Relief of spatiotemporal accessibility overloading with optimal resource placement

Chien Wei Chang, Hao Yi Chih, Dean Chou, Yu Chen Shu, Kun Ta Chuang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the effects of global warming, some epidemic diseases via mosquito (e.g. mosquito-borne diseases) become more serious, such as dengue fever and zika virus. It is reported that the epidemic disease may cause many challenges to the hospital management due to the unexpected burst with uncertain reasons. Furthermore, the imperfect cares during the propagation of epidemic diseases, such as dengue fever (so far the appropriate treatment is not well established), may lead to the increasing mortality rate which should be avoided. In this paper, a novel paradigm for optimizing the placement of medical resource is proposed in pursuit of reducing the overloading cases in hospitals during the epidemic outbreak in the urban area. In this paper we explore the first paper to explore two important issues, including the strategy to evaluate the service quality and the solution to dynamically dispatch the medical resource, along with the spatial variation of epidemic outbreak. As validated in our experimental results in real data of dengue outbreak happening in Tainan (2015), we present the feasibility of our framework to deploy a dynamic placement strategy for medical resource assignment.

Original languageEnglish
Title of host publicationProceedings - 16th IEEE International Conference on Data Mining, ICDM 2016
EditorsFrancesco Bonchi, Xindong Wu, Ricardo Baeza-Yates, Josep Domingo-Ferrer, Zhi-Hua Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages61-70
Number of pages10
ISBN (Electronic)9781509054725
DOIs
Publication statusPublished - 2017 Jan 31
Event16th IEEE International Conference on Data Mining, ICDM 2016 - Barcelona, Catalonia, Spain
Duration: 2016 Dec 122016 Dec 15

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other16th IEEE International Conference on Data Mining, ICDM 2016
CountrySpain
CityBarcelona, Catalonia
Period16-12-1216-12-15

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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