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




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BMC Ecology

, 13:35

Landscape ecology and ecosystems

Abstract

BackgroundLandscape 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.

ResultsLiNK 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.

ConclusionsLandscape 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.

KeywordsAgent-based model Dispersal Pathogen transmission Landscape heterogeneity GIS AbbreviationsLiNKNamed for the authors of the model Lane, Neiderweiser, and Kennedy, this is the agent-based model developed to understand spatial and temporal pathogen transmission patterns

GISGeographic Information Systems

ABMAgent-based Model

ODDOverview Design concepts, and Details.

Electronic supplementary materialThe online version of this article doi:10.1186-1472-6785-13-35 contains supplementary material, which is available to authorized users.

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Author: Kelly E Lane-deGraaf - Ryan C Kennedy - SM Niaz Arifin - Gregory R Madey - Agustin Fuentes - Hope Hollocher

Source: https://link.springer.com/







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