Stories about: HealthMap

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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Tracking Zika? Use HealthMap

Like a virus, the story of Zika virus in the Americas is evolving very, very rapidly. Just in the last week we’ve seen:

To help public health investigators, policy makers, epidemiologists and others keep up with the virus, the team at HealthMap has released a dedicated Zika virus tracking resource at http://www.healthmap.org/zika/. The new map brings in Zika-related information and news from a variety of sources in near real-time, and includes a constantly updated interactive timeline of the virus’s explosive spread across South and Central America.

The HealthMap team is also providing regularly updated coverage of the Zika virus outbreak on their Disease Daily blog.

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Mapping antibiotic resistance near you: ResistanceOpen

antibiotic resistance mapping ResistanceOpen

At the moment, it would appear the bacteria are winning. Antibiotic resistance is on the rise globally (in part because much of the public may not really understand how antibiotics work), threatening doctors’ ability to treat bacterial infections and potentially making surgery, chemotherapy and other medical procedures whose safety depends on antibiotic prophylaxis more risky.

Mapping antibiotic resistance — which bacteria are resistant to which drugs, and where — can help clinicians and public health officials decide how best to focus their control efforts. The challenge to date has been compiling resistance data in geographically useful ways.

“The data about antibiotic resistance are fragmented across laboratories and hospitals globally,” says Derek MacFadden, MD, a doctoral student at the Harvard T.H. Chan School of Public Health who is working with the HealthMap team in Boston Children’s Computational Health Informatics Program. “Most of the data that are available are very high level, so you can’t get an understanding of regional-level antibiotic resistance.”

This is where ResistanceOpen could come in handy. This new tool, launched by HealthMap team this week during the World Health Organization’s World Antibiotic Awareness Week, provides a window into regional and local antibiotic resistance patterns across the globe.

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The MERS death rate in Saudi Arabia is double that in South Korea. Why?

map South Korea Saudi Arabia MERS
(Wikimedia Commons)

The Middle East respiratory syndrome (MERS) virus outbreak in South Korea is essentially over. (Not so in Saudi Arabia, where the virus first emerged, though—authorities there have reported a major uptick in new MERS cases in recent days.) And while the country gets back on its feet, some interesting data are starting to come out, especially about the outbreak’s case fatality rate (CFR; the percent of patients infected with the virus who died from it).

John Brownstein, PhD, and Maimuna Majumder, MPH, from Boston Children’s HealthMap team just reported in the journal Emerging Infectious Diseases that MERS’ CFR in South Korea (22 percent) is fully half that seen in Saudi Arabia (44 percent).

This infographic about Brownstein and Majumder’s MERS paper gives a snapshot of the data the analyzed, and what they think those data mean:

MERS virus South Korea Saudi Arabia infographic

Read Brownstein and Majumder’s analysis and check out Boston Children’s Hospital’s news release about the MERS paper.

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Is that fever a problem? Ask Thermia

Thermia fever calculator HealthMap

Your child’s forehead is warm, and you just took her temperature. The next question is, what to do about it? We all know that an average normal temp is 98.6°F, but is 100° a problem? Should 102° be a concern?

This is where Thermia comes in. It’s an online fever calculator developed by the HealthMap team at Boston Children’s Hospital. Essentially, it’s an educational tool aimed at helping concerned parents interpret a child’s temperature and understand which steps they should consider taking.

“I’m a father of two, and I still wonder sometimes what a temperature actually means,” says HealthMap co-founder John Brownstein, PhD. “We realized that there really aren’t any fever calculators out there to help parents answer that question.

“Our idea with Thermia,” he adds, “was to arm families with information so they don’t panic when their child has a temperature.”

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Yes, poor vaccination rates are fueling the 2015 measles outbreak

CDC measles outbreak map vaccination Disneyland
(CDC)

There’s been a lot of speculation about whether low vaccination rates are feeding the 2015 U.S. measles outbreak, which as I write this stands at 145 cases across seven states. Well, we can stop speculating, because the numbers are in, and measles is taking advantage of pockets of inadequately vaccinated people.

That’s the stark, unequivocal message from a study by epidemiologists at Boston Children’s Hospital, published this week in the journal JAMA Pediatrics.

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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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Hope for the New Year: A dengue vaccine in 2015?

(Photo: CDC Public Health Image Library)

Katherine Broecker is an MPH student at Boston University and a data curator at HealthMap. In this post, which originally appeared on HealthMap’s Disease Daily, she explores the burden of dengue and hopes that a new vaccine will be licensed sometime this year.

What is Dengue?

A virus transmitted by Aedes aegypti and Aedes albopictus mosquitoes, dengue is a flu-like illness characterized by a high fever and severe joint pain, sometimes with hemorrhagic manifestations. There are four distinct serotypes of the virus (DEN-1, DEN-2, DEN-3, DEN-4). Recovery from one infection provides lifelong protection from a homologous (same-strain) infection and partial temporary protection from the other strains. However, subsequent heterologous (different-strain) infection increases the risk of severe dengue manifestations.

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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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