WHO Report Benefits of GIS in Public Health

WHO Report Benefits of GIS in Public Health - WORLD HEALTH...

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Unformatted text preview: WORLD HEALTH ORGANIZATION ORGANISATION MONDIALE DE LA SANTE CONSULTATION ON EPIDEMIOLOGICAL AND STATISTICAL METHODS OF RAPID HEALTH ASSESSMENT Geneva 26-29 November 1990 DISTFl. : LIMITED DISTR :LIMITEE ESM/CONS.RA/90.l3 ENGLISH ONLY THE BENEFITS OF THE APPLICATION OF GEOGRAPHICAL INFORMATION SYSTEMS IN PUBLIC AND ENVIRONMENTAL HEALTH Hank J. Soholtenl & Marion J.C. de Lepper2 1. National Institute of Public Health and Environmental Protection P.O. Box 1 3 '72 0 BA Bilthoven The Netherlands 2. Department of Regional Economics Free University Amsterdam This dowment I5 not Issued to the general DUDIIC, and all rlghts are reserved by the World Health Organization (WHO) The document may not be rewewed. abstracted quoted, reproduced or translated, to part or In whole, without the pnor wrutten permussron of WHO. No part of thus document may be stored In a retrieval system or transmitted in any form or by any means - electronic, mechanical or other wrthout the pram written DEFMISSIOH of WHO. The weWs expressed m documents by named authors are solely the responslballty of those authors. Ce document n’est pas destiné a farm distrrbué au grand public at tous les dronts y afférents sont réserves par l'OrganIsatuon mondlale de la Santé (OMS), II ne peut étre commenté, re’sumé, clté. reproduut ou tradmt. partiallement an en totallte. sans une autorisatlon oréalable écnte de I'OMS. Aucune name ne dolt étre chargée dans un systérne de recherche documen. tatre ou diffusee sous quelque forme ou par queloue moven oue ce sort - électromoue, mécamque. ou autre - sans une auto- rlsanon préalable Ecrlte de POMS. Les opamons exprlmées dans les documents par des auteurs crte‘s nommément n'engagent oue lesdlts auteurs. Contents 1 “40301 (20 Introduction The objectives of GiS Types of data storage Hardware and software In a GIS environment Types of information systems Appiications and users of GIS Applications of GIS In Health Research Conclusions References 1 introduction Health and ill~health always have and always will have a spatial dimension. Already more than a century ago, epidemiologists and other medical scientists began to explore the power of maps in helping the human mind to assimilate and understand the spatial dynamics of disease. One of the most tamous early users of maps in medical science was Dr. John Snow (18134858) - a London anathetist and Queen Victoria's obstetrician. Snow had the idea that cholera — the classic epidemic disease of the nineteenth century - might be spread by contaminated water supplies By using maps showing the geographical distribution of cholera deaths in the Soho area of London in 1854, he demonstrated that associations between cholera deaths and contaminated water supplies resulted in a striking geographical distribution. Nowadays, Aids is projected to be of critical importance in the remainder of this century. Consequently. attempts to forecast and predict its developments are urgently needed. Not surprisingly, Aids is increasingly subject of research. On our current state of knowledge. research on Aids has however to date failed to incorporate the spatial dimension of the disease. Although a vast amount of literature - describing many different aspects of the disease - has already been produced. the important geographical aspect seems to have been largely passed over. As Kabel (1990) points out: " Rarely can one find an attempt to model the spread of Aids incorporating the basic spatial dimensions of human existence. Most modelling seems to be focused completely within the temporal domain." Kabel describes a recently introduced methodology - called Spatial Adaptive Filtering - which enables the examination of the variability of Aids in time and space. One of Kabel's main lines of argument is that modelling the geographic distributions of Aids is useful toward both educational intervention and the planning of health care delivery systems. Mapping can play an important role in both areas as it is an excellent means of communication. in order to be of use to resource planners predictions of Aids should include a spatial component. These two examples describe the use of spatial information in health research. For most people using spatial information is the same as producing maps. whereby the map is used to show the geOgraphical distribution of some medical condition. Cliff and Haggett (1988) give a more than excellent review of the use of maps in health research and the problems and benefits. Based on their work a number of aspects related to the use of spatial information can be formulated. The most important point they make. is that map-making constitutes much more than presenting the geographical distribution of various diseases. Rather, it is a methodology that enables the handling of the spatial dimension of information. Another aspect related to map- making they bring fomrard is: "While maps are sometimes used to good effect, in other instances they tend to obscure evidence, to suggest false concentrations and to start false trails. The spatial distribution of diseases remains one of the oldest of puzzles and yet one of the most contemporary... they need to be handled with as much care and critical attention as any other source of evidence." The authors describe how, by combining cartographic and statistical arguments the value of maps can be sharpened and errors of interpretatioc reduced. Given the fact that health and ill-health contain a spatial dimension, it goes without saying that the science geography has always played a role in health research. Geographical work in this area known as medical geography embraces both the study of geographical variations in the provision of health care and the distribution of disease. Obviously. this includes the study of the relationships between health and environment, which main aim is to understand the relationships between the distribution and diffusion of diseases and the environment (eg. climate, vegetation, water and air quality). The problem is that it is almost impossible as a geographer to Specify cause and effect. "Nonetheless. knowledge about spatial variation in the incidence of disease is of significant value to the broader field of etiology and to medical science in general" {Groenewegen 21.0., 1987). From this it clearly follows that the handling of spatial information can be defined as a methodology with strong links to geography. cartography and statistical science. Needless to say, this methodology may be applied by scientists of all disciplines whose areas of interest contain a spatial component. At the same time that automation processes of industrial production took place. attempts to automate the handling of spatial information were introduced: significant advances have occurred during the last decade. In this article, we Wlll give an overview of the socalled Geographical Information Systems (GIS). These GIS can be deiined as automated information systems based on the methodology of geographic data handling (both spatial analysis and cartography) and the methodology of geographical database management and query. Hardware and software developments are briefly reviewed in SectiOn 4, types of spatial information system are outlined in Section 5 and the variety of application fields. organizations and users are discussed in Section 6 We begin, however, by clarifying the objectives of GIS and by outlining the baSlC types of data and data storage. In section 7 focus will be on the extent to which health research has succeeded in making uss of the possibilities oftered by GIS, that is the role that Geographical Information Systems have and could have played so far in studies focusing on health issues. 2 The objectives of GIS Geographical inlormation Systems represent a technology designed to acnieve particular objectives. In recent years, a variety of GIS products to assist the management and manipulation of spatial and non-spatial data have arrived on the market and users worldwide have begun to gain familiarity With these new systems. Experience suggests that there can be no doubt but that the application of GIS is making Significant contributions in facilitating the availability, integration and presentation of information A GlS can be defined as a set of tools for collecting, storing, retrievmg, analyzing and displaying spatial data. As a technology, a GIS is not necessarily limited to the confines of one independent system. lt may well have several components, each with a particular objective. A GIS must therefore accomplish the followmg four main tasks: Firstly, there is 3‘9 storage, management and integration of large amounts of spatially referenced data. A spatially referenced database contains two types of information, locational and attribute data (Figure l). Locational 0r spatial data are two or three dimensional co-ordinales of points (nodes), lines (segments) or areas (polygons). Non- locational or descriptive data. on the other hand, refer to the features or attributes of points. lines or areas. Data is obtained from a wide variety of sources and one of the most important features of GIS is the facility to integrate data, eg converting data values to a common spatial framework. The second main task of GIS is to enable spatial retrievals. These spatial query possrbllities are very flexible and still very powerful. It is possible to retrieve data for defined areas (polygons) like a municipality or postal code area. but there are also a number of possmilities that would appear to be extremely relevant for public and environmental health purposes (Openshaw and Charlton 1990), like: radial retrieval on a single point, radial retrieval for a search region defined as a buffer around a site's perimeter, retrieval of data lying in a corridor focused on a linear map feature (e.g. an overhead wire), retrieval of data for a by the user delined area, retrieval of data for search ares defined by manipulating existing digital map databases (e.g. relationship of cancer rates With geology patterns). The third main task of GIS is to provide methods that enable analyses which relate specifically to the geographic component of the data. The analysis techniques may be simple or more sophisticated. At the simplest level, for example. data about different spatial entities such as soil type (per square kilometre) and land use (by local administrative area) can be combined by overlay analysis. At an intermediate level. GlS may allow statistical calculations of the relationship between data sets to be computed or distances between entities may be used to determine the route that must be followed to move as quickly as possible from one location to another. The most sophisticated analysis occurs when modelling is introduced. In this context, there are a variety of analytical opportunities. it is possible, for example, to use atmospheric modelling techniques to discover which areas might be affected by pollution resulting from an explosron at a particular hazardous installation (e.g. Chernobyl), given certain wind and weather conditions. Alternatively. modelling methods can be used to determine the‘impact of locating a large public taCiIity (e.g. a hospital) at different sites in a City region. The fourth main task of GIS involves d:splaying data on map forms of high quality. Maps no longer have to be drawn by hand; they are an implicit product of all the work that is carried out within a GIS. However. for many different purposes, other forms of display (e.g. graphs and tables) may also be required, often for use in combination with maps. The RIA (RUimtelijke informatie via Automatisering) system, developed by the National Phys:cal Planning Agency in the Netherlands (Scholten and Meijer 1990) is an good exampte of alternative methods of displaying spatial information in an interactive and user-friendly way. Figure 1: Locational and attribute information 3 Types of data storage The distinction has already been drawn between locational and attribute data. it is important to distinguish further between three forms in which locational data can be incorporated within a GIS: raster. vector and quadtree storage (Figure 2). Raster or grid storage This form of storage tor locational data involves a regular grid of cells being laid over an area. Attribute data are collected for each grid cell which may measure for example 500 by 500 square meters. This means that the whole area is covered by a group of cells each at which has an attribute value. Within a grid-oriented system of this type, it is often the case that only limited use is made of the attribute data. Satellite photographs, in which a considerably smaller grid Size is used, provide raster information. In a satellite photograph, a single value is attached to each cell. in this way. tactual data can be collected in a very efficient way. Curran (1985) indicates how remote sensing data is frequently contained in raster based GlS. Vector storage _ The storage of locational data in vectors gives a very precise representation ol reality. in this way. pornts, lines and areas are incorporated as Cartesian co-ordinates in the computer. Whilst lines can only be represented as a series at cells in a raster structure. in the vector storage method, the exacr middle paint of a line can be identified. An area is represented by a group of cells With an angular boundary in the raster structure, whereas the precise boundary at an area can be included when a vector structure is used. This precise storage oi x- and y-coordinates usually generates larger data sets. Within a vector system. the relationship between locational and attribute data is of great importance. Each element is related to a record in the database with the same, unique identification number. Quadrree storage The quadtree storage method falls between the grid and vector storage methods. In this method, the data are stored in grid cells of variable size. Within larger homogeneous areas. a large cell size is used whereas towards the edges of the area, the cell size diminishes to form a precise picture. An area is therefore covered by considerably lewer quadtree cells of varying size than is the case in the regular grid storage method. The speed with which analyses can be carried out with a quadtree structure is high, whilst the original precision of the data is retained rather well. Figure 2 The three forms of data storage 4 Hardware and software in a GIS environment The initial GIS products date from the 19705. a decade in which the typical hardware configuration comprised a central computer surrounded by memory and storage disks and a number of peripheral dewces. Time share systems enabled a large number of terminals with lines attached to the mainframe to be used at the same time. At the beginning of the 19803. this centralized approach was extended by connecting minioomputers to the central mainframe in order to carry out certain processes. This was the period in which GIS came of age. Very large databases began to be assembled and the need for processor capacity increased enormously. In the middle of the decade, the personal computer (PC) arrived, although its impact for GIS meant little more than an extra terminal in many cases. Nevertheless, it goes without saying that the PC has become central to the popularization of GIS. In the second hall of the 19805, the PC played an important role in simple GIS tasks such as the automatic production of maps. It is exactly this function that has brought GlS to the attention of many people, whilst the basic concept of a common central database tends to be forgotten. Attempts to transter luily-fledged GIS irom the maintrame onto the PC have been commercially successful. even though in many cases their perlormance leaves something to be desired. Of much greater importance in the mid-19805 was the further development of minicomputers and work stations connected to a network. At this time. the larger organizations making use of GIS, realized that the central maintrame option was not the solution to a number of GlS tasks (Figure 3). it was recognized that each separate task required its own processor capacrty or its own working environment. Throughout the 19805. it became clear that hardware vendors were meeting these demands perfectly well by means of further optimization of minicomputers using servers and the increased processor capacity ot work stations. and that hardware costs were decreasing significantly. Identification of the main tasks oi a GIS enVIronment allows us to specify a corresponding set of software demands. Database management software One of the most significant advances in GIS software development came at the end of the 19705 with the introduction of the concept of the relational database. In the relational model, different data sets are linked together by the use oi common key fields. For example. attribute data available for two different sets of Spatial units (areas) wrll require a third sat of information to show how the two spatial bases fit together. This type of structure can also be used to construct spatial databases in which lines are linked together to represent polygons. The creation, maintenance and accessmg ot a database requires a Data Base Management System (DBMS). In order to handle very large quantities of iniormation. a relational DBMS is a necessrty tor most GIS applications (see Frank 1988). It also serves the very important tunction of separating the data user from the technicalities of the computing system and facflitates data manipulation and analysis. Many of the proprietary GIS have their own systems to handle basic storage. management and analysrs operations (e.g. iNFO is the relational DBMS of ARC/INFO: ORACLE is the relational DBMS ot ARGlS). Analysis software The software required to perform certain analytical tasks varies according to the nature of the problem. the quantity of information available and the objectives of the organizations involved. Figure 3: Decentralized GIS tasks A variety of analytical tools are now available within GIS. The overlay procedure, for example, has been widely used for combining different data sets in order to identify areas or Sites With reqwred characteristics (see, for example, Dangermond 1983). Buffering, address matching and network analysis are additional tools adopted in planning applications of GIS. However, the development of analytical functionality within GIS has tended to neglect the important benefits that modelling procedures can contribute through data transformation, integration and updating; simulation; optimization, impact assessment; and forecasting (see: Birkin et al., 1987; Openshaw, 1990). The specialized and complex nature of modelling algorithms and the restrictions imposed by processor capacny have both been influential in keeping the modelling component separate. One of the challenges confronting the next generation of GIS is to improve the integration of modelling and GIS so as to provide researchers, decision-makers and planners with enhanced model based decasion support systems. Access and presentation software One of the most important functions of GIS development is frequently the provasion of access to information by a variety of different users. In the context of planning, individuals in different departments of the same organization (Public Works. Social Services, Transport, Parks, etc.) may require access to the same database. Similarly, users in different national, regional and local organizations may wish to access the database simultaneously. The National On-line Manpower information System (NOMIS) in the United Kingdom IS a good example of a GIS which stores up-to-date information about employment, unemployment, job vacancies, migration and population, and enables users at remote Sites to obtain raw counts, tables, graphs and maps of data at a variety of spatial scal...
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