Exposure in motion: assessing disease risk through movement models and metrics

Exposure represents but one of several processes that underlie disease transmission dynamics in animal and human populations. Infection frequently depends on a number of complex interactions among factors related to the clinical properties of the pathogen (or the magnitude of the dose acquired upon contact) and the immune status of the host. When considering exposure, however, many of these aspects become trivial; the primary consideration is contact between a host and the infectious agent, whether it is harbored by another animal or an environmental reservoir. Contact, in turn, emerges from the space-use decisions of animals over time, potentially resulting in patterns that amplify or dilute the probability of encountering a pathogen. In this sense, the movement behavior of host animals is a fundamental determinant of disease dynamics. Using anthrax as its focal system, this dissertation aims to delve into the exposure process as it relates to the movement behaviors of host animals./nA set of movement trajectories were collected via GPS collars fastened to zebra (Equus quagga) and springbok (Antidorcas marsupialis) in Etosha National Park in Namibia between 2009 and 2010. These data offer insight into the home ranging and habitat selection behaviors that characterize two ungulate species exhibiting susceptibility to anthrax infection and thus, form the basis of the analyses and models developed in this dissertation./nSpatial overlap analysis represents one of the most common methods for evaluating the potential for disease exposure when movement data is available. In the case of an indirectly transmitted pathogen, such as Bacillus anthracis, the overlap between individuals may be less important than other characteristics of individual home range usage. Metrics such as revisitation (the rate at which an animal returns to a specific location) and duration rate (the length of time spent in a specific location) may be more informative, particularly if the locations of locally infectious zones (LIZs) are known. To assess the relative risk faced by zebra and springbok during the anthrax season, I developed a method that reduces the subjectivity in parameter selection when delineating home ranges using the Time Local Convex Hull (T-LoCoH) method. Using a cross-validation-based approach, the resulting site fidelity metrics are more directly comparable. The high values of the two site fidelity metrics imply that similar home ranging behavior among individuals can result in heterogeneous outcomes, contingent entirely upon the presence of a LIZ within an individual's home range./nMuch like spatial overlap analyses, habitat selection approaches can offer insight into patterns of potential risk with respect to exposure to disease, particularly in the case of environmentally-borne pathogens. When certain environmental characteristics can be associated with pathogen persistence, niche models can be developed and directly incorporated into the resource selection function framework. I used remotely sensed data on soil, bioclimatic, and vegetation covariates to build such a niche model for anthrax based on soil samples from 40 carcass sites in Etosha National Park harboring viable anthrax spores two or more years after deposition. When this risk layer was applied as a predictor in a step-selection function of zebra, a behaviorally-dependent pattern was evident. When animals were in the foraging state exhibited an avoidance of high risk areas, whereas the same animals were apparently attracted to those higher risk areas when moving in a directed manner. One possible explanation for this pattern is that zebra recognize not only where but also when they are most susceptible to anthrax, and adjust their behavior to reduce their risk./nAnother means of exploring the exposure process is through the use of simulation models. Due to the difficulty associated with comprehensive monitoring of susceptible host populations and infectious reservoirs, simulation models represent an ideal approach for extending general rules emerging from limited movement data to landscapes with known qualities. Using the behaviorally-contingent habitat selection framework created in Chapter 3, I explored the relationship between a set of environmental covariate layers and the exposure process whereby individuals encounter LIZs on the landscape. The method reveals that Wetness may represent a reasonable predictor of epidemic dynamics, with movement serving as the mediating process./nThe general analytical methods and models applied here serve to elucidate the role of individual movement behavior in the disease exposure process. Rather than analyzing data on case incidence or prevalence, these methods offer insight into the potential contact patterns that might give rise to endemic or epidemic infections. Thus, they reveal the manner by which analysis of host movements, particularly in conjunction with comprehensive (or simulated) data on the spatial distribution of infectious agents on a heterogeneous landscape, might aid in the management of transmission risk before any actual infections occur.

Advisor: Getz, Wayne M