Stories about: digital disease detection

Under the hood of healthcare innovation: Jared Hawkins and the digital phenotype

Jared Hawkins Boston Children's Hospital

What does it take to change healthcare for the better? In the second of a two-part series on digital health innovators at Boston Children’s Hospital, we profile Jared Hawkins, MMSc, PhD. Like Gajen Sunthara, MSc, featured in part one, Hawkins was named among MedTech Boston’s 40 Under 40 Healthcare Innovators for 2017.

Jared Hawkins, director of informatics at Boston Children’s Innovation and Digital Health Accelerator (IDHA), brings a formidable skill set to his work. With a PhD in Immunology from Tufts University School of Medicine and an MMSc in Biomedical Informatics from Harvard Medical School, his background combines biomedical research (immunology, virology, oncology, genomics) with data science, visualization, computational modeling and software development.

His current work spans an equally diverse range of topics, touching on population and public health, patient experience, decision support and pharmacogenomics. A faculty member in the Computational Health Informatics Program, Hawkins is wired into the digital health ecosystem. He serves as a scientific advisor and co-founder of Raiing Medical (home temperature and fertility tracking) and is the head of engineering and co-founder of Circulation (non-emergency medical transportation via Uber).

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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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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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Mapping obesity with Facebook

What you like on Facebook might say something about how obese your neighborhood is. (Dry Martini/Wikimedia Commons)
If one of my Facebook friends were to look through my list of “likes,” they’d find that I’m interested in music, cars, science and photography, among other things (and not necessarily in that order).

But if a researcher were to look across Boston at what people who are like me like—and post and share—on Facebook, a snapshot of data could tell them something else: roughly how obese metro Boston is.

That’s essentially what John Brownstein, PhD, and Rumi Chunara, PhD, concluded in a study recently published in the journal PLoS ONE. In it, they combined Facebook interest data—an aggregate of what people “like,” post on their timeline or share on others’ timelines—with health survey data to geographically correlate activity or television interests with obesity rates. 

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Digital disease detection: Public health by the “web kids”

In his essay, “We, the Web Kids,” Polish poet and pundit Piotr Czerski writes: “We don’t use the Internet…we live on the Internet and along it…communicating with one another in a way that comes naturally to us, more intense and more efficient than ever before in the history of mankind.”

As Czerski emphasizes, we want the option of “here and now, without waiting for the file to download.” We (myself included) expect immediacy. So in my role as a public health advocate in the digital age, waiting for an official infectious disease outbreak report to come weeks after the outbreak started—as often happens with traditional reporting methods—is unacceptable. Earlier detection of disease outbreaks means earlier response—and more lives saved. This video produced by NPR illustrates the “web kid” mindset when it comes to public health:

Such thinking lay at the core of the first International Conference on Digital Disease Detection, brought together last month by HealthMap of Children’s Hospital Boston and funded by the U.S. Centers for Disease Control and Prevention.  

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