Association patterns and insights for disease transmission
Our results demonstrate interindividual and temporal variation in association patterns of wild chimpanzees, which should have profound effects on pathogen transmission dynamics. A main advantage of network analysis over more traditional connectivity measures, such as party size, is that network analysis explicitly quantifies how connectivity varies in relation to demographic and behavioural traits and among individuals in a community. Degree distributions demonstrated that neither party nor 5-m networks were highly aggregated (i.e. most individuals had moderate centrality as opposed to a few superspreaders accounting for a majority of contacts); yet certain types of individuals had significantly higher association rates than others.
Adult females and juveniles with large families (i.e. 3–4 family members) were significantly more central than expected by chance in both party and 5-m networks, and individuals in core-ranging families were significantly more central than those in edge-ranging families. Thus, core-ranging adult females and juveniles with large families were the most central to the community. Additionally, chimpanzees associated more frequently with related individuals and individuals that had similar family sizes. Therefore, it seems that core-ranging chimpanzees with large families associated frequently with family members and also formed what Goodall (1986) referred to as ‘nursing parties’, where mothers and juveniles of different family units socialize together. Notably, there is evidence in West African chimpanzees (Taï Forest) that young juveniles maintain respiratory diseases in the community through play or close contact (Kuehl et al. 2008), a dynamic that has been demonstrated among human children for various childhood diseases (e.g. Fine & Clarkson 1982). Edge-ranging families were nearly always the least central to the study community. In fact, the average degree centrality between a core-ranging adult female with a large family and an edge-ranging adult female without any juvenile offspring differed roughly by a factor of 2 in party networks and 2·5 in 5-m networks. Thus, individuals from edge-ranging families were the least likely to contribute to or be affected by pathogen transmission (although peripheral individuals could be exposed to pathogens from other communities or human settlements that overlap with forest edges).
Among core-ranging individuals, the average centrality of an adult female chimpanzee with three juveniles was roughly 2·5 degrees higher than that of an adult female with no juveniles. Previous wildlife network studies have demonstrated that even small differences in centrality can be linked to key differences in individual infection status. For example, a study examining parasites in gidgee skinks (Egernia stokesii) determined that while network centrality was an effective predictor of parasite burden, the average difference in centrality between skinks with and without ticks was only c. 0·35 degrees (Godfrey et al. 2009). Thus, while we recognize that the magnitude of centrality metrics (which depend on network size and system-specific association definitions) should not be directly compared across systems, the significant increase we observed in chimpanzee centrality due to family size (even if modest in magnitude) could have a crucial impact on individual infection status.
While not as consistently central as core-ranging adult females and juveniles with large families, high-ranking males also had high centrality. Past work on the same study community showed that high-ranking males tend to have increased levels of immunosuppressing testosterone (Muller & Wrangham 2004), and work in a nearby chimpanzee community (Ngogo) recently demonstrated that high-ranking males had both increased testosterone levels and greater helminth burdens (Muehlenbein & Watts 2010). Thus, in combination with the well-established immunosuppressive effects of sex hormones, their moderately central location in the network should make high-ranking males susceptible to contracting and transmitting a variety of pathogens. Taken altogether, we expect that core-ranging adult female and juvenile chimpanzees with large families, and to a lesser extent high-ranking males, should play an important role in pathogen transmission.
Contrary to our predictions, oestrous females were not significantly more central than expected by chance in party or 5-m networks. This is surprising considering that among party networks, pairs including oestrous females had higher levels of association and oestrous females significantly increased association patterns across the community. Because a majority of adult females in our study community were nursing infants, the sample size for oestrous females was limited (N = 3). Furthermore, one oestrous female was frequently absent from the community and was presumed to be engaging in consortships, in which a mating pair travels away from the community (Goodall 1986). In future studies of centrality with larger samples of oestrous females, it may be necessary to develop networks that span shorter time frames (i.e. the length of maximal swelling or roughly 1 week), as examining longer time steps includes intervals when the female does not have an oestrous swelling and is potentially experiencing lower centrality.
While often overlooked in epidemiological analysis, temporal changes in behavioural interactions can affect outbreak timing (Altizer et al. 2006), as demonstrated by peaks in measles transmission in children during school sessions (Fine & Clarkson 1982) or by phocine distemper outbreaks coinciding with the haul-out behaviour of seals (Swinton et al. 1998). Chimpanzee pairs were twice as likely to associate, and party networks were denser when females were in oestrus, suggesting that oestrous events represent times of high vulnerability to infectious disease outbreaks. This result confirms findings from long-term field studies showing that chimpanzee party size increases with the number of oestrous females (e.g. Wrangham 2000). Notably, there was no significant relationship between party and 5-m network density, and the number of oestrous females did not significantly affect 5-m-level associations. Thus, our network analyses suggest that the potential risk of outbreaks from pathogens that require very close contact for transmission might not increase with oestrous events.
Implications for conservation and infectious disease management
Epidemiological modelling studies in humans have shown that targeting central individuals for control efforts is significantly more effective in mitigating disease than applying control efforts randomly (Lloyd-Smith et al. 2005; Salathé et al. 2010). In a handful of cases, vaccination has been used to reduce the impact of emergent epidemics in endangered wildlife populations (gorilla measles and chimpanzee polio: Woodford, Butynski & Karesh 2002; Ethiopian wolf rabies: Haydon et al. 2006). Given the detrimental impacts of pathogens on great ape communities (e.g. Bermejo et al. 2006; Caillaud et al. 2006; Köndgen et al. 2008), some wildlife biologists have called for vaccinating great apes prophylactically for high-risk pathogens (Ryan & Walsh 2011). To effectively plan control strategies and minimize human interference, network models can indicate the minimum number of well-connected individuals that should be vaccinated to reduce outbreak sizes (as per: Salathé et al. 2010). Importantly, using coarser connectivity metrics such as party size or group membership to parameterize infectious disease models would only capture a fraction of the contact heterogeneity observed in the networks described here. Our next steps include using susceptible–infected–recovered (SIR) bond percolation models (Newman 2002; Meyers 2007) to simulate pathogen transmission on the observed monthly chimpanzee networks to assess the effectiveness of different intervention strategies in mitigating epidemics (such as targeting core-ranging individuals with large families for vaccination). This work is already underway with results from these simulations showing that moderately infectious pathogens (e.g. influenza) starting in core-ranging adult females and juveniles with large families are likely to generate significantly larger outbreaks than infections starting in other individuals (J. Rushmore, unpublished data).
Our findings are limited by examining a single chimpanzee community, and we recognize the need for similar analyses at additional field sites to provide a more comprehensive framework for designing disease management plans. Notably, the association data necessary for network analyses are likely available in long-term data bases for many habituated wild ape communities. We encourage additional researchers to analyse such association data with a focus on potential pathogen transmission routes. In conclusion, our findings demonstrate temporal and interindividual variation in association patterns for a wild chimpanzee community and highlight how such behavioural variation could be incorporated into the development of disease management strategies for an endangered wildlife population.