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ISPRS Int. J. Geo-Inf. 2018, 7(11), 432; https://doi.org/10.3390/ijgi7110432

Winter Is Coming: A Socio-Environmental Monitoring and Spatiotemporal Modelling Approach for Better Understanding a Respiratory Disease

1
Geospatial Research Institute and GeoHealth Laboratory, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
2
Cooperative Research Centre for Spatial Information (CRCSI), 204 Lygon St, Carlton, VIC 3053, Australia
3
Department of Geography and GeoHealth Laboratory, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
4
Canterbury Respiratory Research Group, Respiratory Services, Canterbury District Health Board, Private Bag 4710, Christchurch Hospital, Christchurch 8140, New Zealand
*
Author to whom correspondence should be addressed.
Received: 28 August 2018 / Revised: 19 October 2018 / Accepted: 4 November 2018 / Published: 6 November 2018
(This article belongs to the Special Issue Geoprocessing in Public and Environmental Health)
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Abstract

Chronic Obstructive Pulmonary Disease is a progressive lung disease affecting the respiratory function of every sixth New Zealander and over 300 million people worldwide. In this paper, we explored how the combination of social, demographical and environmental conditions (represented by increased winter air pollution) affected hospital admissions due to COPD in an urban area of Christchurch (NZ). We juxtaposed the hospitalisation data with dynamic air pollution data and census data to investigate the spatiotemporal patterns of hospital admissions. Spatial analysis identified high-risk health hot spots both overall and season specific, exhibiting higher rates in winter months not solely due to air pollution, but rather as a result of its combination with other factors that initiate deterioration of breathing, increasing impairments and lead to the hospitalisation of COPD patients. From this we found that socioeconomic deprivation and air pollution, followed by the age and ethnicity structure contribute the most to the increased winter hospital admissions. This research shows the continued importance of including both individual (composition) and area level (composition) factors when examining and analysing disease patterns. View Full-Text
Keywords: Chronic Obstructive Pulmonary Disease (COPD), winter; air pollution; deprivation; spatiotemporal pattern; clustering; Geographically weighted Poisson regression (GWPR) Chronic Obstructive Pulmonary Disease (COPD), winter; air pollution; deprivation; spatiotemporal pattern; clustering; Geographically weighted Poisson regression (GWPR)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Marek, L.; Campbell, M.; Epton, M.; Kingham, S.; Storer, M. Winter Is Coming: A Socio-Environmental Monitoring and Spatiotemporal Modelling Approach for Better Understanding a Respiratory Disease. ISPRS Int. J. Geo-Inf. 2018, 7, 432.

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