Geospatial data is being used to help track pandemics and emergencies

One company is using location data to track and prevent future epidemics.

Company is tracking and helping prevent future outbreaks with geospatial data

TechRepublic's Karen Roby talked to Ajay Gupta, CEO and co-founder of HSR.health, about geospatial data and how it's being used in an effort to better track emergencies and outbreaks. The following is an edited transcript of their conversation.

Karen Roby: Ajay, talk a little bit about geospatial data and how it's going to help.

SEE: Big data's role in COVID-19 (free PDF) (TechRepublic)

Ajay Gupta: That's a great question. It's a question that I think the entire industry is dealing with right now, in terms of how is geospatial data really going to help us identify and respond to a pandemic? And I think really to start that conversation, we need to have some clarity on what geospatial data is. A lot of people think of it as just one type of data when it isn't. It's really any data that is associated to a specific location. So, it could be satellite data if that data is associated to a location. It can be health data, social determinants of health data, education data, as long as you can tie all of those sets of information to a specific location. Essentially we call that geocoding the data. Geospatial data, really data at a location is very relevant to health outcomes.

In healthcare, we do recognize that different diseases and different vectors of disease transmission are in the world at different places, right? For instance, a lot of insect-borne diseases are only in the locations where those insects live. That's something that we've always known, and we know that and clinicians know that when they treat and diagnose patients. And yet, we don't think of location-based data when we want to solve global public health challenges. That's just something that I find interesting that I think that as a technologist, especially a geospatial technologist, we can bring back into healthcare that all of the data around a pandemic, for instance, that takes place at specific locations could be used to help identify trends in the pandemic, the growth in this case of COVID-19. And hopefully soon the regression of the disease. Wouldn't that be exciting? And those who are at risk of it so that we can tailor our approach to the needs in a local community.

Karen Roby: Obviously our lives have changed dramatically in the last year and how we work and where we work. I mean, I'm in my living room, you're in your car and it's such a different look at how life has been for all of us. But tracking and the question of where is a hard piece for people to get their hands around, but yet it's so important. You guys were obviously set up to do this and when COVID started, you went right to work to put your expertise in motion.

Ajay Gupta: That's true. As a geospatial firm, as a geohealth firm, we were well-suited to, and we did, support a lot of response efforts. Here in the United States through our support of FEMA and several state newly established coronavirus task forces, and globally through the WHO and a number of their regions across the world. We were well suited for that. And I think you raised a very interesting point of how individuals may not necessarily ... people at a one-to-one level may not really understand what it means to say data at a location where data is taking place. We better get used to that quickly because more and more data analysis done by companies, by organizations, by governments, by nonprofits are going to be taking a look at where data is happening, where consumers are doing certain things in the health context and a contact tracing context and in other contexts. We've got to come to some terms with what our data at a location and where our data is taking place is happening.

SEE: COVID-19 workplace policy (TechRepublic Premium)

Karen Roby: When we look to the future and how this past year will impact things going forward, how does it help to prevent, or does it by focusing on this data? How does it help prevent things like this down the road? And like you just said, our lives are going to change. We have to get used to this, that this is the way it is now because of all this that we've been living through.

Ajay Gupta: Yes. We have to get used to the way that life is, this is what we've been living through. But yeah, I would say we better find a way to use data at a location, use geospatial technologies to identify and prevent future pandemics because the world can't survive another 2020. I mean, I don't think any of us want that, right?

So, yes, it is our belief and we're very confident in it that not just the data, but the specific ways that we can analyze data through geospatial technologies and through our kinds of special machine learning, artificial intelligence application, but that we can use this information to identify the early signals of human-to-human transmission of both pandemic and endemic type of diseases, as well as emerging diseases. Those are really the kinds of diseases that become pandemic, right? The ones that we haven't seen or heard of before. We forget that the COVID-19 is a novel coronavirus that we hadn't seen before.

But yeah, our approach of understanding how data is taking place and the interaction between health and social factors at locations is essential to identifying and predicting when a future pandemic may be coming so that we can alert the world and global nations can take a concerted effort to stop future pandemics before they occur.

Karen Roby: With geospatial data just that the idea that not something that a lot of people would be concerned with or understand, but you are a specialist obviously in this field. Did it take a pandemic to bring this more to light that, yes, this could be our future in terms of how we can prevent things like this from happening as far as using data in this way?

SEE: Gartner's top tech predictions for 2021 (free PDF) (TechRepublic)

Ajay Gupta: Well, unfortunately sometimes we do have changes that are caused by horrible, terrible events, right? That's not uncommon. We wish it could be a different way, but I think we have to find a way to make the advancement of geospatial technologies and adoption of geospatial technologies a silver lining of this pandemic. I think that's crucial. I would say that the fact that we, as in the society of the world, were able to make so many vaccines to treat this disease with so many new vectors and platforms. That's a positive silver lining for this pandemic. Let's hope for, as a geospatial, as a geohealth company, we have to say that the advancement and the greater understanding among normal people, people who are maybe not technologists, that geospatial data has the capacity to help identify large-scale health disasters in advance and stop them. We have to make that a reality and a benefit, a silver lining of this pandemic.

Karen Roby: Most definitely. Because like you said, none of us want, or I don't know if we can survive another 2020. It's been very difficult on all of us, but good to know that those silver linings, like you said, things that have come of it and people too are hearing a lot more about I think and understanding, Ajay, about how things like machine learning and AI can really play a role in things like this helping down the line.

Ajay Gupta: Absolutely. They can play a role because machine learning and artificial intelligence can analyze much larger sets of data than you and I can do in any kind of practical sense. And we simply will have larger and larger sets of data available to us that we'll never get the people, human analysts, the capacity to read through. That means we have to be careful in what algorithms and what approaches we build out of machine learning, out of artificial intelligence, essentially a computer analyzing the data itself. But that is a very real outcome. In fact, I'd say most of the analysis that we provide on COVID and other things that we've shared with the various task forces around the world that are responding to the pandemic, almost all of them are based on advanced artificial intelligence algorithms. And a lot of those algorithms are brand new. They didn't really exist before in the way that we're using them.

Karen Roby: Most certainly. This really is fascinating work I think, Ajay. And again, something that we would like to follow up with, we can talk to you in maybe a couple of months and hopefully we'll be in a better position as far as how many people are vaccinated and we're moving on to a little bit more of a normal life, but we appreciate you sharing your insight on this. And again, we'd love to talk to you again.

Ajay Gupta: Yeah. I understand that we'll all be vaccinated by the end of May or June, and then maybe we'll be back to normal. Yeah. Let's hope. Let's keep our fingers crossed. Yeah, I would love to come back and speak with you again and hopefully we'll have some great news to talk about at that time, too.

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