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At least 127 records · Page 7Linked to original sources
PubMed2006

Residential exposure to petrochemicals and the risk of leukemia: using geographic information system tools to estimate individual-level residential exposure.

The authors conducted a population-based, case-control study in Kaohsiung, southern Taiwan, Republic of China, to investigate the association between residential petrochemical exposure and leukemia risk among subjects 29 years of age and younger. Between November 1997 and June 2003, 171 cases and 410 controls matched for age and sex were recruited. Since assessment of petrochemical impacts depends on accurate exposure estimates, the authors developed a procedure using geographic information system tools to assign subjects' exposure. The resulting individual-level exposure estimates (the exposure opportunity score) are an integrated exposure measure that accounts for subjects' mobility, length of stay at each residence, distance to petrochemical plant(s), monthly prevailing wind direction, and multiple petrochemical pollution sources. Different conditional logistic regression models were fitted for subjects aged 0-19 and 20-29 years to evaluate separately childhood versus adulthood leukemia. No overall association was observed for the younger age group. However, residential petrochemical exposure was a significant risk factor for leukemia for the older age group. For one unit of increase in the log-transformed exposure opportunity score, the adjusted odds ratio was 1.54 (95 percent confidence interval: 1.14, 2.09). This study illustrates the utility of geographic information system tools for providing refined exposure estimates for residential exposure to petrochemical pollution.

Adolescent↗
PubMedDate not supplied

Using geographic information systems to understand health care access.

BACKGROUND: Determining a community's health care access needs and testing interventions to improve access are difficult. This challenge is compounded by the task of translating the relevant data into a format that is clear and persuasive to policymakers and funding agencies. Geographic information systems can analyze and transform complex data from various sources into maps that illustrate problems effortlessly for experts and nonexperts. OBJECTIVE: To combine the patient data of a community health center (CHC) with health care survey data to display the CHC service area, the community's health care access needs, and relationships among access, poverty, and political boundaries. DESIGN: Georeferencing, analyzing, and mapping information from 2 databases. SETTING: Boone County, Missouri. PARTICIPANTS: Community health center patients and survey respondents. MAIN OUTCOME MEASURES: Maps that define the CHC service area and patient demographics and show poor health care access in relation to the CHC service area, CHC utilization in relation to poverty, and rates of health care access by geopolitical region. RESULTS: The CHC serves a distinctly different area than originally targeted. Subpopulations with unmet health care access needs and poverty were identified by census tract. These underserved populations fell within geopolitical boundaries that were easily linked to their elected officials. CONCLUSIONS: Geographic information systems are powerful tools for combining disparate data in a visual format to illustrate complex relationships that affect health care access. These systems can help evaluate interventions, inform health services research, and guide health care policy. Arch Fam Med. 2000;9:971-978

Catchment Area, Health↗
PubMed2002

Linkage of a geographical information system with the gleams model to assess nitrate leaching in agricultural areas.

The GLEAMS (Groundwater Loading Effects of Agricultural Management Systems, Version 2.10) model was linked with a Geographical Information System (GIS) to evaluate the risk of nitrate pollution in an area of 230 km2 near Valencia (Spain). Under Mediterranean conditions, GLEAMS was calibrated and validated using results from field experiments on citrus orchards and vegetables grown in that area. A graphical user interface (GUI) was implemented in the GIS-model system to allow a non-specialist to run the model, and to represent simulation results as a thematic map. In order to execute the GLEAMS model, data must be grouped in five basic layers: four layers correspond to the base maps (soils, climate, land use, NO3 content in irrigation water), and the fifth layer corresponds to agricultural management practices, introduced in the system interacting to the GUI. To illustrate system capabilities. two rotations with crops in the vegetable area (potato/lettuce/onion/cauliflower, and artichoke/artichoke in 2 years rotation each), and orange trees in the citrus area, were simulated to determine the N leached in the study area. Pollution risk maps show that vegetable crops and areas irrigated with groundwater have the highest potential risk of groundwater nitrate pollution. Further analysis identified potato and artichoke (in the first year) to be the crops with the higher risk.

Agriculture↗
PubMed2005

Building geographic information system capacity in local health departments: lessons from a North Carolina project.

State government, university, and local health department (LHD) partners collaborated to build the geographic information system (GIS) capacity of 5 LHDs in North Carolina. Project elements included procuring hardware and software, conducting individualized and group training, developing data layers, guiding the project development process, coordinating participation in technical conferences, providing ongoing project consultation, and evaluating project milestones. The project provided health department personnel with the skills and resources required to use sophisticated information management systems, particularly those that address spatial dimensions of public health practice. This capacity-building project helped LHDs incorporate GIS technology into daily operations, resulting in improved time and cost efficiency. Keys to success included (1) methods training rooted in problems specific to the LHD, (2) required project identification by LHD staff with associated timelines for development, (3) ongoing technical support as staff returned to home offices after training, (4) subgrants to LHDs to ease hardware and software resource constraints, (5) networks of relationships among LHDs and other professional GIS users, and (6) senior LHD leadership who supported the professional development activities being undertaken by staff.

Community Health Services↗
PubMed2005

Geographic information system method for assessing chemo-diversity in medicinal plants.

The spatial distribution of wild germplasm of Podophyllum peltatum L. (American mayapple) has been analyzed using the Geographic Information System (GIS) with the objective to develop a method and a database for evaluation of biotic and abiotic factors influencing drug yield, and to map elite genotypes for propagation and improvement. The field assessment followed a standard procedure including geographical coordinates of each accession, leaf biomass randomly harvested, identification of associate species, collection of herbarium specimen, soil sample and digital pictures of the site. By overlaying morphological and chemical data with geomorphic information, a thematic map was created locating the podophyllotoxin-rich accessions and the uniqueness of each site was recorded for post-collection analysis. This work has enabled the establishment of a database of P. peltatum germplasm in Mississippi with drug yield linked to spatial locations for rational utilization of our natural resources. While this method integrates information of well-characterized diverse in situ P. peltatum germplasm, it might become a strategy for curators to reduce cost for establishing and maintaining ex situ collections since the genetic material is geo-referenced.

Databases, Factual↗
PubMed2000

Application of a geographic information system to the tracking and control of an outbreak of shigellosis.

A personal computer-based commercial geographic information system (GIS) was applied to an outbreak of Shigella sonnei infection at Fort Bragg, North Carolina. We used a database consisting of demographic, temporal, and home-address information for all recognized cases of S. sonnei that occurred among health care beneficiaries from 23 May 1997 through 14 August 1997. We imported this database into the GIS, which contained a digitized basemap of the local community. Through simultaneous examination of temporal and spatial distribution of the 59 identified cases of S. sonnei, a focus of infection in a single housing area was identified. Targeted education among residents of the neighborhood in which there was intense transmission was associated with prompt extinction of the epidemic. A GIS offers an efficient and practical way to directly visualize the dynamics of transmission of infectious diseases in the setting of a community outbreak.

Adolescent↗
PubMed1992

Use of LANDSAT MSS imagery and soil type in a geographic information system to assess site-specific risk of fascioliasis on Red River Basin farms in Louisiana.

A geographic information system (GIS) was constructed in an ERDAS environment using maps of soil types from the USDA Soil Conservation Service, LANDSAT satellite multispectral scanner data (MSS), boundaries for 25 study farms, and slope and hydrologic features shown in a two-quadrangle (USGS, 7.5') area in the Red River Basin near Alexandria, Louisiana. Fecal sedimentation examinations were done in the fall of 1989, spring of 1990, and fall and winter of 1990-1991 on 10-16 random samples per herd. Fecal egg shedding rates for F. hepatica ranged from 10-100% prevalence and 0.3-21.7 eggs per two grams of feces (EP2G). For Paramphistomum spp., a rumen fluke also transmitted by F. bulimoides but not affected by flukicides, egg shedding rates ranged from 10-91% prevalence and 0.1-42.8 EP2G. Soil types present ranged from sandy loams to hydric, occasionally flooded clays. Herd Paramphistomum spp. egg shedding rates increased with the proportion of hydric clays present, adjusted for slope and major hydrologic features. F. hepatica infection intensity followed a similar trend, but were complicated by differing treatment practices. Results suggest that earth observation satellite data and soil maps can be used, with an existing climate forecast based on the Thornthwaite water budget, to develop a second generation model that accounts for both regional climate variation and site-specific differences in fascioliasis risk based on soils prone to snail habitat.

Animals↗
PubMed1999

A geographical information system to manage mosquito and arbovirus surveillance and control data in the Coachella Valley of California.

A geographical information system was developed to monitor and analyze mosquito abundance and encephalitis virus activity in the Coachella Valley to facilitate mosquito control operations. Data layers include soil types, vegetation types, irrigation method, standpipes, larval occurrence, adult abundance, and viral transmission to sentinel chickens. Base maps are digitized aerial photographs, with data entry done through sections of the range/township system. The image resolution of a section is 100 ft2 (9.3 m2) per pixel. This system currently is operational and in use by the Coachella Valley Mosquito and Vector Control District for data management.

Animals↗
PubMed1991

The benefits of the application of geographical information systems in public and environmental health.

One of the most important issues in public and environmental health today concerns the type of instruments that can be used to devise quick, reliable and scientifically valid methods of rapid assessment which, in turn, can be utilized in health research and in the planning, monitoring and evaluation of health programmes. As the applications of geographical information systems (GIS) relate to the collection, storage, integration, management, retrieval, analysis and display of spatial data, it is not surprising that the potential usefulness of this new technology in the fields of health research and policy is beginning to be realized. This article seeks to demonstrate the opportunities which the use of geographical information systems can offer to research and policy on health issues. The article first describes the principles and objectives of GIS before going on to discuss hardware and software developments as well as the variety of application fields, organizations and users. Some examples of current applications are provided to illustrate the type of work being undertaken. The final sections address issues specifically related to the application of GIS in health research and policies in the European context.

Computers↗
PubMed2005

Use of Geographic Information Systems in the development of prediction models for onchocerciasis control in Ethiopia.

A risk assessment model was developed for onchocerciasis distribution and its control in Ethiopia using Geographic Information System (GIS) methods. GIS data analysis was done to generate 3 separate risk models using selected environmental features of (1) earth observing satellite data on Normalized Difference Vegetation Index (NDVI) and midday Land Surface Temperature (LST) prepared from AVHRR sensor data of the Global land 1-km project for the years 1992 and 1995, (2) FAO agroclimatic databases from the Crop Production System Zone (CPSZ) of the Intergovernmental Authority on Development (IGAD) sub-region of East Africa, and (3) a climate-based forecast index based on the growing degree days (GDD) and water budget concepts. Parasitological data used for the analysis were published and unpublished reports of onchocerciasis surveillance made between 1969 and 2000 in various parts of the country. Analysis of queries based on 1992 and 1995 annual wet and dry season data of the Global land 1-km project resulted in a predictive value of 95.1%, 94.0% and 96.3%, respectively, using data values extracted from buffers centered on sites above 5% prevalence. The model based on CPSZ data predicted an endemic area that best fit the distribution of sites over 5% prevalence; the query was based on CPSZ values of average altitude (442-2134 m), annual mean temperature (18-28 degrees C), annual rainfall (822-1980 mm), annual potential evapotranspiration (1264-1938 mm), rain minus potential evapotranspiration (-124 - 792 mm), average NDVI x 100 (2000-5000) and average terrain percent slope (9-34). The climate-based model based on GDD and water-budget predicted high risk to severe risk areas in the western and southwestern parts of the country. All three of the models predicted suitable areas for the transmission of onchocerciasis outside known endemic areas, suggesting the need for ground-based validation and potential application to current community-directed treatment programs with ivermectin (CDTI) for control of onchocerciasis in Ethiopia.

Agriculture↗
PubMed2003

[Study on the application of geographic information system in spatial distribution of hemorrhage fever with renal syndrome in China].

OBJECTIVE: To analyze the spatial distribution of hemorrhagic fever with renal syndrome (HFRS) in China by geographic information system, and to draw up a map on HRFS risk areas. METHODS: A set of database was set up using the information collected and linked to electronic maps of China in a software ArcGIS 8.01 from 41 HFRS surveillance sites during 1995 - 1998. A HFRS spatial distribution model was developed using inverse distance weighted interpolation of ArcGIS's spatial analysis method. The normalized difference vegetation index (NDVI) in each HFRS surveillance site was extracted from SPOT4 satellite vegetation imagery. Correlation analysis was performed through SPSS 10.0 to analyze the association between NDVI and HFRS incidence, HFRS risk areas were mapped under different colors. RESULTS: Spatial distribution model from HFRS surveillance sites showed that HFRS foci mainly presented in the Heilongjiang River drainage, the middle and lower reaches of the Yellow River, the middle and lower reaches of the Yangtze River, and the Jinghang grant Canal-Huaihe River drainage. It was consistent with HFRS distribution map derived from national infectious disease reporting system. Correlation analysis indicated that HFRS incidence rates were significantly associated with NDVI (r = 0.417, P < 0.01). The HFRS risk areas was mapped according to NDVI of each surveillance site. CONCLUSION: It is promising to apply GIS technology in predication of the distribution of HFRS by establishing this prediction model.

Animals↗
PubMed2001

Geographic information systems as a tool for control program management for schistosomiasis in Egypt.

During a 4-year study a geographic information system (GIS) risk model was constructed for predicting the relative risk of schistosomiasis in Kafr El-Sheikh governorate, Egypt. A 1-year 1990-1991 time series on diurnal temperature difference (dT) prepared from the advanced very high resolution radiometer (AVHRR) sensor on the NOAA-11 satellite was used to develop a regional risk model for the Nile delta based on thermal-hydrological domains. A May 15, 1990 Landsat TM scene (path 177, Row 38) was used to develop a local 'village-scale' environmental risk model based on higher resolution satellite sensor data (30 m picture element size at earth surface). Four of ten classes derived from a tasseled cap (Tcap) transformation of the Landsat TM scene were shown to be significantly related to a 5-year Schistosoma mansoni prevalence database from the Ministry of Health. A risk model was developed based on dT and the proportional area of the four Tcap classes in 5 km(2) buffer zones centered on rural health unit (RHU) reporting units. Available historical data on S. mansoni and its snail host Biomphalaria alexandrina, as well as recent field collected data were gathered and incorporated as separate themes. Model validation was done using data collected on snail population bionomics-infection rates, water quality, underground water table and cercariometry at 13 hydrologically representative sites. The role of soil type, water table and water quality was studied at 79 of 154 rural health unit sites. The model permitted retrieval of relevant data by RHU point location. For the first time in Egypt, the Kafr El-Sheikh GIS schistosoma prediction model can support MOH efforts to make more accurate control program decisions based on environmental predilection sites of endemic Schistosomiasis mansoni.

Animals↗
PubMed2005

Immigration and geographic access to prenatal clinics in Brooklyn, NY: a geographic information systems analysis.

We compared levels of geographic access to prenatal clinics in Brooklyn, NY, between immigrant and US-born mothers and among immigrant groups by country of birth. We used birth data to characterize the spatial distribution of mothers and kernel estimation to measure clinic density within a 2-mile radius of each mother. Results showed that geographic access to clinics differs substantially by country of birth. Certain groups (e.g., Pakistani, Bangladeshi) have relatively poor geographic access despite a high need for prenatal care.

Adolescent↗
PubMed2005

A geographic information systems (GIS) and spatial modeling approach to assessing indoor radon potential at local level.

This study integrates residential radon data from previous studies in Southern California (USA), into a geographic information system (GIS) linked with statistical techniques. A difference (p<0.05) is found in the indoor radon in residences grouped by radon-potential zones. Using a novel Monte Carlo approach, we found that the mean distance from elevated-radon residences (concentration>74 Bq m(-3)) to epicenters of large (> 4 Richter) earthquakes was smaller (p<0.0001) than the average residence-to-epicenter distance, suggesting an association between the elevated indoor-radon and seismic activities.

Air Pollutants, Radioactive↗
PubMedDate not supplied

Using geographic information systems to assess risk for elevated blood lead levels in children.

OBJECTIVES: Targeted screening for childhood lead poisoning depends on assessment of risk factors including housing age. Using a geographic information system (GIS), we aim to determine high-risk regions in Charleston County, South Carolina, to assist public health officials in developing targeted lead-screening. METHODS: Properties built before 1978 were geocoded (assigned latitude and longitude coordinates) from tax assessor data. Addresses of Charleston County children who have been screened for lead poisoning were also geocoded. Locations of all housing, lead poisoning cases, and negative screens were created as separate map layers. Prevalence ratios of lead poisoning cases were calculated, as were relative risks for each category of housing. RESULTS: Maps of Charleston County were produced showing the location of old housing, where screening took place, and where cases were found. One thousand forty-four cases were identified. Twenty percent of children living in pre-1950 homes had elevated blood lead levels (EBLL). Children living in pre-1950 housing were 3.9 times more likely to have an EBLL than children living in post-1977 housing. There was no difference in risk of living in a 1950-1977 home vs. a post-1977 home. A large number of cases were also found in an area of newer houses, but near a potential point source. Eighty-two percent of all screens were from children in post-1977 homes. CONCLUSIONS: Children living in pre-1950 housing were at higher risk for lead poisoning. GIS is useful in identifying areas of risk and unexpected clustering from potential point sources and may be useful for public health officials in developing targeted screening programs.

Child↗
PubMed2006

Validation of a geographic information system model for mapping the risk of fasciolosis in cattle and buffaloes in Cambodia.

Maps showing gradations of risk of fasciolosis due to Fasciola gigantica in Cambodia were produced using geographic information systems (GIS) technology in conjunction with determinants of fasciolosis. A comparison between levels of risk predicted by the maps and field measurements of prevalence in 11 provinces (n=1406) showed general agreement, which suggested the epidemiological determinants and weightings used to produce the maps were appropriate. However, due to logistical constraints, prevalence was measured at the provincial level and animals were not randomly sampled (and thus were unlikely to be representative of variability within provinces). To address this, additional field work was carried out to measure prevalence in more detail--faecal samples were collected from a randomly selected set of animals in four districts across a representative province for areas predicted to be at high risk (n=311), moderate risk (n=268) and no risk (n=262). As with the original field survey, the results show general agreement between prevalence and risk predicted by the maps, with the best fit found for areas predicted to be at high risk.

Animals↗
PubMed2001

Application of geographic information systems and remote sensing to schistosomiasis control in China.

Progress in China on developing prediction models using remote sensing, geographic information systems and climate data with historical infection prevalence and malacology databases is reviewed. Special reference is made to the effects of the Yangtze river Three Gorges dam project on environmental changes that may impact changes in the spatial and temporal distribution and abundance of Schistosoma japonicum in China, and the future success of disease control programs.

Animals↗
PubMed2004

A geographic information system simulation model of EMS: reducing ambulance response time.

Response time is a very important factor in determining the quality of prehospital EMS. Our objective was to model the response by Israeli ambulances and to offer model-derived strategies for improved deployment of ambulances to reduce response time. Using a geographic information system (GIS), a retrospective review of computerized ambulance call and dispatch logs was performed in two different regional districts, one large and urban and the other rural. All calls that were pinpointed geographically by the GIS were included, and their data were stratified by weekday and by daily shifts. Geographic areas (polygons) of, at most, 8 minutes response time were simulated for each of these subgroups to maximize the timely response of calls. Before using the GIS model, mean response times in the Carmel and Lachish districts were 12.3 and 9.2 minutes, respectively, with 34% and 62% of calls responded within 8 minutes. When ambulances were positioned within the modeled polygons, more than 94% of calls met the 8-minute criterion. The GIS simulation model presented in this study suggests that EMS could be more effective if a dynamic load-responsive ambulance deployment is adopted, potentially resulting in increased survival and cost-effectiveness.

Ambulances↗