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How Tracking Population Movement Can Help Fight the Coronavirus

In a Q&A with Direct Relief, Andrew Schroeder, the organization's vice president of research and analysis, weighs in on what can be learned from population movement data, and what can be done about it.

Levels of population movement in different areas of California. (Chart by Direct Relief)
Levels of population movement in different areas of California. (Chart by Direct Relief)

Tracking the way people move in the midst of social distancing – when everyone is supposed to be staying put – may seem counter-intuitive.

But according to Andrew Schroeder, Direct Relief’s vice president of research and analysis, population movement tracking is an essential tool that can help policymakers and public health officials respond to a wide variety of disasters, including disease outbreaks like the Covid-19 pandemic.

As Covid-19 gains ground, Schroeder has been using anonymized data to track how people are moving – or, when social distancing works, not moving.

He’s fielded media calls and consulted with policymakers – including the California Governor’s office – about how best to understand population movement data.

And in a newly-published article in Science magazine, he – along with a group of doctors and fellow researchers – argues that population data is a powerful informational tool that can be used to guide policy and public health measures designed to fight Covid-19.

In the midst of it all, Schroeder found a few minutes to tell Direct Relief about how social distancing is changing the way people move – and how that knowledge can change the way we fight this and future epidemics.

Direct Relief: Tell me a little about the population movement tracking that you’re working on right now. What are you doing, and what are you looking for?

Schroeder: So for a while, we’ve been using aggregated population mobility data to understand how people respond to crisis.

And in the case of Covid-19, we’ve been using that data plus some other measures that help us understand rates of mobility and rates at which people are staying home. [We’re trying] to get a better understanding of whether social distancing measures that have been put in place by governments throughout the United States at the state and city level are actually working. Are people listening to them? Are they staying home? Are they moving around less?

We’ve been providing that information to policymakers in order to make sure that they have some kind of visibility into the consequences of their decisions, so that they can understand whether they need to do more or less.

And we’ve been helping organize [university] researchers into support teams, basically, for public sector agencies that need to have better insight into the consequences of social distancing policies.

Direct Relief: What have you found thus far?

Schroeder: At least in California, I think the key finding has been that the social distancing orders made a difference. There has been, over the last, say, two weeks, significant decline in the rate at which people are moving around in most areas of California. Actually all areas have seen decline, some areas much more so than others.

Probably the highest rate of decline in terms of the rate at which people are moving around is in San Francisco.

However, I would say that kind of changed a little bit in the last couple of days. Probably the low point for mobility was two days ago, and there has been an uptick in rates of mobility, as well as increases in the average length of trips.

So people are moving around more and they are taking longer trips, which does indicate that the social distancing measures – even in California, which has some of the strictest kind of recommendations of any state in the country – are not necessarily sticking.

People are starting to move around already, even though we’re really only about a week into the strongest recommendation.

Direct Relief: How can information like that be used to make policy or public health decisions?

Schroeder: Well, we’ve been assisting the Governor’s office in state of California, for instance, with just having better input into whether or not [social distancing] is even happening. To give them a tool to see – rather than just looking out the window and seeing “Oh, people aren’t really walking down the sidewalk” – could you know whether on a population scale, your recommendation was having any influence?

The reason why this is so important is because social distancing is what the public health community calls a non-pharmaceutical intervention. It is what almost all of the experts who are looking at this right now agree is the last, best tool we have to combat this virus – short of a vaccine or an extremely effective treatment, both of which seem to be many months in the future.

In the absence of those, we really have to get people to reduce the rate of contact and the likelihood that they’re passing the virus from person to person.

As you know, most people don’t get very serious symptoms.

But if we don’t follow these non-pharmaceutical intervention guidelines, those people that are getting acute complications are going to be in need of medical attention at a rate that’s just beyond what most of our current health systems are capable of providing.

That’s going to not only have an immediate impact on things like ICU beds and availability of equipment to treat people. It ripples through the entire health system, which is actually pretty fragile on a good day.

Direct Relief: What are some of the challenges or limitations of using this kind of data for epidemic response?

Schroeder: I think one of the key challenges actually is that it probably doesn’t and can’t tell you as much as you think you’d like to know.

The true purpose here is reducing the case incidence rate or what’s called “flattening the curve,” right?

The only way to do that is to actually practice these social distancing measures. The question comes up with the movement data: Let’s say you show people are actually following these orders. How do you know it’s affecting the case rate? And the answer is, honestly, we don’t.

In part, that’s because there’s a time lag on the effectiveness of any non-pharmaceutical initiative. When you see a number in the media now about [how many cases] are being detected, there are really two problems with that:

One is that it’s limited by the number of tests that are being carried out.

And the second is that it’s really measuring people that were infected several days ago. In some cases, more than a week ago, because it takes a certain amount of time for the disease to actually express.

With those two things in mind, you just won’t see immediate effects from social distancing measures.

We’re [also] not getting any feedback from these measures yet. You have to play them out more, collect data, and then be able to plug that data into models to be able to determine the expected rate of decrease based upon certain kinds of activities.

Imperial College in London did a study on the relative effectiveness of social distancing measures in Wuhan, China. It’s one of the reasons why there’s such a strong consensus around just the general policy of social distancing, because they do show it’s effective.

But it’s important to bear in mind that the United States and Europe are definitely not instituting social distancing policies in the way that was done in Wuhan, China. There’s a patchwork of different policies that are instituted by different authorities at different places. People are listening to those at different rates. They’re being enforced in different ways.

It’s a very, very high level of variability. And that means that it’s very hard to actually model the outcome.

So yeah, that’s a problem.

Direct Relief: How do you think having access to population movement information that will change how we respond to future epidemics?

Schroeder: When I think about what that means, I think back to previous outbreaks that we’ve responded to and what we didn’t have at that time. The first one that I was ever involved in was the H1N1 swine flu back in 2009.

And at that time, the iPhone had just been released and Facebook was, I think, five years old and clearly wasn’t what it is today. We hadn’t gone through 10 years worth of a really tumultuous debate over data privacy and security in the context of a completely new paradigm for having real time sensor information on people as they operate in society.

But now we do have sensor feedback on population dynamics in the middle of a completely relevant crisis for those dynamics.

And I do think that we have a moral responsibility right now, given the scale of the consequences, to use those tools to the best of our ability – in order to reduce case counts, reduce the pressure on the health system and help policymakers with the largest, most consequential public health decisions that any of them are making in their entire careers right now.

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