Contact patterns as a risk factor for bovine tuberculosis infection in a free-living adult brushtail possum Trichosurus vulpecula population

Combining network analysis with epidemiological data to inform risk-based surveillance: Application to hepatitis E virus (HEV) in pigs

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A method is proposed to explore the role of pig movements on pathogen epidemiology.

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Pig farm centrality in the network is associated with higher HEV seroprevalence.

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Some local areas are more at risk for HEV due to incoming pig movements.

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Animal movements should be included in risk-based surveillance strategies.

Animal movements between farms are a major route of pathogen spread in the pig production sector. This study aimed to pair network analysis and epidemiological data in order to evaluate the impact of animal movements on pathogen prevalence in farms and assess the risk of local areas being exposed to diseases due to incoming movements. Our methodology was applied to hepatitis E virus (HEV), an emerging foodborne zoonotic agent of concern that is highly prevalent in pig farms. Firstly, the pig movement network in France (data recorded in 2013) and the results of a nation-wide seroprevalence study (data collected in 178 farms in 2009) were modelled and analysed. The link between network centrality measures of farms and HEV seroprevalence levels was explored using a generalised linear model. The in-degree and ingoing closeness of farms were found to be statistically associated with high HEV within-farm seroprevalence (p < 0.05). Secondly, the risk of a French département (i.e. French local administrative areas) being exposed to HEV was calculated by combining the distribution of farm-level HEV prevalence in source départements with the number of movements coming from those same départements. By doing so, the risk of exposure for départements was mapped, highlighting differences between geographical patterns of HEV prevalence and the risk of exposure to HEV. These results suggest that not only highly prevalent areas but also those having at-risk movements from infected areas should be monitored. Pathogen management and surveillance options in the pig production sector should therefore take animal movements into consideration, paving the way for the development of targeted and risk-based disease surveillance strategies.

Mycobacterium bovis hosted by free-living-amoebae permits their long-term persistence survival outside of host mammalian cells and remain capable of transmitting disease to mice

Bovine tuberculosis (TB) is a zoonotic disease caused by Mycobacterium bovis. Despite intensive TB control campaigns, there are sporadic outbreaks of bovine TB in regions declared TB free. It is unclear how M. bovis is able to survive in the environment for long periods of time. We hypothesized that Free-living amoebae (FLA), as ubiquitous inhabitants of soil and water, may act as long-term reservoirs of M. bovis in the environment. In our model, M. bovis would be taken up by amoebal trophozoites, which are the actively feeding, replicating and mobile form of FLA. Upon exposure to hostile environmental conditions, infected FLA will encyst and provide an intracellular niche allowing their M. bovis cargo to persist for extended periods of time. Here, we show that five FLA species (Acanthamoeba polyphaga, Acanthamoeba castellanii, Acanthamoeba lenticulata, Vermamoeba vermiformis and Dictyostellium discoideum) are permissive to M. bovis infection and that the M. bovis bacilli may survive within the cysts of four of these species for over 60 days. We further show that exposure of M. bovis-infected trophozoites and cysts to Balb/c mice leads to pulmonary TB. This work describes for the first time that FLA carrying M. bovis can transmit TB.

Disease transmission in animal transfer networks

Infectious diseases transmission is strongly determined by who contacts whom. Bovine tuberculosis (bTB) caused by Mycobacterium bovis is a worldwide burden for animal populations. One of the major transmission mechanism between herd is the transfer of infectious animal. In East Africa, pastoralists may receive or bestow livestock to create and strengthen social relationships. Here, we used a network approach to examine the relative importance of such cattle transfer in the transmission of bTB. First, a total of 2550 cattle from 102 herds were tested using the comparative intradermal tuberculin test to assess the presence of bTB infected cattle in the herd. A herd was considered bTB positive if it had at least one tuberculin reactor animal. Next, we calculated the centrality of each herd in the cattle transfer network using four established measures of social network centralization: degree, betweenness, closeness and fragmentation. The relationships between the network centrality measures and bTB infection were examined using generalized linear mixed models (GLMM). We found that a herd's in-degree in the social network was positively correlated with the risk of being infected with bTB (b=4.2, 95%CI=2.1-5.7; p<0.001). A herd that was close to many others (i.e., had a higher closeness index) had a larger chance of acquiring bTB infection (b=2.1, 95%CI=1.4-2.8; p<0.001). Betweenness centrality was also positively associated with the presence of bTB infection. There was a negative relationship between the fragmentation index and bTB infection (b=-2.7, 95%CI=-4.9-1.3; p<0.001). The study clearly demonstrated that the extent to which a herd is connected within a network has significant implications for its probability of being infected. Further, the results are in accordance with our expectation that connectivity and the probability that a herd will transmit the disease to other herds in the network are related.

Contact rates of wild-living and domestic dog populations in Australia: a new approach

Dogs (Canis familiaris) can transmit pathogens to other domestic animals, humans and wildlife. Both domestic and wild-living dogs are ubiquitous within mainland Australian landscapes, but their interactions are mostly unquantified. Consequently, the probability of pathogen transfer among wild-living and domestic dogs is unknown. To address this knowledge deficit, we established 65 camera trap stations, deployed for 26,151 camera trap nights, to quantify domestic and wild-living dog activity during 2 years across eight sites in north-east New South Wales, Australia. Wild-living dogs were detected on camera traps at all sites, and domestic dogs recorded at all but one. No contacts between domestic and wild-living dogs were recorded, and limited temporal overlap in activity was observed (32 %); domestic dogs were predominantly active during the day and wild-living dogs mainly during the night. Contact rates between wild-living and between domestic dogs, respectively, varied between sites and over time (range 0.003-0.56 contacts per camera trap night). Contact among wild-living dogs occurred mainly within social groupings, and peaked when young were present. However, pup emergence occurred throughout the year within and between sites and consequently, no overall annual cycle in contact rates could be established. Due to infrequent interactions between domestic and wild-living dogs, there are likely limited opportunities for pathogen transmission that require direct contact. In contrast, extensive spatial overlap of wild and domestic dogs could facilitate the spread of pathogens that do not require direct contact, some of which may be important zoonoses.

Brown spider monkeys (Ateles hybridus): a model for differentiating the role of social networks and physical contact on parasite transmission dynamics

Elevated risk of disease transmission is considered a major cost of sociality, although empirical evidence supporting this idea remains scant. Variation in spatial cohesion and the occurrence of social interactions may have profound implications for patterns of interindividual parasite transmission. We used a social network approach to shed light on the importance of different aspects of group-living (i.e. within-group associations versus physical contact) on patterns of parasitism in a neotropical primate, the brown spider monkey (Ateles hybridus), which exhibits a high degree of fission-fusion subgrouping. We used daily subgroup composition records to create a 'proximity' network, and built a separate 'contact' network using social interactions involving physical contact. In the proximity network, connectivity between individuals was homogeneous, whereas the contact network highlighted high between-individual variation in the extent to which animals had physical contact with others, which correlated with an individual's age and sex. The gastrointestinal parasite species richness of highly connected individuals was greater than that of less connected individuals in the contact network, but not in the proximity network. Our findings suggest that among brown spider monkeys, physical contact impacts the spread of several common parasites and supports the idea that pathogen transmission is one cost associated with social contact.

Assessing Movements of Brushtail Possums (Trichosurus vulpecula) in Relation to Depopulated Buffer Zones for the Management of Wildlife Tuberculosis in New Zealand

In New Zealand, managing the threat of bovine tuberculosis (TB) to livestock includes population reduction of potentially infectious wildlife, primarily the brushtail possum (Trichosurus vulpecula). Population control is often targeted on forested buffer zones adjacent to farmland, in order to limit movements of possums across the buffer and reduce the risk of disease transmission to livestock. To assess the effectiveness of buffers in protecting livestock we analysed GPS telemetry data from possums located in untreated forest adjacent to buffers, and used these data to characterise patterns of movement that could lead to possums reaching farmland during the season when most dispersal occurs. Analyses of movement data showed that the direction of dispersal by sub-adult and adult possums and the extent of long exploratory movements were not biased toward forest buffers, even though these provided vacant habitat as suitable for possums as untreated forest. Instead, dispersal and exploratory movements were uncommon even for sub-adult possums and such events typically lasted <10 days. Dispersing possums settled predominantly in river valleys. A simulation model was developed for the 3-6-month dispersal season; it demonstrated a probability of <0.001 that an infected possum, originating from a low-density population with low disease prevalence in untreated forest, would move across 3 km of recently controlled forest buffer to reach farmland. Our results indicate short-term reduction in the risk of TB transmission from possums to livestock in New Zealand by the use of depopulated buffer zones, while acknowledging that the threat of disease spread from untreated forest is likely to increase over time as possum population density and, potentially, TB prevalence among those possums, increase in the buffer zone.

Spatial analyses of wildlife contact networks

Datasets from which wildlife contact networks of epidemiological importance can be inferred are becoming increasingly common. A largely unexplored facet of these data is finding evidence of spatial constraints on who has contact with whom, despite theoretical epidemiologists having long realized spatial constraints can play a critical role in infectious disease dynamics. A graph dissimilarity measure is proposed to quantify how close an observed contact network is to being purely spatial whereby its edges are completely determined by the spatial arrangement of its nodes. Statistical techniques are also used to fit a series of mechanistic models for contact rates between individuals to the binary edge data representing presence or absence of observed contact. These are the basis for a second measure that quantifies the extent to which contacts are being mediated by distance. We apply these methods to a set of 128 contact networks of field voles (Microtus agrestis) inferred from mark–recapture data collected over 7 years and from four sites. Large fluctuations in vole abundance allow us to demonstrate that the networks become increasingly similar to spatial proximity graphs as vole density increases. The average number of contacts, , was (i) positively correlated with vole density across the range of observed densities and (ii) for two of the four sites a saturating function of density. The implications for pathogen persistence in wildlife may be that persistence is relatively unaffected by fluctuations in host density because at low density is low but hosts move more freely, and at high density is high but transmission is hampered by local build-up of infected or recovered animals.

Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis)

Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in understanding transmission dynamics, even for environmentally transmitted microbes like E. coli. This study is the first to use microbial genetics to construct and analyse transmission networks in a wildlife population and highlights the potential utility of an approach integrating microbial genetics with network analysis.