Project Information

Introduction

Faculty and graduate students at the University of Iowa collaborated with the National Institute of Urban Affairs, New Delhi, India and the Department of Geography at The University of Ibadan, Nigeria to develop a web-based training program on the application of geographic information systems to urban housing, environment and vital statistics data for the purpose of establishing relationships between indicators of housing and the environment and child health for small areas of cities in developing countries. Other training modules focus on issues of access to and patterns of use of clinic services.

The literature on infant mortality in developed and developing countries has established that areas of high rates are usually localized within metropolitan areas and that intra-metropolitan differences are greater than inter-metropolitan differences.  In developed countries these differences have become clearer as techniques were developed for adding small-area geocodes to urban housing characteristics, environmental data, and to vital statistics records of births, birth characteristics and infant deaths.  At the same time, the 1990s have seen rapid development of methods of smoothing point-based health data and establishing reliable rates of disease in circumstances where population data is sparse (Anselin 2000, Bithell 1990, Rushton and Lolonis 1996, Wall and Devine 2000).

The Project

The University of Iowa has already developed training modules for applications of GIS to public health problems in typical U.S. settings, (Rushton and Armstrong et al. 1997).  These materials were, however, developed before the era of interactive, web-based training, and before the availability of the “Spatial Analyst Extension” to ESRI’s ArcView.  This project revised and extended these materials--see http://www.uiowa.edu/~geog/health/.  The laboratory modules here contain datasets and student-centered, learning materials.  Many of these materials have been developed for the GIS laboratory section of a class taught by Professor Rushton at the University of Iowa.  The class is called “The Geography of Health” (44:131) and it has been taught one semester each year since 1997.  The class uses materials to train students to do practical GIS analyses using geographic framework data, individual records of health events and urban housing data.  Students learn to compute and display density distributions of infant mortality in Des Moines, Iowa.  They also learn to compute measures of geographic access to urban services and to compute indicators of expected changes to access if alternative policies for improving urban services are followed, (Richards et al. 1999, Rushton 2000, Rushton and West 1999).

Relevant Techniques, Training Modules and Data Sets

Training programs cover the following GIS-based techniques for computing, spatially analyzing and displaying health-related indicators at a small-area level.

  1. Alternative approaches for geo-coding vital statistics data and methods for assessing the geometric accuracy and attribute completeness levels of the geocoding.
  2. Mapping types appropriate to the above data characteristics.  Measures of uncertainty associated with the levels and geographic entities mapped.
  3. Methods for computing density estimates for vital statistics and reportable disease data, where available, (Bithell 1990).  Important examples include small-area infant mortality rates, birth rates, fertility rates, age-adjusted death rates, (Rushton and Lolonis 1996; Rushton et al. 1996, Talbot et al. 1999).  As with all density estimates, the feasibility and accuracy of computed rates will depend on the availability of estimates of the appropriate numerators and denominators.  This availability is a constraint on what can be attained.
  4. Methods for visualizing the above computations (ArcView scripts) and for displaying them on geospatial data fields to assist in communicating and interpreting them to the public as well as other concerned agencies. 
  5. Methods for computing statistical significance given the typically small number of observations in small areas reflecting the common rarity of events per unit of population in such areas, (Gatrell et al. 1996; Gelman and Price 1999; Lolonis and Rushton 1996).

Indian and Nigerian Participants

In India, data sets for the training modules were generated by staff at the National Institute of Urban Affairs, for selected small areas (poor communities) in New Delhi. The data sets comprise maternal and child health and related indicators and can be used in training city planners to build their capacity for pro-poor planning of basic services and integrating the poor communities in the overall planning of the city.  The growing number of poor settlements in Indian cities are characterized by low level of access of safe drinking water and inadequate or complete absence of sanitation facilities. Urban poor in the country need security, social protection, and access to basic services. Particularly women and children among the poor need permanent dwelling and associated facilities such as water, drainage, toilet, sewage connections as well as access to social facilities such as health and education. The training modules integrated with the spatial databases of poor communities are targeted towards all those agencies and community groups concerned with the planning, delivery and management of basic services and urban poverty alleviation in the country.  In Nigeria, the city of Ibadan served as our study area.  In Ibadan, additional urban, environmental and child health data were added to the geographic framework data of an earlier project conducted by Professor Bola Ayeni.

Past Experience in Collaborative Work

The University of Iowa project team and their colleagues in India and Nigeria have a long history of collaborative research, training, and development planning applications of computer-based geographic information and decision-support systems in the context of India and Nigeria.  Strong professional and institutional ties play an essential role in the success of international projects such as that envisaged by the UCGIS, HUD and HABITAT program planners. Dr. McNulty directed a three-year (1990-93) USAID University Development Linkages Project linking four institutions in Iowa (Iowa, Iowa State, Northern Iowa, and the DesMoines Area Community College with four Nigerian institutions. That project, which facilitated collaborative research, training, faculty and student exchange and staff development, also resulted in the creation of a Geographic Information Systems Laboratory at the University of Ibadan which now serves as the basis for a Masters degree program in GIS in the Geography Department and provides a site for professional training and consulting activities by the faculty. 

References
(More references can be found in Lab 8 (GIS and Health Resources) and at the end of each lab)

Anselin, L. 2000. “Computing environments for spatial data analysis.” Journal of Geographical Systems 2:201-220.

Armstrong, M.P., Densham, P.J., Lolonis, P., and Rushton, G. (1992) Cartographic displays to support locational decision-making, Cartography and GIS 19(3), 154-164.

Bithell, J.F. 1990. “An application of density estimation to geographical epidemiology.” Statistics in Medicine 9:691-701.

Densham, P.J. (1994) Integrating GIS and spatial modelling: visual interactive modelling and location selection, Geographical Systems , 1(3), 203-219.

Gatrell, A.C., T.C.Bailey, P.J.Diggle, and B.S. Rowlingson. 1996. “Spatial point pattern analysis and its application in geographical epidemiology.” Transactions, Institute of British Geographers NS 21:256-274.

Gelman, A. and P.N. Price. 1999. “All maps of parameter estimates are misleading.”  Statistics in Medicine 18:3221-3234.

Gelman, A., P.N.Price and C-Yu Lin. 2000. “A method for quantifying artifacts in mapping methods illustrated by application to headbanging.” Statistics in Medicine 19:2309-2320.

Richards, T.B.,  C.M. Croner, G. Rushton, C.K. Brown, and L. Fowler. 1999 “Geographic information systems and public health: mapping the future.”   Public Health Reports 114, 359-373.

Rushton, G. 1999. “Methods to evaluate geographic access to health services.” Journal of Public Health Management and Practice 5 (2), 93-100.

Rushton, G. 2000. “GIS to improve public health: Guest Editorial.” Transactions in GIS 4, 1-4.

Rushton, G., G. Elmes and R. McMaster. 2000. “The Challenge of Improving Health and Human Services Using GIS.” The Journal of the Urban and Regional Information Systems.

Rushton, G., R. Krishnamurthy, D. Krishnamurti, P. Lolonis and H. Song. (1996). “ The spatial relationship between infant mortality and birth defect rates in a U.S. City.” Statistics in Medicine 15, 1907-1919.

Rushton, G., and P. Lolonis. 1996. “Exploratory spatial analysis of birth defect rates in an urban population.” Statistics in Medicine 15:717-726.

Rushton, G., and M. West. 1999. “ Women with localized breast cancer selecting mastectomy treatment, Iowa, 1991-1996.” Public Health Reports 114(4):370-1.

Talbot, T.O., M. Kulldorff, S.P. Forand, and V.B.Haley. 2000. “Evaluation of spatial filters to create smoothed maps of health data.” Statistics in Medicine 19:2399-2408.

Wall, P.A. and O.J. Devine. 2000. “Interactive analysis of the spatial distribution of disease using a geographic information system.” Journal of Geographical Systems 2:243-256.

Yen, I.H., and G. A. Kaplan. 1999. “Neighborhood social environment and risk of death: multilevel evidence from the Alameda County study.” American Journal of Epidemiology 149:898-907.