Stories about: digital epidemiology

How social media and a mumps outbreak teach us that vaccines build herd immunity

Mumps virus, pictured here, is usually preventable by vaccination.
The mumps virus, pictured here, has been spreading through Arkansas communities. Surprisingly, many affected people say they have received vaccinations to prevent it. Analyzing social media data helped a Boston Children’s Hospital team understand why so many people got sick.

Residents of Arkansas have been under siege by a viral threat that is typically preventable through vaccination. Since August 2016, more than 2,000 people have been stricken with mumps, an infection of the major salivary glands that causes uncomfortable facial swelling.

The disease is highly contagious but can usually be prevented by making sure that children (or adults) have had two doses of the measles-mumps-rubella (MMR) vaccine. But strangely, about 70 percent of people in Arkansas who got sick with mumps reported that they had received their two doses of the MMR vaccine.

So, members of the HealthMap lab, led by Chief Innovation Officer and director of the Computational Epidemiology Group at Boston Children’s Hospital, John Brownstein, PhD, asked, “Why did this outbreak take off?”

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So, what’s your digital phenotype?

Ideally, we’re all supposed to see our doctor once a year for a checkup. It’s an opportunity to see how we’re doing from a health perspective, address any concerns or issues that we may have and catch any emerging issues before they become true problems.

But those visits are really only one-time, infrequent snapshots of health. They don’t give a full view of how we’re doing or feeling.

Now, think for a moment about how often you post something to Facebook or Twitter. Do you post anything about whether you’re feeling ill or down, or haven’t slept well? Ever share how far you ran, the route you biked or your number of steps for the day?

Every time you do, you’re creating a data point—another snapshot—about your health. Put those data points together, and what starts to emerge is a rich view of your health, much richer than one based on the records of your occasional medical visit.

As John Brownstein, PhD—director of the Computational Epidemiology Group (CEG) in Boston Children’s Hospital’s Computational Health Informatics Program and the hospital’s new Chief Innovation Officer—explains in this episode of the Harvard Medical School (HMS) Labcast (click the image above to hear it), this view has a name: your digital phenotype.

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Measles in America: Why vaccination matters

Maimuna (Maia) Majumder is an engineering systems PhD student at MIT and computational epidemiology research fellow at HealthMap.

The 2015 Disneyland measles outbreak in the United States, which started in late December and spread to more than 100 people in just 6 weeks, has recently become the subject of substantial media scrutiny.

Measles is extremely infectious, exhibiting a basic reproductive number between 12 and 18—one of the highest recorded in history. This means that for every 1 case who gets sick in a totally susceptible population, 12 to 18 other folks get sick, too. Thankfully, when uptake of the measles vaccine is high enough in a given community, it’s almost impossible for the disease to spread—thus halting a potential outbreak in its tracks.

But what happens when vaccine rates aren’t high enough?

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Yelp: A new tool for foodborne illness surveillance?

Yelp iPhone Android social media foodborne illness food poisoning John Brownstein public health digital epidemiologyYou just had a great meal at a restaurant. So you grab your phone and fire off a glowing review on Yelp.

Consider the opposite scenario: You just had a horrible meal at a restaurant. So you grab your phone and fire off a scathing review on Yelp.

Now here’s one more: You had a great meal at a restaurant but woke up vomiting the next morning. Do you grab your phone and fire off a complaint on Yelp that your dinner made you sick?

That’s what a trio from Boston Children’s Hospital’s Informatics Program, are banking on.

A report in Preventive Medicine, authored by John Brownstein, PhD, Elaine Nsoesie, PhD and Sheryl Kluberg, MSc, judges Yelp’s usefulness as a food poisoning surveillance tool. Their efforts are part of a growing trend among public health researchers of trying to supplement traditional foodborne illness reporting with what we, the people, say on social media.

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Tracking the Ebola outbreak in near real-time: HealthMap, ProMED and other tools

This interactive map of the Ebola outbreak, produced by HealthMap, paints a picture of the epidemic's course from its first public signs in March. Mouse around, scroll down, zoom and explore. And click play to see how events have unfolded thus far.

Sobering news keeps coming out of the West African Ebola outbreak. According to numbers released on August 6, the virus has sickened 1,711 and claimed 932 lives across four nations. The outbreak continues to grow, with a high risk of continued regional spread, according to a threat analysis released by HealthMap (an outbreak tracking system operated out of Boston Children’s Hospital) and Bio.Diaspora (a Canadian project that monitors communicable disease spread via international travel).

“What we’ve seen here—because of inadequate public health measures, because of general fear—is [an outbreak that] truly hasn’t been kept under control,” John Brownstein, PhD, co-founder of HealthMap and a computational epidemiologist at Boston Children’s Hospital, told ABC News. “The event started, calmed down and jumped up again. Now, we’re seeing movement into densely populated areas, which is highly concerning.”

If you’re interested in keeping tabs on the outbreak yourself, there are several tools that can help.

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Digital disease detection: We see the trends, but who is actually sick?

Three teenagers wearing hospital masks flu influenza healthmap social media twitter digital epidemiology digital disease detectionElaine Nsoesie, PhD, is a research fellow at Boston Children’s Hospital’s HealthMap, Harvard Medical School and Virginia Bioinformatics Institute. In this post, which originally appeared on HealthMap’s Disease Daily, Nsoesie looks at the trend of detecting disease digitally by monitoring mentions on social media. She delves into one of the major limitations of this technique—namely telling those who are curious about a disease apart from those who actually have it.

There are plenty of studies about tracking diseases (such as influenza) using digital data sources, which is awesome! However, many of these studies focus solely on matching the trends in the digital data sources (for example, searches on disease-related terms, or how frequently certain disease-related terms are mentioned on social media over time, etc.) to data from official sources such as the Centers for Disease Control and Prevention. Although this approach is useful in telling us about the possible utility of these data, there are several limitations. One of the main limitations is the difficulty in distinguishing between data generated by healthy individuals and individuals who are actually sick. In other words, how can we tell whether someone who searches Google or Wikipedia for influenza is sick or just curious about the flu?

Researchers at Penn State University have developed a system that seeks to deal with this limitation. We spoke to the lead author, Todd Bodnar, about the study titled, On the Ground Validation of Online Diagnosis with Twitter and Medical Records.

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What your dinner cancellation on OpenTable says about the flu

An empty restaurant table. Can measuring restaurant cancellations tell us something about flu outbreaks?You wake up feeling like someone has taken a jackhammer to your head. You’re feverish, aching all over and your stomach is doing somersaults. There’s no doubt about it: You have the flu.

You also have reservations for dinner tonight. So after a mug of tea and an ibuprofen, you grope for your phone and cancel the reservations you’d made through OpenTable.

That cancellation might be a signal to public health officials of a flu outbreak. Because, according to a study by HealthMap’s John Brownstein, PhD, and Elaine Nsoesie, PhD, reservation data from OpenTable could offer another view into the seasonal spread of the flu.

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More than a feeling: Making flu surveillance truly participatory

3D reconstruction of an influenza virus
A flu virus. (CDC)
Disease surveillance has long been the purview of state public health departments, the U.S. Centers for Disease Control and Prevention (CDC) and other agencies that collect reports from doctors, clinics and laboratories.

That disease control model is being turned on its head by projects like Boston Children’s Hospital’s HealthMap, which scours the web for information related to disease outbreaks. HealthMap’s Flu Near You goes a step further by encouraging people to report their own flu-related symptoms and help track flu emergence and spread.

To date, though, efforts like these have been limited to the digital sphere—part of the growing field of digital epidemiology. They don’t rely on blood, spit and mucus to get their data—it’s all in bits and based solely on symptoms.

But even that is changing, thanks to a new Flu Near You initiative called GoViral. GoViral brings everyone directly into the flu surveillance process by allowing them to not just report how they’re feeling, but to test themselves for flu at home and submit their results.

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Tweeting and more for public health: Q&A with a digital disease detective

Screenshot of H7N9 patient record posted to Weibo
A photo of the record of a Chinese patient with H7N9 flu. Posted to Chinese social media site Weibo, the photo has spread like wildfire over Twitter and other social media. (Weibo user @phoenix via Twitter user @Laurie_Garret)

From the flu to cholera, obesity to vaccine concerns, data from Twitter, Facebook, mobile phones, search engine queries and other web-based sources are changing the nature of epidemiology, public health surveillance and outbreak preparation and response.

John Brownstein, PhD, director of the Computational Epidemiology Group in Boston Children’s Informatics Program and co-founder of HealthMap, recently co-authored an opinion piece in the New England Journal of Medicine (NEJM) highlighting the roles of social media and other Internet data sources in what he calls “digital epidemiology” or “digital disease detection,” He and his collaborators argue that, in their opinion:

“Since the [2003] SARS outbreak, the world has seen substantial progress in transparency and rapid reporting. The extent of these advancements varies, but overall, digital disease surveillance is providing the global health community with tools supporting faster response and deeper understanding of emerging public health threats.”

Vector sat down with Brownstein to discuss digital epidemiology’s evolution over the 10 years since SARS, especially in light of the rise and spread of avian H7N9 influenza in China and Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV) in Jordan and the Arabian Peninsula.

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