Overcoming inefficiencies arising due to the impact of the modifiable areal unit problem on single-aggregation disease maps
| العنوان: | Overcoming inefficiencies arising due to the impact of the modifiable areal unit problem on single-aggregation disease maps |
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| المؤلفون: | Matthew Tuson, David Whyatt, Mei Ruu Kok, Alistair Vickery, Berwin A. Turlach, M. J. Yap, Kevin Murray, Bryan Boruff |
| المصدر: | International Journal of Health Geographics, Vol 19, Iss 1, Pp 1-18 (2020) International Journal of Health Geographics |
| بيانات النشر: | Springer Science and Business Media LLC, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | General Computer Science, Computer science, Service delivery framework, Health geography, Acknowledgement, 0507 social and economic geography, Context (language use), lcsh:Computer applications to medicine. Medical informatics, Single-aggregation disease maps, Health informatics, Brain Ischemia, 03 medical and health sciences, 0302 clinical medicine, Humans, Computer Simulation, 030212 general & internal medicine, Set (psychology), business.industry, 05 social sciences, Methodology, Public Health, Environmental and Occupational Health, Modifiable areal unit problem, Western Australia, Zonation-dependence, General Business, Management and Accounting, Stroke, Risk analysis (engineering), Research Design, Disease mapping, lcsh:R858-859.7, Resource allocation, Resource allocation efficiency, business, 050703 geography |
| الوصف: | Background In disease mapping, fine-resolution spatial health data are routinely aggregated for various reasons, for example to protect privacy. Usually, such aggregation occurs only once, resulting in ‘single-aggregation disease maps’ whose representation of the underlying data depends on the chosen set of aggregation units. This dependence is described by the modifiable areal unit problem (MAUP). Despite an extensive literature, in practice, the MAUP is rarely acknowledged, including in disease mapping. Further, despite single-aggregation disease maps being widely relied upon to guide distribution of healthcare resources, potential inefficiencies arising due to the impact of the MAUP on such maps have not previously been investigated. Results We introduce the overlay aggregation method (OAM) for disease mapping. This method avoids dependence on any single set of aggregate-level mapping units through incorporating information from many different sets. We characterise OAM as a novel smoothing technique and show how its use results in potentially dramatic improvements in resource allocation efficiency over single-aggregation maps. We demonstrate these findings in a simulation context and through applying OAM to a real-world dataset: ischaemic stroke hospital admissions in Perth, Western Australia, in 2016. Conclusions The ongoing, widespread lack of acknowledgement of the MAUP in disease mapping suggests that unawareness of its impact is extensive or that impact is underestimated. Routine implementation of OAM can help avoid resource allocation inefficiencies associated with this phenomenon. Our findings have immediate worldwide implications wherever single-aggregation disease maps are used to guide health policy planning and service delivery. |
| تدمد: | 1476-072X |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a463f589fc57410876c985b4df8ec87Test https://doi.org/10.1186/s12942-020-00236-yTest |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....5a463f589fc57410876c985b4df8ec87 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1476072X |
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