Integrating Spatial Analysis into Policy Formulation: A Case Study Examining Traffic Exposure and Asthma

AuthorDennis Wollersheim,Bircan Erbas,Marsil Zook,Kathryn H. Jacobsen
Date01 March 2018
DOIhttp://doi.org/10.1002/wmh3.258
Published date01 March 2018
Integrating Spatial Analysis into Policy Formulation: A
Case Study Examining Traff‌ic Exposure and Asthma
Marsil Zook , Dennis Wollersheim, Bircan Erbas, and Kathryn H. Jacobsen
Geographic information systems (GIS) are underused as a tool for health policy analysis. We present
a case study that (i) identif‌ies sociodemographic, environmental, and health variables for which
spatial data are available for Melbourne, Australia; (ii) reviews the literature about the traff‌ic-
related parameters that are risk factors for asthma emergencies; (iii) applies this information within
a GIS to identify populations living in proximity to harmful exposures; and then (iv) maps the most
at-risk neighborhoods. The case study identif‌ies the locations of residential districts with high
asthma incidence rates that are located near highways. These places would likely be priority
communities for public health asthma control interventions. Spatial analysis can be a valuable tool
for design, implementation, and evaluation of cost-effective policies. We recommend integrating
more spatial epidemiology into evidence-based policy, planning, and resource allocation decisions.
KEY WORDS: asthma, GIS, spatial analysis
Introduction
Geographic informatio n systems (GIS) are a powerful t ool for use in areas
such as health planning, poli cy development, monitoring, and disease surveil-
lance (Nykiforuk & Flaman, 2 011), but GIS tends to be underu sed in health
policy analysis. GIS is primar ily used for storing, retriev ing, analyzing, and
displaying data (Clarke, McLafferty, & Tempalski, 1996; Delaney & Van Niel,
2007). GIS software progra ms can map changes in risk expos ures and
population health status over time, and those visua lizations can be very help ful
for enabling policy exp erts and the public to understand evolving threa ts to
health. GIS also allows anal ysts to examine the associations between health and
environmental variabl es by location. Spatial an alysis may reveal pattern s that
would not be apparent in a non-spatial statistical model (Cas tro et al., 2007).
However, some of the valuabl e spatial modeling function s of GIS are not being
used to their fullest extent by p olicy analysts.
World Medical & Health Policy, Vol. 10, No. 1, 2018
99
doi: 10.1002/wmh3.258
#2018 Policy Studies Organization

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