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Abstract
We argue that as the disease map user group grows, disease maps must prioritize several essential properties that support public health uses of disease maps. We identify and describe five important properties of disease maps that will produce maps appropriate for public health purposes: (1) Control the population basis of spatial support for estimating rates, (2) display rates continuously through space, (3) provide maximum geographic detail across the map, (4) consider directly and indirectly age–sex-adjusted rates, and (5) visualize rates within a relevant place context. We present an approach to realize these properties and illustrate it with small-area data from a population-based cancer registry. Users whose interests are in selecting areas for interventions to improve the health of local populations will find maps with these five properties useful. We discuss benefits and limitations of our approach, as well as future logical extensions of this work.
Sostenemos que por cuanto el grupo de usuarios del mapa crece, los mapas sobre enfermedades deben priorizar varias propiedades esenciales que favorecen los usos de los mapas para fines de salud pública. Identificamos y describimos cinco propiedades importantes de los mapas de enfermedades que pueden hacerlos apropiados para los propósitos de la salud pública: (1) Controlan la base poblacional de apoyo espacial para calcular las tasas, (2) despliegan las tasas de manera continua a través del espacio, (3) proveen el máximo de detalle geográfico a través del mapa, (4) consideran directa e indirectamente las tasas ajustadas edad–sexo, y (5) visualizan las tasas dentro de un contexto relevante de lugar. Presentamos un enfoque para comprender estas propiedades e ilustrarlas con datos sobre un área pequeña de un registro de cáncer basado en población. Los usuarios cuyos intereses están en la selección de áreas para hacer intervenciones que mejoren la salud de las poblaciones locales encontrarán útiles los mapas que exhiban estas cinco propiedades. Discutimos los beneficios y limitaciones de nuestro enfoque, lo mismo que las lógicas extensiones futuras de este trabajo.
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Acknowledgments
The authors wish to thank colleagues Marc Armstrong, David Bennett, Qiang Cai, Martha Carvour, David Haynes, Soumya Mazumdar, and Alberto Segre (The University of Iowa); Charles Lynch and Michelle West (State Health Registry of Iowa); David Stinchcomb (National Cancer Institute); James Cucinelli and Dan Kavan (Information Management Services, Inc.); Sam LeFevre and Benjamin Goodrich (Utah Department of Health); and Kevin Henry (New Jersey Department of Health and Senior Services) for their collaboration and suggestions. We would also like to thank three anonymous reviewers. The work described here was funded in part by the National Cancer Institute, SEER Rapid Response Surveillance Study N01-PC-31543.