Simulation Analysis of Beijing H1N1 Influenza Based on Spatial Clustering

Authors

Yitong Zhao, 1. College of Information System and Management, National University of Defense Technology, Changsha 410073, China;;
Mei Shan, 1. College of Information System and Management, National University of Defense Technology, Changsha 410073, China;;
Ma Liang, 1. College of Information System and Management, National University of Defense Technology, Changsha 410073, China;;
Zhang Wei, 2. Institute of Telecommunication Satellite, China Academy of Space Technology, Beijing 110101, China;

Abstract

Abstract: Spatial cluster detection is widely used for disease surveillance, prevention and containment. In the early stages of illness, epidemics have similar symptoms to common diseases, making infectious disease data processing and analysis difficult. The Agent based modeling and simulation was used to generate H1N1 influenza data in Beijing. By designing a set of experiments, the epidemic monitoring results of two spatial clustering algorithms were analyzed. The results show that, using spatial clustering algorithms to analyze the simulation data of the epidemics can help to reveal the spread of the epidemic and play a positive role in the surveillance and prevention of infectious diseases.

Recommended Citation

Zhao, Yitong; Shan, Mei; Liang, Ma; and Wei, Zhang (2020) "Simulation Analysis of Beijing H1N1 Influenza Based on Spatial Clustering," Journal of System Simulation: Vol. 29: Iss. 9, Article 32.
DOI: 10.16182/j.issn1004731x.joss.201709032
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss9/32

First Page

2115

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201709032

Last Page

2121

CLC

TP391.9;R181.3

Recommended Citation

Zhao Yitong, Mei Shan, Ma Liang, Zhang Wei. Simulation Analysis of Beijing H1N1 Influenza Based on Spatial Clustering[J]. Journal of System Simulation, 2017, 29(9): 2115-2121.

DOI

10.16182/j.issn1004731x.joss.201709032