NorthStar GAZE

GIS & Health with Rex Dwamena & Johnnie 'Chip' Allen: Turning Public-Health Data into Action

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Where people live can profoundly influence their access to care, exposure to risk, and overall health outcomes. In this episode, Rexford Dwamena explains how GIS helps public-health professionals look beyond countywide averages to uncover disparities at the neighborhood level.

Joined by Erica Phillips and Johnnie “Chip” Allen, Rex discusses the development and application of the Health Opportunity Index, the role of spatial analysis in directing limited resources, and why maps must lead to meaningful policies and interventions—not simply display data.

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[00:00:00] 

Erica: Okay. Welcome back to another episode of the North Star Gaze, and this is the second episode in our series on GIS and health. In the last episode, we gave you a chance to meet Johnny Chip Allen, who's with the Columbus Department of Health.

And, um, as you heard in that episode, Chip [00:01:00] has really a tremendous background in speaking about, uh, social determinants of health and how they relate to health equity and eliminating health disparities, which is not the same thing. Um, if you did not listen to that last episode, I'm gonna ask you to go back and take a listen to it, because there was a lot of great information covered there.

Chip invited Rexford Anson Dwamena who is our guest for this episode on GIS and health. Rex and I met some years ago, at an event, I believe, with the APHA. But, um, Rex is another,, shining star in the public health arena. He's a graduate of the Eastern Virginia Medical School with his master's in public health, and he has been a longtime user of epidemiological methods and procedures, statistical techniques, and research designs to identify high-priority areas by applying geospatial techniques.

So if there's anybody that we needed to [00:02:00] have on this episode of the North Star Gaze, it's Rex. And get ready for an interesting conversation between Rex, myself, and Johnny Chip Allen. Rex, do you wanna, uh, just take a moment to tell us a little bit more about the work that you have been doing in your capacity at the Virginia Department of Health?

Rexford Dwamena: Absolutely. Thank you very much for, uh, inviting me, uh, to this podcast, and I'm glad to be here with Chip, uh, who I've been working with for a long time uh, to address health equity and health disparities. I've been in Virginia Health Department for the past almost 20 years, and all, all the 20 years I've been using GIS,

so, uh, I do more of data analytics, data management, data modeling using GIS, and also, uh, doing more of a policy, um, how to address health disparity in the state of Virginia or in the Commonwealth of Virginia. So my work has been, uh, oh, in the Office of Health Equity. Uh, in fact, I was once, uh, [00:03:00] the acting director for the, um, health equity, um, uh, social EP, and, uh, uh, my work, a lot of my work has been published.

And, uh, I'm glad to be here, and then hopefully I can impart some ideas this evening. 

Erica: Thank you so much for that. Chip, do you wanna , pick up? 

Johnnie 'Chip' Allen: Yeah. First of all, um, hello everyone, and so glad to be with you, uh, Erica, again, for this important conversation, but also with, uh, Rex. Rex's work has really fundamentally changed how I do health equity work, how I did it in the state of Ohio.

And then I took the things that I learned from Rex and took them to the national level when I was a contractor with CDC, so much so that I asked Rex to be on a national project with me because of his expertise. So, um, I can't say enough about this gentleman in terms of his, his brilliance and also his [00:04:00] commitment to equity and using data, and so I'm really excited about this podcast.

Erica: Fantastic. So, Rex, can you tell us what first attracted you to geospatial technology, and when did you realize that it could become an important part of your career? Did you start as an epidemiologist?

Rexford Dwamena: Yes, I did. In fact, when I was in graduate school, I happened to be, uh, doing my master's in the East Virginia Medical School. I was a, a research assistant for the- Mm-hmm ... dean of the school. And I'll never forget this. Uh, he came to me one time and said, "Hey, Rex, uh, I just purchased, um, this tool.

I don't know what it is. Can you just figure out what it is and what it, what it can do?" So I, I took, um, uh, I had to burn the midnight oil to study what it is and what the GIS could do. That was my first time I heard of GIS. That was in uh, 2006. So, uh, I spent the night reading about GIS. I went to YouTube and stuff, and then I was able to make [00:05:00] my first map of that day.

Mm-hmm. So that, uh, I fell in love with GIS because I was able to put my own address on the map. I could relate to the address and the point on the address. Go, "Oh, this is where I live," and all the streets. So I fell in love with that. So my experience stemmed from that, and then I took it to the next level, not just mapping, also by doing the modeling, by using it to do a spatial analysis and stuff like that.

So when I got to a health department, I used this, uh, what I've learned in graduate school to actually also take it to the next level by doing the, uh, small area estimates using GIS and stuff like that. So my experience has stemmed from graduate school up to now, and since that time, I've been using GIS every day, and I mean it, every day.

Erica: Anything you wanna add to that, Chip?

Johnnie 'Chip' Allen: Yeah, so the thing is, Rex, when did you really begin to start thinking about how to use GIS [00:06:00] to help address the issue of disparate health outcomes? What, made you just really start thinking this would be a good technology to, to really even advance health equity? 

Rexford Dwamena: Right, Chief, uh, thank you for the question.

Um, but when I got to health department, um, I had a boss, uh, who, uh, died, uh, for about three years ago. May his soul rest in peace. I'm just cashing in, uh, the, uh, the legacy of his work. He was, uh, he had attended a course on GIS. So when I came in the Office of Health Equity, I was given a project to look into breast cancer, incidence in Virginia.

So I was able to use GIS, we were able to map, map the incidence rate and also use other variables to triangulate the breast cancer data using GIS. So back then, I I was able to show how the, proximity to all the, mammography or mammogram, , uh, services was very important in addressing breast cancer.

So at that time, the [00:07:00] office decided, "Oh, wow, we can use GIS to do stuff like this, so let's invest in that, the product." That's why they bought me my first GIS, uh, uh, um, software at that time. So, the health equity aspect came in because, 'cause I was working in the Office of Health Equity.

We had to, to show disparities, and we have to show the, areas where we should be targeting to address this disparities. So, um, it has been a milestone for me, and I've, learned so much for doing that, and I've continued to do that 

Erica: So I, I want to ask a follow-up question.

As a result of that work on identifying geographic, um, incidents of breast cancer, did the Department of Health expand access to ma- mammography? What did they do as a result? 

Rexford Dwamena: Absolutely. So when I, when we did that, I told my boss, and my boss said, "Oh, hey, there was a new hospital," or , they trying to build a new hospital in Fredericksburg.

And I said, "Why?" And he said, "Oh, because, uh, they found a, [00:08:00] a, a inst- a higher breast cancer incidence in that area." I said, "Well, that is a good thing," you know? "If we are finding them in, uh, in that area." So breast cancer incidence is good. It's not bad, it's good. But rather, let's focus our mind where we have low incidence and high mortality rate.

Erica: Mm. 

Rexford Dwamena: And, and guess what that was? That was the rural areas. Mm. So by then, uh, my boss was able to work with the VCU, to be able to do ma- mammography in these rural areas. And according to that, that time, 2009 or '10, within a month they were able to find women in those areas who were, you know, were having breast cancer that were not diagnosed.

So under-reporting was an issue because of access to care. So based on that study, we, worked with other stakeholders to, , take the mam- mammography machine to these rural areas to diagnose the, the ... So that's a policy aspect of what came out of that, that project, and I was, I'm very excited about that.[00:09:00] 

In fact, a student in, Virginia Tech did a study on that, and they realized that what we were saying was true. The women in those areas were not going in, , for screening, and as a result, they lead high- higher rate of, uh, late stage and a lower rate of incidence.

So that's how we were looking at the data. 

Erica: That's brilliant. 

Johnnie 'Chip' Allen: So, so Rex, I'm thinking about this 'cause when we talk about GIS, most people don't understand that it means geographic information systems, right? We just kind of, you know, sometimes assume that, that folks understand that. But just kind of following up with something else that, that Eric had mentioned.

You have worked in government for years and you've, , had a number of different roles, and you've used this technology in a lot of different public health operations. So can you kind of explain to us how do you get decision makers, uh, policy [00:10:00] makers, uh, stakeholders who don't have a GIS background, how do you really get them to understand how to, use and interpret this really complex set of tools?

Hmm. 

Rexford Dwamena: , Good question, Chip. When we do any, , project in the he- uh, health department, we try to do dissemination of the information.

So we do presentations to our stakeholders. Uh, remember we work in a government and we, uh, health department, we cannot lobby for policy, but we can work through our stakeholders to be able to, take the data and run with it.

Every report that we produce, we give... We don't come out so strictly about the policy, what they should do, but we tell them what could be done to address what we have, we, we have, we, we have done. And it seems to work in Virginia. 

Erica: You know, I think most people really have a limited understanding of what happens in their public health department,

But maybe you can talk a little bit about [00:11:00] how a public health office works, right? How does it work, and how does GIS support the main things that the Virginia Department of Health is trying to do?

Where are the main areas where GIS is supporting the work of Virginia Department of Health? 

Rexford Dwamena: Good question, too, uh, Erica. How Virginia, Virginia is structured in such a way that we have the central office, and then we have 35 local health districts.

And then for every health district, we have a epi at every health district, not excluding even those who are also, uh, analysts So each one of them have, access to the licenses. So VDH has

invested so much money, into, like, GIS that every individual who wants to learn how to do mapping or GIS could get a license to do whatever they have to do. But guess what? Right. The Office of Health Equity is, is known for doing more of complex, sophisticated analysis. We don't just do mapping, we do more of analysis.

So when people need, [00:12:00] uh, very complicated stuff to be done, they come to us, they come to Office of Health Equity. But if you want to, you just want to do mapping, uh, most people can do mapping,

and the Health, Office of Health Equity is a top-of-the-line, uh, or based on the, the work that we do and also. So Virginia, the, the health department has really invested so much money, uh, to what we do, and then, uh, we continue to do that to help, uh, the state 

Johnnie 'Chip' Allen: Can I follow up on that, uh, Rex? Because one of the things that you're known for is the, uh, Health Opportunity Index, and I'm so excited about that work because you helped me do it in Ohio.

And you talk about complex analysis, and I'm thinking about, for example, when we think about how GIS can help in the understanding of social determinants, um, and community risk levels. So what is the Health Opportunity Index, and how have you used that to really help people understand [00:13:00] the importance of identifying specific social determinants of health as opposed to guessing which social determinants of health might be contributing to, uh, health disparities and health inequities?

Rexford Dwamena: Uh, sure, Chip. And I'm glad that you brought up the, uh, the Health Opportunity Index, which, you know, AKA HOI. So, and I, I'll give you a story about that, okay? When I, when I came to Health Department in 2008, uh, or '07, my boss, uh, asked my boss, I said, "What..." I said, "My dad worked for United Nations, and if he had told his boss that he was going to reduce poverty by 50%, and for 50 years, the same area that we identified is still poor by now, he won't have a job.

He would, you know-" Wow ... he would have lost his job." So what he said next, so I said, "There has to be a way to address this, this disparity in areas that..." He said, "Rex, what, what do you think?" I said, "Well, because most of the analysis that the, that we do is at the higher [00:14:00] level, which is the county level and state level."

Now, I'll give you an example. If you go to Fairfax County, the poverty rate in Fairfax is about 6% however, if you disaggregate the data at a census tract level, there are some pockets within Fairfax that have about 18 or 20 or 25% poverty rates.

So that's why we decided to do HOI at the census tract level. So we term the census track as the, neighborhood, to able to use, uh, those variables to construct an index that will say, "Oh, it's heuristic." It will say, "Okay, look at this area. Look at this area."

It might not be able to tell you the whole story, but if you, if you map the composite index, it will direct you to the area where you should be looking, and then you triangulate those indicators with your outcome to see what the, the drivers are in that area. It does not answer all the questions, but at least it point, it points you to the direction where you should be [00:15:00] looking. We have been able to address a lot of issues in Virginia using the HOI.

We've been able to target the population, able to address what people are going through in the rural areas especially, and also the urban areas, to see if, uh, what indicators should we be focusing on. We have 13 indicators. We don't need all the 13. We just have to need those that are prominent in that area that we need to be addressed, and HOI has done that job for us.

When it comes to HOI, everybody in the health department uses that, the tool, to be able to assess or to evaluate, their programs because it tells them it's more actionable Uh, tells them where they should be looking in the state or to address health disparity, and the HOI does, does exactly that.

So I'm glad that you... What, um, there's been a work done I will not regret, and we keep on doing that. I hope we, there's something out there that can challenge HOI 

Erica: This is fascinating. I've heard you, Chip, talk about the Health Opportunity Index, the HOI. But what [00:16:00] I hear is that the HOI can actually help uncover an issue.

So if you think that the poverty level for the whole county is 4%, you might think, "I don't need to do anything in Fairfax County." Right. But when you, when you go down to those lower levels of geography, it actually can reveal something that would not have been revealed otherwise, if I'm hearing you correctly.

Rexford Dwamena: Absolutely. And I usually tell my students, I say, "Look, um, uh, disaggregation and ag- aggregation of data, they are not linear transformation." So you can't say that because a county is 4%, everybody in that county is, is 4%. But at the, at the census tract level, you will find the pockets.

Mm-hmm. And the HOI is able to do that because , the HOI is at the census tract level, so we're able to identify those neighborhood. And then , we evaluate their health outcomes. We are not saying that every area that has a lower HOI has a poor health outcome. That's a good thing, because now we can find out what are they doing [00:17:00] right that, you know, what you expect is not happening.

So the HOI, , takes it to the area where we should be looking, we should be, paying attention to target. It could be education, it could be employment, it could be transportation, it could be housing, and those things.

So that's why I say it's the DNA of the area. So maybe DNA, uh, uh, housing DNA might not be prominent, but maybe education is the problem that we need to address. Stuff like that, 

Johnnie 'Chip' Allen: So and that's the beauty of the HOI, is that you talked about you have 13 social determinants, and then because the HOI is built on the, uh, statistical analysis tool,

Well, it, first of all, it gives you an overall measure of health opportunity, which is that composite index. But the thing that really excites me about the HOI is that you can have 13 social determinants, but it may be only two that, that based on [00:18:00] the statistical analysis saying you should pay attention to.

Right. It doesn't say those other things are not a problem. 

Rexford Dwamena: Exactly. 

Johnnie 'Chip' Allen: But it allows you to focus on- Let's say if it's employment access or if it's, uh, healthcare, you don't have to be sitting back and thinking about which of the other 10 having that effect, you know? And that, that is the beauty of it, and I think that's what helps really me and my health equity work because, you know, there are a lot of composite indices out there that are geographically referenced, right?

So there are a lot of composite index, indices, but not all of them are built the same. And so one of the things that I have done with your help, actually you and Erica, um, are responsible for some of the things that I do in GIS. Now, Erica has this, uh, saying, I call it the health equity golden rule, but it's really the G.

Erica Phillips rule because I learned it from her. [00:19:00] And when you're trying to think about using data, one of the things that, um, Erica has been very instrumental in, in, in my GIS journey is she'll say, "Chip, before you start using this data, you need to figure out what decisions are you trying to make or what question are you trying to answer?"

That's 

Rexford Dwamena: right. Yeah. 

Johnnie 'Chip' Allen: And then she has me write these things out. And so based on what you're saying, if we're talking about using the Health Opportunity Index, if we really, for example, want to know using her rule, hey, um, what questions do I want to answer? One of the questions could be that in the area that I know that I have, for example, high coronary heart disease or high HIV or high infant mortality, I can have all those conditions at the highest levels in the same neighborhoods, right?

But I may not have a sense of what's driving that. And from what you're saying, the health [00:20:00] opportunity can give us insights and what social determinants do we need to look at that might be really responsible for driving a number of different health conditions out of control. And that's the biggest thing that I learned from both of you all.

Rexford Dwamena: Yeah. 

Johnnie 'Chip' Allen: How to ask the question and how to use a composite index like the HRI. 

Rexford Dwamena: Yeah. 

Johnnie 'Chip' Allen: And, and that's exciting. 

Erica: You guys have me so jazzed because the, the real issue, is creating more equitable outcomes, right?

We want equitable outcomes. We, mortality rate to be low everywhere, right? If you've got an area where mortality due to breast cancer is low over here, can we lower it someplace else? And I, I, I, I'm throwing this question out to both of you.

What is our responsibility as GIS professionals to make sure that the work helps create more equitable outcomes, and how can we influence, that aspect of the work that public health [00:21:00] professionals do? 

Rexford Dwamena: So you want to be able to look at the, um, uh, number of variables to tell a story. 

So, um, using, using the AG- ArcGIS, you'll be able to do , for instance, bivariate analysis through GIS to look at, let's say, uh, heart disease and, let's say, poverty, to be able to map and see where they overlap.

So looking at the population, uh, where they are and what they need and what factors are actually driving the, uh, the poor health outcome, and what policy or what interventions can we look at, we can look at the distance from where people live and where they, they get care, stuff like that.

So all those things are some of the factors that you have to take into account in making sure that everybody has the equal access, equal access to healthcare, especially in the rural areas where access to care is, uh, very challenging. So in my work, I've been able to overlap the different data, da- data sets, like, uh, hospitals, uh, FQACs, and then [00:22:00] look at the outcome, look at the, uh, diabetes and other, other stuff to say, "Hey, somebody lives in here in this particular ZIP code or census tract.

How far do they have to travel to get care in that, particular, uh, census tract? And is it equitable?" And the question is, what do you do? That's where the policy comes in.

And, uh, we have, uh, uh, Virginia has been, uh, one of the states that we always talk, we, we talk about making things equitable for everyone. Everyone have access to equal opportunity in the state. And through GIS, uh, work that we have been doing since I've been here for almost 20 years, has always been making sure that everybody has a equal access based on the data and also based on the, how we can display the data on the map, so people can relate to the data on the map and come out with a policy to address the interventions.

Erica: So Rex, when we started talking, you said your dad worked for the UN, and he started with this premise that if the same problem existed [00:23:00] decades after he started working on it, he would no longer have a job. So in Virginia, how do they measure the success of the Virginia Department of Health overall?

What does success look like, and what are the metrics that they might use to show that GIS led to meaningful outcomes? 

Rexford Dwamena: Abso-absolutely. Because we are dealing with the neighborhood level, we're able to target the population, so we know where to go.

And I'll give you another story, too. I used to live in, uh, northern Virginia, Fairfax area, and when I was moving to, Richmond. A friend of mine, he said, "Don't, uh, don't, don't move to Richmond." I said, "Why?" He said, "Oh, there, there's too much crime in Richmond."

But when I got to Richmond, he realized that he was actually looking at the data for, at the county level. So, uh, after a year, I called him back and said, "Look, there's no crime in Richmond." I said, "Crime in a certain part of Richmond."

So using that analogy, like, that's the same way we build the HOI. So we're able to target the [00:24:00] population.

So my office, Office of Health Equity, we have stakeholders in th- these neighborhoods that we work with to address these concerns. In fact, we realized that, , we used to have were higher, infant mortality rate in certain part of, uh, of, uh, Virginia is going down now because we are able to target this population and then come out with intervention to address what is actually driving the higher infant mortality rate or higher low birth weight, .

So GIS has really helped us to do that by targeting these, these neighborhoods and also addressing their concerns and challenges, uh, based on, uh, what you see spatially, 'cause place matters.

Johnnie 'Chip' Allen: And just to kind of, um, follow up with that, GIS allows me to have, whether it's stakeholders, policymakers, public health practitioners, it allows us to really ask some very hard questions that we don't like to talk about. For example, let's just say, um, one po- um, [00:25:00] really serious public health issue is infant mortality.

And let's say we have five census tracts of five neighborhoods that are right next to one another, and we have infant mortality. And somebody might say, "Well, we need to deal with access to care." But what happens when you use a composite index like the Health Opportunity Index and use GIS to figure out that while you have all of these, let's say infant mortality, it might be bad in all these five neighborhoods, but they may be driven by different root causes.

So the reason why that's important is because it allows, those of us who work in public health, some of the factors that are leading to these poor health outcomes, the health departments don't really have the wherewithal to deal with. We don't deal with, for example, if the HOI, uh, index said it was, um- If it was, let's just say employment.

We [00:26:00] don't deal with that. Let's say there are environmental concerns. Well, we do have some environmental health folks and experts in terms of public health. What happens if the environmental cause is beyond what the health department can do? Or what happens if it's spatial segregation, right? So the GIS gives the science base for you to compel the community and decision-makers and other folks to sit down and say, "Listen, um, these problems didn't get here overnight, but we have scientific evidence that shows if not causation, we can certainly say there's a certain correlation with these health issues and some of these social determinants.

What are we going to do about them?" And it forces us to have conversations that we otherwise would like to gloss over. 

Erica: That's so important, Chip, public health agencies don't have unlimited time, and they don't have [00:27:00] unlimited money.

They never have unlimited money. But with GIS, they can prioritize where investments go or, or where staff goes or where services are distributed. , I think this is one of the most important things that GIS can do. I know there are thousands of applications of GIS, but this, what do you do when you don't have unlimited time or money to address an issue, and how do you decide where do you go first, and w- what do you do first?

Johnnie 'Chip' Allen: I would love to go to the Esri conference this year because they're gonna be talking about how to integrate AI into, uh, geospatial technology.

So two things I got excited about. Rex and I had a chance to go to Esri conference about maybe a year and a half ago, uh, maybe two years ago now. Yeah. And they were talking about, uh, digital twins, which is the, uh, visual representation, a digital representation of the world using [00:28:00] GIS. And I think that is so important because you know, the biggest challenge for people who work in health equity is that When they talk about health equity, they talk about it within the context of a particular disparity.

For example, we talk about- Health equity and birth outcomes, but we talked about it by reducing the infant mortality rate. Which is, if we can do that, that's fine, but we don't necessarily visualize a world of what would happen. What would the world look like if we were able to achieve, uh, health equity for, let's say, birth outcomes?

That's not really concerned with making a, a modest reduction in that problem. And so the new technology, for example, like digital twins, would allow us to be able to envision what the physical environment would look like if health equity were to exist in terms of social [00:29:00] determinants, in terms of these things we call opportunity structures, which are the cause of the cause.

So if you have unfair opportunity structures, it leads to poor social determinants. So to be able to, to use that type of technology, uh, to visualize what the future state would look like. 'Cause the hardest part about people when they talk about health equity is imagining what it looks like if we were actually able to achieve it.

And I think the new GIS tools allows us to do that. And then I could talk about this all day, Erica. And then the last thing is they have this tool, um, it's a particular tool, I know others may have it, but it's called, uh, ArcGIS Knowledge. And what it does is it allows us to use graph database technology.

Uh, and the reason why that is so important is because there, everybody has a system. And when you're dealing with GIS, it's usually based [00:30:00] on maybe some type of database, an underlying geospatial database that you have. But the reason why I like the new technology is 'cause you might actually have a business or a public health department, uh, or, um, another nonprofit agency that has data- And because we don't always are able to connect to other data sources, there's a lot of good information that we're leaving on the table.

The graph database technology allows you to connect to different data sets as long as you know the relationship between different data. The 

Erica: reason why that's ex- So there's not, there doesn't have to be one field in common between the two data sets, if I'm hearing you. Correct. Okay. Wow. 

Johnnie 'Chip' Allen: Correct. 

Erica: Okay.

Johnnie 'Chip' Allen: And what that allows us to do then is to uncover relationship, uh, or even solutions to problems that we didn't know existed because we couldn't connect all the dots. So [00:31:00] those are the types of things that, um, I'm excited about. And as an early adopter to all types of technology, um, you know, you can't learn it all, but you can try to learn it all.

Or if you can't learn it all and be an expert in it all, you can partner with people who are experts and bring them together to see how you can come up with new solution that you didn't even think about until you start getting together with people with other skill sets. 

Rexford Dwamena: Yeah. 

Johnnie 'Chip' Allen: So, um, that's how I got with Rex.

Rex knew about the Health Opportunity Index, and it was a brand-new technology for me. And because of our partnership, he actually , changed the trajectory of my whole health equity practice. And it's that type of... You know, 'cause he knew GIS, but he had another tool, and it's about us connecting with people through GIS.

[00:32:00] Because see, when I used to talk about GIS to other folks, half of them couldn't understand or follow what I was saying because they were interested in mapping, but they really weren't into the spatial analysis. And at least, and Rex was on a whole 'nother level than I was. But because we had that thing in common, we were able to take GIS and then talk about the future of where it could be, it would take us.

And it took us to actually developing a tool for, uh, the CDC on a national level. So I mean, it just, this new technology and this, these possibilities of existing technology, if you get with the right people, like a Rex and like a Erica, uh, Phillips, um, who knows what you can do? 

Erica: Well, uh, uh, you are blowing my mind.

First of all, you're, you're, you're taking me back to a question that I wanted to int- ask [00:33:00] Rex, but I, I'm gonna pull this all together. So, you know, one of the things we often talk about on this podcast is that maps by themselves don't change anything, right? There are a lot of people who do beautiful maps, and I love seeing beautiful maps, but I'm m- more impressed when I see a map that can actually make something different happen.

So when I hear you talking about the Health Opportunity Index and how new technology is going to make even the things that we've done that are, are pretty revolutionary go further, I'm, I'm getting very excited. So Rex, let me throw the question to you. What technologies are you interested in? What are you seeing coming down the pipe?

Geo AI or something else? What are you seeing that you think is going to change, the work that you do and help you to see additional changes at the Virginia Department of Health and throughout the country? What are you seeing that you're excited about? 

Rexford Dwamena: I think I'm very excited about Geo AI.

Uh, I'm pretty sure that Geo AI can, fill in the, the blind spot [00:34:00] of Arc GIS. Mm-hmm. So certain things they cannot see, uh, and this, uh, uh, Geo AI will be able to, um, uh, unveil some of these things to us and use the technology to be able to, uh, do a very complex analysis that we, we, we definitely need .

So I'm very excited about that. I have not used it yet in my work, but I plan to do that very soon 'cause I, I, you know, I'm pretty sure that can, I can utilize that to, to do a lot of work that I do in Health Department. 

Erica: , I think some of GIS, some of GIS has become more democratic, right?

We've got story maps, and we've got tools that make it easy to, um, collect information in the field. But some of GIS is really complicated. I'm hoping that Geo AI will make some of these tools more accessible to more people, because there are people who are asking the right questions, but they don't always have the tools to- Right

do some of that complex spatial analysis. So, let's [00:35:00] also talk about what's coming for the workforce, the geospatial workforce. So Rex, some of our listeners are students or they are people who are new in their careers. What skills should they be working on to help prepare them for careers in public health or at the intersection of GIS and public health?

What should they be doing to get ready to be the next Rex? 

Rexford Dwamena: First of all, figure out, um, and then whatever you do in AGU should be, you know, should be guided by, by theory. And look at- Mm-hmm ... what you, what do you want to do, at what level of analysis that you want to do , your, your project, whatever it is.

So le- le- learning how to do, for instance, simple, uh, geo, um, geo, uh, spatial crossing or autocorrelation or stuff like that, or using, uh, Q- QGIS and all those things, skills are needed to be able to actually take a data and tell a story about it. If you can't tell a story about, uh, uh, [00:36:00] about a map, and then people, people will not be able to relate to it.

Because unlike having a spreadsheet that have over 1,000 records, you can use a map to tell a whole, a short story, and people can say, "Oh, my gosh, this is where my house is. Oh, I know my neighbor, my neighbor's road. I know this road." So they can relate to some, some of these things on a map. So learning how to, first of all, understand the data and understand what the data is saying, and it should be guided by what you intend to do and the theory behind what you are doing.

Don't just map the data, but understand what the data is trying to do. Mm-hmm. 'Cause sometimes data and geography and public health intersect in a single truth Or place, you know, place contain numbers into action. So, like, having, uh, these, uh, uh, uh, skills to be able to take data and put on a map and tell a story about it, and then narrate to, uh, your audience, those are the skills that you need to be able to do to tell a story about some of this da- some of this [00:37:00] stuff that we do on a map.

So I usually tell my students, I say, "Look, if you can't tell a story and come up with a policy to address that problem, then you should much rather not, not touch the data." Because- ... people are gonna say, "Ah, and then what do we do?" You know? But any data you do, don't just do the map.

Don't rush to do an analysis. Take your time to understand the variables in the data, and then figure out how do I answer the question that I'm trying to, you know, how to answer the question. So on the map, you do any map in a geospatial analysis, you'll be able to tell a story. But, uh, remember, that does also, does not replace the community input.

Mm. So the fact that you, you are doing all these maps, you can say, "Oh my gosh, this area is, um... There's high poverty in this area." You need to able to consult the community and, and figure out, um, uh, what is going on at all. Sometimes you might also, uh, uh, you know, uh, re- get a his- historic data to tell you, uh, what is [00:38:00] actually is going on.

Because some areas might be, um, you know, just new area that you don't have historic data to back up what you are saying. So don't, don't just interpret a map, but , be careful that the data you have can tell a story, and also the community involvement is also part of what your, your, your narrative, so that you don't, you don't give any false, uh, uh, narrative about the data.

Erica: I hope I haven't said this 100 times already on this podcast, but I may have. One of the most important lessons I learned when I was working overseas was nothing for us without us, right? So there are often situations where people come in and they think they know what's going on in a community or in a country, and they go, "Oh, we're going to do X, Y, Z for you."

And the people that I worked with said, "All of this is great, but don't come telling us what the problem is in our community without first consulting us," right? Then- Absolutely ... I think that's what, what you're saying, that you need community involvement. Absolutely. I also [00:39:00] heard you say, Rex, um, when you speak to your students, so that means that you are teaching also.

Can you tell me a little bit about that work

Rexford Dwamena: yeah. I, so I was an adjunct, uh, for, uh, uh, VCU some time back. Uh, but I do get students who come to me, uh, for internship. Okay. So every year I get at least, at least five students come to me for an internship to learn GIS and how to do spatial analysis and stuff like that.

Erica: So, how do you approach mentoring others? How does that work for you, and how does it work for the people that you mentor? 

Rexford Dwamena: Well, I mean, they, uh... I, I learned so much from them. In fact, I, I, I used- I read a book, it said that the best way to learn is you have to teach someone so they can learn. Mm-hmm. Uh, 'cause, uh, exactly.

So I, I, um, my doors are always open for students who want to learn more, and I can also learn from them. Uh, so, uh, health department has a, uh, internship program, and, uh, uh, some of them are paid, some of them are paid internship. So people can, uh, those who want to come and learn. I, I mean, I do have [00:40:00] a lot of, uh, ideas that I think I can impart on students.

So anyone, uh, my doors are always open, uh, and, and I always, always welcome students to reach out to me if they have any issue they are working on in terms of GI- GIS. So I can always mentor students. I was, I w- I have, I have a bigger room, so I can accommodate a lot of...

Erica: Well, well, thank you providing that service to others, 'cause that's invaluable. So what keeps you motivated, Rex, when you're working on complex public health challenges? I have to imagine that at some points it gets frustrating or disappointing, but what keeps you motivated?

Rexford Dwamena: Well, what keeps me going, what, whether is the, the impact, the impact- Mm-hmm

of the result, whatever is going on. So even though it's very complex, I try to make sure that whatever I'm doing has an impact on the population, not just do stuff because they are fun to do or not because they are fancy, but what is the impact? And I'm, I'm, you know, I'm try- I'm, I'm trying to get out of what I'm doing.

So the impact there, for instance, uh, if I'm working in rural, areas, for instance, [00:41:00] what can I do? What can I show to make an impact on the lives of the people who live in these areas? So that has very motivating for me. And also collaboration. I do, I do collaborate with the other, other...

you heard Chip saying, Chip and I met about almost about 10 years ago, and we have been working together almost all the time to work on this. So collaboration was what keeps me going. You know, it might be complex. I know who to call. I might not have all the answers, but I know who to call to get- Mm-hmm

to get help when it comes to ideas. So, um, those are the two main things that have really helped me to deal with my complex situations and complex analysis and stuff or challenging that I'm going through. 

Erica: Okay. And, um, what gives you hope about the future of GIS in public health?

Where do you think we're gonna be 20 years from now, Rex?

Rexford Dwamena: Well, I'm very hopeful for GIS because, um, I'm pretty sure that, uh, uh, GIS, uh, 20 years ago is not what we have now.

Things are evolving, you know. And when I started, I started using the ArcMap, I did a 7 point something or 8 point something. Right. And now we have ArcPro, [00:42:00] uh, software. So things are, you know, uh, with, with all the new tools that's coming out, are coming out, you know, incorporated into ArcGIS.

I've always been talking about, uh, agent, agent base, agent base, uh, uh, where you have artificial world, uh, to create, let's say, for vaccination. Be able to create a artificial world and say, look, a simulation, and say, okay, uh, if there's a, uh, let's say, uh, a flu pandemic, and let's say only one person is, is infected, how is it going to disseminate through the population?

So agent base is able to do that. It's not yet in ArcGIS now, but I'm, I'm hoping that in the future, uh, they can incorporate that, that model into ArcGIS so that people can actually do that si- type of simulation, uh, uh, to, uh, figure out how disease like COVID-19 will spread to the population, you know, in, , uh, uh, in that, in that, um, that instance.

So hopefully, uh, uh, the three, four, five years to come, I'm, I'm, I'm hopeful to see stuff like that in [00:43:00] ArcGIS. 

Erica: Is 

agent-based different from digital twins? 

Rexford Dwamena: Yeah, I have, I, I think it's different. So agent-based, you create an artificial world. Okay. And then you, you know, um, I, I used to learn in some ways because there's a tool that can use to do that.

Then you, you, you say, okay, if, if the one person has the, let's say, uh, COVID-19 in this particular zip code, and go to school in, let's say, a zip code number, number, zip code in the other end of the city, uh, and then we have people who... So you look at the mobility and all the, how they're connected, you do the simulation, we're able to tell you where the, it's gonna converge.

Erica: Mm-hmm. 

Rexford Dwamena: Yeah, so, um, so I'm pretty sure, I'm just, I'll look at that and see, but I'm pretty sure, I'm, I'm hopeful that, uh, they, they can add it to ArcGIS and make our lives easier. 

Erica: Okay. And my final question before we wrap up. Rex, what do you want from us here at North Star GIS?

What can we do for you and for the, the [00:44:00] Virginia Department of Health? What would you like the listeners of the North Star Gaze to contribute to the work that you're doing? 

Rexford Dwamena: Absolutely. I mean, there's always, we always, uh, uh, health department always has a need for training, uh, for some of the new tools that come, I don't know, come out in AGGIS.

Hopefully, uh, some sort of training that can help, uh, some of the newcomers who are coming out and those who do- even those that are seasoned ones like me. I learn things, new things every day in AGGIS. So such a training, a, a place, a resource that will, resource that will help us to, you know, tap into in terms of, uh, uh, knowledge.

That would be very, uh, would be something. So Northstar can, uh, uh, can be a very good source for us in terms of, uh, learning the new tools that has been incorporated into ArcGIS. So hopefully we can, uh, uh, Virginia Health Department can, can partner with the organizations like yours to be able to, to do stuff like that.

Erica: Fantastic. I, I have to thank you so much for taking time for us [00:45:00] today. I really appreciate your insights, your experience. Uh, uh, you are a GIS professional, but you're a, you're a p- person who's looking at the big picture. You are looking at ways to really move the needle positively for those of our communities that are least advantaged, and I think that is, uh, work that is a higher calling, and I, I'm just, I'm so honored that you took some time to share with us some of the work that you've been doing.

I hope one of the things that you'll leave us with is maybe an example of a map that you created or maybe an older map, maybe one of the maps that you created when you were looking at breast cancer incidents. I'd love to be able to, to actually show people some of the work that you've done. Would, would you be open to doing that?

Absolutely. 

Can we share? 

Fantastic. Yeah. So I mean, 

Rexford Dwamena: yeah. Some of them are actually... Of course, I did a presentation on the APHN, so some of them are actually online, so it's public information. Okay. Yeah, so I can send those, those to you, and then, uh, and that was very informative to show that, uh- Fantastic

you can, yeah. [00:46:00] 

Erica: Well, thank you. Thank you again. Thank you so much for your time. I truly appreciate you, and, um, I appreciate you, Chip. I, Chip had to step away, everybody, but Chip, you know I appreciate the level of people that you bring to the Northstar Gaze podcast, and I'm grateful to both of you for participating.

Thank you so much.

Speaker 5: If you like what you hear and you wanna hear more, please join the Melanated and Mapping Community as a paid subscriber. Also, we are looking for volunteers. If you're interested in learning how to produce a podcast or you're interested in being on air, please get in touch with us at info@northstarofgis.org

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