A test of agent-based models as a tool for predicting patterns of pathogen transmission in complex landscapes

Annals of Occupational and Environmental Medicine

Kelly E Lane-deGraaf⁵  Ryan C Kennedy³  SM Niaz Arifin¹  Gregory R Madey¹  Agustin Fuentes²  Hope Hollocher⁴ 

[1] Department of Computer Science & Engineering, University of Notre Dame, Notre Dame, IN, USA

[2] Department of Anthropology, University of Notre Dame, Notre Dame, IN, USA

[3] Department of Bioengineering and Therapeutic Services, University of California, San Francisco, USA

[4] Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA

[5] Current address: Odum School of Ecology, University of Georgia, Athens, GA, USA

关键词: GIS;    Landscape heterogeneity;    Pathogen transmission;    Dispersal;    Agent-based model;   

Others  :  1085161
DOI  :  10.1186/1472-6785-13-35

 received in 2013-02-20, accepted in 2013-09-09,  发布年份 2013

【 摘 要 】

Background

Landscape complexity can mitigate or facilitate host dispersal, influencing patterns of pathogen transmission. Spatial transmission of pathogens through landscapes, therefore, presents an important but not fully elucidated aspect of transmission dynamics. Using an agent-based model (LiNK) that incorporates GIS data, we examined the effects of landscape information on the spatial patterns of host movement and pathogen transmission in a system of long-tailed macaques and their gut parasites. We first examined the role of the landscape to identify any individual or additive effects on host movement. We then compared modeled dispersal distance to patterns of actual macaque gene flow to both confirm our model’s predictions and to understand the role of individual land uses on dispersal. Finally, we compared the rate and the spread of two gastrointestinal parasites, Entamoeba histolytica and E. dispar, to understand how landscape complexity influences spatial patterns of pathogen transmission.

Results

LiNK captured emergent properties of the landscape, finding that interaction effects between landscape layers could mitigate the rate of infection in a non-additive way. We also found that the inclusion of landscape information facilitated an accurate prediction of macaque dispersal patterns across a complex landscape, as confirmed by Mantel tests comparing genetic and simulated dispersed distances. Finally, we demonstrated that landscape heterogeneity proved a significant barrier for a highly virulent pathogen, limiting the dispersal ability of hosts and thus its own transmission into distant populations.

Conclusions

Landscape complexity plays a significant role in determining the path of host dispersal and patterns of pathogen transmission. Incorporating landscape heterogeneity and host behavior into disease management decisions can be important in targeting response efforts, identifying cryptic transmission opportunities, and reducing or understanding potential for unintended ecological and evolutionary consequences. The inclusion of these data into models of pathogen transmission patterns improves our understanding of these dynamics, ultimately proving beneficial for sound public health policy.

【 授权许可】

   
2013 Lane-deGraaf et al.; licensee BioMed Central Ltd.

【 图 表 】

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