Using a GIS-based floating catchment method to assess areas with shortage of physicians

This paper presents a geographic information system (GIS) based floating catchment method for identifying physician shortage areas. The traditional designation methods are primarily regional availability measures, which use administrative boundaries such as counties as the basic spatial units for calculating physician to population ratios and designate shortage based on those ratios. Such approaches have been criticized for their inability to account for either the spatial variations of population demand and physician supply within those boundaries or for population-physician interactions across them. The floating catchment method addresses the internal spatial distribution problem by deriving population data from a smaller unit, the census tract. The potential cross border patient-physician interaction is taken into consideration by using circles of reasonable radius around each census tract centroid as the basic spatial units, which can encompass areas on either side of an administrative border. By varying the radius of the catchment circle, this paper demonstrates that the physician to population ratio is scale dependent and that the greatest variability of the ratios and shortages occur at the most local scales (< 20 miles), which argues for using finer spatial resolution data in shortage designation practice.     

Identifying environmental risk factors for endemic cholera: a raster GIS approach

The bacteria that cause cholera are known to be normal inhabitants of surface water, however, the environmental risk factors for different biotypes of cholera are not well understood. This study identifies environmental risk factors for cholera in an endemic area of Bangladesh using a geographic information systems (GIS) approach. The study data were collected from a longitudinal health and demographic surveillance system and the data were integrated within a geographic information system database of the research area. Two study periods were chosen because they had different dominant biotypes of the disease. From 1992 to 1996 El Tor cholera was dominant and from 1983 to 1987 classical cholera was dominant. The study found the same three risk factors for the two biotypes of cholera including proximity to surface water, high population density, and poor educational level. The GIS database was used to measure the risk factors and spatial filtering techniques were employed. These robust spatial methods are offered as an example for future epidemiological research efforts that define environmental risk factors for infectious diseases.     

How far?: Using geographical information systems (GIS) to examine maternity care access for expectant mothers in a rural state

Various factors have made rural access to maternity care a significant problem for rural women. The geographic distance between a mother's county of residence and the county in which she gave birth was examined in a rural state. Analyzing North Dakota county-level data using geographic information system (GIS) software, women from over half of the state's counties, making up nearly 18% of all births, were found to be over 40 miles to the hospital in which they gave birth. These findings suggest that rural women may experience significant geographic barriers as they receive health services in the prenatal, delivery, and postpartum periods of their pregnancy. We highlight the value of GIS, particularly geovisualization power, and note models of care that may be effective for rural women.     

How Far?: Using Geographical Information Systems (GIS) to Examine Maternity Care Access for Expectant Mothers in a Rural State

Various factors have made rural access to maternity care a significant problem for rural women. The geographic distance between a mother's county of residence and the county in which she gave birth was examined in a rural state. Analyzing North Dakota county-level data using geographic information system (GIS) software, women from over half of the state's counties, making up nearly 18% of all births, were found to be over 40 miles to the hospital in which they gave birth. These findings suggest that rural women may experience significant geographic barriers as they receive health services in the prenatal, delivery, and postpartum periods of their pregnancy. We highlight the value of GIS, particularly geovisualization power, and note models of care that may be effective for rural women.     

Payment to health maintenance organizations and the geographic factor

The adjusted average per capita cost (AAPCC) payment system for Medicare risk-based plans uses a county level geographic adjustment factor to account for differences in beneficiary costs across areas. The implications of abandoning the county unit as the basis of the geographic area are examined and the merging of counties to match the geographic definition used in the prospective payment system are considered. Year-to-year variation in a county AAPCC is inversely associated with county population size and, based on year-to-year AAPCC variation, 86 percent of all counties are too small to be used for the geographic adjustment.     

地理信息系统技术在浙江省钉螺监测中的应用

目的 探索地理信息系统(GIS)在浙江省血吸虫病中间宿主钉螺监测中的应用.方法 收集浙江省2005-2009年血吸虫病调查资料,建立GIS螺情数据库,应用ArcGIS9.2软件,导入GIS数据库各项属性并制作所需钉螺面积空间分布电子图和差值图.结果 2005-2009年共有28个县先后查出钉螺,5年累计查出有螺村1580个,有螺面积513.28 hm2.建立了"十一五"期间全省GIS螺情数据库;根据钉螺面积大小标记不同颜色,制作了电子分布图,实现全省钉螺分布信息电子化;2009年与2005年有螺面积比较,差值空间分布图显示有螺面积压缩或增加的县数分别占48.0%(12/25)和52.0%(13/25);在国家级血吸虫病监测点建立了有螺环境卫星迭加图,呈现17个螺点,每个螺点显示螺情有关信息.结论 应用GIS制作的钉螺面积分布图、差值空间分布图能直观地显示螺情变化,为掌握血吸虫病疫情以及制定防治策略提供科学依据.     

Alcohol mortality: a comparison of spatial clustering methods

The identification of spatial clusters of alcohol mortality can be a key tool in identifying locations that are suffering from alcohol-related problems or are at risk of experiencing those types of problems. This study compares two methods for identifying statistically significant spatial clusters of county-level alcohol mortality rates in New York. One method utilizes a local indicator of spatial association to determine which groups of neighboring counties have rates that are significantly related to each other. The other method is a spatial scan technique that calculates a maximum likelihood ratio of cases relative to the underlying population to identify the group of counties that rejects the null hypothesis of "no clustering". The results show that because each technique bases its cluster detection on its own criteria, different counties are selected by each method. However, the overlap of the selections indicates that the two analytic methods illustrate different elements of the same clusters. Consequently, these spatial analytic techniques are seen as complimentary and are best used in tandem rather than individually. These findings suggest that multiple methods are a preferred approach to identifying clusters of alcohol-related mortality at the county level.     

Molecular Epidemiology of Reemergent Rabies in Yunnan Province,Southwestern China

Yunnan Province in China borders 3 countries (Vietnam, Laos, and Myanmar) in Southeast Asia. In the 1980s, a large-scale rabies epidemic occurred in this province, which subsided by the late 1990s. However, 3 human cases of rabies in 2000 indicated reemergence of the disease in 1 county. In 2012, rabies was detected in 77 counties; 663 persons died of rabies during this new epidemic. Fifty two rabies virus strains obtained during 2008–2012 were identified and analyzed phylogenetically by sequencing the nucleoprotein gene. Of the 4 clades identified, clades YN-A and YN-C were closely related to strains from neighboring provinces, and clade YN-B was closely related to strains from Southeast Asia, but formed a distinct branch. Rabies virus diversity might be attributed to dog movements among counties, provinces, and neighboring countries. These findings suggest that Yunnan Province is a focal point for spread of rabies between Southeast Asia and China.     

The Use of Health Service Areas for Measuring Provider Availability*

ABSTRACT: Measurement of the availability of health care providers in a geographic area is a useful component in assessing access to health care. One of the problems associated with the county provider-to-population ratio as a measure of availability is that patients frequently travel outside their counties of residence for health care, especially those residing in nonmetropolitan counties. Thus, in measuring the number of providers per capita, it is important that the geographic unit of analysis be a health service area. We have defined health care service areas for the coterminous United States, based on 1988 Medicare data on travel patterns between counties for routine hospital care. We used hierarchical cluster analysis to group counties into 802 service areas. More than one half of the service areas include only nonmetropolitan counties. The service areas vary substantially in the availability of health care resources as measured by physicians and hospital beds per 100,000 population. For almost all of the service areas, the majority of hospital stays by area residents occur within the service area. In contrast/for 39 percent of counties, the majority of hospital stays by county residents occur outside the county. Thus, the service areas area more appropriate georgraphic unit than the county for measuring the availability of health care.     

基于面到面泊松克里格方法的手足口病发病率空间分布降尺度研究

目的 运用面到面泊松克里格降尺度方法,对山东省2010年区（县）手足口病发病率进行降尺度插值,探究手足口病在乡镇尺度上的空间分布模式,为卫生部门更精准的制定防控措施和分配医疗资源提供参考依据。方法 收集2010年山东省108个区（县）的手足口病发病数,采用面到面泊松克里格方法进行降尺度插值,运用地理信息系统（GIS）对插值结果进行空间可视化,将区（县）发病率降尺度插值到乡镇发病率,得到乡镇发病率空间分布。结果 降尺度插值时,拟合的点尺度半方差方程的自相关距离（变程）为20.38 km,变程范围内发病率具有空间自相关性。区（县）手足口病发病率估计值和实际值散点图拟合函数为y=1.053 1x,R²=0.99,不同尺度之间发病率保持一致。结论 手足口病发病率在20.38 km范围内具有一定的空间自相关性。在某一地区暴发手足口病时,有关部门可重点针对暴发区20.38 km范围内的地区进行重点监控,着重分配治疗药物等医疗资源。面到面泊松克里格降尺度方法能够被有效地应用于手足口病的空间制图中,为公共健康发病率高分辨率制图提供了一种新的方法。     

河南省狂犬病病例县区层面空间分布特征与动态变化

目的 研究狂犬病病例在河南省县区层面空间分布状态及动态变化.方法 对河南省2004-2010年狂犬病县区层面疫情数据进行收集和整理,进行Poisson分布和负二项分布的拟合与检验,分析聚集特征及变化.结果 按照α=0.05水平,2004、2005、2007和2009年狂犬病病例在县区层面服从负二项分布而不服从P0isson分布(P＜0.001);2008和2010年更倾向于服从负二项分布,但同时不排除服从Poisson分布;2006年两种分布均不服从.从负二项聚集性参数k值来看,狂犬病病例在县区层面的聚集程度从2004-2008年逐年降低,2009年有所增强,2010年又呈现聚集性减弱倾向.聚集程度与疫情县区平均病例数呈正相关(r=0.807,P=0.028).结论 狂犬病病例在河南省县区层面的分布更倾向于负二项分布,具有一定程度的空间聚集性,但聚集程度有逐年下降趋势.

Abstract：

Objective To study the spatial distribution and dynamics of human rabies cases at the county level, in Henan province to provide scientific evidence for the development of control program on rabies. Methods Data of human rabies cases at the county level from 2004 to 2010 in Henan province were analyzed by Poisson distribution and negative binomial distribution. Data calculation was conducted manually. Results According to the level of α =0.05 being set, there were three different results appeared: the first was fitted negative binomial distribution in 2004, 2005,2007 and 2009; the second was prioritized negative binomial distribution, but the poisson distribution could not be excluded in 2008 and 2010; the last one was fitted neither negative binomial distribution nor poisson distribution in 2006. By the clustering parameter k, the clustering degree at county level decreased from 2004 to 2008, then ascending in 2009 but descending again in 2010. The degree of clustering showed a positive correlation with the county mean cases in the prevalent counties (r=0.807,P=0.028). Conclusion As a whole,the distribution of human rabies at county level in Henan from 2004 to 2010 showed negative binomial distribution and presented the spatial clustering.However, the degree of clustering decreased in recent years and showed that the infection resource was possibly scattered more evenly at the county level.     

The Use of Health Service Areas for Measuring Provider Availability*

Measurement of the availability of health care providers in a geographic area is a useful component in assessing access to health care. One of the problems associated with the county provider-to-population ratio as a measure of availability is that patients frequently travel outside their counties of residence for health care, especially those residing in nonmetropolitan counties. Thus, in measuring the number of providers per capita, it is important that the geographic unit of analysis be a health service area. We have defined health care service areas for the coterminous United States, based on 1988 Medicare data on travel patterns between counties for routine hospital care. We used hierarchical cluster analysis to group counties into 802 service areas. More than one half of the service areas include only nonmetropolitan counties. The service areas vary substantially in the availability of health care resources as measured by physicians and hospital beds per 100,000 population. For almost all of the service areas, the majority of hospital stays by area residents occur within the service area. In contrast, for 39 percent of counties, the majority of hospital stays by county residents occur outside the county. Thus, the service areas are a more appropriate georgraphic unit than the county for measuring the availability of health care.     

Spatial filtering using a raster geographic information system: methods for scaling health and environmental data

Despite the use of geographic information systems (GIS) in academic research, it is still uncommon for public health officials to use such tools for addressing health and environmental issues. Complexities in methodological issues for addressing relationships between health and environment, investigating spatial variation of disease, and addressing spatial demand and supply of health care service, hinder the use of GIS in the health sector. This paper demonstrates simple spatial filtering methods for analyzing health and environmental data using a raster GIS. Computing spatial moving average rates reduces individual affects and creates a continuous surface of phenomena. Another spatial analytical method discussed is computation of exposure status surfaces including neighbors' influences weighted by distance decay. These methods describe how health and environmental data can be scaled in order to better address health problems. Spatial filtering methods are demonstrated using health and population surveillance data within a GIS that were collected for approximately 210,000 people in Matlab, Bangladesh.     

Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application

Background  

Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS) and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing) systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP) is central to the field known as BI (Business Intelligence), a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP) and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance.     

Ecological factors associated with West Nile virus transmission, northeastern United States

Since 1999, West Nile virus (WNV) disease has affected the northeastern United States. To describe the spatial epidemiology and identify risk factors for disease incidence, we analyzed 8 years (1999-2006) of county-based human WNV disease surveillance data. Among the 56.6 million residents in 8 northeastern states sharing primary enzootic vectors, we found 977 cases. We controlled for population density and potential bias from surveillance and spatial proximity. Analyses demonstrated significant spatial spreading from 1999 through 2004 (p<0.01, r2 = 0.16). A significant trend was apparent among increasingly urban counties; county quartiles with the least (<38%) forest cover had 4.4-fold greater odds (95% confidence interval [CI] 1.4-13.2, p = 0.01) of having above-median disease incidence (>0.75 cases/100,000 residents) than counties with the most (>70%) forest cover. These results quantify urbanization as a risk factor for WNV disease incidence and are consistent with knowledge of vector species in this area.     

How does Poisson kriging compare to the popular BYM model for mapping disease risks?

Background

Geostatistical techniques are now available to account for spatially varying population sizes and spatial patterns in the mapping of disease rates. At first glance, Poisson kriging represents an attractive alternative to increasingly popular Bayesian spatial models in that: 1) it is easier to implement and less CPU intensive, and 2) it accounts for the size and shape of geographical units, avoiding the limitations of conditional auto-regressive (CAR) models commonly used in Bayesian algorithms while allowing for the creation of isopleth risk maps. Both approaches, however, have never been compared in simulation studies, and there is a need to better understand their merits in terms of accuracy and precision of disease risk estimates.

Results

Besag, York and Mollie's (BYM) model and Poisson kriging (point and area-to-area implementations) were applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1) state of Indiana that consists of 92 counties of fairly similar size and shape, and 2) four states in the Western US (Arizona, California, Nevada and Utah) forming a set of 118 counties that are vastly different geographical units. The spatial support (i.e. point versus area) has a much smaller impact on the results than the statistical methodology (i.e. geostatistical versus Bayesian models). Differences between methods are particularly pronounced in the Western US dataset: BYM model yields smoother risk surface and prediction variance that changes mainly as a function of the predicted risk, while the Poisson kriging variance increases in large sparsely populated counties. Simulation studies showed that the geostatistical approach yields smaller prediction errors, more precise and accurate probability intervals, and allows a better discrimination between counties with high and low mortality risks. The benefit of area-to-area Poisson kriging increases as the county geography becomes more heterogeneous and when data beyond the adjacent counties are used in the estimation. The trade-off cost for the easier implementation of point Poisson kriging is slightly larger kriging variances, which reduces the precision of the model of uncertainty.

Conclusion

Bayesian spatial models are increasingly used by public health officials to map mortality risk from observed rates, a preliminary step towards the identification of areas of excess. More attention should however be paid to the spatial and distributional assumptions underlying the popular BYM model. Poisson kriging offers more flexibility in modeling the spatial structure of the risk and generates less smoothing, reducing the likelihood of missing areas of high risk.     

Surveillance of drinking water supply with a geographic information system: a pilot project of the of the Iogd NRM and the Hoxter district

Drinking water surveillance includes the use of spatial data. A geographic information system (GIS) is a practicable tool for work with spatial data in the health sector as well. Co-operation between the Institute of Public Health for North Rhine Westphalia, the local health authority of the Hoexter district and the Institute for Geoinformatics of the University of Muenster started a project testing the use of GIS for drinking water surveillance. A special application was programmed. It includes functions of retrieval and classification of the measured values of drinking water wells, in order to show time trends in a diagram and to visualise the location of the wells and the analysis data in a map. The members of the Public Health Office accepted the method and started using it regularly. In addition, the collaboration between the health authority and other local authorities was strengthened. Several data sets were included in the GIS, such as wells and results of water analysis, water protection areas, land use data, and topographical maps. Basing on to the experiences with this project, the development of a standard application is planned that is supposed to be communicated to all local health authorities in North Rhine Westphalia.     

100% access,zero health disparities,and GIS: an improved methodology for designating health professions shortage areas

The (Health Professions Shortage Areas) HPSA designation process was developed as a mechanism to identify primary care shortage areas eligible for participation in specific federally funded programs including a 10% Medicare supplement, the National Health Service Corps, and health professions training programs. The purpose of this paper was to explore the utility of Geographic Information Systems (GIS) technology as an improved methodology for obtaining HPSA designation status for geographic areas. Results showed that GIS identified 24 Medical Services Study Areas (rational planning areas) in Los Angeles County that met the minimum 3500:1 population-to-primary-care physician ratio for geographic area HPSA designation compared to only three that currently are identified. Authors concluded that restructuring of the state/county responsibilities for HPSA designation is long overdue and that use of GIS as a required methodology would help ensure that all areas in any state that meet the intent of federal legislation are included.     

2010年四川省狂犬病监测

目的分析四川省狂犬病监测点暴露人群流行病学状况,为狂犬病相关防治提供有效的依据。方法选取2005-2009年四川省狂犬病高发的6个县为监测点,要求每个监测点选择1个县级疾病控制中心和2个乡镇卫生院的犬伤门诊对犬/猫伤处置及相关情况进行登记。对其中3个监测点采集的258份犬标本使用免疫荧光法进行犬只带毒检测。使用Epidata3.02建立数据库,Excel2007统计分析。结果 2010年6个监测点共登记4 835例暴露者,男女比例为1.05∶1;15岁以下儿童暴露占32.60%;6～9月暴露占全年的45.93%;上下肢暴露占66.39%;Ⅲ级暴露占55.56%。暴露者注射疫苗率为98.87%,Ⅲ级暴露注射免疫球蛋白为23.49%。结论 6个监测点犬伤门诊就诊数男女几乎相等,低年龄组暴露为主,夏秋季暴露居多,暴露部位主要为上下肢,犬伤者暴露后使用狂犬免疫球蛋白意识不强。尚需加强农村地区乡镇卫生院犬伤处置培训;加强对农民狂犬病预防知识及伤口处置等预防知识的宣传。     

The effects of geography and spatial behavior on health care utilization among the residents of a rural region

OBJECTIVE: This analysis determines the importance of geography and spatial behavior as predisposing and enabling factors in rural health care utilization, controlling for demographic, social, cultural, and health status factors. DATA SOURCES: A survey of 1,059 adults in 12 rural Appalachian North Carolina counties. STUDY DESIGN: This cross-sectional study used a three-stage sampling design stratified by county and ethnicity. Preliminary analysis of health services utilization compared weighted proportions of number of health care visits in the previous 12 months for regular check-up care, chronic care, and acute care across geographic, sociodemographic, cultural, and health variables. Multivariable logistic models identified independent correlates of health services utilization. DATA COLLECTION METHODS: Respondents answered standard survey questions. They located places in which they engaged health related and normal day-to-day activities; these data were entered into a geographic information system for analysis. PRINCIPAL FINDINGS: Several geographic and spatial behavior factors, including having a driver's license, use of provided rides, and distance for regular care, were significantly related to health care utilization for regular check-up and chronic care in the bivariate analysis. In the multivariate model, having a driver's license and distance for regular care remained significant, as did several predisposing (age, gender, ethnicity), enabling (household income), and need (physical and mental health measures, number of conditions). Geographic measures, as predisposing and enabling factors, were related to regular check-up and chronic care, but not to acute care visits. CONCLUSIONS: These results show the importance of geographic and spatial behavior factors in rural health care utilization. They also indicate continuing inequity in rural health care utilization that must be addressed in public policy.