Modeling of Wildlife-Associated Zoonoses: Applications and Caveats

被引:60
作者
Alexander, Kathleen A. [1 ]
Lewis, Bryan L. [2 ]
Marathe, Madhav [2 ,3 ]
Eubank, Stephen [2 ]
Blackburn, Jason K. [4 ,5 ]
机构
[1] Virginia Polytech Inst & State Univ, Dept Fish & Wildlife Conservat, 152 Cheatham Hall, Blacksburg, VA 24061 USA
[2] Virginia Polytech Inst & State Univ, Virginia Bioinformat Inst, Blacksburg, VA 24061 USA
[3] Virginia Polytech Inst & State Univ, Dept Comp Sci, Blacksburg, VA 24061 USA
[4] Univ Florida, Emerging Pathogens Inst, Spatial Epidemiol & Ecol Res Lab, Gainesville, FL USA
[5] Univ Florida, Dept Geog, Emerging Pathogens Inst, Gainesville, FL 32611 USA
基金
美国国家卫生研究院;
关键词
Mathematical models; Transmission; Wildlife; Zoonotic disease; BACILLUS-ANTHRACIS; GEOGRAPHIC-DISTRIBUTION; SPECIES DISTRIBUTIONS; UNITED-STATES; DISEASE; TRANSMISSION; AGENT; POPULATION; RESERVOIRS; INFECTION;
D O I
10.1089/vbz.2012.0987
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Wildlife species are identified as an important source of emerging zoonotic disease. Accordingly, public health programs have attempted to expand in scope to include a greater focus on wildlife and its role in zoonotic disease outbreaks. Zoonotic disease transmission dynamics involving wildlife are complex and nonlinear, presenting a number of challenges. First, empirical characterization of wildlife host species and pathogen systems are often lacking, and insight into one system may have little application to another involving the same host species and pathogen. Pathogen transmission characterization is difficult due to the changing nature of population size and density associated with wildlife hosts. Infectious disease itself may influence wildlife population demographics through compensatory responses that may evolve, such as decreased age to reproduction. Furthermore, wildlife reservoir dynamics can be complex, involving various host species and populations that may vary in their contribution to pathogen transmission and persistence over space and time. Mathematical models can provide an important tool to engage these complex systems, and there is an urgent need for increased computational focus on the coupled dynamics that underlie pathogen spillover at the human-wildlife interface. Often, however, scientists conducting empirical studies on emerging zoonotic disease do not have the necessary skill base to choose, develop, and apply models to evaluate these complex systems. How do modeling frameworks differ and what considerations are important when applying modeling tools to the study of zoonotic disease? Using zoonotic disease examples, we provide an overview of several common approaches and general considerations important in the modeling of wildlife-associated zoonoses.
引用
收藏
页码:1005 / 1018
页数:14
相关论文
共 85 条
[1]  
Adjemian JCZ, 2006, J MED ENTOMOL, V43, P93, DOI 10.1603/0022-2585(2006)043[0093:AOGAFR]2.0.CO
[2]  
2
[3]  
Alexander KA, 2010, FRONT ECOL ENV
[4]  
Alexander KA, 2012, PLOS ONE, V7
[5]   Novel Mycobacterium tuberculosis Complex Pathogen, M. mungi [J].
Alexander, Kathleen A. ;
Laver, Pete N. ;
Michel, Anita L. ;
Williams, Mark ;
van Helden, Paul D. ;
Warren, Robin M. ;
Gey van Pittius, Nicolaas C. .
EMERGING INFECTIOUS DISEASES, 2010, 16 (08) :1296-1299
[6]  
ANDERSON R M, 1991
[7]   Real vs. artefactual absences in species distributions:: tests for Oryzomys albigularis (Rodentia: Muridae) in Venezuela [J].
Anderson, RP .
JOURNAL OF BIOGEOGRAPHY, 2003, 30 (04) :591-605
[8]  
[Anonymous], 2008, AGENT BASED MODELS
[9]   Agent-based modeling of host-pathogen systems: The successes and challenges [J].
Bauer, Amy L. ;
Beauchemin, Catherine A. A. ;
Perelson, Alan S. .
INFORMATION SCIENCES, 2009, 179 (10) :1379-1389
[10]  
Beatty A., 2008, ACHIEVING SUSTAINABL