TY - JOUR
T1 - A test of agent-based models as a tool for predicting patterns of pathogen transmission in complex landscapes
AU - Lane-deGraaf, Kelly E.
AU - Kennedy, Ryan C.
AU - Arifin, SM M.N.
AU - Madey, Gregory R.
AU - Fuentes, Agustin
AU - Hollocher, Hope
N1 - Funding Information:
The authors would like to thank Udayana Universitas, Pusat Kajian Primata. We would also like to thank Gerhard Neiderweiser, Adeline Dozois, and Amy Klegarth for their helpful comments and insights. This research was supported in part by the Notre Dame Center for Research Computing, with valuable assistance provided by Paul Brenner. This work was supported by funding from the National Science Foundation (BSC-0629787), the Leakey Foundation, and the University of Notre Dame. All collections were approved by the University of Notre Dame IACUC (protocol 07–001 and 09–011) and the Indonesian Institute of Science (permit number 662.02/1090.DIII).
PY - 2013/9/25
Y1 - 2013/9/25
N2 - 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.
AB - 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.
KW - Agent-based model
KW - Dispersal
KW - GIS
KW - Landscape heterogeneity
KW - Pathogen transmission
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U2 - 10.1186/1472-6785-13-35
DO - 10.1186/1472-6785-13-35
M3 - Article
C2 - 24063811
AN - SCOPUS:84884514965
SN - 1472-6785
VL - 13
JO - BMC Ecology
JF - BMC Ecology
M1 - 35
ER -