Dr. Liang Mao

Assistant Professor
liangmao@ufl.edu

Areas of Specialization

• Spatial modeling for disease epidemics
• Disease control strategies
• Spatial/Social network analysis
• GIS/RS for envnvironmental health

Educational Background

• PhD Geography, State University of New York at Buffalo, 2010
• MS GIScience, Nanjing Univerisity, 2005
• BS Geography, Nanjing University, 2002

Recent Courses

GEO 3452/6451: Medical Geography (Fall)

GIS 3420C/6938: GIS models for public health (Spring)

GEO 3930/6938: Introduction to network analysis (Fall)

GEOG 3930/6938: Applied Geostatistics (Spring)

Recent Publications

1. L. Bian, Y. X. Huang, L. Mao, E.J. Lim, G.J. Lee, Y. Yang, D. Wilson,& M. Cohen, 2012. Modeling Individual Vulnerability to Communicable Diseases – A Framework and Design. The Annals of the Association of American Geographers 102(5):1016-1025.PDF.
2. L. Mao, Y. Yang, Y. L. Qiu, Y. Yang, 2012. Annual economic impacts of seasonal influenza on US counties: Spatial heterogeneity and patterns. International Journal of Health Geographies 11:16 PDF
3. L. Mao,Y. Yang, 2012. Coupling infectious disease, human preventive behavior,and social networks — A conceptual model for simulation. Social Science & Medicine 74(2):167-175.PDF.
4. L. Mao,Y.L. Qiu, C. Kusano, X.H. Xu, 2012. Predicting regional space-time variation of PM2.5 with land use regression model and MODIS data.Environmental Science and Pollution Research, 19(1):128-138.PDF
5. L. Mao, L.Bian, 2011. Agent-based Simulation for a Dual-Diffusion Process of Influenza and Human Preventive Behavior. International Journal of Geographical Information Science 25(9): 1371-1388. PDF
6. L. Mao, 2011. Agent-based simulation for weekend-extension strategies to mitigate influenza outbreaks. BMC Public Health , 11(1): 522 PDF.
7. L. Mao, 2011.Evaluating the combined effectiveness of influenza control strategies and human preventive behavior. PLoS ONE , 6(10): e24706. PDF .
8. J. Liang, F.X. Li, L. Mao, 2010. Review of the methods of delimitation for the spatial scope of urban agglomeration. Proceedings of Geoinformatics, 2010 18th International Conference. PDF
9. L. Mao, L. Bian, 2010. Spatial–temporal transmission of influenza and its health risks in an urbanized area. Computers, Environment and Urban Systems, 34(3):204-215. PDF
10. L. Mao, L. Bian, 2010. A Dynamic Network with Individual Mobility for Designing Vaccination Strategies. Transactions in GIS, 14(4):533-545. PDF
11. L. Bian, T. Whalen, M. Cohen, Y. Huang, G. Lee, E. Lim, L. Mao, Y. Yang, 2008. Explicit Spatial-Temporal Simulation of a Rare Disease. Joint Conference on Information Sciences Proceedings: Advances in Intelligent Systems Research PDF
12. W. Guo, S.H. Li, L. Mao, Y. Yin, D.K. Zhu, 2007. A Model for Environmental Impact Assessment of Land Reclamation. China Ocean Engineering, 21(2):343-354. PDF
13. Y.X. Liu, M.C. Li, L. Mao, F. Xu, S. Huang, 2006. Review of remotely sensed imagery classification patterns based on object-oriented image analysis. Chinese Geographical Science, 16(3):282-288. PDF

Graduate Students Currently Supervised

• Allasane Barro Ph.D. (Fall 2012)
• Dawn Nekorchuk Ph.D. (Fall 2012)
• Michael Falkner M.S. (Fall 2010)
• Sheldon Waugh M.S. (Fall 2012)

In My Own Words

Human and diseases composes a complex and interactive system, where diseases infect human beings and human beings react to prevent infection. In recent years, emerging and re-emerging infectious diseases have obtained unprecedented attention due to the wide spread of severe acute respiratory syndrome (SARS), bird flu, and new H1N1 flu. My research aims to offer better understandings on the human-disease system with GIS techologies, agent-based simulation, and statistical methods. My dissertation established an agent-based dual-diffusion model to couple the diffusion of influenza and the diffusion of human preventive behavior. This spatially explicit model is used to: 1) understand the spatio-temporal dynamics of this dual-diffusion in the city of Buffalo, NY, 2) evaluate the combined effects of mitigation strategies and human preventive behavior, and 3) explore health policies to promote preventive behavior against influenza. The research results are expected to inform scientists, health policy makers, and local governments to overcome current challenges from looming influenza pandemics.

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