From the Journals

Big data ready to revolutionize infectious diseases research


 

FROM THE JOURNAL OF INFECTIOUS DISEASES

An all-encompassing definition of “big data” in health care remains elusive, but most researchers and public health experts believe big data may be poised to revolutionize the field of infectious diseases research.

Big data could provide the means to finally achieve effective and timely surveillance systems, which form a “pillar of infectious disease control,” according to Shweta Bansal, PhD, of the department of biology, Georgetown University, Washington, and her associates (J Infect Dis. 2016 Nov;214[S4]:S375-9. doi: 10.1093/infdis/jiw400).

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For infectious diseases researchers, surveillance systems are critical, as they track disease incidence and mortality rates as pathogens spread across the globe. “An ideal surveillance system is representative of the population, flexible, economic, and resilient, with timely reporting and validation of its outputs,” Lone Simonsen, PhD, of the department of public health, University of Copenhagen, Denmark, and her associates wrote in a supplemental article (J Infect Dis. 2016 Nov;214[S4]:S380-5. doi: 10.1093/infdis/jiw376).

“Further, full situational awareness requires availability of multiple surveillance data streams that capture mild and severe clinical outcomes (death certificates, hospital admissions, and emergency department and outpatient visits), as well as laboratory-based information (confirmed cases, genetic sequences, and serologic findings),” Dr. Simonsen added.

But unlike marketing or meteorology, two fields that have “perfected the art of real-time acquisition and analysis of highly resolved digital data,” the field of infectious diseases research has suffered from slow and incomplete surveillance of emerging and reemerging pathogens and pandemics, Dr. Bansal said.

What has changed in recent years is that physicians and researchers now have better access to patient information. Today, electronic health records and nontraditional patient data sources such as social media and remote sensing technology provide multiple surveillance data streams, and millions of people around the world can participate as the Internet, cell phones, and computers pervade even low income countries.

Several private and federal public health agencies have already launched successful initiatives “to use electronic data and patient records in a more timely fashion to track important events,” Dr. Simonsen said. For example, the Food and Drug Administration’s Sentinel Initiative aims to augment traditional surveillance (which relies on passive case reporting by physicians) with private sector electronic health data to identify severe adverse drug events.

The Centers for Disease Control and Prevention’s BioSense platform collects electronic health records to achieve “real-time awareness and tracking of pandemic influenza or any other novel health threat.” Google tracks influenza epidemics by analyzing Internet search query data. In Germany, researchers use medical claims data to track vaccination rates. In Canada, public health analysts compile multiple sources of disease outbreak information into online computational systems and then use this information to identify and track novel outbreaks and drug resistance.

The authors of these two papers warn that while big data is promising, it must be “balanced by caution.” Privacy concerns, barriers in access to e-health systems, and ill-fitting big data models must be addressed, and continued validation against traditional surveillance systems is imperative.

The authors of both papers reported no relevant conflicts of interest.

On Twitter @jessnicolecraig

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