Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology - Rilegato

Arifin, S. M. Niaz; Madey, Gregory R.; Collins, Frank H.

Rilegato

ISBN 10: 1118964357 ISBN 13: 9781118964354

Casa editrice: John Wiley & Sons Inc, 2016

Riassunto

Agent-Based Modeling (ABM) is a powerful tool for representing complex biological systems. Beginning with a biological core model of Anopheles gambiae (An. gambiae for short) for malaria epidemiology, the authors develop agent-based simulation models, iteratively refine existing biological concepts, and incrementally add new concepts to the core model.  Using the spatial ABM, the effects of spatial heterogeneity are described.  The book also includes vector control interventions and geographic informations systems as two examples applications of ABM as well as a brief description of epidemiology modeling, which is an advanced individual-based model.  GIS and spatial statistical methods have been extensively used in entomological and epidemiological studiesis in multiple domains (i.e. urban land-use change, military mobile communications, etc.); however, no model-based malaria study has yet to illustrate how to effectively integrate ABM with GIS and other geo-spatial features, and thereby harness the full power of GIS.  There is an advantage in building robust integration frameworks that guide the use of geo-spatial features (related to malaria transmission) as model inputs, as opposed to simply using these features as cartographic outputs from the models (as done by mostprevious studies).  In addition, the authors discuss how to effectively
integrate spatial ABM with a GIS.  The presented location-specific mosquito abundance maps play an important role in malaria control activities, including monitoring the changes of key transmission indices, which, in turn, may assist in guiding future resource allocation for malaria control and identifying hotspots for further investigation.  The book concludes that such integrated approaches, which combine knowledge
from entomological, epidemiological, simulation-based, and geo-spatial domains, are required for the identification and analysis of relationships between various transmission variables of the disease, as demonstrated by the application. Eventually, such integration efforts may facilitate the Integrated
Vector Management (IVM) agenda, promoted by the World Health Organization (WHO) to achieve improved efficacy, cost-effectiveness, ecological soundness, and sustainability of vector control for malaria.

Su questo libro

L'autore:

S. M. Niaz Arifin, PhD, is Research Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame. A member of The Society for Computer Simulation and American Society of Tropical Medicine and Hygiene and the recipient of The American Society of Tropical Medicine and Hygiene Travel Award in 2011, his research interests include agent-based modeling and simulation, public health, data warehousing, and geographic information systems.
 
Gregory R. Madey, PhD, is Research Professor in the Department of Computer Science and Engineering at the University of Notre Dame. A member of The Society for Computer Simulation, Institute of Electrical and Electronics Engineers Computer Society, and American Society of Tropical Medicine and Hygiene, his research interests include agent-based modeling and simulation, cyberinfrastructure, bioinformatics, biocomplexity, e-Technologies, open source software, disaster management, and health informatics.
 
Frank H. Collins, PhD, is Professor in the Department of Biological Sciences at the University of Notre Dame. His research interests include genome level studies of arthropod vectors of human pathogens, the biology of malaria vectors with a focus on the development of molecular tools that will permit better resolution of questions about vector population ecology, ecological genetics, and the epidemiology of malaria transmission.

Dalla quarta di copertina:

Presents an overview of the complex biological systems used within a global public health setting and features a focus on malaria analysis

Bridging the gap between agent-based modeling and simulation (ABMS) and geographic information systems (GIS),Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology provides a useful introduction to the development of agent-based models (ABMs) by following a conceptual and biological core model of Anopheles gambiae for malaria epidemiology. Using spatial ABMs, the book includes mosquito (vector) control interventions and GIS as two example applications of ABMs, as well as a brief description of epidemiology modeling. In addition, the authors discuss how to most effectively integrate spatial ABMs with a GIS. The book concludes with a combination of knowledge from entomological, epidemiological, simulation-based, and geo-spatial domains in order to identify and analyze relationships between various transmission variables of the disease.

Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology also features:

• Location-specific mosquito abundance maps that play an important role in malaria control activities by guiding future resource allocation for malaria control and identifying hotspots for further investigation
• Discussions on the best modeling practices in an effort to achieve improved efficacy, cost-effectiveness, ecological soundness, and sustainability of vector control for malaria
• An overview of the various ABMs, GIS, and spatial statistical methods used in entomological and epidemiological studies, as well as the model malaria study
• A companion website with computer source code and flowcharts of the spatial ABM and a landscape generator tool that can simulate landscapes with varying spatial heterogeneity of different types of resources including aquatic habitats and houses

Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology is an excellent reference for professionals such as modeling and simulation experts, GIS experts, spatial analysts, mathematicians, statisticians, epidemiologists, health policy makers, as well as researchers and scientists who use, manage, or analyze infectious disease data and/or infectious disease-related projects. The book is also ideal for graduate-level courses in modeling and simulation, bioinformatics, biostatistics, public health and policy, and epidemiology.

S. M. Niaz Arifin, PhD, is Research Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame.  A member of The Society for Computer Simulation, and American Society of Tropical Medicine and Hygiene, and the recipient of The American Society of Tropical Medicine and Hygiene Travel Award in 2011, his research interests include agent-based modeling and simulation, public health, data warehousing, and geographic information systems.  

Gregory R. Madey, PhD, is Research Professor in the Department of Computer Science and Engineering at the University of Notre Dame.  A member of The Society for Computer Simulation, Institute of Electrical and Electronics Engineers Computer Society, and American Society of Tropical Medicine and Hygiene, his research interests include agent-based modeling and simulation, cyberinfrastructure, bioinformatics, biocomplexity, e-Technologies, open source software, disaster management, and health informatics.  

Frank H. Collins, PhD, is Professor in the Department of Biological Sciences at the University of Notre Dame.  His research interests include genome level studies of arthropod vectors of human pathogens, the biology of malaria vectors with a focus on the development of molecular tools that will permit better resolution of questions about vector population ecology, ecological genetics, and the epidemiology of malaria transmission.

Su questa edizione

• Editore: John Wiley & Sons Inc
• Data di pubblicazione: 2016
• ISBN 10: 1118964357
• ISBN 13: 9781118964354
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 288