Natural simian immunodeficiency virus transmission in mandrills: A family affair?

Understanding how pathogens spread and persist in the ecosystem is critical for deciphering the epidemiology of diseases of significance for global health and the fundamental mechanisms involved in the evolution of virulence and host resistance. Combining long-term behavioural and epidemiological data collected in a naturally infected mandrill population and a Bayesian framework, the present study investigated unknown aspects of the eco-epidemiology of simian immunodeficiency virus (SIV), the recent ancestor of HIV. Results show that, in contrast to what is expected from aggressive and sexual transmission (i.e. the two commonly accepted transmission modes for SIV), cases of SIVmnd-1 subtype were significantly correlated among related individuals (greater than 30% of the observed cases). Challenging the traditional view of SIV, this finding suggests the inheritance of genetic determinants of susceptibility to SIV and/or a role for behavioural interactions among maternal kin affecting the transmission of the virus, which would highlight the underappreciated role of sociality in the spread of infectious diseases. Outcomes of this study also provide novel insights into the role of host social structure in the evolution of pathogens. © 2012 The Royal Society.

Mandrills are NHPs endemic of the dense rain forests of the Congo Basin (southern Cameroon, Gabon, Equatorial Guinea and northern Congo). Mandrills are long-lived (more than 20–25 years life expectancy), and live in hordes of extreme sizes (up to 1000 individuals) that are highly structured both socially and spatially [21]. Females and dependent offspring (representing greater than 95 per cent of the group) are cohesive throughout the year, whereas sub-adult (more than 6 years of age) and adult (more than 9 years of age) males live alone and only join the groups seasonally when females are in oestrous [21]. Therein, they represent a valuable model to investigate both long-term host–parasite interactions and the processes of pathogen transmission and persistence in complex social structures. Owing to the difficulty in studing this elusive species in the wild [21], most of the current knowledge concerning mandrill biology is derived from the semi-free-ranging population housed at the International Centre for Medical Research of Franceville, Gabon (CIRMF), the largest captive mandrill colony in the world with approximately 200 individuals at present. This colony was initially created in 1983 after the release of 15 unrelated, wild-born individuals (eight females and seven males) into a 6.5 ha rainforest enclosure (E1) [22]. The long-term monitoring programme for this colony [22–27], based on ad libitum observations of individuals and annual captures for veterinary examination, has provided information about individual life history, pedigree, medical history and SIV serological status of each animal. In this colony, sexual maturity is reached at 3–4 years of age in females and at 4–5 years of age in adolescent males. Males begin to develop secondary sexual adornments at 6–7 years of age [24,28] but do not attain social maturity or mate until they reach adulthood at more than 9 years old [23]. Using their especially long canines as weapons [29], adult males compete fiercely with each other, and only a few dominant individuals gain access to fertile females [30]. In 1994, a second semi-free-ranging group was established in another enclosure (E2, 3.5 ha) to maintain a pool of SIV-free mandrills in E1. Four matrilines (a total of 17 mandrills), in which at least one individual was SIV-infected, were transferred from E1 to E2. Since then, individuals testing SIV-positive from E1 during the annual serological screening have been transferred into E2 to keep E1 SIV-free. Following incidents in which adult males crossed the fence out of or into E2 in search of mates in the neighbouring enclosure in 2005, new infections were detected in E1. These voluntary intrusions and transfers of adult males from one enclosure to another are reminiscent of the natural patterns of seasonal male immigration into social groups during breeding periods [21]. Our aim was to decipher the major SIV transmission routes and spread patterns using data collected from colony records between 1983 and 2009. We focused on individuals within enclosure E1 prior to 1994 and on those transferred into enclosure E2 after 1994, as E1 was kept SIV-free from 1994 onwards. The occurrence of physical injuries inflected though bites during aggressive encounters—susceptible to facilitate SIV transmission—were recorded through daily observations of the colony. In order to provide a good approximation of how aggressiveness is affected by age in both genders, biting frequencies were calculated as the total number of bite wounds recorded for a given gender and age divided by the total number of individuals of that gender and age observed in the study population between 1983 and 2009. This parameter, however, probably underestimates the actual occurrence of biting events because it is impossible to detect all bite wounds (e.g. superficial wounds or wounds where animals disappeared following deathly fights). The pedigree of the colony was determined as previously described [31]. Maternity was routinely allocated from maternal behaviour during the first six months of life and paternity from genetic analyses using human microsatellite loci. Age- and gender-dependent reproductive success was estimated by the mean number of offspring produced per individual for a given age and gender. In males, this rate was used as an approximation of the age and gender-dependent frequency of mating. As for aggressiveness, this rate reflects how sexual behaviour is affected by age in both genders, while it underestimates the real frequency of mating because: (i) each mating event does not necessarily result into the production of an offspring; and (ii) paternity could not be determined for all individuals (in particular, for those born after 2002). Wild mandrills are naturally infected with two SIV subtypes, SIVmnd-1 and SIVmnd-2. Mandrill serum samples were initially tested for SIV using either commercial kits detecting anti-HIV antibodies [25,26], or a peptide-based enzyme immunoassay [27,32], which yielded consistent results [32,33]. Knowing that SIVmnd-1 and SIVmnd-2 subtypes existed within the CIRMF mandrill population, genetic analysis to discriminate the subtypes was also performed [27]. After 1999, when SIVmnd-2 was no longer detected, commercial kits (Determine, Abbot, Rungis, France) were routinely used and new cases were confirmed using Western blotting. Family trees were created based on maternal kinship, and the distribution of SIVmnd-1 cases within matrilines was analysed. Relationships between cases were assessed by an index measuring the familial links between all possible pairs of infected and infecting individuals within the study population. Family links between two individuals were considered to equal 0.5, 0.25, 0.125, etc., at the first, second, third, etc., order within maternal kin. For all infected individuals (I), we considered the set of potentially infecting individuals (i.e. individuals who were infectious the year before the observed infection of individual I). We calculated the statistic s as the sum of the family links between all possible pairs of infected individuals and their potentially infecting counterparts. The distribution of the s statistic under the H0 hypothesis, which contends that maternal kinship does not affect the frequency of SIVmnd-1 transmission, was estimated by randomly permuting the new infections observed each year while keeping the set of already infected individuals non-permuted. We designed an age- and gender-structured discrete-time stochastic model to analyse SIVmnd-1 transmission in E2. Different transmission modes were considered. Transmission modes were differentiated by the gender of the infecting and infected animals along with the age distribution of the animals that were able to infect others or were susceptible to infection. The respective effect of each transmission mode was quantified using a Bayesian framework. We constructed a mathematical model to express how infected individuals affect the probability of infection in susceptible individuals depending on their respective age and sex: The term pk(t) represents the probability that individual k becomes infected between t − 1 and t if it is susceptible at t − 1, and λk(t − 1) represents the infection rate of individual k, which depends on both its individual characteristics (gender and age) and the state of the population (number, gender and age of infected individuals at time t − 1). We modelled the three transmission routes by dividing the infection rate into three terms: The term represents the aggressive route and describes SIVmnd-1 transmission through saliva and/or blood during aggressive interactions between individuals of the same gender: The term G(k) represents the gender (M or F) of individual k, a(k,t) represents its age at time t, Ω(t,G) represents the set of observed infected individuals of gender G at time t, and βA,G represents the SIVmnd-1 infection rate associated with the biting route of transmission in gender G. BG(a) is the age (a)- and gender (G)-dependent rate of biting injuries. In the absence of data on ‘who is doing the biting’, we assumed that the age-dependent frequencies of doing the biting and being bitten were the same. Age-dependent biting rates were parametrized using biting data (described in §2b). We considered a logistic function to model how biting increases with age: and The term represents the sexual route of transmission and describes the SIVmnd-1 infection of one individual through sexual contact with infected individuals from the other gender. We chose a proportionate mixing law in which females have a constant number of sexual contacts regardless of the number of males in the population. We called rG(a) the rate at which gender G has sexual contacts, leading to: The term is the opposite gender and Ψ(t,G) is the set of individuals from gender G in the study population at time t, regardless of their serological status. We made rF = 1 if a ≥ 3 years old and rF = 0 if a < 3 years old. For rM, we assumed that the frequency of mating in males was a Gaussian function: βS,G represents the SIVmnd-1 infection rate associated with the aggressive route of transmission in gender G. Parameters and were derived from paternity data by estimating how the frequency of reproduction is affected by age. The term represents the familial transmission route and describes the transmission of SIVmnd-1 from one infected female (F) to a related individual of any gender. The rate at which transmission occurs is directly proportional to the familial link (FL) between the two individuals: The term βF,G represents the SIVmnd-1 infection rate associated with the familial route of transmission in gender G. Because we had access to quasi-exhaustive data on the SIVmnd-1 status of each individual, the likelihood of each transmission route could be calculated independently for males and females. As a result, parameters associated with males (βA,M, βS,M, βF,M) and females (βA,F, βS,F, βF,F) could be estimated independently. The most intuitive way to compare the different transmission routes in gender G was to compare their associated rates of transmission (βA,G, βS,G, βF,G). However, direct comparisons were not possible because of the different choices made for the incidence function of the different transmission modes. Interpreting the ratio between the two coefficients could only be performed with a fixed male population size, which was not the case in this study. Instead, we calculated the total rates at which an individual from gender G should have been infected through the different routes (sexual, aggressive and familial): and Then, we defined the following quantities: and The term ΛT,G represents the total force of infection suffered by gender G and , and quantify the respective contributions of the aggressive, sexual and familial routes of transmission to the force of infection. = 0 infers that route R is absent in gender G, and = 1 infers that it is the only route of transmission. The likelihood of any model is the product of the probability of the individual histories and written as a function of the transmission parameters (ΛA,G, ΛS,G and ΛF,G). Posterior distributions of ΛA,G, ΛS,G and ΛF,G were obtained from Monte Carlo sampling as follows. Parameters associated with aggressive and reproductive (only for males) interactions (ρM, μM, ρF, μF, and ) are treated as nuisance parameters. Prior values for these parameters are chosen based on biting and mating data (figure 1c–e) and using Gaussian sampling centred on the maximum-likelihood estimation and using the variance–covariance matrix of the parameter estimators derived from the Hessian matrix. Then, these are fixed while ΛA,G, ΛS,G and ΛF,G are estimated by Markov chain Monte Carlo (using a Metropolis–Hastings algorithm). This effectively cuts the feedback in the model: behavioural parameters (i.e. associated with aggressive and reproductive interactions) are evaluated from independent data and considered as a constraint to determine the different transmission routes to explain data. This means that behavioural parameters are thus not re-evaluated from epidemic data. Using this process, the relative weights of transmission routes are estimated based on the consistency between behavioural and epidemic data. The operation was repeated 10 000 times to obtain 10 000 independent realizations of the posterior distribution of ΛA,G, ΛS,G and ΛF,G. For ΛA,G, ΛS,G and ΛF,G priors were chosen as independent truncated (negative values were removed) normal distributions of mean zero and a variance common for the three parameters. In practice, the variance was chosen to be very large so that the priors were non-informative. Factors affecting reproduction and aggressiveness within the CIRMF semi-free-ranging mandrill population. (a) Changes in male (blue line) and female (red line) population size across the study period. (b) Annual individual offspring production in females. (c) Annual individual offspring production in males. (d) Effect of age on biting frequency in females (dark red, severe; light red, minor). (e) Effect of age on biting frequency in males (dark blue, severe; light blue, minor). (f) Changes in the number of bites recorded in males during the study period (dark blue, severe; light blue, minor). Data presented are for the E2 enclosure only after 1994. Posterior distributions of were simply derived from the formula

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