Although pathogen transmission dynamics are profoundly affected by population social and spatial structure, few studies have empirically demonstrated the population-level implications of such structure in wildlife. In particular, epidemiological models predict that the extent to which contact patterns are clustered decreases a pathogen's ability to spread throughout an entire population, but this effect has yet to be demonstrated in a natural population. Here, we use network analysis to examine patterns of transmission of an environmentally transmitted parasite, Cryptosporidium spp., in Belding's ground squirrels (Spermophilus beldingi). We found that the prevalence of Cryptosporidium was negatively correlated with transitivity, a measure of network clustering, and positively correlated with the percentage of juvenile males. Additionally, network transitivity decreased when there were higher percentages of juvenile males; the exploratory behavior demonstrated by juvenile males may have altered the structure of the network by reducing clustering, and low clustering was associated with high prevalence. We suggest that juvenile males are critical in mediating the ability of Cryptosporidium to spread through colonies, and thus may function as "super-spreaders." Our results demonstrate the utility of a network approach in quantifying mechanistically how differences in contact patterns may lead to system-level differences in infection patterns.
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Acknowledgments We thank Jennifer Dike and Katryna Fleer for their assistance in data collection and Allison Heagerty for her comments and contributions to data analysis. We also thank two anonymous reviewers for their constructive comments on an earlier version of this manuscript. This work was conducted under the auspices of the Bernice Barbour Communicable Disease Laboratory, with financial support from the Bernice Barbour Foundation, Hackensack, N.J., as a grant to the Center of Equine Health, University of California, Davis.
- Ground squirrels
- Infection patterns
- Pathogen transmission
- Social networks
- Wildlife disease