DISCUSSION: The Snow cholera map (Fig 1), is the first and simplest example of GIS presented here. It shows the spatial relationship between cholera cases and led to the correct conclusion about the source of the cholera outbreak. The dramatic decrease in the cost of computing (Fig 2) enables the study of more complex processes. The correlation between the presence of malaria vectors and land use (Fig 3) enables predictive modeling of malaria risk based on geology, land use, and seasonal factors such as rainfall and river stage (Ageep). Public health authorities can now target malaria vector eradication efforts in the highest risk areas. This improves the cost effectiveness of these efforts. This is very important since malaria disproportionately affects poorer developing nations. An exposure intensity map of a presumed risk factor from the Vinceti study of birth abnormalities around a solid waste incinerator in Italy (Fig 4) demonstrates how data from a limited number of sample points can be extrapolated to infer risk or exposure to environmental hazards. This study found no correlation between exposure intensity and birth abnormalities. Excluding exposure to a toxin in the environment as a disease risk factor is also an important result as demonstrated in the final case study regarding the correlation between consumption of well water and Parkinson’s disease in rural California. This study did find a correlation between the risk factor (consuming well water) and the disease. The presumed agents in this study were agricultural chemicals in the well water. Rather than test specifically for the presence of the chemicals, this study used detailed public records of pesticide applications to create a model of exposure intensity. The researchers could not rule out other exposure routes in this study nor could they rule out that exposure to other classes of chemicals such as industrial waste and toxic metals may have also played an important role in the observed increase in disease. Calculating risk based on exposure is extremely difficult. Not only are there thousands of chemicals in the environment, the levels of which are constantly changing over time, but, people do not normally remain stationary for very long. They therefore have a constantly changing exposure profile. This study provided no graphs or maps.

ABSTRACT: Epidemiological studies involve analyzing public health factors in the context of timeand space, with the goal of mitigating disease outbreaks. Emerging advances in computerprocessing power and cost are facilitating research into linkages between geospatially-distributedrisk factors for illness and disease. Geographic Information Systems (GIS) provide a softwaretechnology that allows scientists to easily link public health databases to geospatial informationand forms the cornerstone of epidemiology in the 21st century.

Improved resolution of datasets allows visual representation of complex, multilayered, logical,numerical, and statistical relationships between populations, risk factors, and known orhypothesized causal factors. Geospatial relationships combined with raw and processed dataenable researchers to identify, mitigate, or prevent both epidemic and endemic disease fosteredby vectors that have a geographic component. This developing technology comes with the costof upgrading computer workstations and network bandwidth to accommodate the geometricallyincreasing size of the datasets, however the potential benefits to public health management aresignificant. This paper provides an overview of GIS applications in the public health sector, andpresents case studies demonstrating the efficacy of the technology.

9. Geographic Information Systems and Geospatial Analysis:

A 21st Century Tool for Epidemiology and Public Health Management.

REFERENCES

Ageep et al, 2009, Spatial and temporal distribution of the malaria mosquito Anopheles arabiensis in northern Sudan: influence of environmental factors and implications for vector control Malaria Journal 8:123 doi:10.1186/1475-2875-8-123 Beale et al, 2008, Methodologic Issues and Approaches to Spatial Epidemiology: Environ Health Perspect 116:1105–1110 doi:10.1289/ehp.10816

Bunnell et al., 2005, GIS in Human Health Studies, in Selinus, 2005doi: unavailable

Gatto et al, 2009, Well-Water Consumption and Parkinson’s Disease in Rural California: Environ Health Perspect 117:1912–1918doi:10.1289/ehp.0900852

Vinceti et al, 2009, Risk of congenital anomalies around a municipal solid waste incinerator: a GIS-based case-control study International Journal of Health Geographics 8:8 doi:10.1186/1476-072X-8-8

Nielsen and Jensen, 2005, Environmental Epidemiology, in Selinus, 2005doi: unavailable

Saxena et al, 2009,Application of spatial technology in malaria research & control: some new insightsIndian J Med Res 130, August 2009, pp 125-132doi: unavailable

Weinstein and Cook, 2007, Epidemiological Transitions and the Changing Face of Medical Geology, Ambio, v. 36, no. 1 doi: unavailable

W. VreelandES473 Environmental Geology

INTRODUCTION: A geographic Information System (GIS) can be as simple as points plotted on a paper map with some attribute attached to the points. One classic example of this is the map of cholera cases prepared by Dr. John Snow during the London epidemic of 1854. This map enabled authorities to close the well at the center of the cholera cluster and abate the epidemic. GIS today involves sophisticated software and can be integrated with Remote Sensing (RS) and Global Positioning Systems (GPS) technologies to provide real time monitoring of geological processes and epidemiological vectors. The key element of GIS is that attributes are related spatial and some system is utilized to process and analyze these relationships.

The exponential decay in the cost of computer resources is now enabling cost effective studies at spatial resolutions that could only be dreamed of a few decades ago. Using the cost of computer hard drives as a proxy for the overall cost of computing resources puts this in perspective. A two terabyte hard drive can be purchased today for as little as $149. The same amount of disk storage would have cost about $2 billion in 1980.

This poster examines three case studies that rely on these technologies. These studies examine the spatial and temporal distribution of the Malaria mosquito,well water consumption and Parkinson's disease in rural California, and the risk of congenital anomalies around a municipal solid waste incinerator in Italy.

CONCLUSION: GIS, RS, and GPS are now being combined to provide a synergistic force multiplier for efforts to monitor and improve human health. The world is a very complicated place. The human body is also very complicated. Individual response to risk factors varies greatly. GIS technology is now robust enough to begin sifting through myriad temporal and spatial relationships and categorize and quantify risk factors that were not obvious just a few decades ago. As the technology continues to evolve we can expect that the cost of protecting human health from geologic or spatially related risk factors will diminish.

Figure 1 Dr. John Snow cholera map, 1854.

Figure 2 Graph depicting exponential decline in computer hard drive storage as proxy for cost of computing.

Figure 3 Map of mosquito larvae and water sources along Nile River.Figure 4 Exposure intensity map near a solid waste incinerator, Italy