New perspectives on the use of Geographical Information Systems (GIS) in environmental health sciences
Thomas Kistemanna , Friederike Dangendorfa , J¸rgen Schweikartb
a Institute for Hygiene and Public Health, University of Bonn, Bonn, Germany b Department for Cartography, University for Applied Sciences, Berlin, Germany
International Journal of Hygiene and Environmental Health , Volume 205, Issue 3, 2002, Pages 169-181
Abstract
At first glance, the domain of health is no typical area to applicate Geographical Information Systems (GIS). Nevertheless, the recent development clearly shows that also within the domains of environmental health, disease ecology and public health GIS have become an indispensable tool for processing, analysing and visualising spatial data. In the field of geographical epidemiology, GIS are used for drawing up disease maps and for ecological analysis. The striking advantages of GIS for the disease mapping process are the considerably simplified generation and variation of maps as well as a broader variety in terms of determining areal units. In the frame of ecological analysis, GIS can significantly assist with the assessment of the distribution of health-relevant environmental factors via interpolation and modelling. On the other hand, the GIS-supported methods for the detection of striking spatial patterns of disease distribution need to be much improved. An important topic in this respect is the integration of the time dimension. The increasing use of remote sensing as well as the integration into internet functionalities will stimulate the application of GIS in the field of Environmental Health Sciences (EHS). In future, the integration and analysis of health-relevant data in one single data system will open up many new research opportunities.
Key words GIS-environmental health sciences -medical geography - disease mapping- ecological studies - remote sensing
Introduction
Geographical Information Systems
According to Bill (1999) a Geographical Information System (GIS) is a computer-supported system consisting of hardware, software, data and the corresponding applications. By means of GIS, data can be digitally recorded and edited, stored and reorganised, shaped and analysed as well as presented in an alphanumerical and graphic mode. In its definition the WHO (1999) states another essential: the trained staff. Basically, GIS has two different types of data: on one hand geometric data which are the co-ordinates of points defining also curves and areas and on the other hand the attribute data containing the factual information
The functionalities of GIS include, among other things, the following selected aspects (Scholten and de Lepper, 1991; Briggs and Elliot 1995; Clarke et al., 1996):
- Data capture: data input by user employing scanner, digitizer tablet, keyboard etc., or data import from digital sources.
- Data check: plausibility, revision and completion.
- Data integration: transfer of data sets into a consistent geographic data structure by generalisation, co-ordinates transformation resp. translation etc.
- Data storage: spatial data are stored as grid or vector data. Advanced GIS can process both types of data in hybrid systems. Normally, the data are stored in intrasystem data bases. Data retrieval: basic functions for a user-defined query of data bases.
- Data analysis: GIS provides a broad range of tools to analyse the database. In this respect, all GISfunctionalities can be used, in particular the visualisation methods (Table 1)
- Data display: the most important display formats of GIS are maps. But also tables and graphics are possible formats for the presentation of results.
The application of GIS does by no means overcome two major concerns of any empirical research: data availability and data quality. Data collecting is both time-consuming and expensive, and GIS offers some helpful tools for integration and matching of data that are already available. An increasing amount of datasets is becoming available as public domain (Clarke et al., 1996). However, if pre-collected data are used, it is often difficult to get information about their quality and the methods used for generation. Furthermore, the intended data use is regularly different from that intended by the researcher. Thus, often neither spatial boundaries and resolution are those desired by the researcher, nor are all the items present.
There is currently a movement towards regarding GIS as a science (Geographic Information Science) rather than simply a technology (Goodchild, 2000, Haining, 2001). In this broader understanding GIS comprises geographical information systems and geographical concepts as well as methods for spatial analyses.
Introduction
The trends of the last decades and their effects in the fields of hardware, software and network technology, in particular in the internet domain, have created the prerequisites for a broad acceptance of GIS. Not only experts are nowadays able to use these complex systems as the user-friendly possibilities of advanced GIS versions have smoothed the way for its wide-spread utilisation. Today, each scientist and each planner is potentially able to process spacerelated data (Goodchild, 1998).
Besides, several practical requirements have to be complied with. The implementation of GIS consists of many worksteps which are partly very labourintensive. All objects of the system must be registered and geo-referenced, i.e., geometry and attributes are to be integrated. Thereby, it can be started from the assumption that the relation between data acquisition costs and all remaining costs ranges between 5: 1 up to 10: 1. Neither the set-up phase nor the data analysis offer many opportunities for automation. The interaction with the user is indispensable (Klemmer and Spranz, 1997). In particular, with regard to the complex topics related to the health sector, no satisfactory results can be achieved without the interaction of the user.
Reflecting the high input which is necessary for the set-up of GIS, the critical question concerning the added value arises. One has to wonder whether really new possibilities have been created or whether only new methods have been developed to generate and to analyse maps in a way as it had been done already 150 years ago. There is agreement on the point that GIS, due to its central features, does indeed open up new possibilities in terms of processing research issues in a way that has not been possible before. GIS does not mean digital cartography but is indeed an information and analysing tool which permits the processing of space-related data. Certainly the map itself keeps on playing a prominent role and is, of course, the most frequently used output of GIS. On the basis of maps, regional interconnections and relations can be revealed, identified and imparted. The information provided by the map is influenced by a multitude of factors that have to be taken into account. The distribution of basic variables, particularly those related to the population, may influence the appearance of a map to a considerable extent. Factors not depending on the data pool, such as map layout or display method of the statistical data, should not be underestimated since they may manipulate the interpretation (Wilkinson et al., 1998). The influence of visualisation should be considered at any rate. In many cases, a low-quality or even wrong map may lead to a misinterpretation of facts (Schweikart, 1999).
The setting up of a topical map with a definite content by using GIS is not a methodological revolution but means nothing more than a change of tool. Digital maps can be designed by means of more simple methods, and the strong point of GIS is not the graphic display. The reality of map design is, however, completely different: at the beginning there are a new idea and statistical data. During a scientifically creative process, space-related and health-relevant relations are analysed and finally visualised by using a whole package of different methods: varied pieces of information are overlapped and clipped, data are statistically evaluated, indices are developed and calculated, maps are iteratively discussed, analysed and further on developed. Only at the end of a long process the maps are finalised. The way how a map is generated is therefore most essential: the explorative handling of the data, the continuous development of the original idea and the generating of hypotheses. This process can be realised most effectively by GIS. Already the standard functionalities of GIS extend the conventional analysing methods in terms of leading to innovative results.
Today, the most ambitious approaches to apply GIS to health-relevant topics exist in the United Kingdom and in the US. A multitude of publications show applications in numerous fields of epidemiology and health system research. GIS can support the geographic epidemiology to a considerable extent and may inspire its development (Scholten and de Lepper 1991; Briggs and Elliot, 1995; O'Dwyer, 1998). There is still a high potential for possible applications. Within computerised hospital information systems, for instance, a new large-scale GIS application for health issues arises. The environment of health care settings is rather special, but highly relevant to both patients' and personnel's health. GIS may support surveillance and prevention of nosocomial infections as well as detection and investigation of outbreaks (Kistemann et al., 2000).
The implementation of spatial-statistical methods for cluster identification and hypothesis testing is currently not very satisfactory although the potential of GIS in this field is seen to be substantial. Integration of time dimension remains to be another, yet unsolved, problem.
Undoubtedly, GIS will rapidly disseminate in the fields of spatial environmental health sciences and public health. Availability of huge environmental data quantities from remote sensing as well as integration of GIS into internet-functionalities will contribute substantially to the growing acceptance of GIS within health sciences. There is, however, a risk that the easy and quick application of geographic-epidemiological methods may promote the distribution of incorrect conclusions if the underlying theory and methodological restrictions are not sufficiently considered (Briggs and Elliot, 1995).
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