Next Article in Journal
Health Profile of Construction Workers in Hong Kong
Previous Article in Journal
The Association of Hypertriglyceridemic Waist Phenotype with Chronic Kidney Disease and Its Sex Difference: A Cross-Sectional Study in an Urban Chinese Elderly Population
Article

Minimizing Spatial Variability of Healthcare Spatial Accessibility—The Case of a Dengue Fever Outbreak

1
Department of Geomatics, National Cheng Kung University, Tainan City 700, Taiwan
2
Research Center for Humanities and Social Sciences, Academia Sinica, Taipei City 115, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Peter Congdon
Int. J. Environ. Res. Public Health 2016, 13(12), 1235; https://doi.org/10.3390/ijerph13121235
Received: 2 October 2016 / Revised: 24 November 2016 / Accepted: 2 December 2016 / Published: 13 December 2016
(This article belongs to the Section Global Health)
Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model’s demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations. View Full-Text
Keywords: floating catchment area; particle swarm optimization floating catchment area; particle swarm optimization
Show Figures

Figure 1

MDPI and ACS Style

Chu, H.-J.; Lin, B.-C.; Yu, M.-R.; Chan, T.-C. Minimizing Spatial Variability of Healthcare Spatial Accessibility—The Case of a Dengue Fever Outbreak. Int. J. Environ. Res. Public Health 2016, 13, 1235. https://doi.org/10.3390/ijerph13121235

AMA Style

Chu H-J, Lin B-C, Yu M-R, Chan T-C. Minimizing Spatial Variability of Healthcare Spatial Accessibility—The Case of a Dengue Fever Outbreak. International Journal of Environmental Research and Public Health. 2016; 13(12):1235. https://doi.org/10.3390/ijerph13121235

Chicago/Turabian Style

Chu, Hone-Jay, Bo-Cheng Lin, Ming-Run Yu, and Ta-Chien Chan. 2016. "Minimizing Spatial Variability of Healthcare Spatial Accessibility—The Case of a Dengue Fever Outbreak" International Journal of Environmental Research and Public Health 13, no. 12: 1235. https://doi.org/10.3390/ijerph13121235

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop