Interview with Amy Wesolowski

In this edition of FOCUS In Sound, we meet a Burroughs Wellcome Fund grantee who is innovating in methods of detecting infectious disease.

Dr. Amy Wesolowski is an assistant professor in the Department of Epidemiology at the Johns Hopkins University Bloomberg School of Public Health. She holds a BA from College of the Atlantic, and earned her PhD from Carnegie Mellon in 2014.

She completed her postdoc at the TH Chan School of Public Health at Harvard University.

Amy received a 2016 Career Awards at the Scientific Interface, or CASI, grant from the Burroughs Wellcome Fund to further her work on the impact of human travel on infectious disease dynamics. She has studied those elements associated with malaria, dengue fever, rubella, measles, Ebola, and most recently, COVID-19. She uses data generated from mobile phone calling records to quantify travel patterns.

Transcription of “Interview with Amy Wesolowski”

00;00;02;00 – 00;00;34;00
Ernie Hood
Welcome to Focus In Sound, the podcast series from the Focus newsletter published by the Burroughs Wellcome Fund. I’m your host, science writer Ernie Hood. In this edition of Focus In Sound, we meet a Burroughs Wellcome Fund grantee who is innovating in methods of detecting infectious diseases. Dr. Amy Amy Wesolowski is an assistant professor in the Department of Epidemiology at the Johns Hopkins University Bloomberg School of Public Health.

00;00;34;10 – 00;01;03;27
Ernie Hood
She holds a B.A. from College of the Atlantic and earned her Ph.D. degree from Carnegie Mellon in 2014. She completed her postdoc at the T.H. Chan School of Public Health at Harvard University. Amy received the 2016 career awards at the Scientific Interface, or Cassie Grant from the Burroughs Wellcome Fund to further her work on the impact of human travel on infectious disease dynamics.

00;01;04;07 – 00;01;24;28
Ernie Hood
She has studied those elements associated with malaria, dengue fever, rubella, measles, Ebola, and most recently, COVID 19. She uses data generated from mobile phone calling records to quantify travel patterns. Amy Wesolowski, welcome to Focus In Sound.

00;01;25;17 – 00;01;26;12
Amy Wesolowski
Thanks for having me.

00;01;26;27 – 00;01;30;10
Ernie Hood
Tell us about the overall approach your research employs.

00;01;30;27 – 00;01;59;15
Amy Wesolowski
Sure. The majority of my research is really focused on trying to understand how people travel and ways that we can measure and quantify human mobility patterns and then how that relates to infectious disease dynamics. So that’s sort of the focus of the first welcome grant that I have. It’s really trying to use particularly mobile phone data and other sources of data in low and middle income countries to try to quantify and model human travel patterns.

00;01;59;15 – 00;02;04;06
Amy Wesolowski
Then look at how those patterns can help inform models of disease spread.

00;02;05;03 – 00;02;11;25
Ernie Hood
How did you use that approach to study COVID 19 patterns, as you published recently in Nature Communications.

00;02;12;12 – 00;02;40;25
Amy Wesolowski
That Nature communications paper is trying to look at how we might be able to use mobile phone data to monitor and evaluate different aspects of the pandemic. So in general, mobile phone data is often used to try to look at how people are traveling or if there’s like aggregations or congregations of people in different places. And given that most of COVID is transmission, a lot of it happens in sort of like enclosed places and things.

00;02;41;10 – 00;02;59;04
Amy Wesolowski
We’re trying to figure out different ways that you can kind of measure these things. So if you put in travel restrictions, do people travel less if you put in additional social distancing? Do people go to grocery stores less? And so mobile phone data can help provide sort of a real time estimate of those measures and metrics that we can try to evaluate.

00;02;59;27 – 00;03;21;23
Amy Wesolowski
Are people actually traveling less and going fewer places? And so in this paper, we just tried to review and outline sort of different aspects and different epidemiological questions and how mobile phone data might be used. So not just in terms of contact tracing apps, which I think is what they’re often thought about, but also thinking about population mobility patterns, too.

00;03;21;28 – 00;03;39;09
Amy Wesolowski
And then sort of what are going to be some of the biases by using mobile phones. And if you’re using things that rely on smartphones, for example, what are the biases in terms of who is the actual population at risk and what are these different kinds of data is in these different kinds of methods able to measure.

00;03;39;22 – 00;03;42;11
Ernie Hood
So what were some of the results of that study?

00;03;42;28 – 00;04;07;02
Amy Wesolowski
Yeah, So I think some of the results are that there’s a lot of promise in using mobile phone data because a lot of people own a mobile phone. It’s possible now and companies and telecom regulators are becoming much more open to being able to utilize some of these data for public health purposes. And there’s a lot of work and a lot of like pipelines on how you can actually extract these data and analyze these data.

00;04;07;13 – 00;04;28;00
Amy Wesolowski
I think one of the main points that we sort of wanted to raise in this was that ultimately you really want to be able to show that you’re capturing patterns that are relevant to disease transmission. So, for example, like a mobile phone data might be able to say that to people or within x meters within one another. But there’s a lot of variability in that.

00;04;28;00 – 00;04;51;26
Amy Wesolowski
They could be in completely separate buildings. They could both be wearing masks. And as you need to get a finer and finer measure of behavior, it’s important to think about are these data actually able to capture those patterns and are they able to capture those patterns for the populations you’re most interested in? So with COVID 19, there’s a lot of disparities in who actually has the most severe disease and who actually is getting infected.

00;04;52;02 – 00;05;13;19
Amy Wesolowski
So thinking about sort of how those biases, you know, if you’re really interested in mortality, that’s predominantly in older age groups who might be people who are less likely to own a smartphone, for example. So these kinds of data might not be as relevant for some of those questions, even if they’re still able to estimate sort of population level clustering and mobility patterns.

00;05;14;07 – 00;05;19;16
Ernie Hood
Do you think there are further opportunities to use your methods in relation to COVID 19?

00;05;19;25 – 00;05;43;27
Amy Wesolowski
Yeah, I think so. I think increasingly what they might be able to be used for is trying to look at how populations are sort of going back to normal travel patterns and behavioral patterns and aggregation. So I think there is a lot of different studies that sort of show mobility measures of clustering aggregation, all these things in different mobile phones that have all dropped as the pandemic started.

00;05;43;27 – 00;06;06;03
Amy Wesolowski
But they’re all going back up. And we’re also seeing there’s a lot of other factors that are not just related to mobility that are probably coming into play. You know, how well can people isolate? How can people quarantine? So I think there’s still going to be a useful measure alongside other types of data and metrics of being able to sort of get some sort of real time estimate about how populations are behave yet.

00;06;06;22 – 00;06;13;26
Ernie Hood
What about issues of privacy related to mobile phone data? How do you safeguard against inappropriate breaches?

00;06;14;01 – 00;06;38;17
Amy Wesolowski
It’s a really big concern, and particularly as you’re trying to get information on a much, much finer scale. So most of the work that we’ve done has been a lot of aggregated mobility and population level mobility patterns. So looking at how many people are traveling on a given day between, you know, like counties or state or something, which is, you know, that’s thousands and thousands of people often, or mobile phone subscribers.

00;06;38;23 – 00;07;13;16
Amy Wesolowski
And I think that increasingly with SARS-CoV-2, you’re really interested in really, really fine scale behaviors. And the finer you get, the more issues there are with privacy. And so oftentimes, you know, we will analyze data if it’s only one subscriber who’s made a trip or something, because that could be identifiable. We’ve been working a lot with mobile phone operators and regulators to try to sort of push and and have a platform where aggregated data and aggregated mobility patterns are able to be shared more broadly and that they’re aggregating in a way that there’s fewer privacy concerns, but they’re still there.

00;07;13;21 – 00;07;34;18
Amy Wesolowski
But I think the issue with SARS-CoV-2 is, as you want a really, really fine understanding of behavior and individual level behavior. A lot of those privacy concerns have not been really fully addressed. So I think that it’s still an issue and it still hasn’t really been fleshed out in in the regulators aren’t really sure, you know, the companies aren’t.

00;07;35;00 – 00;08;01;08
Amy Wesolowski
And so I think there are things that can be done about sort of like still making the data sort of aggregated or like summary measures and those sorts of things. But I think that part of it is about that everyone is sort of aware about like the public health utility and sort of the public health good about these kinds of data and that ways that it’s still getting information to policymakers who often don’t actually want very, very individual level details.

00;08;01;08 – 00;08;37;10
Amy Wesolowski
Right. They want to have summaries and ideas about behaviors. So I think it’s sort of always going to be sort of a play between what is actually useful to inform decision making and what is actually protecting the privacy of subscribers. But I think the more that there are like general discussions or frameworks about sort of how these data are being used and and sort of processes and everyone’s sort of aggregating it and analyzing them similarly, I think that sort of helps a lot of these discussions along, but I think it is a different question about sort of like the contact tracing apps, which are sort of a different aspect versus sort of like the mobile

00;08;37;10 – 00;08;45;29
Amy Wesolowski
phone companies collect data from their subscribers aggregating and analyzing that. So I think there’s still differences, too, between the applications.

00;08;46;08 – 00;08;59;18
Ernie Hood
Amy, I know you’ve used this approach and other studies for the past several years in various places and various diseases. Would you give us some examples and tell us more about the evolution of your ideas and your career?

00;09;00;07 – 00;09;21;02
Amy Wesolowski
Sure. Yeah. So we’ve used it for a bunch of different other pathogens. So my favorite pathogen is malaria. And so we’ve used it a lot for looking at malaria control and elimination. So one of the issues with malaria is if you’re able to sort of reduce it in in a particular location, there still might be a lot of mosquitoes and a lot of people who could be getting malaria.

00;09;21;02 – 00;09;43;29
Amy Wesolowski
So if people are infected and then they come into a location, they might be able to reintroduce the pathogen and then cause additional transmission events related to those introduction events. And so in a lot of areas with malaria in sort of these lower transmission areas where they’ve they’ve gotten transmission down to really, really far away. But they’re sort of like still possible that they could have secondary cases.

00;09;44;11 – 00;10;03;25
Amy Wesolowski
We’ve used these data to try to estimate and look at those patterns. So where those parasites likely coming from, where are they going to, what sort of the rate of those and and trying to identify where additional control measures should be targeted. So a lot of the work that we’ve done has been using mobile phone data to inform malaria control and elimination.

00;10;04;04 – 00;10;23;16
Amy Wesolowski
And the other application that we’ve done a number of times is looking at measles outbreaks. So people can introduce measles. Vaccination rates aren’t really high. It’s sort of the same story where it’s like, oh, you can have an outbreak of the disease. So trying to use these data to look at those different patterns of mobility and how that can impact your control efforts.

00;10;23;19 – 00;10;59;16
Amy Wesolowski
And then we’ve also been sort of working on developing models of mobility. So how can we you can’t always get these data everywhere. It’s a lot of effort and a lot of work and there is going to be issues. So can we better model mobility if you don’t have these data, if you have other kinds of data, And then sort of also trying to provide evidence and proof of concept that these data are able to be, you’re able to aggregate them in a way that it’s not fringing on the privacy of subscribers where it’s making like individuals identifiable from these data, but also you’re able to sort of like provide like pipelines that operators can

00;10;59;16 – 00;11;04;29
Amy Wesolowski
use where these data can get aggregated and anonymized and analyzed more broadly for public health.

00;11;05;16 – 00;11;09;04
Ernie Hood
What is the Cassie Grant meant to your scientific career?

00;11;09;29 – 00;11;39;11
Amy Wesolowski
Cassie Grant is definitely the best grant that I have had and that everyone I know who’s had them has also really, really valued it. I mean, I think the best part of it is that it gives you a huge amount of freedom and support. If I want to start thinking about how this might apply to Ebola or some other pathogen like Cassie is like the Burroughs Wellcome Fund has always been super supportive and very excited about sort of like they just want to figure out the best way that to support you to do the science that you want to do.

00;11;39;11 – 00;12;12;24
Amy Wesolowski
So there’s very, very few other grants to provide that kind of like freedom of being able to think about new problems and sort of expand the research that you’re working on. With very few restrictions about things, you know, they’re never like coming out and like you said, you would do this very specific, very exact thing. It’s more about sort of supporting you in what you’re interested in and sort of helping you, particularly with that really early stage where you’re sort of transitioning and starting some new kinds of projects and and working on maybe some different things with different collaborators.

00;12;12;24 – 00;12;20;15
Amy Wesolowski
It’s just like a really flexible, very supportive grant to have. It’s the best grant. I highly recommend it to everyone.

00;12;21;05 – 00;12;28;22
Ernie Hood
Amy, it’s been a great pleasure meeting and chatting with you. We wish you the best for continued success. Thank you for speaking with us.

00;12;29;02 – 00;12;32;29
Amy Wesolowski
Okay, great. Thanks so much.

00;12;32;29 – 00;12;41;21
Ernie Hood
We hope you’ve enjoyed this edition of the Focus In Sound podcast. Until next time. This is Ernie Hood. Thanks for listening.