GIS plays expanding role at the Centers for Disease Control
Friday, June 29, 2018
In the last few years, geographic information systems (GIS), geography, geospatial science and visualization have been applied much more often in the public health work of the U.S Centers for Disease Control and Prevention (CDC).
A major operating component of the federal, cabinet-level Department of Health and Human Services (HHS), the CDC is the principal government agency charged with conducting and maintaining a wide range of critical public health activities.
It wields health science, logistics and technology as weapons to defeat hazards to Americans’ health, lives and safety, at home or abroad. This includes threats that are merely unsafe, physical or environmental conditions, or substandard workplace practices or diseases; and whether diseases are chronic or acute, contained or communicable (infectious and otherwise); or whether the danger is passive and static, or proactive (that is, it may represent a deliberate attack).
Over the last few decades, at least eight of the CDC’s 11 major departments or divisions (known as centers, with one exception — the National Institute for Occupational Safety & Health or NIOSH) have applied, with ongoing programs, GIS systems, geospatial data and geographic science to their work.
The CDC’s excellent portal, entitled "GIS and Public Health at CDC," gives a rundown of the CDC’s departments and their ongoing, increasingly sophisticated GIS-related programs.
As with the organization’s overall work, a casual observer notes that the preponderance of this endeavor involves the less sensational, noninfectious disease threats to public health. An initial misapprehension is certainly excusable: the CDC is the successor agency of early federal organs, set up during and after World War II, intended to control and prevent communicable diseases, such as malaria and tuberculosio, among others.
That GIS methods and data would dovetail with the CDC’s wider mission is only logical.
By definition, geographic data (also known as spatial or geospatial data) identifies the global location of features. Conversely, a feature may include anything that can be mapped or otherwise associated with a location.
The CDC’s public health researchers and investigators start off with a corresponding duality as a basic, fundamental premise: They must not only track the spread of a communicable disease or the incidence (new cases) of a chronic mass condition. They’re also called upon to formulate a response.
And that’s as soon as possible, before the epidemic or condition grows unmanageable. In the simplest terms, GIS allows CDC workers to map a problem and then overlay that map with a map of its solution. So there must usually be a way to map those areas, for example, most seriously affected by a condition or disease and to map nearby facilities and clinics capable of, or at least instrumental in, addressing the condition.
GIS is applied via a number of specialized software programs designed to assist public health officials. These are often used with other types of software, such as statistical packages, databases and programming languages, in the CDC’s work.
Some good examples of GIS riding shotgun, so to speak? Widespread application of GIS data, software and methodology has been common in the field for decades now. The CDC’s history is rich with examples.
Lately, the CDC issued a report and related press release on the vastly greater incidence — in the last dozen or so years — of so-called vector borne diseases (spread by mosquito, tick or flea bites) — like Zika, West Nile and Lyme.
It turns out such cases have more than tripled since 2004 — nearly doubling in just the years 2015 and 2016. In fact, nine new vector-borne germs were introduced or otherwise exposed in the U.S. during the 12 years from 2004 to 2016 alone.
It was key that, before and during that time, GIS had been used in the surveillance and monitoring of vector-borne diseases. Its spatial, analytic and display capabilities greatly eased and expedited the analysis of associations between location, environment and such diseases.
One of the earliest such studies, conducted in Baltimore County, Maryland, used GIS to identify and locate the environmental risk factors of Lyme disease. Environmental data — as to forest distribution, geology, soil types, watershed and land use — was collected at the homes of Lyme disease patients.
This was then compared with data gathered from a randomly selected array of local addresses. The researchers generated a risk model combining both GIS and a logistic regression analysis to pinpoint areas where Lyme disease was most likely to spread and take hold.
Needless to say, researchers continue to use GIS to identify locations of high prevalence of certain diseases, not to mention monitor intervention and control programs.
Investigators’ ability to combine spatial, ecologic and epidemiological data enables the timely analysis of variables that play critical roles in disease transmission. The integration of such data at the CDC and at state and local health departments across the country is essential for the CDC’s ongoing surveillance efforts, identification of resources, and overall health policy planning.
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