Different routes may allow M. bovis transmission between wild and domestic hosts. The largest part of M. bovis shedding seems to occur through aerosols (respiratory tract secretions) and to a lesser extent through saliva, urine, feces (20, 22, 23), milk in cattle (24) and even wound exudates in badgers (20). Therefore close contacts (e.g., nose to nose) between infected individuals and susceptible ones can allow the transmission of M. bovis. However, several studies have shown that M. bovis may survive outside a host in a favorable environment for several months (24–26), allowing transmission through indirect contacts. M. bovis transmission between cattle can also involve different susceptible species either wild (27) or domestic [although the implication of other domestic species than cattle remains unclear regarding cattle transmission (24)]. At the herd level, several risk factors of bTB have been identified such as larger herd sizes, neighborhood with other herds, cattle movements, farm management practices such as grazing, dispersion of slurry on pastures or the share of water points (24, 28–31). Environmental risk factors have also been studied, with certain environmental conditions favoring the survival and persistence of M. bovis (such as shade, moisture or even some soil types) that foster M. bovis transmission (24–26). A third category of risk factors involves wildlife interactions, especially with badgers, wild boars and deer. For the latter two species, the sharing of feed or water on pastures appears to be a risk factor of M. bovis indirect transmission (23, 32, 33). The transmission between badgers and cattle seems a bit more complex, with uncertain direct contacts on pastures (34–36) and/or inside farm buildings (37). This interspecies transmission could occur on pastures through the shedding of the mycobacteria in urine and feces of infected badgers (24), and in respiratory tract secretions and feces of infected cattle (6, 29).

BTB molecular types are stable (38, 39) and can be used to trace independent epidemics (4). In France, while the officially bTB-free status was obtained in 2000, M. bovis infection has persisted in several regions. In 2014, 46% of incident outbreaks were detected in south-western France, with a national number of 105 cattle herds newly detected infected (40). Molecular typing methods spoligotyping (39) combined to MLVA (Multiple Loci Variable Number of Tandem Repeats, VNTR Analysis) based on MIRU-VNTR [Mycobacterial Interspersed Repetitive Unit– VNTR; (4, 38)] have allowed identifying 16 molecular types in this area between 2007 and 2015 from cattle isolates, two of which were shared between cattle and wildlife (4). Because spoligotype and MIRU-VNTR are considered stable markers (at least at a time horizon of several years), these 16 molecular types allow identifying 16 independent epidemics spreading in the same area during the same time period.

An effective way of representing the structure of contacts between hosts of an infectious disease consists in building networks (41), with epidemiological units as nodes, to which an infection status is associated. Edges linking nodes represent the contacts between epidemiological units that may allow the transmission of the disease agent. Regarding M. bovis transmission between cattle in France and in light of the above, nodes can represent cattle farms and edges may represent direct or indirect contacts between them. Two types of direct contacts may be featured by edges between farms: (i) contacts due to the trade of live cattle (42, 43) and (ii) contacts due to pasture neighborhood between cattle belonging to different farms but with nose to nose contacts over the fence (31, 44, 45). Besides, indirect contacts between cattle farms due the presence of wildlife may also be represented by edges. Concerning the badger, a known susceptible species to M. bovis infection (21, 40), the spatial organization of social groups with stable home ranges around setts (46, 47) allows us to represent indirect contacts with cattle based on the spatial intersection between farm pastures and home ranges (48).

The aim of our study was to analyze M. bovis transmission between cattle farms in a south-western area of France using contact networks and molecular types as infection status information. We built different networks featuring possible direct and indirect contacts between cattle farms and analyzed the association between their structure and the observed pattern of infected farms.

# MATERIALS AND METHODS

# Cattle Data

The study population was made up of the 1946 farms having reported cattle between January 2007 and March 2016 (end of the 2015 herd skin-testing period) and owning at least one pasture included in a 2,735 km² study area, an area straddling the border of Pyrénées-Atlantiques and Landes French departments (**Figure 1**). Pastures were defined as land parcels used by cattle for grazing according to the "Relevé Parcellaire Graphique" (RPG) of 2013 provided by the French Ministry of Agriculture. Two pastures were considered neighbors if the minimal distance between their borders was less than 3 m. Farm sizes (number of bovine females over two years old) and types (dairy, beef, fattening, mixed, small and other herds) were obtained from the French cattle tracing system ("Base de Données Nationale d'Identification" denoted below BDNI) (**Table 1**).

BTB surveillance data were provided by the French Ministry of Agriculture. Herd skin-testing was performed each year in the study area in communes (the smallest French administrative subdivision) where infected farms had been detected the previous year, as well as in the neighboring ones, using either single intradermal comparative tuberculin tests (SICTT) (in all dairy farms or in farms located in the communes with confirmed infected farms) or single intradermal tuberculin tests (SITT) (in all the other situations), both performed in

TABLE 1 | Description of cattle farms included in the study population.

\*, pastures included in the study area; \*\*, number of females of more than 2 years old; \*\*\*, at least once over the study period

the cervical region. In the other communes of the study area, herd testing was biennial in Landes department, and triennial in Pyrénées-Atlantiques department. M. bovis infection was confirmed by polymerase chain reaction (PCR) and/or bacterial culture (either following a positive skin test or the detection of a suspect lesion during routine meat inspection at a slaughterhouse) (40) in 69 cattle farms of the study area during the study period; all the cattle of these farms were subsequently slaughtered and molecular typing was performed on each bovid found infected (with a mean of four cattle per farm detected infected during the study period). Molecular typing results were provided by the National Reference Laboratory (NRL) (Anses, Maisons-Alfort). The combination of spoligotyping and MLVA based on MIRU-VNTR allowed identifying 16 distinct molecular types (**Table 2**). A unique molecular type was identified in all of the 69 detected infected farms, except two where several molecular types were identified.

A farm was classified infected by a given molecular type if this type had been detected at least once in the farm during the study period. Because of the geographic differences in the frequency of skin testing, having detected M. bovis earlier in a given farm than in another one does not imply that the former had been infected earlier than the latter. For this reason, the detection dates could not be taken into account.

# Badger Data

Two thousand four hundred and 25 badger setts were identified and geolocalised by hunters in the study area, between 2013 and 2015. Around those setts, considered as main setts (i.e., hosting a social group), we defined badger home ranges using a two-step procedure: (i) a Dirichlet tessellation was first built TABLE 2 | Number of cattle farms detected infected per molecular type during the study period and within the study area.

amolecular types found both in cattle and badgers.

bmolecular types found in the farm where six molecular types were identified.

cmolecular types found in the farm where two molecular types were identified.

d the same farm as in 2012 (recontamination).

around all setts [in which the perpendicular bisectors of each segment between two adjacent setts delineate the home range around one given sett, thus assuming that boundaries were located halfway between neighboring main setts (47)] and (ii) to avoid unrealistically home range large sizes, a home range was defined as the intersection of a tile with a 1,000 m-radius buffer area drawn around the setts (48). Two setts were considered neighbors if the corresponding home ranges were adjacent. A sett and a farm were considered neighbors if one of the farm pastures intersected with the badger home range.

BTB surveillance data were provided by the French Ministry of Agriculture. In the study area, bTB surveillance in badgers was performed according to the "Sylvatub" surveillance network, which started in 2012 in the study area (49). Surveillance protocol included badger trapping (i) within a 1.5 km-radius around confirmed infected farms, (ii) within a 2 km radius around setts with confirmed infected badgers and (iii) in communes at less than 5 km of communes where confirmed infected farms were located (one badger per sett). Trapping was performed using stopped restraints (https://www.plateforme-esa. fr/filedepot\_download/35377/100) and snares were checked the morning after the day they were set up within the 2 h following sunrise, in order to limit the stress of trapped badgers. Trapped badgers were culled by head shot except in a minority of cases where they were found already dead (due to trap related injuries that sometimes occurred when snares were placed on sloping terrain, with no possible alternative). Road-killed badgers were also considered. Stopped restraints used for trapping were placed near sett entrances, those setts being considered as the sett of the trapped animals. Where badgers were found dead along roads, hunters reported the most probable sett according to their knowledge of the area (48). All the trapped and roadkilled badgers were tested for M. bovis infection. Among 401 analyzed badgers (4.5% were road-killed badgers), 11.2% were detected infected (45 animals, one was a road-killed badger), of which 39 harbored the SB0821 molecular type and 6 the SB0832 molecular type, both molecular types having also been found in cattle (**Table 2**). All the badgers trapped could be attributed to 113 distinct setts, of which 33.6% hosted at least one infected badger (32 setts with at least one badger detected infected by SB0821 and 6 by SB0832). Road-killed badgers were attributed to five distinct setts. For four of these setts, the analysis of road-killed badgers did not provide additional information as they had also been subjected to trapping measures. For the fifth sett, the analysis of one road-killed badger allowed the detection of infection (SB0821 molecular type), not revealed by trapping. Setts with at least two badgers tested negative were considered as uninfected (n = 75). All the remaining setts, either with only one badger tested negative or without analyzed badger were considered of unknown status.

# Contact Network

A contact network was built using farms of the study population as nodes, and four types of edges (**Figure 2**):

To avoid duplicated edges, the types of edges (T, P, B and D) were aggregated at the edge level. The full contact network thus contained only unique edges labeled by one or several edge types (**Table 3**). Because the T-edges are directed, each undirected P-, B- and D-edge was transformed into two symmetric directed edges. The full contact network was thus a directed network.

Subnetworks were extracted from the full contact network by restricting the edges to those of specific types (**Table 3**). These subnetworks are termed below T-network, P-network, B-network and D-network. Similarly, we used edge types to split the full contact network in three non-overlapping subnetworks:

# Statistical Analysis

Each of the 16 molecular types of M. bovis identified in the study area was considered as a marker of an independent epidemic. For a given molecular type, the contact network may be considered as supporting M. bovis transmission between two farms only if a path exists in the network between these farms. The transmission tree rooted on a detected infected farm should then be entirely located in a single component of the network. The contact network may then be considered as supporting the spread of a given molecular type if most of the farms infected by this molecular type are located in the same component of the contact network. We thus first computed, for each molecular type identified in more than one farm, the number of components in which these infected farms were located (50). For the same subset of molecular types, we also computed, for each infected farm, the length of the shortest path to another farm where the same molecular type was detected.

To evaluate whether the observed pattern of bTB infected farms may have resulted from transmission processes in the contact network, we used the k-test proposed by VanderWaal et al. (51). This permutation-based test is based upon the calculation of the k-statistic: the mean number of infected cases among the neighbors of an infected node (the approach is easily extended to neighborhoods of order >1). The observed value of this statistic is then compared to the distribution of the same statistic obtained by randomly reallocating the location of cases, thus simulating a possible pattern of cases under the null hypothesis of an absence of association between bTB case location and network structure. The empirical p-value of the k-test is then the proportion of permutations for which the k-statistic is greater than the observed one. We adapted this test to a multi-type epidemic by redefining the k-statistic as the mean number of cases among the neighbors of a node, which were infected by the same molecular type as that node.

TABLE 3 | Label of edges in the different networks of contacts between cattle farms in the study area..

T, trade edge type; P, pasture neighborhood edge type; B, simple badger-mediated edge type; D, second level badger-mediated edge type; edge labels with several letters correspond to combinations of edge types; gray cells indicate the presence of the label within the network.

The k-test was first performed on the full contact network. It was then applied on the cattle-specific, badger-specific and mixed subnetworks; and this, for two groups of molecular types: those observed in cattle only and those observed in cattle and in badgers. Seven tests were thus performed and the Bonferroni correction was applied. Ten thousand permutations were used to compute the empirical p-value.

To further analyse the association between edge types and bTB occurrence, we focused on edges originating from infected farms. A binary status was assigned to each of these edges, with a value of 1 when the destination node was infected by the same molecular type as the originating node, and 0 otherwise. The association between this status and the edge type was then assessed using a case-control design: cases were edges having a status of 1, and controls the edges having the status 0. Four binary explicative variables were defined, based on the types labeling the edge: T, P, B, and D. In addition, we took into account the size (number of bovine females over the age of 2 years) of the edge originating and destination farms, herd size being a well-known risk factor for bTB detection in cattle farms (24). We thus modeled the probability for an edge starting from a detected infected farm to end at a farm detected infected by the same molecular type, using a logistic regression model including six independent variables: four binary variables (presence/absence of the T, P, B and D edge type) and two quantitative variables (sizes of the originating and destination farms). We checked the absence of multicollinearity using variance inflation factors (VIF) with a threshold of 10 (52). Odds ratios (OR) and their associated 95% confidence intervals were computed. Finally, attributable risk fractions (AF) were computed for each edge type.

The definition of badger-mediated edges was based upon the neighborhood between pastures and one (B-edges) or two (Dedges) badger home ranges. For some of the corresponding setts, the trapping results allowed defining an infection status: setts were considered as (i) infected when at least one trapped badger had been found infected with an identified molecular type and (ii) uninfected when at least two trapped badgers had been tested negative and no occupant badger had been found infected [for more details, see (48)]. Based on these data, we finally used a Fisher exact test to analyze the association between the status of B- or/and D-edges and the infection status of the corresponding setts.

Dirichlet tessellations were computed using the deldir package (53) and buffers using the sp package (54). Network analyses were carried out using the igraph package (55) and variance inflation factors were computed using the car package (56). Attributable risk fractions were finally computed using the AF package (57). All those cited packages were used in R 3.3.2 (58).

# RESULTS

Within the full contact network, the most frequent edge type was the combination of B- and D-edges, followed by single D-, T-, and B-edges. The P-edge type was less frequent alone than in combination with the other types (**Figure 3**).

The largest weak component of the full contact network incorporated 99.8% of the study population. Regarding the four edge-type-specific networks, the proportion of nodes included in the largest component was higher in trade and badger related networks (94.4% for the T-network, 94.7% for the B-network and 93.6% for the D-network) than in the pasture network (50.4%) (**Table 4**) (a more detailed analysis of networks topology is given in Supplementary Tables 2–4 and Supplementary Figures 1, 2).

For each of the 16 molecular types, the farms where the type had been observed were always located in the same component of

TABLE 4 | Description of the full contact network and of the four edge-type specific networks.

are in light gray and combinations of several types are in gray).

TABLE 5 | Distribution of detected infected farms in the components of the full contact network and in the four edge-type-specific networks for the molecular types identified in more than one farm.

\*, molecular types found both in badgers and cattle; see Table 2 for more details.

the full contact network. This was also the case for the B-network, but not for the T-, P-, and D- networks (**Table 5**).

Four molecular types were observed in at least two detected infected farms (**Table 2**). For 87% of these farms, the path to the closest farm detected infected by the same molecular type was made of a single edge. It included one intermediary cattle farm in 11% of cases (**Figure 4** and Supplementary Table 2). This result suggests a prominence of M. bovis transmission between an infected farm and its direct neighbors in the full contact network.

We computed the proportion of shortest paths made of a single edge between farms infected (i) by molecular types found only in cattle and (ii) by molecular types found both in badgers and cattle. The difference between these two proportions was not significant (Fisher exact test: p = 0.13).

Using k-tests, a significant association was observed between the pattern of bTB detected infected farms and the structure of the full contact network (observed k-statistic: 2.3; distribution obtained by randomly reallocating the location of cases: mean = 0.39, SD = 0.12; p < 7.14∗ 10−3 , threshold after Bonferroni correction) (**Figure 5**). No significant association was observed for the cattle-specific network, neither for the molecular types observed in cattle only, nor for those found both in cattle and badgers. Conversely, a significant association was observed between the pattern of farms detected infected by molecular types shared between badgers and cattle and the structure of the badger-specific network (p < 7.14∗ 10−3 ). Finally, the structure of the mixed network was significantly associated with the pattern of bTB-infected farms for both groups of molecular types (p = 0.006 and p < 7.14∗ 10−3 respectively) (**Table 6**).

The four edge types were included in the logistic regression model as no significant multicollinearity was detected. T-, B-, and D-edge types were significantly associated to the probability of being a case with an OR of 7.13 for the T-edge type (95% CI: [3.39–15.06]), 1.89 for the B-edge type (95% CI: [1.32–2.76]) and 10.44 for the D-edge type (95% IC: [4.38–26.66]). The size of the destination farm of the edge was also significantly associated to the probability of being a case. Regarding edge types, attributable risk fractions were 84% for the D edge type, 32% for the B edge type, and 12% for the T edge type (**Table 7**).

Among edges representing badger-mediated transmission (i.e., B- and D-edges), the infection status of badger setts involved (one sett regarding B-edges and at least one of the two setts regarding D-edges) was known for 264 edges (5%) originating from a farm infected by one of the two molecular types shared between badgers and cattle. Among them, 44 were case edges (i.e., the destination farm had also been found infected by the same molecular type) of which 38 (86%) were supported by positive badger setts; and 220 were control edges of which 102 were supported by positive badger setts (46%). These differences were significant (Fisher exact test: p < 0.0001) with an associated OR of 7.3 [95% CI: (2.9–21.9)].

# DISCUSSION

The objective of this study was to provide a better understanding of M. bovis transmission mechanisms between cattle farms in south-western France using networks which represented the direct and indirect contacts that may allow M. bovis transmission among farms of this area between 2007 and 2015.

Four types of edges were represented because of their potential involvement in M. bovis transmission between cattle farms and we assumed that they represented the main transmission mechanisms in the study area. Cattle movements due to trade are a known M. bovis transmission route in Great Britain (59, 60), but also in France (42). The neighborhood with an infected farm

through adjoining pastures (allowing over the fence contacts between herds) has also been identified as a potential risk factor for the M. bovis transmission between French cattle farms (31). The intersection of badger home ranges with cattle pastures and between each other's was considered a proxy for badgermediated transmission, considering the territoriality of badgers (36) and the ability of M. bovis to survive in the soil (25, 26). BTB surveillance measures in badgers were not homogeneous among setts of the study area, as they were dependent on bTB detection in the cattle farms in their vicinity. For this reason, although the location of setts was known, we did not model badger setts as nodes in the contact network (we would have been unable to attribute an infection status to each of them). Instead of that, sett location data were used to represent badger-mediated contacts between farms by specific edges, based on neighboring badger home ranges. Two types of badger-mediated contacts were thus modeled by edges. B-edges represented a situation in which two farms neighbored the same badger home range: farm to farm M. bovis transmission through such edges thus only assumed cattle to badger and badger to cattle transmission. Conversely, D-edges represented a situation in which two farms neighbored two distinct but neighboring badger home ranges: farm to farm transmission through such edges thus also assumed badger to badger transmission in animals from neighboring setts. Because the epidemiological unit of this study was the farm, P-, B-, and D-edges were built based on the aggregation of pastures of each cattle farm. In the study area, cattle are often moved from one pasture to another one belonging to the same farm, TABLE 6 | Results of the k-tests for the cattle-specific, the badger-specific and for the mixed subnetworks of the full contact network, for the molecular types only found in cattle only and for those found both in badgers and cattle.

\*significant difference after Bonferroni correction (p < 7.14\*10−3 ); SD, standard deviation.

TABLE 7 | Logistic model of the probability of an edge starting from a detected infected cattle farm to join another detected infected cattle farm and with the same molecular type according to the type of edge.

OR, Odds ratio; CI, Confidence Interval; AF, Attributable Risk Fraction; SD, Standard Deviation.

(\*) Odds-ratio corresponding to an increase of ten animals.

e.g., when rotational grazing is used, we thus assumed that this simplification was meaningful.

The frequency of testing cattle was different in the different parts of the study area and this could have biased our results. However, testing was performed each year in communes where infected herds had been detected, and was also performed reactively in farms identified by contact tracing from these herds, based on cattle trade data and on pasture neighborhood. For these reasons, farms directly connected (in the full contact network) to a herd detected infected were considered having been submitted to similar testing regimens, both for B and D edge types (as in most cases the connected farms were located in the same commune), and for the T and P edge types (because of contact tracing). As only edges originating from herds detected infected were considered in the k-tests and in the logistic regression model, the corresponding results should not have been biased by geographic variations of the frequency of testing in the study area.

Taking into account the molecular types of isolates allowed considering 16 independent epidemics, of which 12 appeared restricted to a single farm, and 14 to less than 10 farms. All of these 14 molecular types affected only cattle. This predominance of molecular types found in a single cattle farm (75%) was in line with a previous study carried out in France between 1979 and 2000 in which a large majority of molecular types (84%) were found at a low frequency (less than 10 farms). This result has been interpreted as the sign of a poor spread of these strains (61), which could be traces of older epidemics that would have spread prior to 2007, but without significant transmission afterwards. Indeed, in our study, the 14 molecular types found in less than 10 farms were all detected not later than 2012 (**Table 2**).

Farms detected infected by a given molecular type were always located in the same large weak component of the full contact network that contained 99.8% of farms, whereas it was not the case for three of the edge-type-specific networks: the T-, P-, and D- networks. This indicated that, although the T-, P-, and D-edge-type-specific networks could not alone have supported the spread of bTB infection within the study area (contrary to the B-network), the strong connectivity resulting from the union of the four networks into the full contact network provided a structure that might enable the spread of the M. bovis infection in the study area. This result is in line with multifactorial mechanisms of bTB spread previously suggested by other studies (24, 29). As an example in Great Britain, dynamic modeling of cattle taking into account farm environment helped understanding M. bovis transmission routes (62). Prominent identified routes of M. bovis transmission were moving infected cattle between farms and reinfection from an environmental reservoir. The conclusion of this study was that control measures should simultaneously address several transmission routes to be effective.

Using k-tests, a significant association was observed between the pattern of bTB-infected farms and the structure of the full contact network. Moreover, the structures of the badgerspecific and mixed networks were significantly associated with the pattern of farms detected infected by molecular types shared between badgers and cattle. This result was expected and confirmed that badger-mediated edges could be viewed as paths for the interspecies M. bovis transmission. In addition, the structure of the mixed network was significantly associated with the pattern of bTB-infected farms for molecular types found only in cattle, whereas it was not the case for the cattle-specific network. We could assume that the spread of cattle molecular types would be more efficient when direct contact (trade and/or pasture neighborhood) are associated with indirect badger-mediated contacts. In addition, we should be cautious about the cattle specificity of these molecular types, as these molecular types may be (or have been) present in the badger population without being observed, because of the relatively low sensitivity of bTB surveillance in the badger population.

Considering edges originating from detected infected farms, we used a case-control design and a logistic model to analyse the relationship between the types of an edge and the detection of the same molecular type at the originating and destination farm of the edge (case edges) or at the originating farm only (control edges). Because the detection dates could not be considered in the study to infer dates of infection, the cooccurrence of the same molecular type at both ends of case edges does not model the transmission of M. bovis through the edge, although the edges of the full contact network represent possible transmission paths for the bacteria and case edges thus represent possible transmission events. The largest oddsratio was attributed to the D edge type, followed by the T edge type. This predominance of badger-mediated edges reflects the specific situation of the study area, where molecular types shared between badgers and cattle were predominant (84% of detected infected farms **Table 2**), and the predominant effect of the D edge type suggests a probable spread of M. bovis between badgers from neighboring setts, and not only between badgers and cattle. However, B and D edges were defined based on a geographic representation of home ranges, with a maximal distance of 1,000 m to the sett. This distance threshold, the Dirichlet tessellation used to model home ranges, and the fact that some setts may have been unoccupied, are three elements that may have led to an underestimation of home range size, and to an overestimation of the role of the D edge type.

The T edge type was also associated with a putative transmission of M. bovis (AF = 12%). This result is in agreement with a previous French study conducted at the national scale, according to which the population attributable risk fraction of bTB infection had been estimated at 12% [5–18%] for cattle trade (42), often allowing long distance bTB spread.

In a previous study conducted in France, pasture neighborhood was found significantly associated with the farm infection status (31). However, in the present study, the P edge type was not significantly associated with M. bovis transmission when using the case-control design. This may be first explained by the fact that some of farmers of the study area use rotational grazing, with some pastures left unoccupied for grass re-growth. Furthermore, P-edges were defined based on a direct neighborhood between pastures (<3 m). This short distance does not allow other opportunities of direct contacts between cattle, such as the wandering of livestock, to be represented.

The badger-specific edges (B and D edge types) were defined based on sett locations, one or two setts being associated to each. For some of these setts, an infection status could be determined based on bTB surveillance data. We showed that this infection status was significantly associated with the fact that the sett as well as the originating and the destination farms had all been found infected by isolates of the same molecular type (OR = 7.3; 95% CI:[2.9-21.9]). This result supports an actual badger-mediated transmission through these types of edges. Nevertheless, wild boars have also been found infected with M. bovis within the study area. Indeed, among 548 analyzed wild boars between 2011 and 2015, 15 (2.7%) were found infected. The corresponding molecular types found in these wild boars were the two molecular types shared between badgers and cattle. Therefore we cannot exclude the role of this wild species that we could not consider in this study because of a lack of field data that would have allowed its spatial organization (captured through radio tracking, for example) to be represented. Not considering wild boars in our analyses could have led to an over-estimate of the role of B and D edge types in M. bovis transmission between cattle farms.

Other indirect contacts through herd practices could also have contributed to the predominance of the D edge type. Indeed, this type of edge created links between farms without direct contacts at pasture but being in a kind of vicinity. As examples, the sharing of material or the loan of animals could create links between farms that may overlap the D edges. However, no data were available to investigate this assumption. Its confirmation or refutation would require supplementary investigation.

In conclusion, this study supports the multifactorial nature of M. bovis transmission between cattle farms within the Pyrénées-Atlantiques–Landes area, France from 2007 to 2015. The largest part of bTB spread seemed to be due to badgermediated contacts, however cattle trade played a significant role. Consequently, to be truly effective, control measures should not focus on a single type of contact but ought to act on the different mechanisms we raised.

# AUTHOR CONTRIBUTIONS

MB-Z, AC, and BD conceived and designed the study. MB-Z prepared the data for the analysis. MB-Z and BD performed the analysis. MB-Z wrote the manuscript. MB-Z, AC, and BD revised the manuscript. All the authors approved the submitted version of the manuscript.

# ACKNOWLEDGMENTS

The authors thank the French Ministry of Food, Agriculture and Forest, Directorate General for Food (DGAl) and by the University of Paris-Sud, which both funded MB-Z's PhD grant. The authors also warmly thank Pierre Jabert (DGAl), Christian Peboscq (Pyrénées-Atlantiques Departmental Federation of Hunters-FDC 64), and all the hunters of the Pyrénées-Atlantiques and Landes for the census of badger setts in the study area.

# REFERENCES

# SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fvets. 2018.00173/full#supplementary-material

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Bouchez-Zacria, Courcoul and Durand. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Baiting and Feeding Revisited: Modeling Factors Influencing Transmission of Tuberculosis Among Deer and to Cattle

#### Melinda K. Cosgrove1 \*, Daniel J. O'Brien1 and David S. L. Ramsey 2

*1 Wildlife Disease Laboratory, Michigan Department of Natural Resources, Lansing, MI, United States, 2 Department of Environment, Land, Water and Planning, Arthur Rylah Institute for Environmental Research, Heidelberg, VIC, Australia*

Although tuberculosis caused by *Mycobacterium bovis* (bTB) is endemic in white-tailed deer (*Odocoileus virginianus*) in northeastern Michigan, USA, baiting and feeding of deer continue despite a regulatory ban. Previous modeling suggests aggregation at bait sites slows the rates at which harvest and/or vaccination decrease bTB prevalence, prolongs time to eradication, and increases the likelihood that once eradicated, bTB will re-establish following an incursion. However, the extent to which specific factors such as food density, attractiveness to deer, and persistence on the landscape influence bTB transmission is unknown. We used an individual-based, spatially-explicit stochastic simulation model of bTB in deer and cattle to investigate effects of feed density, attractiveness, and spatial and temporal persistence on bTB prevalence in deer and the probability of breakdowns in adjacent cattle herds. Because hunter harvest remains key to controlling bTB in deer, and harvest rates are in long term decline, we modeled these feeding-associated factors at harvest rates prevailing both when the model was developed (2003–2007) and in 2018. Food placement at randomized locations vs. fixed sites had little effect on bTB prevalence in deer, whereas increasing the probability that deer move to food piles (attractiveness) had the greatest effect of factors studied on both prevalence and herd breakdowns. Reducing food pile density reduced prevalence, but decreased herd breakdowns only modestly. Consistent availability of food over longer periods of time, as would occur with supplemental winter feeding or persistent recreational feeding, increased both prevalence in deer and cattle herd breakdowns dramatically. Though perhaps implausible to the public, altering how bait and feed for deer are used can reduce cattle herd breakdowns. Baiting and feeding bans have contributed to declining bTB prevalence, but non-compliance and continued legal sales of feed impede eradication. Requiring hunters to move food piles is unlikely to mitigate effects on transmission and is not a useful management tool. Compared to baiting, winter supplemental feeding or extended recreational feeding is likely to magnify bTB transmission by prolonging temporal availability. Because attractiveness of feed is influenced both by type of feed and deer behavior, research to quantify factors influencing deer movement to food should be a priority.

Keywords: baiting, cattle, feeding, management, Odocoileus virginianus, simulation model, tuberculosis, white-tailed deer

#### Edited by:

*Julio Alvarez, VISAVET Health Surveillance Centre (UCM), Spain*

#### Reviewed by:

*Javier Hermoso-de-Mendoza, Universidad de Extremadura, Spain Javier Bezos, Complutense University of Madrid, Spain*

> \*Correspondence: *Melinda K. Cosgrove<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Veterinary Epidemiology and Economics, a section of the journal Frontiers in Veterinary Science*

Received: *27 June 2018* Accepted: *19 November 2018* Published: *04 December 2018*

#### Citation:

*Cosgrove MK, O'Brien DJ and Ramsey DSL (2018) Baiting and Feeding Revisited: Modeling Factors Influencing Transmission of Tuberculosis Among Deer and to Cattle. Front. Vet. Sci. 5:306. doi: 10.3389/fvets.2018.00306*

# INTRODUCTION

Infectious disease management in a wildlife reservoir is a contentious issue, especially when changes in human behavior are necessary. While there may be general agreement that control measures are warranted, the specific actions adopted are often controversial. The elimination of human-provided supplemental food for wildlife is of notable debate. Although the use of supplemental food for wildlife is recognized as a mechanism for both inter- and intra-species disease transmission (1–7), disagreements regarding the potential benefits vs. consequences related to this practice are still prevalent. Nonetheless, zoonotic diseases can have serious ecological and economic impacts (5, 8) and the disease management strategies chosen influence the magnitude of the impacts. Advocates for the use of supplement food as bait (an attractant during legal hunting seasons) argue that baiting is necessary to increase and maintain harvest for disease control, yet evidence for this is lacking (9, 10). However, the use of bait increases deer concentrations around these sites, increasing contact rates and so the potential for disease transmission. Supplemental food used in winter to (theoretically) aid survival can have similar consequences (5–7).

In Michigan, baiting and feeding of white-tailed deer (Odocoileus virginianus) is recognized as one of the biggest risks for transmission of tuberculosis caused by Mycobacterium bovis (bTB) (4, 8, 11, 12). In the wake of extensive logging and the decimation of deer populations by market hunting that occurred in the 1800s, large tracts of land were bought into private ownership and "hunt clubs" were established, both to conserve what deer remained and to provide populations for sport hunting and sustainable harvest. In the 1920's deer numbers in the northern Lower Peninsula of Michigan rose dramatically, in part due to lower harvest pressure on privately owned lands effectively maintained as refuges, and winter starvation became common (13, 14). In an attempt to reduce starvation, supplemental feeding became prevalent, yet starvation continued as the biological carrying capacity of the marginal habitat had been exceeded (13). During this same time, bTB reactor rates in cattle across the state were relatively high, reaching 20–30% in some counties (15, 16). Although Michigan was later successful in lowering bTB reactor rates in cattle and was eventually declared bTB free in 1979, contact between infected cattle and concentrated numbers of deer had been occurring for decades. Large scale supplemental feeding increased in the 1980's as competition increased between private land owners to attract deer to their property. It is hypothesized that spillover of bTB from cattle to deer occurred sometime during the 1950s to 1960s (17, 18), although deer were not recognized as a maintenance host until the 1990's (11). By that time bTB had become self-sustaining in the free-ranging deer herd and persists to the present day (11, 19).

Although bTB is endemic in deer in northeast Lower Michigan, winter feeding and baiting of deer continue despite a regulatory ban, albeit at lower levels than historically practiced. The sale of bait and feed remains legal and widespread, even where its use is banned (8). The current economic value of these sales is thought to be substantial. In 1995, it was estimated that baiting and supplemental feeding generated \$15 million for Michigan farmers (20), and predictably, bans are typically opposed by farmers gaining from the sale of crops otherwise unmarketable for human consumption. This presents a persistent struggle to eradicate a contagious disease in the face of exacerbating practices. Previous modeling, using estimated levels of current baiting practices, suggests aggregation at bait sites slows the rates at which harvest and/or vaccination decrease bTB prevalence, prolongs time to eradication, and increases the likelihood that once eradicated, bTB will re-establish following an incursion (21). However, not well known are the extent to which specific factors such as feed site density, attractiveness to deer, and persistence on the landscape influence bTB transmission among deer and between deer and cattle.

Both direct and indirect interactions between livestock and wildlife have been well documented as a source of disease transmission (22–26). Increased bTB reactor rates in livestock resulting from alterations in supplemental food use for deer could be associated as well. We used an existing spatially-explicit model of bTB in deer and cattle (27) to evaluate how altering supplemental food density, attractiveness, and temporal and spatial persistence impact bTB prevalence in deer and the rate of cattle herd breakdowns.

# MATERIALS AND METHODS

# Study Area

We conducted simulations over a 48 x 51 km land area in the northeastern Lower Peninsula of Michigan consisting mainly of Deer Management Unit (DMU) 452 [12, 27, **Figure 1**]. Deer Management Unit 452 includes parts of Alcona, Alpena, Montmorency, and Oscoda counties, is ∼148,018 ha (1,480 km2 ), and comprised of 93% privately-owned land and 7% public land (28, 29). Topography, habitat, and deer management practices are described elsewhere (12, 30, 31). Historically, this area has defined the core outbreak area for bTB in Michigan (8).

# The Model

We used an individual-based spatially-explicit stochastic simulation model of bTB in white-tailed deer and cattle for all simulations. The structure, parameters, testing, validation, and assumptions of the model are described at length elsewhere (12, 27, 31). We used two Geographic Information System (GIS) layers to distribute deer and cattle across the landscape and account for movements and spatial concomitance that facilitate bTB transmission among deer and from deer to cattle. We used a deer layer that quantifies winter habitat potential for deer (as a surrogate for biological carrying capacity) to spatially distribute deer throughout the landscape (12, 31–33). We added a second layer that incorporated cattle producer locations, pasture areas, and cattle densities for all farms within and directly adjacent to DMU 452 to approximate cattle distribution (27). The model was originally calibrated to closely approximate steady-state age and sex specific bTB prevalence matched to long-term bTB surveillance data for deer from 2003–2007 (12, 31) and cattle herd breakdown rates 2003–2012 (27). A cattle herd breakdown is defined as a herd having at least one bTB reactor in the herd during whole herd testing.

Because rates of hunter harvest have declined over the last two decades, primarily due to demographic factors (34), the model was recalibrated in 2018 to adjust bTB transmission rates to accommodate current harvest rates. Briefly, sex- and agespecific harvest rates for DMU 452 were estimated from MDNR deer hunter harvest survey data via the sex-age kill method (35). Using those harvest rates, simulations were run to calibrate the sex-specific transmission rate parameters (betas) so that the predicted sex-specific bTB prevalence closely approximated field prevalence rates recorded from 2012–2016.

in northeastern Lower Peninsula of Michigan, USA.

The baseline model simulates aggregation of deer around supplemental food sources by estimating the movement of a deer to the food source based on the location of the food source within its home range (12, 31). During each time step (2 months), each deer conducts a search of habitat cells within its home range. If a food pile is encountered, there is assumed to be a 0.2 probability of a change in the deer's current location to the food pile if it occurs at the center of its home range. That probability declines as a half normal function of the distance of the food pile from the home range center and was zero for food piles outside the home range. Food piles were randomly distributed across the landscape. Supplemental food was available from September to December, coinciding with deer hunting seasons in Michigan when bait is used.

In this study, we define supplemental food in two ways: (1) Baiting—the autumnal use of food to attract deer in an attempt to aid harvest; and (2) Feeding—the use of food for deer outside of legal hunting seasons (e.g., to facilitate wildlife viewing, or in an effort to aid winter survival). Our previous modeling suggests that aggregation of deer at food sites has a substantial effect on bTB transmission (12). However, that work only investigated the effects of the presence or absence of bait. The spatial nature of the model affords the ability to assess a variety of parameters associated with baiting and feeding. We altered four different supplemental food parameters to evaluate the effect on bTB prevalence in deer and cattle herd breakdowns over a 30-year period. Other model parameters were kept at default values as described previously (12, 27, 31). We ran each scenario under the original and current harvest rates for 5,000 replicates, discarding simulations for the first 50 and 150 years, respectively, (burn-in period). Due to the stochastic nature of the model, the burnin period was required to ensure bTB and cattle breakdown rates had stabilized prior to changing the parameters under investigation. For comparison to our treatments, we conducted baseline simulations for both the original and current age- and sex-specific bTB transmission and harvest rates.

# Simulated Scenarios

### Food Pile Density

Baiting and feeding is illegal in DMU 452 and has been since 1999 with limited use allowed in 2001 (8). However, a noncompliance rate of ∼25% was estimated for hunters in the area (36). By dividing the number of potential baiters (determined from deer hunting license sales; see (12)) by the area of DMU 452, the bait pile density was set at 0.02/ha. We evaluated the effect of reducing the non-compliance rate by 50% (e.g., via more stringent enforcement) which in turn reduced the bait pile density to 0.01/ha.

## Food Pile Attractiveness

We define bait attractiveness as the probability that a deer will visit a bait pile if the bait pile is located within the center of the deer's home range. Attractiveness is influenced by both feed type and deer behavior and is thus difficult to quantify with certainty. Consequently, we evaluated three arbitrary variations of this probability: 0.05, 0.1, and 0.5, which were considered to be plausible bounds on the likely attractiveness of bait to deer, assuming the odds of deer being attracted to accessible bait are 50:50 or lower.

### Spatial Persistence

Most hunters have preferred hunting locations and often establish permanent tree stands or deer blinds at these locations from which they hunt each year. In turn, if the hunter uses bait, the food piles are located in approximately the same location every year. We simulated the effect of requiring hunters to move food piles to new locations each year by randomizing pile locations, thus potentially affecting contact rates between habituated deer.

### Temporal Persistence

Supplemental feeding commonly takes place during winter months when the public attempts to supplement reduced natural food sources for wild deer. This type of feeding can potentially aid winter survival, thus increasing deer densities to a level that exceeds the biological carrying capacity of the habitat. Both supplemental and prolonged recreational feeding (typically for the purposes of viewing) can unnaturally congregate deer for extended periods and in turn increase the probability of disease transmission. We evaluated the effects of prolonged food provision by humans on bTB prevalence and cattle herd breakdowns by expanding the temporal duration of food piles for two different time frames: September–February and September– April. The former simulates feeding through the most severe months of winter in Michigan, and the latter supplementing food through the entire winter.

### Analysis

We used R (version 3.0.2, R Foundation for Statistical Computing, Vienna, Austria) for analyzing model output. Summary plots were generated for deer (bTB prevalence) over the simulated 30-year time frame. We compared output from the baseline simulation (no change to current deer management) to output from the simulations evaluating changes in baiting and feeding practices, to detect the direction and magnitude of influence on prevalence and herd breakdowns. Changes in bTB prevalence are expressed as absolute differences in year 30 vs. year zero of each simulation.

# RESULTS

The baseline simulation for the original harvest rates resulted in a 0.001 decrease in deer prevalence after 30 years, and no change in prevalence over 30 years under the current harvest rates (**Figures 2**, **3**). Cattle herd break downs were 2.8 per year on average under the original harvest rates and 3.4 per year under the current rates for the baseline simulations after 30 years (**Table 1**).

# Food Pile Density

Reducing the baiting non-compliance rate (and thus food pile density) by 50% reduced bTB prevalence in deer by ∼0.005 under both harvest rates, and reduced cattle herd breakdowns by an average of ∼1.5 per year under both harvest rates (**Table 1**).

# Food Pile Attractiveness

Under the original harvest rates, reducing the probability that a deer visited a bait pile within its home range to 0.05 and 0.1, reduced prevalence by ∼0.007 and 0.008 respectively, and by ∼0.012 and 0.011 under the current harvest rates (**Figure 2**). Increasing the probability of visitation to a bait pile to 0.5 increased prevalence by 0.06 and 0.069 for the original and current harvest rates respectively. Cattle herd breakdowns were reduced to ∼1 breakdown every 2 years under the original harvest rates and ∼1 breakdown every 5 years under the current harvest rates for the visitation probability of 0.05. For the visitation probability of 0.1, breakdowns were reduced to ∼1 breakdown every 2 years under both harvest rates (**Table 1**). However, increasing the probability of visitation to 0.5, increased herd breakdowns dramatically, ∼22 per year under original harvest and ∼19 per year under current harvest rates.

# Spatial Persistence

Changes in harvest rates notwithstanding, randomizing the location of bait piles each year had a negligible effect on bTB prevalence (0.002 decrease) in deer and on cattle herd breakdowns (**Table 1**).

# Temporal Persistence

Extending the time supplemental food was available by 2 months (i.e., through February) increased bTB prevalence by ∼0.019 and 0.028 for the original and current harvest rates, respectively (**Figure 3**). When food was available through April, prevalence increased by ∼0.051 and 0.061, respectively. Cattle herd breakdowns were approximately triple for both harvest rates after a 2-month increase in supplemental food (**Table 1**). Breakdowns were 5–7 times higher after a 4-month extension of supplemental food.

# DISCUSSION

Over the 10 years since our model was first developed, there has been a decreasing trend in deer harvest, requiring the recalibration of our model. We simulated our scenarios under both old and new harvest rates, to illustrate the effect of this harvest reduction, and to enable comparisons to our previously reported findings. Many of the scenarios simulated under the current harvest rates showed increased bTB impacts as compared to the original harvest rates, emphasizing that hunter harvest remains an important factor controlling bTB in deer. Yet, hunter retention and recruitment are recognized as being in critical decline, and this may have detrimental effects for wildlife disease management (37–40). For density dependent diseases, such as bTB in deer, population control of wildlife reservoirs is crucial. However, after more than 20 years of providing increased harvest opportunity in DMU 452, harvest has likely been saturated and further extending harvest opportunity is unlikely to increase harvest (12). A survey of hunters and livestock producers in northeast Lower Michigan more than a decade ago indicated that only 23% of resident hunters supported a further reduction in deer numbers, whereas and somewhat surprisingly, only 57% of livestock producers in the area were in support of further reductions (41). Future bTB management in Michigan must take into consideration what can realistically be accomplished given the likelihood that reductions in harvest experienced over the past two decades are permanent. Thus far, policymakers have been reluctant to entertain other potential options for bTB control such as culling or vaccination, likely because prevalence in the deer population could be kept low via hunter harvest alone. However, as demographic changes continue to reduce the number of deer hunters (34), harvest may no longer be as efficacious as in the past.

In addition to deer density reduction, prohibiting the use of bait and feed for deer is generally one of the first control strategies

FIGURE 2 | Tuberculosis prevalence in white-tailed deer over 30 years under different probabilities of deer movement to a supplemental food pile, assuming original (A) and current (B) harvest rates.

implemented to limit disease transmission (5). However, a complete ban, in practice, is usually unattainable. Baiting and feeding bans have contributed to declining bTB prevalence in Michigan, but non-compliance, problematic prosecution of violators, and continued legal sales of feed impede eradication. Consequently, attempting to keep the non-compliance rate as low as possible becomes the goal. Even if a 50% reduction of the estimated non-compliance rate in DMU 452 could be achieved, our results show that only modest decreases in bTB prevalence and herd breakdowns would result. While we did not examine the effect of an increased non-compliance rate and an increase in food density, a resurgence in baiting may be occurring in DMU 452. Observations by MDNR field staff have noted an increase in supplemental feed sales (pers. comm. B. Mastenbrook). Moreover, it is not clear that a decreasing number of hunters will necessarily result in fewer bait sites on the landscape. If younger hunters are more likely to employ bait than the older hunters who are gradually leaving the hunting population, it is conceivable that the amount of bait on the landscape may not mirror the decline in hunter numbers.

If a complete prohibition of bait could be achieved, the benefits realized could be diminished by reduced hunter participation (42). In Michigan, there is a cultural significance to deer hunting, and traditions of deer hunting in some regions of the state have long included the use of bait (8, 42). Because reducing deer density is currently the primary strategy for bTB control, the willingness of hunters to harvest deer in endemic areas is crucial for success. If hunters are reluctant to hunt without bait due to the perceived increase in hunter effort, or if hunters choose to hunt elsewhere, baiting bans could potentially decrease harvest further. Following the 2001 hunting season in Michigan, a segment of hunters indicated through surveys that they eliminated or decreased their hunting activities due to the baiting ban (10, 42–44). However, participation and antlerless harvest were similar between DMU 452 and the remainder of the state where baiting remained legal (42). Notably, evidence

\**Scenarios: Density 0.1* = *Food Pile Density (0.01 food piles/ha); Prob 0.05, 0.1, 0.5* = *Food Attractiveness (probabilities of deer moving to a food pile); Random* = *Spatial Persistence (randomizing food pile locations annually); Sept-Feb, Sept-Apr* = *Temporal Persistence (extension of time food piles are available).*

suggests that in general, baiting does not increase harvest (9, 10, 20, 45).

Even if minimal baiting was allowed in an attempt to maintain hunter satisfaction, a method to mitigate the increased disease transmission resulting from supplemental food has not yet been found (6, 7). We simulated requiring hunters to move bait piles to new locations each year, but the practice had a negligible effect on bTB prevalence and herd breakdowns and is thus unlikely to be a useful management tool. Previous research has shown deer in northeast Lower Michigan to have a high fidelity to baited areas, but not to specific bait locations (46). Effectiveness notwithstanding, requiring hunters to move their bait sites is likely to be impractical. In DMU 452, thousands of hunters are spread over a 1,480 km2 area, >90% of which is privately-owned land. The effort necessary to enforce such an approach is not feasible and would arguably be more constructively applied to enforcing a strict baiting ban.

The more attractive a bait pile, the more likely a deer is to move to it. In our simulations attractiveness had a considerable impact on bTB prevalence and cattle herd breakdowns. Reducing the likelihood of a deer moving to a bait pile had a desirable impact on prevalence. However, increasing the probability of visitation to a bait pile resulted in 3.5-fold increase in prevalence and an average of 19 cattle herd breakdowns per year after 30 years. Hunters deliberately use bait piles to attract deer. Thus, expecting hunters to use less "attractive" bait defeats the purpose of using bait in the first place. However, attractiveness is also driven by deer behavior. Although supplemental food influences deer behavior (6, 46), quantifying that influence is difficult. Our modeling results are sensitive to variation in this parameter [see (12), Appendix A) and research to better quantify the combined effect of food attractiveness and deer behavior would be valuable.

Compared to baiting, winter supplemental feeding or extended recreational feeding is likely to magnify bTB transmission by prolonging temporal availability. In our simulations, each 2-month extension of food availability increased bTB prevalence 2–3% and herd breakdowns increased dramatically (**Table 1**). The longer food sites are maintained, the greater the cumulative transmission of disease over time (6, 7, 47). These simulations suggest that even 5 years of feeding throughout the winter increased prevalence by more than 50%. Although historic large-scale winter feeding (11) has decreased significantly, a resurgence of this practice could wipe out gains made in bTB control to date after only a few years. Should managers ever allow winter feeding to become widespread again, knowing the likely consequences, the temporal window during which it is allowed must be a critical consideration.

Our temporal persistence scenarios extended the time bait was available on the landscape to simulate winter feeding, a reasonable but imperfect approximation. Bait is used theoretically to aid harvest in autumn. Winter feed sites occur without harvest and generally contain a greater quantity of food than bait sites, potentially attracting more deer to the site. Yet there are usually fewer feed sites in winter than bait sites during the hunting seasons. Historic winter feed site locations were documented previously via aerial surveys when winter feeding was extensive. Future research could incorporate these sites into our model as a new GIS layer to more precisely estimate site densities for comparison against these results.

Our model does not explicitly account for indirect transmission of bTB resulting from environmental contamination; if it did, we hypothesize that both prevalence of bTB in deer and the number of cattle herd breakdowns would likely increase, although the magnitude of those increases is uncertain. Deer infected with M. bovis shed infectious bacteria in oronasal secretions (48), and food items contaminated by infected deer are infectious for susceptible deer (49). In a field setting, bait and supplemental feed sites facilitate both the contamination of feedstuffs and surrounding soil with saliva and nasal secretions of deer feeding there (**Figure 4**), and so act as an efficient source of bTB transmission even after both the infected deer, and perhaps the feed itself, are gone. Experimental studies conducted both under laboratory (50) and Michigan outdoor (51, 52) conditions have shown that M. bovis can remain viable on feedstuffs for days to several months, depending on the substrate and ambient conditions such as temperature, humidity, and shade. That said, efforts to isolate the bacteria from documented deer feeding sites in Michigan have thus far proven unsuccessful (53). Although yet to be explicitly shown in Michigan field settings, research from other bTB-infected ecosystems has elegantly demonstrated the efficacy of environmental substrates such as watering holes as sources of bTB exposure (54). To parameterize indirect environmental transmission in our model, further research to determine the visitation rates of deer to sites where food was once, but is no longer, present would be necessary, along with rates of soil ingestion. Persistence times for M. bovis could be drawn from existing distributions of bacterial survival on foodstuffs (50). Alternatively, a value for indirect transmission could be estimated arbitrarily, and subjected to sensitivity analysis as in previous work (12). In any case, our model has demonstrated the importance of bait piles for bTB transmission in WTD, notwithstanding the additional risk due to environmental contamination.

No matter how feed sites are used, their presence, and potentially their past presence, increases bTB prevalence (12). Aggregation, crowding, increased competition, exposure to unrelated individuals, and increased predator-prey interactions are a few of the consequences of feed sites (5–7, 46, 55). These effects in turn increase stress and lower immune response, increasing susceptibility to disease (7, 56). Supplemental feed is often of lower quality than naturally available food and does not provide complete nutrition (57), leading to deficiencies and lowered immune response. Feeding deer to aid winter survival can be successful if begun early, but resulting increased survival and fecundity can increase densities, increasing bTB transmission. Feeding later in winter after nutritional deficits are realized often does not aid survival because body condition is often too poor to be reversed, putting these deer at even greater disease risk (57).

Our results indicate that altering how bait and feed for deer are used can reduce, or increase, cattle herd breakdowns, which is frequently implausible to the public. Discussions regarding the use of bait and feed are often considered of relevance only to bTB transmission among deer. While not effective as the sole management tool (27), how food provided by humans for deer impacts broader issues of bTB eradication from cattle must be considered by both regulators and agricultural producers. While deer bait and feed provide a market for crops that have limited marketability as human food, agricultural stakeholder groups should carefully consider the trade-offs between income generated for crop farmers vs. the economic costs of herd breakdowns to the cattle industry and the larger agricultural economy. Such introspection has largely been lacking in Michigan thus far.

Managing disease in deer must not preclude the use of other means of disease management for livestock. Increased biosecurity on farms in areas where bTB is endemic should remain a priority. Brook et al. (25) argue that a "bottom-up" approach for reducing transmission risk at the wildlife-livestock interface would be more practical and effective. This approach tailors risk mitigation to the individual farm level, taking into consideration spatial overlap and resources, winter feeding areas, animal behavior, fencing, and farm management, in contrast to relying primarily on wildlife culling or harvest, disease testing, baiting and feeding regulations, and cattle depopulation. Clearly, changing farm management can reduce disease transmission between wildlife and livestock substantially (23, 25, 26, 58–60). Our model includes a parameter to account for the proportional reduction in deer-to-cattle contact likely to be afforded by increased biosecurity [see Equation 1 in (27)]. For this study, we chose to hold that parameter at its default value of 1 (unmitigated deer to cattle contact). While heightened biosecurity could help reduce the effects of increased deer baiting and feeding, previous work suggests quite a high level of biosecurity would be necessary in order to have a high probability of reducing herd breakdowns [Figure 10 in (27)]. Although increased biosecurity alone is unlikely to eliminate herd breakdowns in the absence of broader measures to control bTB in deer (27), improving farm management in conjunction with altering supplemental food use for wildlife may facilitate reductions in interspecies bTB transmission.

# CONCLUSION

The use of supplemental food for deer continues to be one of the biggest regulatory challenges to bTB eradication in Michigan. As long as widespread baiting and feeding continue, successful eradication of bTB is likely unattainable. As wildlife managers learn to compensate for the decline in hunter numbers and adjust to changes in hunter demographics, the challenges for disease management become more complex. Even if a low level of bTB in deer is acceptable to the public, the ever present and serious risks to livestock remain problematic. Our modeling results demonstrate that a link between supplemental feeding of deer and occurrence of bTB in livestock exists and that feeding has implications not only for deer. Wildlife management necessarily involves managing people and their behaviors as well as wildlife populations. Disease management programs need to include educating people on how perceived short-term benefits from the use of bait and feed can lead to adverse long-term consequences. Convincing people not only to change their own behavior, but to also encourage others to do so, requires a culture change. Invoking this change is one of the most difficult challenges wildlife disease managers face.

# AUTHOR CONTRIBUTIONS

DR developed and recalibrated the model. DO provided the project concept and design. MC conducted the simulations, analyzed output, and drafted the manuscript. All authors contributed to intellectual material, manuscript

# REFERENCES

review, and editing, and have approved the submitted manuscript.

# FUNDING

This work was supported by the Federal Aid in Wildlife Restoration Act under Michigan Pittman-Robertson Project W-147-R.

# ACKNOWLEDGMENTS

The authors are grateful to A. Locher for allowing use of habitat potential data from which the habitat layers of the deer model are constructed.

30, 1922. Lansing, MI: Michigan State Department of Agriculture (1922). pp. 71–82.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Cosgrove, O'Brien and Ramsey. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Persistent Spillback of Bovine Tuberculosis From White-Tailed Deer to Cattle in Michigan, USA: Status, Strategies, and Needs

#### Kurt C. VerCauteren1 \*, Michael J. Lavelle1 and Henry Campa III 2

#### *Edited by:*

*Daniel J. O'Brien, Michigan Department of Natural Resources, United States*

#### *Reviewed by:*

*Graham John Hickling, University of Tennessee, Knoxville, United States Todd Shury, Parks Canada Agency, Canada Michelle Carstensen, Minnesota Department of Natural Resources, United States*

*\*Correspondence:*

*Kurt C. VerCauteren<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Veterinary Epidemiology and Economics, a section of the journal Frontiers in Veterinary Science*

*Received: 02 July 2018 Accepted: 12 November 2018 Published: 29 November 2018*

#### *Citation:*

*VerCauteren KC, Lavelle MJ and Campa H III (2018) Persistent Spillback of Bovine Tuberculosis From White-Tailed Deer to Cattle in Michigan, USA: Status, Strategies, and Needs. Front. Vet. Sci. 5:301. doi: 10.3389/fvets.2018.00301* *1 National Wildlife Research Center, USDA/APHIS/Wildlife Services, Fort Collins, CO, United States, 2 Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, United States*

Free-ranging white-tailed deer (*Odocoileus virginianus*) are believed to be a self-sustaining reservoir for bovine tuberculosis (bTB) in northeastern Lower Michigan, USA. Although a comprehensive control program is in place and on-farm mitigation strategies to curtail bTB transmission between cattle and deer have been implemented for over a decade, cattle and deer continue to become infected with the disease. Thus, renewed motivation to eradicate bTB is needed if that is truly the goal. Recurrent detection of bTB in cattle in the region is of mounting concern for state and federal agricultural agencies, producers, and wildlife managers. Current on-farm mitigation efforts include fencing and refined cattle feeding and watering practices. Liberal removal of antlerless deer through hunter harvest and disease control permits (DCPs) issued to cattle producers and agency sharp shooters have also been ongoing. Although these strategies have merit and efforts to reduce prevalence in deer and occurrence of positive farms are elevated, additional actions are needed. Heightened management actions to combat bTB in deer could include deer vaccination programs, strategic habitat manipulations to redistribute deer from farms, and precision removal of deer in proximity to high-risk farms. Foundational research to address development and delivery of vaccine to free-ranging deer is complete. Strategic management and habitat manipulation could reduce and disperse local concentrations of deer while better meeting wildlife, forestry, and agricultural goals. The responses of local deer populations to targeted removal of individuals are generally understood and there is potential to reduce deer activity around agricultural operations while allowing them to persist nearby on natural foods. We summarize the history and progress to date, discuss the realized merit of novel management strategies, and suggest options to rid deer and cattle in Michigan of bTB.

Keywords: bovine tuberculosis, cattle, disease, *Odocoileus virginianus*, transmission, spillback, spillover, whitetailed deer

# KEY CONCEPTS

**Integrated disease management:** employing a variety of proven strategies simultaneously to most efficiently achieve management objectives.

**Mitigation measures to protect cattle:** specific actions taken to reduce potential for direct and indirect transmission of M. bovis from wildlife to cattle.

**Management strategies for deer:** specific actions designed to reduce potential for maintaining disease within free-ranging deer such as using hunters or professional sharpshooters to reduce deer numbers and eliminating the provisioning of anthropogenic food sources with the intent of attracting and maintaining deer concentrations.

**Negative impacts of supplemental feeding and baiting:** anthropogenic feeding leads to artificially high and concentrated populations of wildlife which in turn increases disease transmission risk and prevalence.

**Setting realistic goals:** developing a documented and wellinformed formal strategy designed to reach a common and achievable goal.

**Public support, political will:** varying stakeholder motivations must be considered, reconciled and presented to decision makers so they can empower the pursuit of common goals.

# INTRODUCTION

# History of Bovine Tuberculosis in Michigan, USA

Bovine tuberculosis (bTB), caused by the Mycobacterium bovis (M. bovis) bacterium was historically a disease among cattle that spilled over into free-ranging wildlife where it persists (1– 3). Bovine tuberculosis is a threat to national and international beef and dairy markets. There are currently more than 13,000 cattle producers maintaining >1.1 million cattle in Michigan. The United States Department of Agriculture (USDA) has 5 levels of zoning regarding bTB status that states, or zones within states, fall into regarding presence of bTB infection in cattle ranging from 1 with no apparent prevalence in cattle and bison (Bison bison) to 5 with an unknown or ≥ 0.5% herd prevalence. The 5 levels include: (1) Accredited-free zone ("TB free"), (2) Modified accredited advanced zone (MAAZ), (3) Modified accredited zone (MAZ), (4) Accredited preparatory zone, and (5) Nonaccredited zone. Zoning enables agencies to tailor surveillance and management strategies relative to regional disease prevalence and potential risk of spread (4). The continual appearance of bTB in livestock facilities in Michigan annually keeps the zoning status of the state at risk while maintaining producer's ability to engage in national and international markets (5).

Movement of cattle from the MAZ must originate from a bTB accredited-free herd or one that has had a negative whole herd test within the previous 12 months and requires a movement certificate, unless the cattle are being moved directly to slaughter. On March 21, 2018 a new TB Zoning Order was signed into effect by the Michigan Department of Agriculture and Rural Development (MDARD) that established the Enhanced Wildlife Biosecurity Area (EWBA; an area slightly larger than Deer Management Unit (DMU) 452 in the center of the MAZ) (6). Development of the EWBA and increased disease mitigation efforts were an intensified effort to avoid another spike in incidence of infected herds like was seen in 2016 when 4 beef herds, 1 feedlot, and 1 dairy herd within the MAZ were found bTB positive (see **Figure 1**) (5, 7). As such, if the incidence of bTB infected cattle herds continues to rise or fluctuate like it has in recent years, there is a chance that the 4-county MAZ status or even statewide status (TB Free) could be in jeopardy (5).

# History of bTB in Deer in Michigan

In 1975 and again in 1994 bTB was detected in white-tailed deer in the northeastern lower peninsula (NELP) of Michigan. After which the Michigan Departments of Natural Resources (MDNR) initiated a surveillance program of testing hunterharvested deer (8–10) (**Figure 2**). A collaborative effort was initiated in 1996 by Michigan Departments of Agriculture (MDA), Community Health (MDCH), MDNR, the USDA, and Michigan State University (MSU) to manage bTB by initiating the Michigan Bovine Tuberculosis Eradication Program (11). In 1997, bTB was identified in the first positive cattle herd in the core disease outbreak area since 1974 (12) (**Figure 2**). In January 1998, the Governor of Michigan directed the MDCH, MDA, and MDNR to develop a plan for eradicating bTB from Michigan deer (13). In summary, the directive included the following components for the 5-county endemic area: (1) implement a deer feeding ban, (2) develop deer harvest quotas consistent with eradication goals, (3) develop methods for eliminating contact between cattle and deer, (4) continue surveillance and determine actual prevalence and evaluate trends, (5) educate stakeholders on managing deer with the goal of eradicating bTB, and (6) enlist a Coordinator to implement the eradication strategy (13). The directive was prepared based on the prioritization of public health and natural resources and insuring the vitality of agricultural industries.

Cattle are acknowledged to be the original source from which bTB or more specifically, M. bovis bacterium were disseminated into the spill-over host, deer, which now spill the pathogen back over to cattle (3, 14). The deer in this area of Michigan, then, are acting as a maintenance or reservoir host sustaining the disease on the landscape (see **Figure 2**) (3). Likelihood of maintaining disease would be increased if there was continued spillover from another reservoir host, such as the original source, cattle. Though considerable attention is paid toward protecting cattle and their feed and water sources from potentially infected wildlife species, it must be emphasized that deer are at risk of infection from cattle as well (3). As bTB-positive livestock operations are identified every year, more novel and aggressive approaches will be required to eradicate bTB from the NELP of Michigan, USA.

The infected deer population of the endemic area contributes to continued infections in cattle (1, 3, 10). This area lies within state-designated DMU 452 which is within a 4-county area consisting of Alcona, Alpena, Montmorency, and Oscoda counties. By 1994, the estimated deer densities where bTB occurred were at or beyond biological carrying capacity (19– 23/km2 ) and there were high densities maintained largely

through supplemental feeding by hunters and other deer enthusiasts (**Figure 2**) (15). Apparent prevalence rates for bTB in deer in the endemic area as of 2011 ranged from 1.2% (2005) to as high as 4.9% (1995) and has hovered just below 2% over the two decades since (12). Although apparent prevalence rates are an imperfect predictor, they are frequently the best information available to monitor trends in disease (16). From 1994 to 2009 apparent prevalence of bTB in deer correlated with deer population estimates in the endemic area very well (**Figure 2**) (12).

# History of Baiting and Feeding Relative to Maintenance of bTB in Deer in Michigan

In general, the bTB endemic area of Michigan consists of several land management types that are relevant to perpetuating the disease and managing the situation: first, several large privately owned parcels of deer habitat are managed exclusively for hunting (17); second, large tracts of public and privately owned forests exist in multiple successional stages thus providing ample deer habitat components in proximity to one another (18); and third, interspersed agricultural lands consisting of dairies, crops, pastures, and beef cattle operations. The makeup of these agricultural lands provides high quality deer habitat in the region.

Supplemental feeding to sustain and concentrate deer and baiting to attract them to specific locations for hunting purposes were common practices in this area and contributed largely to high deer densities and disease transmission (17, 19–21). Prior to restrictions and bans on feeding and baiting, 72% of non-resident and 87% of resident hunters in the NELP of Michigan used bait while hunting (22), illustrating how prevalent these practices had become. Feeding and baiting helped develop a deer population that ultimately exceeded an estimated 20 deer per km2 (8). As discussed by 8 baiting and feeding are recognized by natural resources professionals as the primary reasons originally enabling deer to become reservoir hosts for bTB in this area.

# KEY CONCEPTS IN MOVING FROM MANAGEMENT TOWARD ERADICATION

Approaches to eradicating disease are situational dependent though often include common key components. Components of previous eradication strategies include: (1) implementation of mitigation measures to protect against transmission of M. bovis to and from livestock, (2) implementation of management strategies to reduce prevalence in host species including wildlife and livestock; (3) establishment of well-defined goals, plans and policies; and (4) initiation of strategies to build and maintain support of the broad array of stakeholders.

# Current Efforts Toward Eradication in Michigan

As in most disease eradication situations, any single strategy alone will rarely eliminate the disease, especially when there are more than a single reservoir host and free-ranging wildlife are involved (23). As such, a combination of strategies need to be implemented in an integrated approach as this will improve efficacy while reducing overall effort and cost (24). In 2008 MDARD initiated the Wildlife Risk Mitigation Project (WRMP) which focused on enrolling and assisting livestock producers in implementing and maintaining an array of measures to reduce risks for transmission of M. bovis between deer and cattle on their properties (2, 25–27). Producers were encouraged to participate in the project which entailed education, completing an on-farm assessment of risks, committing to a formal action plan, initiating the action items within the plan, and passing a verification visit to ensure they implemented the plan (25).

A primary risk of transmission between wildlife and cattle stems from shared resources like food, water, and habitat (19, 27–29). Thus, mitigation measures were directed at protecting resources that are concentrated such as stored cattle feed, watering systems and areas routinely occupied by cattle (2, 26–28). It was also recognized that commonly used farm management practices needed to be evaluated and improved upon. Practices such as the collection of waste slurry from cattle that is then applied to crop fields is questionable especially when there's potential for M. bovis to be present (30, 31). This practice often occurs during spring green up when nutritionally stressed deer are dispersing from winter concentration areas in search of nutritious food sources like crop residues and lush new growth emerging in crop fields following snow melt (32).

At the initiation of a plan within the WRMP, landowners meet with an agency wildlife biologist on the farm to assess risk factors for disease transmission. Mitigation measures ranging from strategic feeding practices to constructing feed storage facilities are then recommended based on identified risk factors. The WRMP is a science-based program and the efficacy of many of the recommended mitigation strategies have been supported by research findings including the use of fencing (26, 33) and gates (34, 35) to protect stored feed and feeding areas. Risk mitigation strategies prescribed included, but were not limited to: (1) protecting cattle feed by storing it in buildings or within deer-proof fences with gates closed, (2) feeding cattle daily and away from deer cover, (3) strategically positioning water sources to minimize access and potential contamination by deer, and (4) using disease control permits (DCPs) to reduce antlerless deer numbers on and around farms (5). The majority (545 of 620; 88%) of the farmers in the 4-county MAZ participated in the Program and were subject to annual inspections to insure compliance and maintain their verification (5).

When motivation for deer to access food and water is elevated, such as during late winter, increased vigilance and additional measures to exclude or deter deer may be required (26, 36). The efficacy of mitigation measures is directly related to the motivation of an animal to overcome it and the vigilance of the farmer. Motivation also varies with circumstances relative to season (e.g., severity or length of winter, drought conditions in the summer) and availability of natural foods and water. Producers must be cognizant of these factors, and therefore, when risk is increased, must increase vigilance to maintain an effective level of biosecurity (26, 36, 37). Such mitigation measures and environmental influences are discussed during risk assessments to insure producers understand that wildlife risks are not static and identify factors and scenarios that may increase risk.

### Current Efforts: Exclusionary Fences

The use of fencing to exclude deer is an effective means for protecting concentrated resources meant for livestock (2, 26, 33). Numerous fence types exist and fence selection can be based on the predicted level of motivation for deer to breach, the desired longevity, and associated cost (33, 38). In high-biosecurity situations where essentially no deer breaches are acceptable, woven-wire fences ≥2.44 m in height are recommended (33, 39). Interestingly, the "weakest link" of a fence is the gate, which obviously must be closed to be effective (26, 34). While this may seem like common sense, in areas where frequent access is needed, livestock producers commonly become lax, leaving gates open, especially during daylight hours. Deer, then, have been documented entering fenced areas of stored feed through open gates in the middle of the day when it was assumed they would not be nearby or active (26).

### Current Efforts: Livestock Protection Dogs

Livestock protection dogs (LPDs), traditionally developed and used for reducing the killing of livestock by predators, have also proven effective in keeping deer from directly and indirectly coming in contact with cattle (40). Using specially trained dogs for protecting numerous agricultural resources is becoming more widespread (41, 42). For example, LPDs have proven effective in protecting crops (43), cattle pastures, and feed (40, 44). In the case of transmission of M. bovis between cattle and deer in which concerns over indirect transmission through contaminated resources are greatest, LPDs employed to protect stored feed and other resources would be beneficial (40, 44). Although LPDs can effectively repel deer to protect localized areas and livestock, there is a point in which the size of the area or the amount of deer activity exceeds the abilities of a single LPD and either additional LPDs or integrating other measures such as exclusionary fences are needed (33, 44).

# Current Efforts: Strategically Locating Feed and Water for Cattle

Currently, 88% of commercial farms in the MAZ are incorporating practices focused on protecting cattle-related resources from wildlife that is potentially harboring bTB (5). Although participation is high, increased emphasis on consistent use and maintenance of mitigation measures is needed (26). Such resources include water, feed, and mineral supplements, all of which are sought by deer and other wildlife and should be a focus of concern regarding the transmission of M. bovis (19, 28, 45, 46). Initially, USDA cost-share programs assisted producers in incorporating secure feed storage options including hoop barns and deer-exclusionary fencing to minimize deer access to cattle resources. Refined feeding strategies including limiting provisions to just what a group of cattle will consume that day and constricting the time and duration of availability to just daylight hours can help reduce deer activity in cattle feeding areas (5). Water, though, needs to be available continuously so could be more difficult to protect from contamination by deer (5). Storing and providing cattle resources (feed, supplements, minerals, water, etc.) away from permanent deer habitat and closer to areas of human activity is also recommended.

## Current Efforts: Cattle Identification and Tracking

Annual whole-herd testing of cattle for bTB and outfitting cattle with radio-frequency identification (RFID) tags became a requirement for Michigan producers in the endemic area to move live cattle off their farms in 2007. These requirements enable trace-back investigations to locate where and when bTBinfected cattle shared the same space as other cattle, with the goal of identifying other potentially infected animals and premises (29, 37, 47). Although the infection of a herd due to movement of an infected cow into that herd occurs (48), it was presumed to be a lesser risk for cattle producers in Michigan than infected deer (29, 47). Yet recent cases outside of the endemic area and within the accredited-free zone of southern Michigan suggest spread of bTB via infected cattle may actually be increasing (49).

## Current Efforts: Reducing Deer Numbers

Population reductions are often considered or used in response to outbreak of disease and involves reducing the density of the host population through strategic lethal removals, usually through culling by professional sharpshooters, or increased recreational hunter harvest (50, 51). Large-scale removals of reservoir species have been implemented and proven effective in some cases (23, 52–55). Though used to a degree in the endemic area of Michigan, these options have proven controversial and have not been wholly accepted by producers, hunters or other publics in Michigan (24, 56).

With the goal of reducing the potential for transmission of M. bovis between deer and cattle the MDNR initiated a program in 1998 in which cattle producers could acquire DCPs allowing them to personally address the deer situation on their land by harvesting deer themselves or enlisting the help of sharpshooters with the USDA Wildlife Services (12). Producer use of these permits, though, was low. Only 12% of 6,427 tags were filled in 2008 and deer numbers have since increased as have associated disease prevalence rates (12, 57).

Damage tags or block permits were also available to producers who were experiencing damage to crops by deer, allowing them to harvest deer on their property to alleviate ongoing problems (57, 58). Similar to DCPs, participation was low and lack of local public support was presumed to be the cause (12, 57, 59). Occasionally, negative concerns about these non-traditional deer harvest strategies were voiced by owners of recreational lands adjacent to at-risk farms (12). For example, even when deer density estimates were 8–15/km2 and crop damage was substantial, only five of 31 alfalfa growers participating in a crop damage project requested permits to control damage on their property and only 42% of issued permits were used. Similarly, red kidney bean growers were issued a total of 88 permits and only 23% were used (60, 61). These data illustrate that even when landowners were faced with substantial amounts of crop damage and provided permits to reduce deer numbers, they were not using them (60, 61).

The MDNR increased the number of available deer tags and the number of hunting seasons, with the focus on removal of antlerless deer, and successfully reduced deer numbers within DMU 452 by 50% from 1995 to 2004 (12, 62). However, deer numbers rebounded rapidly since 2005 to >110,000 and remained steady through 2009 (12). More recently hunting opportunity and harvest potential has been essentially unlimited in DMU 452, though hunters have harvested less than one thousandth of the tags available (i.e., 4,388 deer from 5,575,390 potential tags), demonstrating that demand for opportunity has been saturated (63). Although the MDNR was effective in reducing deer numbers initially, hunters were not overwhelmingly supportive of these actions (22). As a new strategy to address insufficient harvest on farms, it is now a requirement for livestock producers to include and implement a deer reduction component within their EWB Plan, specifically focused on those deer routinely in proximity to farms with cattle (5). As this is a recently enacted requirement, the effects are yet to be seen.

# Intensifying Efforts to Reduce Potential Transmission of *M. bovis*

Nearly 20 years ago it was stated that "The measures of apparent bovine TB prevalence have decreased by half since 1997, providing hopeful preliminary evidence that eradication strategies are succeeding" (15), but bTB still persists in Michigan. Ongoing and increased efforts to reduce the persistence of M. bovis continue; however, the rate of cattle operations being identified as positive for bTB fluctuates at levels that put the accredited-free status of Michigan in jeopardy (>3 positive herds detected/year) (5). Despite extensive efforts prescribed by the previous WRMP, bTB-positive herds continue to be identified each year, thus new approaches are needed if the goal is still to eliminate the disease. To this end the EWB Project was initiated to involve more thorough on-the-ground assessments of properties housing cattle by an "EpiTeam," similar to what is used following the detection of positive cattle. Each team includes a MDARD veterinarian, a USDA or Alpena Conservation District wildlife biologist, a MSU Extension cattle specialist, and a local producer (5). Each assessment results in an action plan (now entitled "Enhanced Wildlife Biosecurity Plan") that needs to be implemented on the ground by the producer, similar to how the WRMP was implemented from 2008 to present. Producers must implement and maintain all prescribed mitigation measures relating to high-risk areas on their farms by December 31, 2019 or will lose their ability to sell cattle other than directly to slaughter (6).

## Intensified Efforts: Targeted Deer Removals

All existing 130 commercial cattle producers in the EWB Area require a deer removal component that enables sharpshooters to remove deer from in and around farms and pastures. For example, in Dressel's (32) study up to 13 deer were removed from a single landowner's property. Action plans in the EWBP are designed to eliminate deer whose home range includes farms and deter others from establishing ranges in proximity to farms (5). The frequency of visitation to highly-desirable resources such as stored feed and agricultural crops may be a learned behavior that could be curtailed by removing mature does or entire family groups of offending deer (64). It has been documented that fawns can learn movement patterns from adult does and that it is typically a few specific deer in a given area that will share space and time with cattle or frequent stored feed areas (27, 36, 37). As such, targeted removal of offending individuals may curb present and future visitation of farms by deer. Research has shown deer frequent farms the most often during: January through mid-April; and Mid-July through August (26, 36), thus these periods are when removal efforts should be focused.

### Intensified Efforts: Strategic Habitat Manipulations

Wildlife management consists of three components: (1) the biota or populations, (2) the habitats or ecosystems organisms need to persist, and (3) the people or stakeholders that live in the ecosystems and interact with the wildlife resource (65). To date, bTB research and management practices have been directed primarily at two components, namely the biota (i.e., deer) by reducing numbers through recreational hunting and targeted deer removals and the people (i.e., hunters, producers) by manipulating harvest regulations, deer baiting, and feeding practices, and how producers store and protect feed and water resources. Historically, the third component of wildlife management, the species' habitat, has not been factored into bTB management strategies. Perhaps because, as Felix et al. (66) suggested, "managers may lack sufficient understanding of long-term spatial and temporal links between habitat supply and population response." There has, though, been an extensive amount of research on why and how forest management practices can be used to enhance or reduce quality of deer habitat [e.g., (67, 68)] and potentially influence the distribution of deer across a landscape (18).

The Alpena-Montmorency Conservation District of Michigan has recently initiated a cost-share program that may assist in influencing deer movement patterns, potentially away from stored feed, water sources and livestock concentrations, by initiating habitat improvements for deer through forest management activities. This new program, if implemented strategically could stimulate deer to redistribute themselves away from agricultural areas to other, naturally occurring vegetation types. The program also includes incentives that encourage data collection and the liberal harvest of antlerless deer (69).

The quality and distribution of a species' habitat is a primary driver influencing the spatial and temporal distribution of species [e.g., (70)], including deer [e.g., (18, 71)] and elk [e.g., (72, 73)]. Recognizing how habitat quality and its distribution can influence the movement patterns of a species, a strategy could be to use this basic ecological principle as a tool to combat bTB in the NELP. An additional step may be to take measures to lessen the quality of habitat for deer on and adjacent to farms, lowering the area's carrying capacity, the desire of deer to be there, and the fitness of deer that persist.

The core of the bTB area, DMU452 is composed primarily of private land (93%) (74) that is dominated by forest cover types. For example, within Alpena County alone, 60% of the area is covered by lowland conifer swamps and northern hardwood forests interspersed among agricultural areas. Much of the forest is relatively later successional stage, especially on private lands. Given that the life requisites of deer in this area include: spring and summer food, thermal cover, and fall and winter food (66), much of the agricultural lands and livestock areas are often under tremendous feeding pressure by deer especially in latewinter through summer (32, 60, 61, 75). A cover type lacking in this area that deer could use extensively for feeding and cover is regenerating deciduous stands (e.g., aspen clearcuts of predominately early age classes) (66). Experimenting with forest management practices as a method to manipulate how deer use the landscape has merit.

Habitat management on public lands is a primary activity used by agencies to meet wildlife management objectives and satisfy a diversity of stakeholders, yet it is poorly understood how frequently or what types of management, if any, occur across private lands. The use of landowner incentive or costshare programs to manipulate forest cover types to improve habitat conditions away from agricultural lands and livestock operations should be investigated for their efficacy in: (1) providing quality habitat, (2) shifting the distribution of deer away from agricultural areas at high risk for transmission of M. bovis, (3) reducing crop damage, and (4) meeting economic objectives of landowners for harvesting forest types. Such a habitat-based bTB management and research approach could be initiated and simultaneously integrated with other bTB mitigation practices. The successful management of this complex problem could be enhanced if the habitat for deer were factored into the management equation.

# Potential Future Efforts

Original actions to eradicate bTB in Michigan combined with recently emerging science-based strategies have all been insufficient to date, primarily due to waning stakeholder support. Several new strategies and directions are mentioned above and have begun, here we discuss additional potential measures to consider if the collective desire of agencies, stakeholders, and other publics is to eradicate bTB from Michigan.

# Potential Future Efforts: Reducing Deer Numbers

As stated by Riley et al. (76), "An assumption in most conventional deer harvest strategies is that adequate demand for and successful use of antlerless deer permits exists to achieve desired deer harvest." As deer densities decline and number of deer encounters are reduced, hunter perception and support, effort, and desire to continue hunting fade and hunters will often transition to other locations or species (77, 78). When hunter harvest is no longer effective in maintaining deer populations at or below goal, additional measures must be contemplated. In such situations "Hunting eventually may become less a recreation and more a community service or civic duty . . . Culling may be a more appropriate term for the kind and purpose of hunting under such circumstances" (76). Although recreational hunting is and should remain the primary means for managing white-tailed deer, there are situations in which it may not be safe, feasible, or effective and other means need to be considered (79). Within DMU 452 where deer reductions are needed and current harvest is insufficient, strategies like earn-a-buck or incentivizing hunters by allowing easy donation or profiting from venison may be worth consideration (79–81).

Most (>90%) of the bTB area in Michigan is privately owned (74) which has contributed to challenges in achieving wildlife management goals (9). Although purely speculative, it is uncertain about what the future for large privately-owned "hunt clubs" will be with consistently declining numbers of hunters. Will the owners of these lands want to hunt them in the future or use them simply as family get-aways? How will this affect the local deer population? A decreasing trend in hunters has been well-documented in the US (82, 83) and in Michigan specifically (84, 85). Because of these trends, other approaches might be warranted such as the MDNR purchasing large tracts of hunt clubs or other private lands (farms) to improve access. For example, from January 1998 to November 2018, the MDNR purchased a total of 34,240 ha state-wide with an average of 1,630 ha being purchased annually and the mean amount of land acquired per transaction was 53 ha (K. Wildman, Biologist, MDNR, personal communication, 05 Nov 2018). Non-profit conservation organizations such as the Rocky Mountain Elk Foundation are often partners in purchasing land which the state then manages and oftentimes provides public access for hunting. A local example in northern Michigan was the purchase of the Green Timbers tract in 1982. This property is now attached to the Pigeon River Country State Forest and provides unique walk-in only hunting and other recreational activities (e.g., backpacking, hiking, cross country) for the public. Acquisitions such as this improve the ability of the MDNR to manage the deer population and provide opportunity to its constituents.

### Potential Future Efforts: Vaccination Program for Deer

An additional novel tool that could aid eradication of bTB in Michigan is an oral vaccine against bTB for deer. Interest in using a vaccine for bTB in deer is increasing (32, 63, 86). Bacille Calmette-Guerin (BCG) vaccine reduces disease severity by decreasing gross lesions and sites of infection, suggesting potential for reducing transmission and minimizing endemic infection in wildlife (87, 88). Significant progress has been made in demonstrating the safety, efficacy, and feasibility of implementing a vaccination program against bTB for deer (89– 92). Researchers modeled vaccination and demonstrated that vaccinating just 50% of the deer would contribute to an 86% probability of eradicating bovine tuberculosis in DMU 452 in 30 years (63). Interestingly, in the presence of recreational baiting it would be highly unlikely to achieve eradication within the next 30 years at the same vaccination rate (63). A vaccination rate higher than 50% could likely be achieved based on an experiment where placebo vaccine baits were effectively delivered to free-ranging deer (32) which would increase the probability of eradication. Of course, implementing a vaccination program while maintaining the use of additional management strategies; restrictions on baiting, liberal recreational harvest, DCPs, and fencing stored feed and other cattle resources would be the most efficient path to eradication (63, 86).

# Potential Future Efforts: Novel Diagnostic Tests for bTB

As current live-test methods involve multiple animal handlings, take 48–72 h to produce results, or require specialized laboratory procedures, improved methods are needed for reliable and timely detection of bTB (93, 94). A "trap–test–cull" project was evaluated using a rapid test and live capture of deer, though it was deemed cost-prohibitive (>\$1.5 million US annually) and ineffective in reducing prevalence of bTB (95). Recently developed methods that enable the antemortem detection of unique biomarkers of disease suggest improved diagnostics are becoming available. For example, infection by M. bovis results in the presence of specific peptides in the blood which can be detected with common laboratory analyses (96). Additionally, the analyses of breath from cattle to detect bTB-specific volatile organic compounds has proven effective in experimental settings and has potential for applications with deer (94). Also, genotyping particular strains of bTB pathogens enable back tracking to determine the source herd of cattle for the disease (97). New tools like these and the support to develop them are desperately needed.

# The People Piece

Public support and involvement is essential if complete eradication is the goal. Are Michigan residents accepting of a low level of bTB sustained in their deer herd? It was apparent in 2006 that Michigan hunters felt bTB was not a problem, ranking it considerably lower than "more extensive problems" including too few mature bucks and too few deer in general (12). Are Michigan livestock producers comfortable with the risk that they may have a reactor cow in this year's wholeherd test and that theirs could be the next positive herd? It is clear that Federal and State agricultural agencies are losing tolerance for reoccurring positive cattle farms. As it should be, input from stakeholder groups and various publics have played a large role in political and management decisions regarding bTB in Michigan since 1994 when the second bTB positive deer in 20 years was found. There is potential that had managers been more empowered or convincing and decision makers more stalwart the bTB situation in NELP may be quite different today. Despite extensive surveys examining strategies used to improve stakeholder appreciation of the situation with bTB in deer (98– 101), public and political support has been too little to enable the actions necessary to improve the situation (101). To make better progress going forward, more emphasis must be placed on the human dimensions aspects of the issue by more effectively engaging the diversity of stakeholders associated with this deerbTB-agricultural industry issue.

# Policy Based on Science or Public Demand?

 In 1996, Michigan voters elected to transfer the responsibility for managing game animals from the MDNR to the 7-member governor appointed Natural Resources Commission (NRC). The NRC was mandated to integrate scientific findings and public input into new policies that the MDNR follows; in turn, the MDNR provides recommendations to the NRC to help them make informed decisions when establishing such policies (20). Policy established by the NRC in 2007 presents the goals of the MDNR as using science-based management practices to maintain a healthy deer population as determined by the carrying capacity of its range and the effects upon native plant communities, crops, and public safety (103). Additionally, they set out to maintain an active educational program to inform the public on practices of deer management for achieving a healthy and vigorous herd (103). Despite these basic, well-intended goals driving policy, public trust (of NELP residents) in the ability of MDNR to set deer hunting rules relative to eradicating bTB was lower than 50% in 2011 (104). This distrust has impacted the ability of MDNR to manage bTB and created backlash by local residents and hunting constituency groups (105).

Tools such as spatial models for forecasting likelihood of disease eradication given various approaches are the types of informative tools needed to aid in establishing goals and creating policy (63). A key strategy for facilitating scientifically based decisions leading to effective management actions lies in providing policy makers with accurate information derived from high quality research while respecting their role of representing those that elected or appointed them (102). Further, educating the general public and earning acceptance and trust are also essential to successful management of healthy wildlife populations and their habitats (15, 22).

# Building Widespread Stakeholder Support

Initial efforts by state and federal agencies to eradicate bTB in Michigan were extensive despite minimal public support (106). To be effective and successful, actions initiated by agencies have to be accepted and adopted by citizens including hunters, livestock producers, and wildlife viewers. For example, MDNR initiated strategies to reduce deer numbers through increased availability of hunting licenses and implemented baiting and feeding restrictions (20, 56). Public support and action was needed to harvest additional antlerless deer and to cease baiting and feeding. Although there was a documented 50% decline in apparent prevalence from 1995 to 2004 due to reductions in deer numbers and restricting baiting and feeding (107), deer numbers and prevalence rates have since rebounded. As demonstrated by the incessant reappearance of bTB in deer and cattle, it is apparent public support and involvement are essential for successful eradication or even tempered control (20, 106, 108). It is also apparent that the lucid presentation of specific disease-related risks to one's personal interests are needed to truly bring about action and change (99, 100). Frequently updated information with an emphasis on successes is essential to maintaining or increasing stakeholder support (98).

In addition to insufficient stakeholder support, there has been decreasing financial support to and from federal and state agencies to enable the eradication of bTB from wildlife and livestock in Michigan. This issue has led to fewer personnel and waning awareness and support from most publics. Thus, current and future efforts toward eradicating bTB require maximizing knowledge gained from past efforts to inform next steps for research and management (62). To this end, modeling efforts have helped predict likely outcomes given the tools and resources available to begin answering questions to help optimize and select combinations of strategies to implement (63). Without incorporating new tools and revising strategies, it was predicted that eradicating bTB from Michigan in the next 30 years was unlikely (63, 95).

It has become clear that ongoing strategies for eradicating or even minimizing the transmission of bTB in Michigan have been insufficient, primarily due to lack of sufficient long-term determination of stakeholders. If the Michigan and US goal is to protect the entire country's cattle herd and trade status, increased support and strategies are needed. Further, it is apparent that increased public acceptance and involvement will be required to defeat the challenges associated with the eradication of bTB (56, 107).

Unfortunately, these challenges are deeply rooted in the culture of the area and will not be overcome easily. There are apparent divides and disconnects amongst the interests and demands of various factions of the public (i.e., hunters, cattle producers, policy makers, general public), with public servants from natural resource and agricultural agencies struggling to regain healthy wildlife and livestock populations for them. It seems that through efforts to achieve healthy deer densities in Michigan following the appearance of bTB, public resentment has actually grown (12, 62). Agencies need improvements in public outreach about all aspects of the bTB issue to reverse this trend and garner support for the intentions behind management actions. Given the current popularity and user involvement in social media (i.e., YouTube, Instagram, Podcasts, etc.), it is a new tool that could be used to aid ongoing and future efforts associated with bTB. Although previous efforts to engage and motivate hunters to actively participate in non-traditional deer management actions (i.e., increased harvest of antlerless deer) failed over the long term, significant changes such as providing extended or alternative seasons and increasing attention on new hunters may improve participation (101). Unfortunately, common trends such as managing for more, larger, and more mature (i.e., older) male deer on the landscape, primarily through imposing antler point restrictions, does not align well with disease management strategies focused on removing more males with an emphasis on older age classes (10).

# Optional Approaches Toward Managing bTB in Michigan

Going forward, agencies need to (1) establish long-term, mutually agreed upon objectives, (2) develop well-defined strategies that align with those objectives, and (3) develop and implement practices to evaluate the efficacy of those strategies (109). All options toward managing disease, including no action, need to be considered in establishing objectives (24, 86). First and foremost it needs to be determined what the long-term goal is: status quo, eradicating bTB throughout Michigan, eliminating bTB in deer in Michigan, or eliminating bTB in cattle in Michigan. If the presence of bTB in Michigan truly is acceptable, there is always the option of no additional management action whatsoever, although this may need to be coupled with the buyout of all cattle across the region to eliminate potential for cattle becoming infected. Additionally, compartmentalization could be considered to limit the potential for geographic spread of bTB through the use of significant barriers such as large-scale exclusionary fences for deer (24). It was well-stated by Olmstead and Rhode (110) regarding the interconnectedness of the cattle industry, "Given the benefits from trading in livestock and the contagious nature of the disease, it was more efficient to build a "fence" around the entire country than to create barriers around each and every farm."

If the goal is still to eradicate bTB across Michigan as stated by the Governor in 1998, then the potential exists to make great strides. Actions should include but are not limited to: significantly reducing deer densities with focus on those in the vicinity of cattle operations, eliminating baiting and supplemental feeding, segregating wildlife and cattle/cattle resources, using habitat management to change the spatial distribution of deer, and deploying a vaccine for deer.

If the goal is only to eliminate bTB in cattle, the strategy is relatively straightforward especially if all transmission is occurring only between deer and cattle (111). With cattle being the primary concern, excluding deer from all cattle-related resources with true deer exclusionary fencing (i.e., 2.4-m-h woven wire fence) is needed (24, 26, 39). Where this is not possible, such as a body of water bordered by cover used by deer and cattle pastures, either the deer or cattle must be excluded. Although reliable deer-exclusionary fence is initially expensive and may be considered unsightly, it is effective when maintained and would minimize potential for transmission via indirect and direct contact (24, 26, 33, 38). This level of biosecurity is commonplace in other production animal systems such as within the swine industry (24, 112, 113), especially in areas where the threat of disease transmission is a reality. Permanent deer-proof fences are also commonplace and widely accepted in areas where the captive cervid industry is active, as well as along expansive stretches of highway systems throughout the US where deer-vehicle collisions had been common. These fences are also used around the world in places such as in Africa because they enable managers to achieve extensive and reliable manipulation and protection of various species (33). Given the serious nature of eradicating bTB, reliable management of deer and cattle are needed in Michigan and thus similar measures could be considered.

# CONCLUSION

The ongoing situation with bTB in Michigan has been a persistent and expensive management challenge for livestock producers and state and federal agencies for more than a quarter of a century. As biologists and public servants, we may feel ethically committed to ridding the landscape of this disease that impacts the wildlife resource and a primary agricultural industry. But unless the societal and related political support for this exists, perhaps we need to either stand down or double down. The situation in Michigan is a multi-faceted issue with several imposing barriers, ecologically and socially, that are impeding the possibility for progress toward eradicating the disease. The first and foremost challenge is inadequate public concern over the health of the deer population and cattle herd and subsequent lack of political support and action. This challenge obstructs many crucial steps in wildlife management toward eradication, including the banning of baiting and feeding, reducing host populations, and understanding and accepting the severity of the bTB situation across the landscape.

If there was increased public concern about the occurrence of bTB in wildlife, livestock, and humans there would likely be compounded support and participation in actively pursuing eradication. As demonstrated during the era of market hunting, even before the advent of modern hunting tools and technologies (i.e., high-powered rifles and scopes, night vision, remote cameras, helicopters, drones), Americans demonstrated our ability to severely reduce, and in some cases, decimate deer populations when motivated. Conversely and more recently, due to changes in motivators, we have demonstrated our ability to

# REFERENCES

develop large numbers and concentrations of white-tailed deer. Now we must refocus on maintaining populations of fewer but healthy deer in concert with the limitations of local agricultural goals and available natural vegetation types that can provide deer habitat. In 1949, Aldo Leopold wrote, "A thing is right when it tends to maintain the integrity, stability, and beauty of the biotic community, it is wrong when it tends otherwise" (114). Natural resource professionals can still keep this goal in mind while simultaneously acknowledging and addressing the food production needs of our continually growing and hungry populous.

The toolbox contains much of what is needed to combat bTB in Michigan; including increased hunting license allocations, increased availability of disease permits, financial cost-share programs to increase biosecurity on farms, feeding and baiting bans, the use of educational stakeholder meetings, new novel tools to facilitate diagnosis and surveillance, and even a vaccine for deer or evaluating the use habitat manipulations to redistribute deer. None of these tools will be effective alone, they must be applied aggressively and in unison to complement each other. Progress has been made in understanding and managing livestock-wildlife interactions and the transmission of bTB in the Michigan landscape and recent decisions and new strategies have great potential.

# AUTHOR CONTRIBUTIONS

KV, ML, and HC contributed equally in the development of the idea, collection of the data, and preparation of the manuscript. KV fleshed out the original outline. ML drafted the manuscript and continually incorporated and massaged his, KV and HC's thoughts. All authors continually reviewed and edited the manuscript, producing the submitted draft.

# ACKNOWLEDGMENTS

We appreciate the assistance and support provided by R. Smith, recently retired MDARD. This research was funded in part by the U.S. Department of Agriculture.

experimentally challenged with Mycobacterium bovis. Zoonoses Public Hlth. (2009) 56:243–51. doi: 10.1111/j.1863-2378.2008.01198.x

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The handling editor declared a past collaboration with one of the authors HC.

Copyright © 2018 VerCauteren, Lavelle and Campa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Bovine Tuberculosis Management in Northwest Minnesota and Implications of the Risk Information Seeking and Processing (RISP) Model for Wildlife Disease Management

#### Megan Cross 1 \*, Alex Heeren2 , Louis J. Cornicelli 3 and David C. Fulton4

*1 Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, United States, 2 Sierra Nevada Research Institute, University of California, Merced, CA, United States, 3 Minnesota Department of Natural Resources, Division of Fish and Wildlife, St. Paul, MN, United States, 4 U.S. Geological Survey, Minnesota Cooperative Fish and Wildlife Research Unit, University of Minnesota, St. Paul, MN, United States*

#### Edited by:

*Daniel J. O'Brien, Michigan Department of Natural Resources, United States*

#### Reviewed by:

*William F. Siemer, Cornell University, United States Adam Zwickle, Michigan State University, United States*

> \*Correspondence: *Megan Cross<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Veterinary Epidemiology and Economics, a section of the journal Frontiers in Veterinary Science*

Received: *07 May 2018* Accepted: *25 July 2018* Published: *17 August 2018*

#### Citation: