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Title: Simulation of HIV/AIDS distribution using GIS based cellular automata model
Authors: Yang, S
He, DH 
Luo, J
Chen, WZ
Yang, XH
Wei, M
Kong, XY
Li, YC
Feng, XX
Zeng, ZQ
Keywords: Acquired immune deficiency syndrome
Cellular automata
Geographic information systems
Issue Date: 2017
Publisher: Scientific publishers India
Source: Biomedical research (India), 2017, v. 28, no. 9, p. 4053-4057 How to cite?
Journal: Biomedical research (India) 
Abstract: Objective: To predict the epidemic distribution of HIV/AIDS cases in Chongqing using Cellular Automata (CA) based on the real geographic information and surveillance data. To explore a better model to simulate the transmission of HIV/AIDS based on the different epidemic parameters and initial periods. Methods: GIS-based cellular automata models were formulated in this study, the cells were defined with regard to the real geospatial information. The distribution of HIV/AIDS was predicted and the initial value of each cell was from the real surveillance data. Results: Six models were developed in this study under two individual epidemic parameters (0.1 and 0.05) and three initial periods (1995 similar to 2000, 1995 similar to 2001 and 1995 similar to 2002). When the individual epidemic parameter (I) was set to 0.1, with three different initial periods, the steps of iterations were 111, 103 and 91. When I was set to 0.05, the number of steps was 208, 199 and 178 respectively. The differences between predicted and real data were narrowed when the epidemic parameter was set to 0.05 and the initial period was chose from 1995 to 2002. The results showed that there was statistical significance between predicted and real distribution in four regions of Chongqing. The results, however, were improved by adjusting the individual epidemic parameter and the initial periods. Conclusion: Our findings indicated that the models were feasible to predict the distribution, although the best epidemic parameter and initial period should be explored in further studies. The findings could provide some clues for further simulation of HIV/AIDS distribution.
ISSN: 0970-938X
EISSN: 0976-1683
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