability index. This is a metric published by the CDC to spatially identify communities that are likely to be most vulnerable in adverse impacts of disasters and disease outbreaks. It contains 15 variables that fall into four broad categories. These categories are socio-economic status, household composition and disability, race, ethnicity and language, and finally housing. YPLL, our second metric represents communities specific health vulnerability in the United States by measuring rates of premature death. The state's highest values for SDI also have highest values for YPLL. Next, Medicaid. Vulnerability is also reflected by the number of residents enrolled in Medicaid. The enrollment criteria shares some factors with SDI such as income, household composition, disability, and employment status, but also have other communities. And our fourth metric on employment is a data set that's released monthly. As the pandemic has rolled through the United States, the unemployment rate has increased really dramatically. So this increase is a scientific, economic vulnerability that we've used on the map. For many workers in America, healthcare access is tied to the job specifically. So with the rise of unemployment, many have been left uninsured or underinsured. I'll pass it over to Der to talk about our COVID case. So in addition to these pre-existing or sort of longer standing structural forms of vulnerability, we've also seen that the direct effects of COVID-19 have exacerbated many of these. And so to examine the overlaps between the current ongoing COVID-19 crisis and these pre-existing conditions. We have used three different ways of measuring the impacts and the direct impacts of COVID-19. Sometimes these impacts align directly with some of the pre-existing or long standing vulnerabilities and other times they don't. So first here we're looking at total recent COVID cases in the last 14 days. These highlight places where the epidemic is currently very large, often directing us to very populous counties, places with large populations. Normalizing these values by population looking at cases per 100,000 residents highlights different areas, often more rural zones where the epidemic is currently very large relative to the population. And then lastly, we look at deaths since the beginning of the pandemic per 100,000 residents. This measure highlights places where the epidemic has been very large at any point since the beginning of the crisis. And so for each of these sort of in conclusion, talking about these seven different ways of measuring vulnerability, and we want to highlight that they're all incredibly partial and flawed and describe some populations while excluding others. But our hope with this project and by bringing these seven different ways of looking at the COVID-19 crisis covering both current and ongoing impacts of the virus itself as well as pre-existing and structural conditions is to provoke policy responses that consider vulnerability holistically and in ways that account for these structural inequalities that have been exacerbated by the pandemic. And so, as Thomas and Sudan will now walk through how these vulnerabilities were used in our project in order to facilitate distribution of community health workers to states and then to counties. Next slide. Oh, they are there. So I'm going to briefly discuss two challenges that are intertwined throughout our project. Next slide. So first, here's a starting definition of community health workers for the American Public Health Association to help give some form to the breadth of our proposed intervention. And at some points I want to kind of stress is that it's a close understanding that there's a kind of link between different communities that they're improving the quality and cultural competency of service delivery. And that it's a lot of emphasis on outreach and community education, informal counseling, social support and advocacy. Next slide. So the first challenge is epistemological. So over the past two decades, there's been an increasing recognition of community health workers in the United States. In 2010, the US Department of Labor designated community health workers with a specific standard occupational classification. In that same year, the Patient Protection and Affordable Care Act included community health workers as a health profession. Finally, the literature on community health workers in the US remains sparse, consisting of either broad descriptive accounts, or more narrow randomized trials for specific conditions with limited generalizability. Examples range from a retrospective study of high resource consuming Medicaid enrollees into Mexico over a period of only six months that suggests community health workers improved access to preventative and social services, and may have reduced resource utilization to a randomized trial of Latinos with poorly controlled type two diabetes in Miami, Florida. And finally, community health workers led to modest improvements in blood sugar levels, but had no effect on blood pressure or cholesterol. Importantly, few studies look at the impact of community health workers across a range of populations and critical outcomes, such as death, averted or health costs minimized. As I said, recently there's been a series of promising randomized trials in Pennsylvania on a standardized community health worker intervention to address unmet social needs for disadvantaged people called individualized management for patient centered targets or impact. And separate from community health workers. In the larger body literature on social vulnerabilities and health disparities touching upon our populations of interest, the publicly available data for these factors has poor spatial and temporal resolution. The scarcity of data is a challenge for the field of health policy and our political leaders. We need more rigorous evaluations of the effects of community health worker programs in the US. There's a general that is all to say that there remains a number of uncertainties concerning the potential benefits of community health workers. Next slide. So the second challenge is ethical. So let us assume that epistemological problems are satisfied, such that we knew with absolute certainty, the marginal benefits each individual would gain from a community health worker. Given it a limited number of community health workers, how should we allocate them? What is fair? I want to highlight kind of five relevant conceptions of fairness. Equality of opportunity, dessert, utilitarianism, prioritarianism and pluralism. Equality of opportunity gives everyone a fair chance of for access, such as a lottery, or a first come first serve. So whether this dessert is based on the idea of rewarding or deserving, given what's due. An example would be reciprocity in which frontline workers are rewarded for putting themselves at risk. Utilitarianism maximizes social benefits and waits all lives equally. Whether it is maximizing the number of lives saved, or maximizing the number of life years saved, such as qualities or dailies, or maximizing instrumental value saved. An example would be such as saving the number of health care workers who in turn benefit the health of the community as a whole. Prioritarianism, like utilitarianism, maximizes social benefits, but it differs by prioritizing the worst off. Prioritizing the most vulnerable, the most sick, or the youngest, as it could be argued that the young have the most potential life to live and therefore have the most to lose. And under pluralism, these various approaches can be combined. An example would be sufficiency, where the aim is to bring everyone up to a determined sufficient level of health. This is a combination of prioritarianism, until the threshold, and then any other method thereafter. A consequence of these two challenges, the epistemological and the ethical, that there is no one correct choice for how to allocate community health workers. This project uses what data we have available now, and paints a picture of how different kinds of vulnerability shape the landscape of the US in different ways. And while we can make better choices with better data, we also must be transparent and critical about our methods in respect to justice and fairness. So far we discussed about different types of vulnerabilities and challenges of fairness. Now we will look at the allocation of resources with the limited data. Next slide, please. In this project, one of the main questions is how to prioritize individuals and communities while allocating limited number of community health workers. We consider allocating 1 million community health workers between counties in the US, and there are 3,221 counties. To do so, first we allocate community health workers between states proportional to the number of medicaid enrollees in each state. The current available data shows that the total number of medicaid enrollees in the US is 76,256,043. So we divide the total number of medicaid enrollees in each state by the total number of medicaid enrollees in all over the US. And then we multiply this ratio by 1 million to find the total number of community health workers we need to allocate to each state. Here in this slide we can see the example for New York, Massachusetts and Connecticut. And we can see how many community health workers we allocate to New York, Massachusetts and Connecticut and all other states will get the rest of it. Next slide, please. When we look at the results of this allocation, we observed that most of the community health workers go to California and then New York, Texas and Florida follows. Next slide, please. After we decide how many community health workers we allocate to each state, as a second step we allocate community health workers between counties in each state. Here we will use Connecticut as an example. There are eight counties in Connecticut, but I will use four of them as an example. By allocating community health workers between counties, we can use different types of metrics. In this one, I will go with last 14 days code cases. Here we can go to the previous slide, please. So let's look at the proportional allocation to last 14 days code numbers between the counties in Connecticut. We are going to use a similar approach, I just showed you in two slides before. When we did this, when we use the same approach, again, we divide the total number last 14 days, code cases number in, for example, New Haven, and we divide it by the total number of code cases in Connecticut. And then we multiply it by the number of community health workers which we assign to Connecticut, which is 11474. When we multiply this, we get the total number of community health workers we assign to New Haven and the rest of the counties in Connecticut. Next slide, please. In the website, under the allocation tab, we can choose different types of vulnerabilities and see the allocation of community health workers proportional to the chosen vulnerability. So for example, we did the calculation for last 14 days code cases, and when we choose vulnerability as last 14 days code cases, the numbers here we observe will be a result of the calculation I just showed you. Next slide, please. And then we can choose different types of vulnerabilities as we talk earlier in the presentation. Here, we can see the social vulnerability index allocation, and we can see the numbers change the number of contact workers we assign each county change. Next slide, please. In the comparison tab, we can compare the differences between different types of vulnerabilities we choose, and then see which counties get the higher number of community health workers. Here, we observe that while Fairfield assigned the most community health workers, when we consider last 14 days COVID cases, Wilhelm assigned the most community health workers when we consider social vulnerability index. Thanks. Thanks, Suzanne. So just before Greg takes over just kind of go to the next slide there. I just want to point out that these abstract shapes refer to real landscapes on the ground and our research is going to take us in new directions as we try and explore things county by county in terms of where populations actually live. For example, this is the Bronx compared to a whole range of different categorized counties. Next slide, which go from urban to rural, right? So you can see over here that the Bronx has tons and tons of people while some of these other counties which show the same kind of SVI range from suburban to rural. Next slide. This is an amazing drawing done by Sarah Zommler and Nelson Dehesus Ubrey in my current advanced studio where they're looking at all the counties in terms of their categories of urban, suburban and rural. Next slide. And just to zoom in on four of these that they're using that they're working on in the studio. Next slide. Next slide. Yeah. And so just for example, this one series of buildings on the upper left hand side is a group of apartments called Riverview, which happened to be the highest owned by the highest evictor in New York City, and was also labeled the Tower of Death because there were so many COVID cases in this building. So Greg, over to you and just to, you know, and thanks to this amazing team, you can see how interdisciplinary the group is and how many different methods we've been using to try and understand vulnerability in the United States. But I guess the question for for us all is what this kind of collaboration brings to each of our to each of our teams and particularly for you how the spatial understanding has furthered your understanding of what community health workers should be tasked to do should a program like this be put into place by the by the Biden administration. Thanks, Laura. And thanks to Gia and Derek, Suzanne and Tommy for all the hard work that went into putting this product together. So, we see numbers every day coming out across our screens, or our newspapers about the number of COVID cases in the United States. And numbers are abstract. And at a certain point we've all become numb to them. But I think what's really important about this project is that many communities were vulnerable way before we ever heard the acronym sorry COV to. And I think we can talk about the social vulnerability index of the CDC or or metrics like years of potential life loss. Again, they take on a certain abstraction that allows us to sort of disconnect from what they really mean. What's important to me about the spatial mapping project we've done here is that this puts facts on the ground. It tells us what the United States looks like. In terms of the shifting nature of vulnerability, depending on how you define it, and how COVID sort of doesn't does not align with with those kinds of pre existing problems that we faced across the US. What's also important is to watch out how things shift in time and place. We talk about the impact of the epidemic in March and April in places like New York City and the tri-state area where we all are right now. But now, as you watch the epidemic shift, the middle Midwest and upper plain states are on fire. And so risk doesn't remain static in space or time and I think that's something that was incredibly important to think about as we're trying to understand how we need to sort of deploy human resources on the ground. We need people to be working on the current claims for public health around COVID, but there's going to be devastation left behind and it's going to be worse in some places than in others because there are existing pre-existing vulnerabilities that the virus preyed on and made worse. And so, for me, seeing is believing. As you watch this map and you click through each of its seven vulnerabilities, you start to think about how you would allocate based on different priorities. As you look at the trade-offs you make when you think about, I'm just going to deal with COVID cases in the past 14 days versus SVR or years of preventable life loss. You realize what kind of trade-offs you're making that there are existing claims on our resources for health vulnerability that COVID may sort of obscure in the moment of this crisis. And so, for me, this is an exciting step to try to think about how we sort of represent the sort of facts and figures in the quantitative modeling that, you know, is based on Tommy and I do as part of our work and puts it into a picture that people can understand and relate to because you can click on any county and call it home. And you can understand what the vulnerabilities look like in your own backyard, even though you may not be able to access the CDC data or the background data that we have. You can look through this mapping project as an x-ray of your own home life and your own neighborhood life, your own county life, your own city life. So that's where I ended. Thanks, Greg. So maybe we should unshare the screen. And if anyone in the audience has any questions and answers, now would be a good time to ask questions. I can put it in the Q&A box. Yes, it's in the Q&A box. So it is interesting as the Biden administration is thinking about this. It was just an article this morning in the New York Times, which outlines that they're thinking of starting a much larger testing program and providing much more access to testing. And I think it's very different to what we're calling for over here, which is the community health workers which go beyond simple contract tracing into, you know, a larger sort of care in terms of health care, which is so different. Do you want to just talk a little bit about the difference between care and health care as we're proposing it? So, you know, in the, this is an anonymous attendees asking, what is it community health worker? And let me try to define it. I'm going to answer both questions. The first question is anonymous attendees. First of all, the Biden pandemic plan says we're going to hire 100,000 people to contact tracing. They want to do testing, right? It's a very specific kind of public health test, which is narrowly defined upon the needs of the epidemic. A couple of things. One is, is that most Americans are experiencing the pandemic, not just as a crisis about the virus. It's a social economic crisis. All the 250,000 dead that we have, there are many communities that are suffering because of unemployment, other health conditions that are sort of starting to, we've seen the highest rates of measles outbreaks in the country right now. So all these health events are happening at the same time as COVID and our emphasis on COVID alone, risk making us foreground the present and not think about what our other health needs are out in our communities. Community health workers are generally sort of a another kind of component of the health system that do preventive care that can help people learn about their health. They do health education. They can do diabetes screening, asthma checks, other things. They're sort of an adjunct to the larger health system that goes out to the communities and works to sort of build up health in the ground up. What we're doing is saying, you know what, in the context of COVID, we're going to need a lot more than that. We're going to need things like food delivery or eviction assistance, you know, legal support. We could need domestic violence counseling and linking up to services. So in our conception, we're moving away from sort of the idea that we need a contact, we need 100,000 contact tracers and saying we need a million community health workers but writ large, that move beyond sort of just the sort of health as health, but think about the social and economic needs of people in our communities so that we can address those needs right now in real time and allow us to sort of build a firmer foundation for recovery from this pandemic. There's a, there's another question here. Thank you for this exemplary piece of research. Was there any type of data you could not get as open data from official institutions and you needed to extrapolate yourself. And did you take the densities within counties into account while mapping COVID-19. Dar, can you answer this question. I think that one of the key questions that's come up for us over the course of the project is the county level scale that we've looked at. And I think this has been really sort of the core challenge for us is that all of COVID-19 data in order to get that at the scale of the US as a whole. And that's really been sort of our biggest limitation in terms of being able to tell more varied and particular stories about how this is playing out on the ground across the US because information about social vulnerability and other demographic factors from the US census is available at finer grained spatial scales. But being able to speak about the contours of the pandemic hasn't been possible at those levels except in a couple of specific instances like New York through zip codes and we're working as a next phase of the project on looking at New York specifically at the sub county level. I don't know if others might have additional things to add but that would be the sort of core point for me. Yeah, this is I would add one more thing so one example of place where we had to extrapolate data was with Medicaid by county. So while you get a lag of Medicaid enrollees by state, it's not available off at the county level only a few states do that. And so we use historical estimates and Medicaid from the census data. Yeah, great point. Did this project look into labor skills aspect of recruiting or training, i.e. addressing the localized social links needed by CHWs. Are there enough workers with a baseline skill set available. This is Greg, you know, we didn't, you know, I, I think, I can't remember what the, I think we have 200,000 community health workers in the United States at the current moment. You know, Charlie Baker in Massachusetts has said he wants to scale up. He said, I can't remember how many contact tracers in the state maybe 1000. So they're, they're big scale ups in different states around the country for for sort of contact tracers we're saying we need a larger more diverse workforce. And they're not going to have this sort of only need the traditional skills of community health workers but a little bit of a social worker background as well. And so there may be a diverse cadre of people who are going to lump under community health workers but could be could be providing a whole set of tasks that that extend behind the traditional motion of the task. Okay. Thank you for the presentation, this is from Diego and Enrique of this awesome mapping project could these maps include observations from local communities with some kind of participation grassroots input process. That would be, that would be amazing. If we if we could do that, you know, I think it would be, it would be a different kind of mapping project, which is not to say we couldn't do it, but it would, it would take a, you know, a different kind of activist approach to making sort of a partial, a partial map rather than this, you know, map which tries to describe the whole of the United States I don't know Greg have you done, we've done some projects like that. But have you done anything that goes community grassroots. We have not but you know, it would be interesting to think about how participatory community research project like this would work. You know, because it's national, it's a little bit difficult to think about how you would do but it could be like a sub project. I mean I just brainstorming right now that you know for New York City to think about what you can see from maps and a neighborhood but which can also see from sort of firsthand reports in the neighborhood as well. Yeah. So, so when we're not making prescriptions about what community health workers should do on the ground I think the one sort of major sort of tenant of community health workers that they should live in the communities they come from and do work to the community needs. And so a community health worker program in Connecticut may look very different than one in New York City or one in North Dakota. But we didn't really go into details about what each of these kinds of tasks should be be done community health workers sort of defined as Tommy talked about it in the PHA definition, but we're talking about a whole wide range of tasks that could be crafted at the local level at the state level. Yeah. Alex this is a great long question over here which is that care, you know just to perhaps try summarize it that care is often informal. It's not out of the legal system I think that's what we're advocating for that care become acknowledged that the kind of many different kinds of care become acknowledged and compensated. You know, so I'm not. I appreciate this thing of pirate care and things that happen below the radar at an upgrade you have anything to say. Can you see this question from Alex skill. Yeah, I think I wanted to answer it. Okay. I think dare. Yeah. I was just flagging for for others, others to answer but I'll put it in our panelists chat but I think the, really, I think that others can maybe now see the answer questions with the really great fantastic link to the amazing work that the library is really sprung into action on the pandemic. Yeah, so I would just echo what Laura said about it is about formalizing. Yeah. Right. Yeah, I mean they're all these mutual aid networks, popping up across the country. Yeah, this is to say that give communities the resources they need to do this pay people in the communities to do this work train them to do this work. Leave them behind after the pandemic is over so when the next health crisis hits, or just the health crisis that already exists diabetes breast cancer heart disease or dealt with with local resources with local talent and local skills. Right. And also just to to quote Greg, he said it in other contexts like you go to the doctor, but community health workers come to you and when they come to you, they learn a lot more about your community than otherwise and community. There's a lot of things about what what's the baseline of what community health workers should know. I think they should know. I think and I'm not a public health expert, but from a spatial point of view they need to know different things in different communities so in Flint Michigan they need to understand about water contamination. You know whereas in the Bronx in New York they need to understand about lead poisoning or you know I don't know what what what other kinds of things or Right. You need to look across the street and see what's going on or the person on the corner what kind of things they're selling in their food cart that's you know compensating for the lack of things that are in the supermarkets. So many things that community health workers can do that go beyond conventional health care. I think that's what we're calling for you know. And it's, and it's part of the research that we need to develop moving moving forward. We're very close to our limit any, any last questions or comments or answers from the team to any of these questions. I mean quickly SBI so SBI is a CDC determined index which you can go to the CDC website and and find that out. So we need to find baseline skills at community health workers Tommy in his slide mentioned the the American public health association definition of it. And we send you to our article called the new politics of care in the Boston review that talks about our expanded vision for for a community health work core. And so that's what I think that's linked in the about it's linked in the about section on the map. And also all the methods and definitions of all of these data sets are linked in the about section on the map and in the GitHub repository on our methods like everything that we've done, you know, even the biases in the algorithm we, we are, you know, are part of the net methods there's no magic here in terms of the numbers unless we don't know how the CDC did their calculation but at least we show all the different layers and how those play out. So, okay so I'd like to move over to the student presentations which give you'll see a much less abstract view and have taken the research to a finer grain of detail. So we're going to start with, we'll be starting with with Spencer Cret and Adeline Chum. And they've done a project called flatten the curve policies and outcomes in covert 19 and Spencer is also a TA this semester in the in CSR. And the second is Nelson Deheso Spooberry, who has done a project code covert 19 and household overcrowding and he used one specific layer of the social vulnerability index to do an analysis. And the fourth project is Nadine Fatale and Adam Fossberg, who have done a project called supply chain, which goes into the long history of various labor forms of labor as you'll see when they show their video. The next project is Caitlin Blanchfield she's a PhD student in the history theory program at in at GSAP and she's done a project called covert 19 and water rights in the Navajo nation. So thank you students and take it away. Spencer and Adeline. Hello, my name Spencer Cret and with my partner Adeline Chum will present our summer project titled flatten the curve policies and outcomes of covert 19. So our project began this past June with an early interest in the topic of flattening the curve. We knew the flatten the curve diagram itself was a rhetorical device, promoted to make individuals conscious of their impact in the fight against but we were interested in discovering more about the actions underlying the kind of change advocates for. And we understood these actions to be synonymous with preventative measures or policies that promote social distancing. So in the first month of research and methodology development for the project, we were reminded over and over again of just how much analysis and visualization is being done at the current moment. And we spent a lot of time trying to find a unique approach to looking at this topic of policies that are influencing or influenced by the curve. So it became apparent that in order for our research to possibly share or uncover something novel, we would have to create our own data set. This project has two main components. It's this new data set and the way we chose to visualize this information. And these both live on our projects website, along with a more thorough introduction and another interactive chart that adds useful context. We examined hundreds of state policies and other forms of published guidance to generate nine preventative measure categories. We looked at declarations, school closures, gathering restrictions, mask policies, quarantine or case isolation, stay at home orders, non essential business closures, restaurant restrictions and bar restrictions. With our data we created a research tool pairing social distancing policies with case outcomes per state. This image explains in detail how to read the fingerprints. Each state has a unique fingerprint which is composed of three sections along the same timeline. The top being the state's cumulative case cases per capital account as a bar graph and overall us case per capital account as a dash line. The middle section is the social distancing policies put in place in the bottom is the cumulative death count starting from January 1 to July 31. The fingerprint is also colored based on the 2016 presidential election popular vote with swing states being those within 10% difference. When using the website the fingerprint first lands on alphabetical order but can also be sorted by most cases per capita and most deaths. The fingerprints can also be filtered by Northeast Midwest Western packs and other states that were not part of any past. These are states formed to coordinate the implementation and rollback of restrictions. We observed in an initial analysis of correlation between case counts with impacts and wanted to see if these agreements played out. This project strength as a research tool is derived from its focus on when certain policy types ended and the ability to evaluate case outcomes with that information overlaid. The summarizer synthesize this project is interested in pairing coronavirus case outcomes per state with the day to day evolution of preventative measures enforced at state level. So since there's not a top down approach nationally directives issued by states very greatly. In March and early April all 50 states declared a total of 10 different types of emergency declarations, not including wildfires heatwaves or hurricanes in order to gain more flexibility in their responses to the virus. Further whether important information is shared in executive orders or by other means by other state departments, various depending on the state. So this project presents the numerous approaches to certain preventative policies related to COVID-19 enacted across the nation, inviting closer scrutiny of our combined efforts to flatten the curve. For my summer project, I focused on understanding the social vulnerability index and the 15 social factors that make it up is include crowding unemployment housing type income and so on. I was interested in understanding how counties were impacted by coronavirus based on their social vulnerability index. In this graphic I plotted all of the counties in the US particularly looking at overall as vi ability on the y axis I located the corresponding state and on the x axis I located the metric of the SBI, which ranges between zero and one one being the highest. Finally I added the COVID-19 out of each state. So the size of the circles represents the amount of cases. This helped me understand how vulnerability based on the SBI and COVID-19 was spread across the country. Now you can see some of the countries that were the highest vulnerability index in the current amount. I then mapped the counties that were most vulnerable overall, and then also looking at them within the state. Here you can see them highlighted in red. I will go back and plot all of the counties with the same graphic but only using the credible social factor of the social vulnerability index as some measure of vulnerability during the coronavirus pandemic crowding serves as a metric to identify counties with the high rates of occupancy per room. Now you can see, calculate occupancy per room at 1.5 or more person per room, which leads to higher vulnerability of a household. This metric is particularly important during the spread of newly infectious contagious disease because crowding is an indicator that helps understand a vulnerable county, rural county urban and rural scale. Now you can see how counties that have higher number of COVID-19 are also have higher number of high rate of vulnerability per room crowding. I mapped again highlighting the most vulnerable counties in each of the states and the most vulnerable countries overall. I then also mapped these counties on a map that shows COVID rates per 10,000 of rural populations. You can see how these counties fair based on their states in the rural country. I then isolated these counties based on the crowding vulnerability, looking more deeply at demographic population size, their classification, and these friends from urban to rural and also ranked in different regions of the country. So today I wanted to focus on two examples that show urban and rural. So for example in this case the Bronx, which has a crowding vulnerability of 9.99. So I zoom in into a census track, which also has very high vulnerability in terms of crowding, looking at architectural typology and essentially satellite imagery on the ground. So kind of mapping these census track population, household type, architectural typology, demographics and overall vulnerability. And on the flip side, I shows this county in North Dakota, which also has a very high vulnerability rate based on crowding. And then I looked at the three population centers and specifically focusing on Oglala, which is one of the highest population centers in the county, and then looking at the architectural typology, which is mostly mobile homes and single family houses. I wanted to show these two examples because based on the research that we developed with summer, crowding vulnerability in this case can range greatly from an urban to rural setting, also just shows us how architecture is implicated in this vulnerability. My name is Adam Vosberg, and I'm currently a second year master of architecture student. Together with Nadine Fetale, who is in our final year of CCP, we made supply chain, which is a video project about COVID-19 and meatpacking plants. So this project started from consideration of spatial clusters that have created COVID-19 hotspots and non densely populated, predominantly rural geographies in the United States. And meatpacking plants alongside prisons and nursing homes that featured prominently in defining pandemic geographies beyond urban areas. Extensive reporting on COVID-19 outbreaks and meatpacking plants highlights perceived tension between the national food supply chain and workers' lives, supposedly justifying the presidential executive order, designating meatpacking plants as a central infrastructure. However, official reporting on the scale of the impact of COVID-19 on meat and poultry processing facilities remains relatively obscure. For us, the state of the data precluded a holistic data analysis, so we instead focus on a narrative supported by certain data sources in a wide swath of secondary literature. So the map on the screen right now shows all meatpacking plants identified as large by the USDA with the gray cross. There are 436 in total. The yellow cross shows meatpacking plants with reported outbreaks, 138 in total, at least as of when we finished this project at the beginning of September. Among those we picked three plants located in rural or semi-rural areas, all operated by diets and foods, and dive deeper into the patterns of vulnerability undergirding them. So we can use the moves between coral pluck maps to visualize our data and satellite images of meatpacking plants and the surrounding areas to show the geography of the data abstracts. Here's a clip from the video. So we looked at the data and we started to zoom in to try to look at the demographics of the sites. And I think it took us a short time to realize that the truth and this is something that can be recounted statistically, but it also exceeds the need for data is that the meatpacking industry primarily relies on racialized forms of labor. Throughout the research process I was deeply moved by an article in the monthly review, which I can share in the chat by a deeply committed scholar called Kerry for sure. In title poultry in prison stewards a general strike for abolition. It relies on writings by the black radical tradition to discuss the intersection of COVID-19 and poultry processing plants as quote, critical sites of racial racial capitalist accumulation produced through an unequal valuation of people in places, which simultaneously robs the worker and the soil. Within this framing we were emboldened to try to use cartography and data to relate how COVID-19 has laid bare traces of historical dynamics that transformed in less than a century. The meat and poultry industry from a household business into an extractive consolidated industry with some of the most exploitative poorly paid and dangerous jobs in the country. So now at one case study from southern Georgia, but there's two more that you can look at with the entire video. So just some closing mediation on the question of ethics. Our project relies on the satellite view and its ability to commensurate geographic and social difference into a continuous plane from which we effortlessly zoom in and out. While seeking to connect patterns of capitalist exploitation across diverse US domains, the dominance of the satellite image admittedly amidst the voices of workers activists in their organizing and struggles against corporate greed. The coalition of worker advocacy groups have taken important steps by filing a title six claim against Tyson foods keystone foods in GBS USA, accusing them of racial discrimination for failing to protect minority workers from exposure to COVID-19. Similarly, the labor of activists and critical journalists in assembling alternative and accessible COVID-19 data sets that correct the partial image provided by official sources must be recognized and acknowledged. Our work would not have been possible without them. Also, thank you so much for our colleagues in the center for special research team for valuable research throughout the process. And please check out the full video. My name is Caitlin. I'm a PhD student in architecture at GSAP. And just a quick thank you to Laura Dare and Gia at the CSR and to Lila in the events office for making this event possible. And so today I'm going to share my project which took the form of a paper. And that looks at questions of social vulnerability and care in the context of the COVID crisis, the questions that I think both the interactive map and the other case studies have addressed so powerfully and asks how vulnerability is historically produced. So if on the one hand we see vulnerability is this kind of chloropleth geography I ask who is rendered vulnerable and how and in this project I look specifically at the Navajo Nation and unpack how COVID took hold there as a legacy of settler colonial policies around the right to land and the right to water. So I want to zoom in here on on three states actually from the politics of care map. This is Arizona and New Mexico and Utah and in this map compares the high SPI rate and COVID mortality rates in in these three states. So you can see kind of in this region here. The incidents of both high SPI and high mortality. And so, when looking at this pattern we can ask, ask why and see perhaps the geographies that sometimes these boundaries of states and counties can occlude. So this is the Navajo Nation, which is a Native American nation in that spans Arizona, Utah and New Mexico. It's roughly the size of West Virginia. And in April cases on the Navajo Nation started to climb really rapidly by May, it had surpassed New York for the highest cases per capita. And the first under reported for the way that COVID data is aggregated by county, the Navajo Nation soon emerged as a site of much media coverage so many news articles with you know images of, of signs announcing kind of new, new protective measures and COVID restrictions within the landscape. And the virus also shed light on the underlying conditions that had allowed it to spread. So underlying health conditions, long distances to care, multi family households and lack of running water. And this is this is what my project focuses on. So over 30% of households on the Navajo Nation don't have access to piped water, making kind of travel to communal wells and taps are households of, you know, other family members and friends, necessary. This is a result of really centuries of expropriating Navajo or DNA water, and also decades long fights to restore water rights in DNA lands, and then to create the infrastructure to make access to this water possible. So here we have a quote from Andrew Curley, who's a DNA geographer, saying that when we see statistics stating that 30 to 40% DNA communities lack running water during a global pandemic. They're not statistics without history, the entire situation is an artifact of colonialism. It is the result of decades of indifference, neglect and deliberate under development. And so, as Curley states, you know, this, this is a crisis with a history, and one that citizens grassroots collectives NGOs, tribal government agencies have been confronting with particular urgency during the pandemic. And so what my project wanted to do was to chronicle the history of settler colonial policies that have attempted to take water from DNA homelands, and the work of tribal members to restore their water rights. So basically seeing how we go from a landscape, or an understanding of the landscape like this I mean this is to be a landscape that that is still existing. From many native nations overlapping to a history where DNA homelands which is kind of in this dashed outline here are first forcibly expropriated by the American Army. In the 19th century and then through a series of treaties and land purchases, built back to the size that the reservation is now. And this is also to say that land isn't just the surface it's what's below and above, and to chronicle a process of the, the expropriation of water that sought to divvy this valuable resource in the, the arid lands of the southwest. There are two laws of prior appropriation that allow states to adjudicate water rights to private property property owners and settler agriculture and industrial processes so here we see sort of when the land entered the jurisdiction of the Navajo Nation, and when the water entered the jurisdiction of the state. And this was also true in laws like the Colorado River compact that divided the water in the Colorado River shed among the seven states that it went through with no provision to provide any specific amount of water to native nations. In the 1963 after a 1908 Supreme Court ruling, called the Winters ruling, the Supreme Court did establish a method to quantify water rights for indigenous nations, which was done by Aragable water feet so how much land could be irrigated. This was used in the 1970s for native nations to take legal action to restore their water rights. So in the 1970s water was taken to court. And what followed was a series of water rights settlements where tribal governments are encouraged to settle for reduced water rights in order to have access to the funding to create the infrastructure. So that makes accessing that water possible so here we have a map by DNA engineering firm that shows existing water infrastructure homes without water and propose new water lines so at state kind of in these settlements are the ways to build this kind of infrastructure. Settlements are a very contested topic and contested issue as many grassroots organizers are trying to push for the full restoration of water rights and see water rights as really an essential issue of indigenous sovereignty. So I want to bring us back to this question of care and the politics of care, especially during the pandemic, many of these activist groups have also been really at the forefront of mutual aid efforts in the Navajo and the Hopi reservation, speaking to the people that are that are really forged on the ground, while President Jonathan Nez of the Navajo Nation has put aside over $400 million of his cares of the CARES Act funding that the tribe received to improve water infrastructure or improve infrastructure, generally but also water infrastructure. So just to kind of close and to return us to some of the questions that that have been asked throughout this, this panel. To me what what I hope this project prompts is a question of what does care look like. And what does it take to get to it how can we maybe think about care in this expanded sense of of caring for water and also caring for the treaties that are that enshrine the protection of it. Thanks everyone for the amazing work. And we have about 15 minutes for questions for questions for our from the researchers. No, Greg, are you, are you still there? Yeah. Yeah. Yeah, great. I wonder if you have any, any comments as well. I know you haven't seen all of these projects, but maybe I know that you're interested in the meatpacking. I had a question for Nelson first. Okay. So you saw a correlation between overcrowding and public cases on the county level. Yes, so. Yeah, yes. So that was the at the, when we were looking when I was looking at the each of the counties through this metric. One way that I started to zoom in a little closer was through the FBI but also true local news article that reported on this phenomenon so I was like, only English. We don't have the covered data at census track level or census block level, but there's reporting that's been going on and so some some cases, they've been reporting on how families have been affected by large families that have our household and working parents that are deemed central workers and how they feel at risk because they have to work. And so, so during this current corollary between that vulnerability in terms of crowding like the FBI and looking at the Yeah, and Spencer and Adeline, I was looking at the New York Times page this morning and they've actually started doing the updates on mask wearing and, you know, all of that but they don't go into nearly as much detail on all the policies as as you do I just noticed it actually this morning have you seen what they've done. Okay, just take a look. I haven't seen the full video but you talk about the racialized nature of poultry and be packing plants but is there any geography of of like what's going on around the be packing plants and this this and Nelson's work a little bit about how people are in what kind of living situations are happening in these communities as well. I'm just curious. Thanks for that first 18 then maybe you can add something but I mean there's a there's a kind of a sort of a long history to that because obviously the normal condition of me packing plants with urban geography in the early 20th century was definitely in sort of like large metropolitan areas and then it post war meaning the 60s and 70s, I guess, maybe the 80s a bit too. There was a lot of consolidation of taking smaller meat packing plants which there were thousands of the United States and then, and then basically putting everything into like super be packing plants that were consolidated by large corporations and they were usually put in more rural areas often because then the majority of cost savings would then be in the cost of labor which is much cheaper than the city So basically what we saw is that like the predominant relationship between all of these spaces geographically was just that they were rural and that was actually by design. Yeah, I mean, we also try to establish that in some places you can see very clearly that a rural outbreak is almost one to one correlated with me packing plants and so that's the first case study we have in the video. So it's clear that a lot of the outbreak is coming in the new ventures for the new packing plants. Can I ask one other question. Yeah, go ahead. The state home policies and the policies in the in the earlier presentation. A lot of people stayed home before there was any institution of state orders to do so. Have you seen any of the mobility data that Uber media and others have had that that it just might be interesting to see what that data says as well on top of the policy data and the COVID data you have. Yeah, that seems like a really interesting direction to take it we definitely tried to go a bit finer detail in terms of when state home orders were required just for a certain population like whether it was out early or whether it was at risk. But we, we, we simplified things pretty seriously to get it into those nine categories, but mobility data would be really interesting to see in relation to the case outcomes to. Yeah. Not seeing any questions from the audience I'm not seeing any. Maybe I can see any. Yeah. Okay. Yeah, if there's no other questions we can, we can wrap up just so that you know we're continuing different kinds of case studies of zooming of zooming in on the data and Greg I know you're going to be teaching a class around these topics in the, in the spring Yeah, correct. Yeah, so, so any kipchinsky I run something called the global health justice justice partnership with Ali military Yale between the law school and the public health school. And we decided, you know, Laura found the new policy of care is something that sort of pulled her in and it's pulled us into. What we're going to do is to usually we, we put our class on three different projects and they work with a community based organization here around the world. The whole class is going to work on coded. And what we're going to do is we're going to go back into the history of the United States of white supremacy of how we think about social welfare in the United States that about the role of the liberalism in the context of the American healthcare system. And think about how our past brought us to this present, and then think about how we take new politics care and move forward. But with the idea that we would work with groups that we've been talking with this past summer like, I see I you move on and others about how partners in health, how we could sort of take a new policy with care actually into the political sphere and make it a reality potentially over the next, in the next administration if it's possible to do with the Cal State Congress but the classes is designed to take this to a next step to sort of move us from an idea of new politics of care to a representation of it out in the real world. Yeah. And the student work was amazing I loved all of it. It was great. Yeah. It's really, it's amazing work right here. Is it here. Is it shareable by the way like I saw the website is open, which like, we can share that stuff. It's 100% shareable it's finished as of today. So it's also a launch of that of that of the student work from the, from the summer. Some questions for Caitlin have you thought about the political results of Native Americans this political cycle, as opposed to the past. And then just thinking about how much more activism in native communities is being discussed and I even remember in 2016. I think thanks for the question. And I mean, in looking over these, these maps over the last couple days. I think one thing that's, that's interesting is comparing kind of as I think Laura was talking about with Georgia in the beginning like voting by or even kind of a smaller degree of zip code or census tract or something. And how that aligns with the COVID maps I know in Arizona specifically the results of which just came in today. I guess finally, I did that like looking at the voting patterns basically aligns to reservation lands and to cities. Pretty exactly. So, I mean I think, in a sense, like that. I mean, I think that mainstream media is looking at this a lot more now in this close election but I think kind of in asking these questions of like, I guess have been overlooked and why I think that, you know, both of these, both COVID and the election has kind of come up as moments in which the media is starting to notice. I guess, things that are affecting indigenous communities more closely. Yeah. Can I share the screen can I share my screen. I think let me just see if I can. Yeah. Just end by showing you the story map which is just what Caitlin is referring to it. It sort of explains how to read the map through looking at Arizona. And I think he has Apache County you can say Caitlin which of these are native lands right. There's quite a few in here. And so, yeah, it goes, you know, and then it also explains to you all the different vulnerabilities that we've included in the map this is sort of the how to read the map. And then it explains all the different vulnerabilities compared to one another and where the highest and lowest are in each of these, and then it goes right in here to some of these native lands within the Navajo Nation and the Apache Reservation. So I encourage you to read this. And then it goes to Yuma County and Maricopa County which is the biggest city, you know, Phoenix and Arizona. And then it goes to what Suzanne was explaining about allocations about the tradeoffs about comparisons between two different vulnerabilities. And then you go to the map. And, you know, on the map, you can look at the various vulnerabilities you can also sort of scroll over to get actual information. Then when you go to allocations, it goes state by state. And then you can go through a number of different vulnerabilities. Again, right, we're asking, we are making a map proposal about how to allocate community workers, but we're asking a lot of questions about how one should prioritize where to send them. And then here are the comparisons again where you can choose to compare two different things. And you can also click on the scatterplot to to get information you can click on the county. This is all incredibly beautifully designed by GSM. And when you go to the about page, it takes you to an understanding of all the vulnerabilities to all the definitions of everything and to a large, large set of references. So I encourage everybody to use this link. And I want to send you and perhaps you can put the link into the to the student to the student work as well into the into the chat. So any other questions here. I can't see there's a there's a new question. It seems like there's some weird timing things happening in the in the Q&A but there's a new question regarding for the students for any of the students to answer. Do you draw any connections between your work and the potential green, red or public health new deal seems a little big maybe for Well, the, I mean, the project is the new deal for community, you know, for public health in terms of assigning community health workers that the students should answer. Yeah. Yeah, I mean, not so much for us I can say I think if there was any kind of legislation that we were plugged into it was kind of the various propositions for regulation of meat packing companies which actually were also quite helpful for like framing of like rhetorical concerns about meat packing plants but not so much for a new deal. Yeah. Greg, do you have an opinion about that. One last thing that we can maybe finish on this is a question that came in during the previous panel. And maybe is a great place to close is what's next in terms of proposing this on a policy level, like is there a sort of vision for for who might use this and and how maybe we can make like a plea to them to. Yeah. So there's a coalition of groups around the country that are starting that are starting to think about how we take a new politics of care and a new deal for public health into sort of the political future starting in January. And I think, you know, just to link it to the question of the green new deal I think it's all tied together. Climate and health are tied together and we need a green new deal but we also need a new deal for public health and they're intertwined intimately so I think, going forward, I think the climate activists and the public health activists in the country are probably going to have to have a meeting of the minds about this but there's definitely a group of people who starting in January or starting now or starting to think about this around pushing for a new deal for public health in this community health worker core. So stay tuned, you'll probably see from different channels. Appeals to help us out in pushing this forward on Capitol Hill and at the White House. Yeah. So while we were working on this we had no idea what the outcome of the election was going to be, you know, had it been a Trump administration this project might have fallen on deaf ears except that, you know, on the ground work would have continued, you know, despite federal, you know, federal funding but I think with this new administration we do have to pressure them into doing the right thing. I do think it's sort of the launcher that has been in some ways perfectly timed, which we didn't plan, can never plan something like that too, too carefully. So but it is, I don't know that people are asking about the project so that's a good thing. Oh, yeah. I'm just going to add like one little comment to the question of the green, red public health new deal is I think kind of like all these projects and thinking about in the context of the public health core, or sort of like pushing for this sense of public infrastructure that I think brings all of these things together. I know from housing to, to health care to, to land rights and policy so and I just to add to, to that as we kind of think about, you know, sort of what constitutes an infrastructure in this context. Yeah. Okay. Thank you so much everybody I want to end on time since we said everything will end at 230 and thank you so much. Thanks students, thanks Greg, thanks Suzanne, Tommy, Daria, everyone.