Linking Health and Environmental Data in Geographical Analysis: It’s So Much More than Centroids

719813…in Spatial and Spatio-Temporal Epidemiology, Volume 1, Issue 1…

Linda J. Young, Carol A. Gotway, Jie Yang, Greg Kearney, Chris DuClos

“Programs and studies increasingly use existing data from multiple sources (e.g., surveillance systems, health registries, or governmental agencies) for analysis and inference. These data usually have been collected on different geographical or spatial units, with each varying from the ones of interest. Combining such disparate data creates statistical challenges. Florida’s efforts to move toward implementing the Centers for Disease Control and Prevention (CDC)’s Environmental Public Health Tracking (EPHT) program aptly illustrate these concerns, which are typical of studies designed to measure the association between environmental and health outcomes. In this paper, we develop models of spatial associations between myocardial infarctions (MIs) and ambient ozone levels in Florida during August 2005 and use these models to illustrate the problems that can occur when making inferences from aggregated data, the concept of spatial support, and the importance of correct uncertainty assessment. Existing data on hospital discharges and emergency department visits were obtained from Florida’s Agency for Health Care Administration. Environmental data were obtained from Florida’s Department of Environmental Protection; sociodemographic data were obtained from the US Census Bureau; and data from CDC’s Behavioral Risk Factor Surveillance System were used to provide additional information on other risk factors. We highlight the opportunities and challenges associated with combining disparate spatial data for EPHT analyses. We compare the results from two different approaches to data linkage, focusing on the need to account for spatial scale and the support of spatial data in the analysis. We use geographically weighted regression, not as a visual mapping tool, but as an inferential tool designed to indicate the need for spatial coefficients, a test that cannot be made by using the majority of Bayesian models. Finally, we use geostatistical simulation methods for uncertainty analysis to demonstrate its importance in models with predicted covariates. Our focus is on relatively simple methods and concepts that can be implemented with ESRI’s ArcGIS software.”

California Governor Schwarzenegger Praises GIS at Oracle Openworld

scwartz…from California Governor Schwarzenegger’s remarks at the 2009 Oracle Openworld Conference…

“Now working together, I know that the sky is the limit for you and also your employees. And of course I love seeing all this great action in the private sector. But let’s not forget that’s not the only place where there should be action. Also in the public sector there should be action. The only thing is that six years ago when I became governor, the state of California’s IT was in the dark ages, let me tell you. IT infrastructure was stale and it was outdated, so I hired Teri Takai, who was the head of IT in Michigan and made Michigan be the number one in IT, and we now are moving our way up. First we were not even in the top 20 percent — in the top 20 — now we — then we moved to 15th, then to tenth, now we’re in the top five, and within the next few years we will be also number one in this particular area. So as she –

“The perfect example of the progress that we’re making is if you look at GIS, which is the Geographic Information Systems — I’ve seen that firsthand. GIS is a form of digital mapping technology that our fire departments are now using. So many times when there are big fires, people are wondering why did they have helicopters, you know, at the airport, and why are they not taking off and dumping fire retardant? Well, when there is a lot of fire and there is a lot of smoke and no wind, they cannot see the ground, and therefore they cannot go and dump the fire retardant at that time. They’re waiting for a little wind to take that smoke away.

“But now through this technology, digital mapping technology, our fire departments are using this continuously and through big firestorms it allows firefighters to see through that smoke, giving them more accurate and realtime view of the conditions on the ground. Think for a second about the awesome power of this technology. That information could quite literally make the difference between life and death, make the difference between a home burning or not. And like I said, I’ve seen it firsthand, the kind of advantages that the fire departments have. And of course, California’s — we have already the best trained and the most courageous firefighters in the world, but with the great technology that they have it makes them literally the best in the world. There’s no two ways about that.

“So as you can see, technology not only is some abstract concept. If it is where they’re saving homes from a fire, or saving lives through medical technology, or cleaning the air that our children breathe, or making our businesses more efficient, technology’s impact is in flesh and blood. All across this state and all around the world I’ve seen the infinite limits of technology. I’ve seen the infinite limits of the human potential, and that is why even though that we are in the midst of a crisis, of an economic crisis, and we’re going through tough times, I’ve never seen — been more confident about the future. I am confident about the future because of all of you, because while it is true that we face enormous challenges in the next ten, 15 or 20 years, but stop for a moment and just think back 30 years ago. Could you have imagined the progress that we have made in these last 30 years? Computers, the internet, DNA, GPS, catalytic converters, global networking, email, the cell phones that are the size of a fist, and so on. The list goes on and on.”

Map of the Day: The Plains CO2 Reduction Partnership Region

…from the Map Book, Volume 23


“Although uncertainty still clouds the science of climate change, there is a strong indication that the signficant reduction of anthropogenic greenhouse gas (GHG) emissions is needed. Carbon capture and storage (CCS) offers a promising set of technologies through which carbon dioxide (CO2) and potentially other GHGs can be stored in sinks represented by biologic materials and geologic formations. Within central North America, the Plains CO2 Reduction (PCOR) Partnership is investigating CCS technologies in order to provide a safe, effective, and efficient means of managing carbon dioxide emissions across the center of the continent.

“The PCOR Partnership confirmed that while there are numerous large stationary CO2 sources, the region also has a variety of sinks that represent a tremendous capacity for CO2 sequestration.

“The map was created to provide an understanding of the number and extent of large stationary CO2 sources in central North America. The map also depicts the distribution and extent of oil fields and major sedimentary basins in this region. Many oil fields and deep strata in the basins are suitable targets for the safe, long-term sequestration of CO2.

“Courtesy of University of North Dakota, Energy & Environmental Research Center, 2008.”

Quote of the Day

“You have noticed how, quite suddenly, everybody has become seriously concerned to protect the natural environment. It happened almost overnight, and one can understand how one can ask the question, ‘Where did this idea come from?’ You could say, of course, from biologists, from conservationists, from ecologists, but after all, they’ve really been saying these things for many years past, and previously they’ve never even got on base. Something new has happened to create a worldwide awareness of our planet as a unique and precious place. It seems to me more than a coincidence that this awareness should have happened at exactly the moment man took his first step into space.”

–Fred Hoyle, Astrophysicist, after Apollo 11

Comparison of Tests for Spatial Heterogeneity on Data with Global Clustering Patterns and Outliers

plague…from the International Journal of Health Geographics 2009, 8:55…

Monica C Jackson, Lan Huang, Jun Luo, Mark Hachey, Eric Feuer


“The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated.


“We compare methods for global clustering evaluation including Tango’s Index, Moran’s I, and Oden’s I*pop; and cluster detection methods such as local Moran’s I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango’s MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States.


“For simulated data with outlier patterns, Tango’s MEET, Moran’s I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango’s MEET and I*pop (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran’s I has powers around 0.2-0.3. In the real data example, Tango’s MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango’s MEET. SaTScan also found clusters and outliers in the lung cancer mortality data.


“SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango’s MEET and Oden’s I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango’s method should be used for global clustering evaluation instead of SaTScan.”