An analysis of Beijing HFMD patients mobility pattern during seeking treatment

Zhaonan Zhu, Zhidong Cao, Daniel Dajun Zeng

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

Abstract

Previous epidemiological researches have studied HFMD transmission pattern, but the study on the patients mobility pattern while seeking treatment is absent. In this paper, we present a statistical analysis of the spatialtemporal pattern of the Beijing HFMD patients mobility based on a complete works dataset containing over 40,000 cases in 2010. The main findings are as follows: (1) the patents incline to take their sick children to hospitals on weekdays, especially on Monday; (2) the patients living far from city center are more likely to get to hospitals in the afternoon, while the patients in the downtown in the morning; (3) patients (or their parents) either select the nearby hospitals, or the Class-A hospitals in the downtown. Furthermore, we employ a gravity model to describe the spatial mobility pattern of patients. The experiment results show a good fit.

Original languageEnglish (US)
Title of host publicationSmart Health - International Conference, ICSH 2013, Proceedings
Pages24-30
Number of pages7
DOIs
StatePublished - Aug 12 2013
Externally publishedYes
Event2013 International Conference for Smart Health, ICSH 2013 - Beijing, China
Duration: Aug 3 2013Aug 4 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8040 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2013 International Conference for Smart Health, ICSH 2013
CountryChina
CityBeijing
Period8/3/138/4/13

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Keywords

  • Hand-foot-mouth disease
  • gravity model
  • mobility pattern
  • spatial-temporal analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Zhu, Z., Cao, Z., & Zeng, D. D. (2013). An analysis of Beijing HFMD patients mobility pattern during seeking treatment. In Smart Health - International Conference, ICSH 2013, Proceedings (pp. 24-30). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8040 LNCS). https://doi.org/10.1007/978-3-642-39844-5_4