Comparative look at the transmission of parasites in macaque social and spatial networks

Abstract

Pathogen transmission is a key issue in both public health and wildlife conservation. Predicting pathogen transmission using social network analysis (SNA) has been trending upward following numerous studies of wildlife showing positive relationships between an individual’s social network centrality (a measurement of its importance in a network) and its probability or degree of infection; including in macaques. Based on this work, we aimed to test whether social network centrality can predict parasite infection in different macaque species and populations. We constructed 4 data sets based on behavioral observations and parasitological investigation using 2 groups each of rhesus macaques (Macaca mulatta) and Japanese macaques (Macaca fuscata). We modeled the relationship between social network centrality and intestinal parasite infection intensity in each group and compared the results among them. We also conducted simulations to control for the effect of sample size (i.e. number of fecal samples for parasitology) on the determined relationship. Generalized linear mixed models suggest a positive relationship between centrality and infection in only one macaque population (Japanese macaques of Koshima). Simulations show that small sample size was unlikely to have affected our results. Overall, our results suggest that social network centrality does not generally predict parasite infection across species and populations, which may relate more strongly to the various local ecologies of the studied groups. However, we cannot rule out the possible influence of seasonality in our study because our data were collected at each site in different seasonal conditions. Furthermore, human influences such as degree of provisioning and population management may also play a role. Ultimately, this work emphasizes the importance of understanding the mechanisms underlying transmission and how they might vary across populations and groups when attempting to relate social factors to infection.