Elise's Review of "Geographic information systems (GIS) for Health Promotion and Public Health: A Review"

Geographic information systems (GIS) for Health Promotion and Public Health: A Review

Authors: Candace I. J. Nikyforuk and Laura M. Flaman

When medical professionals and researchers and sociologists as well as politicians are seeking a means to project the best setting and location to provide health care, GIS has become a highly reputable tool to analyze demographics of an area and other variables such as need for health care and locations that are more susceptible to dis-eases. According to Candace I. J. Nikyforuk and Laura M. Flaman, GIS combines mapping and statistical analysis to “link people to place” through a simple computer generated visual (63). Nikyforuk & Malan’s description of GIS is spot on and can be linked to any subject matter that involves people and places. The manner in which it links people to health care, however, is very important especially in the public health sector and imporverished areas with little access to health care. When GIS is used to analyze the need for health care, this research is used by policy makers who make the health care decisions for the people.

This article is a review of 621 journal articles and health care literature that contained the topic of GIS as a means to connect more people to health care. The two main purposes of the review were:

“(a) to identify how GIS applications have been used in health-related research, including policy development, planning, monitoring, and surveillance and

(b) to critically examine the issues, strengths, and challenges inherent to those applications. (64)”

Nikyforuk and Malan used GIS to analyze four GIS applications common to the literature which included: Disease Surveillance, Risk Analysis, Health Access and Planning, and Community Health Profiling.

Disease Surveillance is the most common use for GIS in the public health arena. Disease Sureveillance uses disease mapping and disease modeling which compiles and tracks information on the “incidence, prev alence and spread of disease (66).” Through extrapolation, the GIS applications, disease mapping and modeling can be used to predict and prevent the spread of disease.

Risk Analysis looks at health risks as it relates to environmental hazards such as living in close proximity to factories, industrial waste sites, high amounts of traffic, highly poluted areas and areas that have poor social health conditions. The use of GIS allows for an objective visualization of all environmental hazards as it relates to population densities in the hazardous areas. These analyses can help communicate public health risks as well as identify need.

Health Access and Planning can be used as a way of marketing and networking for healthcare service and delivery especially for those places with the most need. Access pertains to a population’s ability to seek health care providers when needed.

Community Health Profiling is the GIS application that maps out the general health of a community using sociodemographic information. This data can help determine the link between health and location.

Nikyforuk and Malan discuss that the four health related GIS applications are distinct in mentioning but not distinct in the way that their information often overlaps. This makes sense since generally the main focus behind using GIS to analyze health conditions in certain areas is to prevent disease and provide health care. The biggest challenges that GIS faces when analyzing health care are the biases and errors that happen when using certain variables that don’t represent a population very well. This can easily be rectified with an experienced GISer especially experienced in medical applications. Lastly, a large purpose behind using GIS is to provide objective data to sway policy makers when it comes to making health care policies.   

GIS and Local Politics: How GIS is Helpful in Analyzing Voting Patterns

In its early Years GIS software was used purely to create basic maps, but as time has gone on the possibilities for what it can do have grown exponentially. GIS has even found a major place in the world of political science. In their 2002 article A GIS-based spatial analysis on neighborhood effects and voter turn-out: a case study in College Station, Texas Danile Z. Sui and Peter J. Hugill uncover the base of what can be done in the field of Political Science using GIS. They hypothesize that neighborhood effects manifest themselves in different ways according to the spatial distribution of voter turn-out, and they use GIS to prove it.

The study area is Brian/College station a city with a population of 160,000 people in 2006, and the home to Texas A&M a university with 42,000 students. The complex system of city government in place causes many local issues. This in turn makes College station a perfect location for this experiment to occur in. This experiment looked at three major issues:

1)      In 1995: a $10 Million Bond for the acquisition of 3.5 acres of land for municipal service facilities, and to reconstruct, improve, and extend existing streets, to construct and improve sidewalks, traffic signals, and necessary drainage.

2)      In 1997: the construction of a city convention center.

3)      In 1999: an issue over an overused residential street named Munson Ave.

The GIS-based spatial analysis methodology was as follows: First voting lists were obtained from the city secretary’s office. These lists had the voter’s names, addresses, voting district, and whether or not they voted. It is important to note that the voting districts lined up with major residential subdivisions. Then using the addresses and ARC View’s address matching module the voters (and non-voters) were geocoded. On average 87% of voters were matched with an address the problems were due to either incomplete/incorrect addresses or multiple voters at the same address. Once the voters were geocoded they examined the spatial patterns of actual voter distribution. Followed by conducting a second-order voter distribution analysis using Ripley’s K-function (a common, yet complex formula used to analyze spatial distribution of data).

The First Bond Election was the least controversial and thus was least cared about by the voters. Voter turn-out was extremely low. It received little media coverage, had no local grass roots organization working for or against it, and passed by an overwhelming majority. Voters clearly perceive that it is appropriate to spend tax dollars. Those voters against the bond initiative seem to have been motivated primarily by fear of the potential negative environmental impacts of such municipal service facilities as incinerators and garbage disposal facilities. Contextual/neighborhood effects had a clear impact on voter turn-out, with those precincts slated for the infrastructural improvements having by far the biggest voter turn-out.

Unlike the tax bond issue of 1995, the 1997 referendum on the construction of a city convention center was controversial and received considerable media attention, and grass roots organizations sprang up to attack it. This referendum also confirmed voter clustering, only on a broader scale of between a 1 and 2 mile radius.

The third Issue of re-opening the street Munson Ave. was by far the most controversial issue; it had major media attention and Grass roots organizations on both sides of the issue. The ordinance to re-open Munson Avenue passed by a near 2–1 margin in almost all precincts it had an unusually large voter-turn out. Analysis of the geographic pattern of that turn-out shows it extending in a line south of the TAMU campus. This street provides major north-south relief to traffic. The geographic analysis showed that people in the voting precincts south of TAMU presumably saw the closing of Munson Avenue as restricting their travel behavior and reducing their route alternatives.

This paper shows that GIS-based spatial analysis is immensely helpful in exploring the impacts of voter turn-out on neighborhood effects. On a broader scale this proves that GIS can and should be applied in politics and that politics is deeply rooted in GIS technology and its applications. Enlarge the awareness of political geographers on the potentials of GIS in electoral geographical research. Evidently, the role of GIS has shifted from being simply a data storage/map making tool in the early 1990s to a analytical tool that is used to develop geographic knowledge.

https://lms.southwestern.edu/file.php/3722/Literature/Sui-2002-GIS_Voter_Turnout.pdf

Conservation Deficits for the Continental United States: an Ecosystem Gap Analysis

The main conservation agencies of the United States utilize a course-filter conservation approach, which is about “protecting representative portions of each ecological community across a landscape.” This approach is recognized as the most effective approach for protecting the most biodiversity, or number of species, in a particular community. In order to determine the best sites for course-filter conservation, adequate data to analyze ecosystems is needed. This data is collected and analyzed through the Gap Analysis Program to determine the adequacy of existing conservation efforts and to prioritize the best sites for course-filter conservation. Lots of data exist for gap analysis but none of these data sets are complete. In this paper, the authors conduct a gap-analysis on ecosystem types with the best available data. This represents the first continental-scale gap analysis conducted in the United States.

Geospatial data is aggregated for each state and used to determine the stewardship status for parcels of land. This status ranges in degrees of conservation. Conserved lands are rated status 1 to 3, and land that is not conserved at all is status 4. This data represents the most complete source of data available. Gap analyses use National Land Cover Data Set geospatial data on vegetation cover to make inferences on the biological health of a region, but this data is often low quality due to the lack of high resolution satellite imagery. To develop a quality national map on vegetation cover, this data was combined with data on ecosystem regions from the Nature Conservancy. A specific combination of ecosystem region type and land cove type is called an ecosystem analysis unit, each a unique type of ecosystem. 

Figure 1. Conservation status (Table 1) of lands in the Protected Areas Database for the continental United States.

Using GIS, the area with stewardship statuses 1, 2, and 3 was analyzed to determine the effectiveness of existing conservation. There are three problems with attempting this sort of analysis:

1.       “Deciding what level of protection for a particular ecosystem type is sufficient.”

2.       “Defining a baseline amount of area for each ecosystem analysis unit.”

3.       “Deciding which GAP status lands constitute the conservation estate.”

Figure 2. Conservation of ecosystem analysis units: (a) current conservation, (b) hypothetical 10% conservation of
all natural lands.

Of the 554 ecosystem analysis units, an average of 4% of the area was within areas of active conservation. The results of this study illustrate that “the majority of ecosystem analysis units have a small percentage of their total area residing in lands that are managed to support biodiversity.” This finding shows the urgent need for more complete data to be able to design more effective conservation that encompasses high priority areas. The continuous improvement of GIS technologies is important for the development of better and more complete data.

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Dietz, Robert W.; Czech,  Brian. (2005). Conservatoin Deficits for the Continental United States: an Ecosystem Gap Analysis. Conservation Biology, 19(5), 1478-87.