Utilizing spatiotemporal analysis of influenza-like illness and rapid tests to focus swine-origin influenza virus intervention

In their study of H1N1 cases within Cameron County, Texas, Wilson et. al. sought to analyze the outbreak of April 2009 on “a fine spatial scale within a community”. Researchers drew on data from three different methods of testing for H1N1 – the presence of flu-like symptoms recorded by a health professional (ILI), a rapid test that could be done on site with quick results (RIDT), and a laboratory-confirmed test that is highly accurate but takes weeks to process (S-OIV). After obtaining these datasets from health centers, Wilson et. al. geocoded all cases into a GIS and grouped them by testing method. Researchers also categorized the data by age and estimated time of outbreak. The tool SaTScan was used to identify clusters and analyze the spatial distribution of cases in and around Brownsville, the urban center of Cameron County. 

Wilson et. al.’s findings showed that all three measures used to identify cases of H1N1 were spatially correlated – indicating that cheaper, faster methods of testing (such as RIDT) could be used just as effectively as slower methods to identify cases, reducing the time needed to locate patients sick with H1N1. The findings also suggested that real-time analysis of ILI and RIDT tests, at the peak of an initial outbreak, could be used to identify the “highest geographical risk areas” early. 

By mapping the areas with greatest risk of infection in real-time, medical professionals could have enough information to act quickly and target resources at the areas that most need them in the event of an outbreak. Wilson et. al. suggest that these measures could “[minimize] the impact of future outbreaks on local communities”, potentially saving money and lives.

Wilson, J. G., Ballou, J., Yan, C., Fisher-Hoch, S. P., Reininger, B., Gay, J., ... & Lopez, L. (2010). Utilizing spatiotemporal analysis of influenza-like illness and rapid tests to focus swine-origin influenza virus intervention.Health & place, 16(6), 1230-1239.

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I have acted with honesty and integrity in producing this work and am unaware of anyone who has not.

Simone Yoxall

GIS for Health and the Environment

GIS can be used in a number of different beneficial ways, GIS helps investigate questions related to location, trends, condition, routing, patterns and modeling. GIS can be used to help track down diseases in a specific area, and control the effects of this disease within this area. In the map below, heart disease among adults older than age 35, tend to be more prevalent in the Southeast.

 By mapping this out, this provides a scientific base for the health ministries to deliver  health equity and strengthen primary health care.  GIS is the tool that can take a look at statistics by interpreting the situation out on a map. All sorts of data can be transformed and subjected to GIS analysis. Tsaselle Nuttall et al. provide examples of GIS application in the integration of environment and health in the control of schistosomiasis in Botswana and Senegal. In Morocco, surveillance data from the schistosomiasis control program of Botswana and Senegal will be integrated and subjected to GIS analysis. environmental factors caused by diseases or disease transmission can also be determined by GIS. Images mapped would be applied to the study of eco-epidemiology, a branch of epidemiology that focuses of the environmental effects and factors determined by health, and can indicate what resources could be mobilized for the benefit of mankind. Malaria transmission in the Brazilian Amazon was tracked using GIS tools and strategies in order to find the root of the outbreak. GIS can be applied to identify specific features in the land that are responsible for these epidemics. GIS can take a variety of data to track and measure outcomes, such as topological sheets of soil types,  water table, topography, irrigation drainage, water bodies  and meteorological data. GIS is not only useful for tracking numbers, but is also useful to find solutions to these health and environmental issues we are facing in certain areas of the world today.

I have acted with honesty and integrity in producing this work and am unaware of anyone who has not. Colleen Nair
Sharma, V. P. (May 01, 1997). GIS for Health and the Enviroment. Tropical Medicine & International Health, 2, 5, 508.

Global Consequences of Land Use

          Land use has been an environmental issue for quite some time, but is now becoming a "force of global importance". Specifically, nearly the whole world relies on land use practices to provide food, water, and shelter. In this article, Jonathan A. Foley outlines the major impacts of land use. First, the effects land use has on food production. Modern agriculture has become a major reliance on the increase of food production. Grain harvests have doubled in the amount it produces, however the increase in food production has also increased the use of fertilizer, by 700% in the past 40 years. This causes soil erosion, the loss of native habitats, and degradation in water quality. Land use has also had an effect on freshwater resources. Irrigation is a major problem because it directly affects the resource and reduces the flow of the river or dries it up completely. Not only that, but all the fertilizer from the runoff gets into the river killing fish and other species. The forest ecosystem also comes into the picture because of land use. By taking timber, forest grazing, and road expansion it still harms the forest in terms of productivity, biomass, and species composition. Lastly, modifying habitats, road and dam construction, irrigation, increase in people and livestock, and the concentration or expansion or urban areas lead to infectious outbreaks. Specifically, disrupting a habitat increases the chance of disease because 75% of human diseases links back to wildlife or domestic animals. 

            The figure below exemplifies the effects land use has on the ecosystem. The first picture, is the natural ecosystem, with no production. It can maintain most things, except for food production. The middle picture depicts intensive cropland. This place can only maintain crop production, it does not have habitat or water flow. The third picture, however, is the cropland restored. This ecosystem can sustain all things: food, life, water, etc. 

                

             In conclusion, modern land use practices help short-term in ways of providing an abundance of food and water, but long-term have negative effects on the ecosystem. Confronting land use practices will require the assessment and management of human needs versus ecosystem needs and finding a balance between the two where we are not destroying our ecosystem faster than we are gaining human needs. 

I have acted with honesty and integrity in producing this work and am unaware of anyone who has not. Nataley Ford

Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., ... & Helkowski, J. H. (2005). Global consequences of land use. science, 309(5734), 570-574.       

Quantifying the Extent of Food Deserts in Lawrence, Kansas, USA

In an ever-developing country, it seems counterintuitive that food deserts are becoming more of a problem. But unlike its name, which implies images of an arid climate and an empty landscape, a food desert refers to the availability of food within a 500meter radius of a certain location, such as a home or a school, whether in a large city or a small town. When trying to determine whether a food desert is present or not, it is important to take into consideration several influential factors, such as public transportation, quality of food, and culture surrounding food in the area.  In an effort to better understand food deserts and to challenge the implications of a food desert, authors Lucius Hallett and Dave McDermott conducted a project in Lawrence, Kansas.

Within the study, the intent was to identify if there a relationship between lower socioeconomic status households and food deserts, and more importantly, why. To conduct this project, a survey is sent out to 1,000 random households in four different zip codes in Lawrence asking questions about transportation, socioeconomic status, distance to grocery store, and preference of available food in the store. From the 673 responses, they conclude that: it depends. Food deserts are not within strict boundaries and the concept becomes more fluid when a wider variety of factors are taken into consideration. But this study concludes that food deserts are most likely to affect individuals without any means of transportation, such as the bus, a friend, or a car of their own, who must walk to purchase food. With this conclusion, food deserts could exist for some that in the same area does not for others.

To find their result, Hallett and McDermott look at several factors that promote food deserts. The first and biggest is transportation. Through the survey responses, the households without any personal transportation are identified and then compared to public transportation routes. The second factor is quality and availability of food. The study identifies stores that meet a set standard of a footprint of at least 30,000 square feet, including specialty stores and cultural food outlets. Overlaying the map of transportation and the locations of the store, potential food deserts can then be identified.  The results of the survey question that identify lower socio-economic households prove, at least for Lawrence, that food deserts are less affected by lower income than they are urban development. The food deserts of Lawrence, Kansas are in areas of the city that have been fully developed since the early 1900s, before the demand for a high-volume grocery store existed. Because chain stores such as Wal-Mart and Target also use traffic routes and patterns to determine locations, neighborhoods, such as the one in Lawrence, typically don’t have multiple-lane or high-speed highways through the middle that are would be conducive to large business grocery stores.

Food deserts are a phenomenon that can occur anywhere, especially as development continues to grow. When identifying the presence of a food desert, it is important to be mindful of the many factors that contribute, and remember how it affects different populations to different extents. Studies such as this one make it easier to pinpoint and begin to correct the reasons for lack of food.

I have acted with honesty and integrity in producing this work and am unaware of anyone who has not. Mattie Cryer

Hallett, L. F., & McDermott, D. (2011). Quantifying the extent and cost of food deserts in Lawrence, Kansas, USA. Applied Geography, 31(4), 1210-1215.

Five Essential Properties of Disease Maps

    Five Essential Properties of Disease Maps 

          Maps are used in a number of different ways to signify countless things. They are especially helpful in understanding patterns in, specifically disease. In the article titled “Five Essential Properties of Disease Maps,” Beyer, Tiwari and Rushton explain the importance of disease maps, and how to make them. It is key that the map is made in the best way possible to fully understand the pattern of disease. Over the past 20 years, they began to recognize the problems with disease maps and were able to classify the problems in 4 categories. These categories include 1) the small numbers problem, 2) the modifiable areal unit problem, 3) the limited variability problem, and 4) the visual impact of large areas problem. They saw that disease maps with these issues were unable to provide useful information when being studied. They decided to develop a methodology in order to create disease maps to make them more adaptive to the area being studied. Their method is called the “adaptive spatial filtering” which means that the map is made based on the density of the population in the area. They argue that this is able to fix the main problems with disease maps.

            Further Beyer et al explain that there are five essential properties of a disease map. These include 1) controlling the population basis of spatial support for estimates of rates, 2) displaying rates continuously through space 3) providing maximum geographic detail across the map, 4) considering directly and indirectly age-sex adjusted rates, and 5) visualizing rates within a relevant place context to enhance interpretation. The maps below show the difference between a map with many of the problems Beyer et al described compared to one with the five essential properties.

The authors of this piece believe that their method is critical when creating a disease map because it allows viewers to better see the patterns of disease. In the future they suggest that the measure of statistical confidence is used to explore implications of disease. Through these maps we can gain an understanding of the spread of disease in order to reduce health inequalities.  

References 

Beyer, K. M., Tiwari, C., & Rushton, G. (2012). Five essential properties of disease maps. Annals of the Association of American Geographers, 102(5), 1067-1075.

I have acted with honesty and integrity in producing this work and am unaware of anyone who has not

Jolene Klenzendorf 

The Effect Urbanization Has On Watershed Runoff

A study conducted by Francisco Olivero and Buren B. DeFee in 2007 sought to understand how to most effectively urbanize a watershed area without dramatically increasing runoff and harming the local ecosystem. They wanted to study this so they could find a way to develop areas while being sustainable, and to see how much the watershed could take before runoff flooded the land. Therefore, the Harris County Appraisal District, creators of the study, turned their attentions to the Whiteoak Bayou Watershed in Texas, and studied its runoff level from 1949 to 2000.

To gather data, researchers first measured daily precipitation for the duration of the study, and averaged the daily amount of rainfall for all five decades it spanned. They found a statistically significant change in precipitation. They then measured development by gathering city and flooring plans for the 52-year period. They also visited the locations in person and took measurements of their areas to avoid error. The scientists then compared the precipitation data with the development plans, and synthesized both datasets into GIS applications (the Landscape Ecology Program) to create 52 individual maps of runoff data, which were then combined into a raster format.

This map shows development and "impervious" areas over the years (1949, 1972, 2000), areas which the researchers considered important to changing the amount of water runoff in the watershed. Using the maps as data, they used an algorithm to calculate the increase of runoff.

Ultimately, the researchers found that before 1970, urban development did not affect runoff levels as much as natural precipitation did. However, after 1970, the landscape was altered sufficiently that runoff depths and peak flows increased by 146% and 159%! This posed a flooding risk to the area around it. However, they also stressed that it was important not to blame urbanization for the increase entirely, as precipitation and global warming still had a hand in it.

Olivera, F., & DeFee, B. B. (2007). Urbanization and Its Effect On Runoff in the Whiteoak Bayou Watershed, Texas1.

Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning

This study evaluates the accuracy of the iPhone 3G location services, being the first to feature a hybrid of Assisted Global Positioning System, cellular positioning, and WiFi. To begin, the article gives an overview of the history of the Global Positioning System (GPS), the leading system in transmitting information to the Location Based Services (LBS). GPS devices have historically been affordable and reliable to all users. However, after smart phones began incorporating Assisted Global Positioning Systems (A-GPS) into their design, users became dependent on this feature.

                The A-GPS feature of iPhones uses remote servers such as satellites to operate. When the A-GPS system is turned on, the iPhone does not need to decode complex messages from satellites that would otherwise compromise the effectiveness of the GPS. However, despite the perks of using an A-GPS, the A-GPS and standard GPS are less effective in largely populated, urban areas or indoors because of limited satellite exposure. High-sensitivity geographic information systems (HSGPS) were attempting to correct this issue when this article was written. But no matter what the system being used by the iPhone device, WiFi positioning is needed to determine the specific position or access point (AP) of the device. There are several APs in urban areas, making the coverage and performance of WiFi positioning much stronger. There are many WiFi systems out there, but the way they all work remains the same: first, an application needs to be installed to a WiFi-enabled device. The iPhone 3G already has this application installed in the device’s firmware. Once this is complete, the application records surrounding WiFi signals and sends them back a remote location server. The server then compares the information to information already recorded in its database and the estimated location is then sent back to the iPhone. There is varying effectiveness from system to system. Cellular networks have jumped on the opportunity to improve wireless connectivity. This competition amongst networks has allowed wireless networks to stretch worldwide. Each network has a series of its own towers, and the device’s location is determined in order to transfer its signal to the nearest tower. This process is known as cell identification (cell ID) or cellular positioning. The accuracy of this process, much like LBS, depends heavily on the density of the device’s location.

                With a hybrid of all three of these systems, the iPhone caught a lot of attention. To study the effectiveness of this system, this study adopted the following method:

“A-GPS locations were collected at outdoor sites under ideal conditions, i.e. excellent satellite visibility. WiFi and cellular positions were collected at indoor sites where A-GPS position fixes were not available. Switching between these two positioning modes was accomplished by turning the iPhone’s WiFi receiver on and off – when no A-GPS or WiFi is available, the iPhone’s location service defaults to cellular positioning. A third-party application was used to record the locations as waypoints and these were transferred to GIS software for processing.”

With ten field tests, all 20 minutes in length, the study resulted yielded that the iPhone 3G is much less accurate than singular GPS devices that only have one function: to determine location. The iPhone 3G resulted in an average median error of 8 meters in each of the ten 20-minute field tests. However, when WiFi abilities were enabled on the iPhone 3G, it resulted in an average median error of 74 meters after 58 field tests. When cellular positioning services were enabled in the iPhone 3G, this resulted in the least accurate results: an average median error of 600 meters for 64 field tests. In order to improve results, this study suggests that “future research in this area should try to extend the recent progress made in controlled indoor environments to larger indoor/outdoor environments.”

Zandbergen, P. A. (2009). Accuracy of iPhone locations: A comparison of assisted GPS, WiFi and cellular positioning. Transactions in GIS, 13(s1), 5-25.

The NDVI and Animal Ecology

The Normalized Difference Vegetation Index (NDVI) is a tool that uses the reflection of near-infrared and red light and satellite technology to analyze the vegetation growth in an area. However, NDVI has also made an impact in studying animal species migration patterns, population, and spatial patterns, allowing for analysis of an area's biodiversity over time. In their study, Pettorelli et al., write that understanding and being able to predict people's effects on land use and habitat destruction "is fundamental to designing appropriate adaptation and mitigation strategies" (Pettorelli et al.). Therefore, having a tool that allows for studying and anticipating these changes in biodiversity over time is essential to humans being able to combat climate change.

Table 1 (below) provides a list of studies that have been conducted using NDVI to research animal species' dynamics. As shown in the list, it is not only the habits of herbivores that can be analyzed using NDVI technology, but also insectivorous and carnivorous species as well, based on the idea that the primary production of an ecosystems vegetation affects the entire food web of that area.

The uses of NDVI have a great impact on models that predict how areas will change as the effects of climate change worsen. One 2009 study cited in the article, done by De la Maza et al., was able to show that although rainfall in parts of Chile was expected to decrease by 15 to 40%, primary production would only decrease 2 to 9% (Pettorelli et al.). So, NDVI presents a "cheap, systematic, repeatable, and verifiable monitoring method" for wildlife management and climate change mitigation (Pettorelli et al.).


Pettorelli, N., Ryan, S. J., Mueller, T., Bunnefeld, N., Jedrzejewsk, B., Lima, M., & Kausrud, K. (2011). The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology. Climate Research, (46), 15-27.

GTography: Race and City Council Members in Georgetown

This map shows the distribution of Hispanic populations in Georgetown and city council districts.  Georgetown has 7 city council districts and a high Hispanic population (21.8%).  Cities are typically racially segregated, as seen in GIS lab #18.  Here, it is apparent that some council districts (like that of Councilman Gonzalez) have high populations of Hispanics, while other districts (like that of Councilman Hesser) have very small Hispanic populations.  This means that issues faced by Hispanic populations might be dealt with more heavily by those council members located with heavy clusters of Hispanic populations.  The city council person for Southwestern University is Rachael Jonrowe, District 6.  Data for this map was obtained from the city of Georgetown and Williamson County GIS databases.

This article talks about the geographic features of Florida. The natural landscape of Florida, specifically southern Florida, is the everglades. These areas are wet and unpredictable which makes it especially difficult to build structures. The slow, constant flow of water from Lake Okeechobee is a natural phenomenon that disrupts the plan of man.

In order to change this and make the land usable for construction, the Everglades Drainage District (EDD) and the Internal Improvement Fund (IIF) spent about $18 million towards the drainage and maintenance of the land to build structures. People took advantage of this and the water flow and are now growing crops in these areas. Despite an immense growth in the economy, these actions are disturbing the natural ecosystems of this region and we are not sure what long-lasting effects it may have.

 Robert Walker & William Solecki (2004): Theorizing Land-Cover and Land-Use Change: The Case of the Florida Everglades and Its Degradation, Annals of the Association of American Geographers, 94:2, 311-328