scholarly journals Defining health catchment areas in Jeddah city, Saudi Arabia: an example demonstrating the utility of geographical information systems

2008 ◽  
Vol 2 (2) ◽  
pp. 151 ◽  
Author(s):  
Abdulkader A. Murad
2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Abdulkader Murad

Geographical information systems (GIS) is used for health care planning due to the increasing availability of geo-coded health data that is moving the field towards to health information systems. The aim of this paper is to present GIS applications for planning health services in Jeddah City. The discussion is focused on three major issues: i) identifying the location of health service facilities and their distribution; ii) modelling the level of density needed for health service facilities; and iii) identifying the required levels of accessibility to these health services. The issues covered include GIS, choropleth mapping, kernel density modelling, Euclidean (straight-line) distance and drive-time distance models. These approaches are essential and considered the major spatial decision models required to support health care for decision- makers and planners in Jeddah City, Saudi Arabia.


The study of the spatial Interpolation of rain is an important aspect of climatic and hydrological studies, especially as it relates to projects related to the development of the country. Perhaps one of the most important problems related to rain studies within the climate studies is the inability of meteorological stations to cover large areas in Saudi Arabia enough, including the Medina. The ArcGIS program allows for mapping rain-equality by interpolation of areas not covered by rain. The interpolation process involves several different application methods that vary in accuracy depending on the variance of the input data and the arithmetic methods of each model. Significant for the actual Interpolation of rainfall. This study was based on the inductive approach to achieve the objectives of the study, which seeks to evaluate three methods of spatial Interpolation methods within ArcGIS: IDW, Kriging and Spline for rain studies through several interrelated applications. To estimate the general error of the derived values, the researcher used RMSEZ (Root-mean-square standardized errors RMSSE) and then calculated the validity of the Interpolation at 95 % confidence level. The study found that the method of IDW was the best of the three methods in the of spatial Interpolation of rainfall. The overall error value of the RMSE index was (13.2) mm while the mean value of the Interpolation was (25.9) mm, meaning that the Interpolation value would be correct for the actual data within the range of (25.9) mm and (25.9) mm. Geographical Information Systems - spatial Interpolation - Spatial Analysis - Root-mean-square standardized errors RMSSE. Keywords: Geographic Information Systems, Spatial Derivation, Spatial Analysis, Square Root of Average Square Prediction Errors -------------------------------------------------------------------- تعد دراسة التوزيع المكاني للأمطار أحد الجوانب المهمة في الدراسات المناخية والمائية, خاصة مع ارتباطها بالمشاريع التي ترتبط بالتنمية في البلاد. ولعل من أهم المشاكل التي تتعلق بالدراسات المطرية ضمن الدراسات المناخية عدم قدرة محطات الأرصاد الجوية على تغطية مساحات كبيرة في المملكة العربية السعودية بشكل كافٍ بما فيها منطقة المدينة المنورة. ويتيح برنامج ArcGIS رسم خرائط تساوي الأمطار من خلال عمل استيفاء - اشتقاق Interpolationللمناطق غير المغطاة بقيم مطرية، وتشتمل عملية الاشتقاق Interpolation على عدد من الطرق التطبيقية المختلفة التي تتباين من حيث دقتها, تبعا لتباين البيانات المدخلة وطرق التقدير الحسابية لكل نموذج؛ إذ قد تعطي هذه الاشتقاقات اختلافات كبيرة عن التوزيع الفعلي للأمطار. واعتمدت هذه الدراسة على المنهج الاستقرائي لتحقيق أهداف الدراسة التي تسعى إلى تقييم ثلاث طرق من طرق الاشتقاق المكاني داخل برنامج ArcGIS وهي: IDW وKriging وSpline وتحديد أكثرها صحة للدراسات المطرية من خلال عدد من التطبيقات المترابطة فيما بينها. ولتقدير الخطأ العام للقيم المشتقة استخدمت الباحثة مؤشر RMSEZ (الجذر التربيعي لمتوسط أخطاء التنبؤ المربعة) ومن ثم حساب صحة الاشتقاق عند مستوى ثقة 95%. وتوصلت الدراسة إلى أن طريقة IDW كانت أفضل الطرق الثلاث في عملية الاشتقاق المكاني لكمية الأمطار؛ إذ بلغت قيمة الخطأ العام لمؤشر RMSE (13.2) ملم, في حين بلغت قيمة صحة الاشتقاق (25.9) ملم؛ أي أن قيمة الاشتقاق ستكون صحيحة بالنسبة للبيانات الفعلية ضمن مدى يتراوح بين (+25.9ملم) و(-25.9ملم). الكلمات المفتاحية: نظم المعلومات الجغرافية – الاشتقاق المكاني – التحليلات المكانية – الجذر التربيعي لمتوسط أخطاء التنبؤ المربعة.


2008 ◽  
Vol 17 (3) ◽  
pp. 192-200 ◽  
Author(s):  
Marco Garrido-Cumbrera ◽  
José Almenara-Barrios ◽  
Enrique López-Lara ◽  
Juan Luis Peralta-Sáez ◽  
Juan Carlos García-Gutierrez ◽  
...  

SummaryIntroduction– There is a need to develop composite indicators to monitor mental health care in countries such as Spain, where there is wide variability of care systems in 17 different regions. The aim of this study is to generate and to test the usability of synthetic indexes in Andalusia (Southern Spain).Method– Seven mental health indicators were selected by expert opinion from a previous list of simple indicators used to compare mental health care systems across Spain (Psicost-74). A Geographical Information Systems (GIS) was used to delineate 71 sectors based on the catchment areas of the mental health centers in Andalusia. Synthetic indexes were obtained through linear combinations of simple indicators via Principal Components Analysis (PCA), using activity data from the Mental Health Information System of Andalusia (SISMA). Maps of these indexes were drawn for 71 catchment areas.Results– Two synthetic indexes were obtained and showed high consistency in the PCA. The Care Load Index (component 1) related to population size and total outpatient care provided within the area. The Case Load Index (component 2) related to assisted morbidity in relation to the population size. The care load index was higher in populated urban areas, whereas the case load was higher in rural areas.Discussion– Care and case load indexes show a different pattern in urban and rural areas. This may be related to a different underlying model of care related to the degree of urbanisation. Geographical Information Systems (GIS) improved recognition and assessment of the spatial phenomena related to the mental health care system, and support policy decision making process in mental health.Declaration of Interest:None.


Author(s):  
Е.М. Studenikina ◽  
Yu.I. Stepkin ◽  
O.V. Klepikov ◽  
I.V. Kolnet ◽  
L.V. Popova

The paper considers the problematic issues of the geographical information systems (GIS) use in the sociohygienic monitoring (SHM). We analyzed scientific and practical publications on this subject that are freely available on the largest Russian information portal of scientific electronic library eLIBRARY.RU during 2014- 2018, which allowed us to formulate the principles of organization and requirements for effective operation of geographic and information systems in the socio-hygienic monitoring. An analysis of the implementation of these principles at the present stage of development for the socio-hygienic monitoring system is presented, the results of which were used in formulating priority tasks in the area of geographic and information technology implementation into socio-hygienic monitoring and risk-based planning of control and supervisory measures: to determine the necessary level of detail and an information list depicted on electronic maps for the implementation of risk-based control planning; to provide organizational and regulatory and methodological support for the hierarchical principle of GIS within Rospotrebnadzor operating on a single software product of domestic developers for organizations and institutions; to work out the need to combine GIS with similar systems of other departments involved in the data collection of social and hygienic monitoring (Rosstat, Roshydromet, Rosprirodnadzor, Ministry of Health, etc.) to enable automated data export and import; to solve staffing issues to ensure customization and subsequent GIS operation; to provide budget funding for the purchase of licensed software products for GIS in SHM, preferably of Russian developers.


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