Stories about: Computational Health Informatics Program

The threat from mosquito-borne diseases: Forecasting mosquitoes’ global spread

Aedes albopictus
Aedes albopictus (ADOBE STOCK)

Outbreaks of mosquito-borne illnesses like yellow fever, dengue, Zika and chikungunya are rising around the world. Climate change has created conditions favorable to mosquitoes’ spread, but so have human travel and migration and accelerating urbanization, creating new mini-habitats for mosquitoes.

In Nature Microbiology yesterday, a large group of international collaborators combined these factors into prediction models that offer insight into the recent spread of two key disease-spreading mosquitoes — Aedes aegypti and Aedes albopictus. The models forecast that by 2050, 49 percent of the world’s population will live in places where these species are established if greenhouse gas emissions continue at current rates.

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Using multiple data streams and artificial intelligence to ‘nowcast’ local flu outbreaks

(PHOTO: ADOBESTOCK)

Because influenza is so contagious, it’s been challenging to track and forecast flu activity in real time as people move about and travel. While the CDC continuously monitors patient visits for flu-like illness in the U.S., its information can lag by up to two weeks. A new study led by the Computational Health Informatics Program (CHIP) at Boston Children’s Hospital combined multiple approaches, providing what appear to be the most accurate local flu predictions to date.

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Only a third of Federally mandated ‘post-marketing’ pediatric drug trials are complete

too few mandated pediatric drug trials are getting done
Despite new requirements, pediatric drug trials largely aren’t getting done. (ADOBE STOCK)

The FDA requires clinical studies of new drugs in pediatric populations, since many drugs developed for use in adults are also used in children. These studies are often “post-marketing” trials after the drug is approved in adults. But an audit by researchers at Boston Children’s Hospital found that only about a third of these mandatory trials were completed within an average of seven years. As a result, most new drug labels continue to lack child-specific information, and most FDA-approved drugs remain untested in children.

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Scientists find link between increases in local temperature and antibiotic resistance

Image representing the rise of antibiotic resistance
Illustration by Fawn Gracey

Over-prescribing has long been thought to increase antibiotic resistance in bacteria. But could much bigger environmental pressures be at play?

While studying the role of climate on the distribution of antibiotic resistance across the geography of the U.S., a multidisciplinary team of epidemiologists from Boston Children’s Hospital found that higher local temperatures and population densities correlate with higher antibiotic resistance in common bacterial strains. Their findings were published today in Nature Climate Change.

“The effects of climate are increasingly being recognized in a variety of infectious diseases, but so far as we know this is the first time it has been implicated in the distribution of antibiotic resistance over geographies,” says the study’s lead author, Derek MacFadden, MD, an infectious disease specialist and research fellow at Boston Children’s Hospital. “We also found a signal that the associations between antibiotic resistance and temperature could be increasing over time.”

During their study, the team assembled a large database of U.S. antibiotic resistance in E. coli, K. pneumoniae and S. aureus, pulling from hospital, laboratory and disease surveillance data documented between 2013 and 2015. Altogether, their database comprised more than 1.6 million bacterial specimens from 602 unique records across 223 facilities and 41 states.

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Families and data scientists build insights on Phelan-McDermid syndrome

querying stacks of data

This is the third year that Jacob Works has made the trip down to Boston Children’s Hospital from Maine. With research assistant Haley Medeiros, he looks at pictures, answers questions, manipulates blocks and mimes actions like knocking on a door. His father, Travis, and another research assistant look on through a window.

“At first, we had to practically bribe him with an iPad with every task,” Travis says. “This year he’s more excited, because he understands more and is more confident and able to share more.”

Jacob, 11, was diagnosed in 2011 with Phelan-McDermid Syndrome, a rare genetic condition that typically causes children to be born “floppy,” with low muscle tone, and to have little or no speech, developmental delay and, often, autism-like behaviors. At the time, Jacob was one of about 800 known cases. But through chromosomal microarray testing, introduced in just the past decade for children with autism symptoms, more cases are being picked up.

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More than half of type 2 diabetes patients may not take their medication as prescribed

Image of medications: A new study found that many people with diabetes are not taking their medication as prescribedNew research reveals why treatment might appear to fail to control glucose levels in many people with Type 2 diabetes: not taking their medication as prescribed.

“When patients have poor glycemic control, their physicians may assume that there was a medication failure when they were, in fact, not filling their prescriptions,” says Ken Mandl, MD, MPH, of Boston Children’s Hospital, the senior author of a new report in Diabetes Care.

The study raises the question of whether the same might be true for patients with other conditions.

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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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Predicting influenza outbreaks faster with a digitally-empowered wearable device

Influenza viruses. Outbreaks can be predicted using digital health tools like Thermia.The Thermia online health educational tool, developed at Boston Children’s Hospital, has enabled one-month-faster prediction of seasonal influenza outbreaks in China, via its digital integration with a commercially-available wearable thermometer. The findings appear in a new study published in the American Journal of Public Health.

 “The fact that we were able to predict influenza outbreaks faster than China’s national surveillance programs really shows the capacity for everyday, wearable digital health devices to track the spread of disease at the population level,” says the study’s lead author Yulin Hswen, who is a research fellow in Boston Children’s Computational Epidemiology Group and a doctoral candidate at the Harvard T. H. Chan School of Public Health.

China has 620 million mobile internet users who can theoretically access the standalone Thermia application from any computer, smartphone or even the Amazon Alexa assistant.

Although the Boston Children’s team has previously demonstrated that social media can be used to track disease, this is the first time they’ve shown that outbreaks can be predicted through an integrated wearable device and online tool.

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Lessons from the data: Applying machine learning for clinical decision support

machine learning clinical decision support

Mauricio Santillana, PhD, faculty member in the Computational Health Informatics Program at Boston Children’s Hospital, had an idea as he witnessed the volume of continuous real-time data generated in the pediatric intensive care unit (PICU). He realized that tapping the data on patients’ ever-changing vital signs, with the help of machine-learning algorithms, could support clinical decision-making and predict (and help head off) up-coming health issues.

He started a dialogue with the hospital’s Innovation & Digital Health Accelerator, and now collaborates closely with clinicians in the PICU to create machine-learning algorithms that can help them provide the highest level of care.

“It’s fairly recent that clinicians realized people with backgrounds in math and statistics can be very helpful in a clinical context,” says Santillana

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Lack of drug testing in kids exposes them to off-label harm

drug testing in children
Loopholes in current legislation let drug companies defer testing their products in children, so the majority of prescriptions are off-label.

Florence T. Bourgeois MD, MPH, is assistant professor of Pediatrics and Emergency Medicine at Harvard Medical School, faculty in the Computational Health Informatics Program, and Scientific Director of the Biobank for Health Discovery at Boston Children’s Hospital

Every day, more than half of children seen in outpatient clinics are prescribed a medication that is not FDA approved for the child’s age or diagnosis. Such off-label prescribing is widespread across pediatric conditions and treatment settings and as many as 90 percent of pediatricians have knowingly prescribed off-label medications.

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