A versatile, interactive model to predict geographically resolved epidemic progression after pathogen introduction into a population is presented. Deterministic simulations incorporating a compartmental disease model run rapidly, facilitating the analysis of mitigations such as vaccination and transmission reduction on epidemic spread and progression. We demonstrate the simulation model using rinderpest infection of cattle, a devastating livestock disease. Rinderpest has been extinguished in the wild, but it is still a threat due to stored virus in some laboratories. Comparison of simulations to historical outbreaks provides some validation of the model. Simulations of potential outbreaks demonstrate potential consequences of rinderpest virus release for a variety of possible disease parameters and mitigations. Our results indicate that a rinderpest outbreak could result in severe social and economic consequences.

#### Edited by:

Douwe Bakker, Independent Researcher, Leystad, Netherlands

#### Reviewed by:

Andrea Apolloni, Centre de Coopération Internationale en Recherche Agronomique Pour le Développement (CIRAD), France Jarkko Niemi, Natural Resources Institute Finland (Luke), Finland

\*Correspondence:

Judith R. Mourant<EMAIL_ADDRESS>
#### Specialty section:

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

Received: 01 November 2017 Accepted: 17 July 2018 Published: 03 September 2018

#### Citation:

Mourant JR, Fenimore PW, Manore CA and McMahon BH (2018) Decision Support for Mitigation of Livestock Disease: Rinderpest as a Case Study. Front. Vet. Sci. 5:182. doi: 10.3389/fvets.2018.00182

Keywords: rinderpest, mechanistic model, spatial model, vaccination, culling, epidemic, mitigation

# 1. INTRODUCTION

Rinderpest has been among the most devastating livestock diseases in history (1, 2). Rinderpest virus is a virulent and highly contagious pathogen that infects many cloven-hoofed livestock and wildlife species, resulting in death rates as high as 90%. Rinderpest has ravaged cattle populations in Europe, Asia, and Africa over several centuries. Use of highly effective vaccines in the context of regional and national zoosanitary control and eradication efforts led to a world-wide effort for eradication beginning in 1994. The last wild case was reported in 2001 and rinderpest was declared officially globally eradicated in 2011. It is the first animal pathogen and only the second pathogen (after smallpox virus) that has been eradicated.

While rinderpest does not exist in the wild, several countries maintain rinderpest samples and vaccines as a hedge against reintroduction (3), although this number is decreasing with 3 African countries removing their stores in 2016 (4). Current maintenance of virus and vaccine stocks is a balancing act between risk and reward. The primary purpose of the modeling presented here is to provide quantitative assessment of the consequences of virus release.

Past and potential rinderpest outbreaks are modeled as single epidemic entities amenable to control by a single vaccine, and with a reasonably well-defined presentation and progression of disease. The rinderpest virus is an RNA virus, a member of the morbillivirus family; Measles virus is related by divergence in the historical era (5). Several biological features support modeling rinderpest disease as a single epidemic entity. The phylogenetic diversity of the virus is not recognized to contain distinct clades. The empirical observation that vaccination using a single strain is an effective population-level control, coupled with the comparative ease of diagnosis in advanced disease, suggests low phenotypic diversity.

One of the crucial lessons that underpins our approach to modeling rinderpest in this paper is the importance of distinguishing epidemic growth due to spread in new locations vs. continued growth in areas of older infection. This observation may seem self-evident, but consideration of past analyses (e.g., Ebola in West Africa in 2014–2015), demonstrates that models which inappropriately aggregated geography can mask vital dynamics of mitigation and disease control in areas of older infection by relatively uncontrolled epidemic growth in areas of recent infection. A number of technical choices in the formulation of our decision-support oriented epidemiological model are driven by the critical importance of separating geography (see section 2.3) from temporal dependence. Making this separation in a robust way allows for far more reliable differentiation between the fundamental processes of contagion and disease progression, and the human interventions and actions that modulate those dynamics. In the modern world, it is these modulations that determine the outcome of epidemics. Aiding the analyses of interventions is the central challenge of epidemiological decision support, and provides the chief drivers for the design of our model in this paper.

The simulation model includes rinderpest disease progression, geographic spread, and the ability to perform historically successful mitigations such as vaccination, culling, and transmission reduction. Both a deterministic and a hybrid stochastic-deterministic version were developed. Challenges in developing compartmental, deterministic models arise from fractions of animals present in compartments–particularly at the start of disease progression in a geographical region. Similarly, fractions of animals can cause deterministic methods to have difficulty modeling extinction events (6). Spread can occur too rapidly and vaccination appears less effective because tiny fractions of individuals can start an outbreak in a new location in deterministic SIR-type models. This drawback of deterministic models was avoided by choosing a threshold for the number of exposed individuals required to start disease propagation in a geographic region. The exact value of this threshold was determined by calibration with the hybrid stochastic-deterministic model.

We first provide an overview of historical rinderpest outbreaks relevant for predicting a novel outbreak in a naïve population outlining important factors determining the scale of consequence as impacted by various mitigations. The epidemic model is then described in detail with a discussion of its accuracy and limitations. Possible outcomes resulting from reintroduction scenarios of the rinderpest virus are presented and discussed.

## 1.1. Historical Perspective of Rinderpest Outbreaks

We guide our modeling of rinderpest outbreaks in immunologically naïve cattle populations with consideration of historical examples provided in reviews (1, 7, 8). In reviewing this history, we pay particular attention to the rate at which the geographic extent of the epidemic increases, the overall mortality rate, and the circumstances under which the epidemic was ultimately brought under control.

In 1715, Giovanni Lancisi demonstrated effective control of rinderpest outbreaks in areas of Papal Authority through zoosanitary controls (7), such as effective separation of sick and healthy animals including removal of healthy cattle from pastures where sick animals previously resided, fumigating the clothes of shepherds, burial of carcasses in deep pits, and instantly throwing milk from sick cows into a hole in the ground. The killing of animals was preferred over treatment (9). The ability to stop a small outbreak via culling and zoosanitary methods was also demonstrated by control of a 1923 outbreak in Australia through slaughter of 3,000 cattle, sheep, goats, and pigs (10).

A particularly devastating epidemic, The Great Rinderpest Pandemic of ∼1887–1898, was the first in Africa (11) and is described in detail by several authors (1, 11, 12). In eastern Africa, cattle mortality rates were 98% (12) and the Massai (Masai) were devastated by the almost complete loss of their cattle (1, 11). The epidemic spread many hundreds of miles in a single year, whether inland to the Sudan from the coast, from Kenya into Tanzania, or through Zimbabwe into South Africa (1, 11). After being stopped by the Zambesi river for ∼3 years, rinderpest crossed the river and spread rapidly toward South Africa at a rate of 20 mi/day (32 km/day), roughly equal to the distance an ox cart traveled in a day. Control methods of fencing, safety corridors, armed border police, and slaughter by government order (with compensation) were implemented in Transvaal and Cape Colony (South Africa). However, by late 1896 these methods were failing (12). Research into vaccine development in South Africa led to the development of a bile and serum vaccine in 1897 that had some efficacy(12).

Motivated by this pandemic, and numerous other epidemics throughout Europe, Africa, and Asia, both vaccines suitable for mass vaccination, and molecular diagnostic techniques were developed throughout much of the twentieth century (7, 13). An intensive vaccination program in China from 1950 to 1955 combined with zoosanitary measures successfully eradicated rinderpest from China (7). In other locations, however, vaccination led to tremendous reduction in rinderpest cases, followed by a later resurgence due to incomplete eradication. Joint Project 15 (JP-15) operated in the the field in Africa from 1962 to 1976 involving 22 African countries, 17 of which had active rinderpest (14, 15). This vaccination program eliminated rinderpest from large portions of Africa. However, at its end, small pockets of rinderpest existed in both east and west Africa (1, 16). By the early 1980's these pockets had expanded to cover most of sub-Saharan Africa (1) and expensive international emergency efforts were needed to bring them under control (1, 13).

The 1994 outbreak in the Shangri-La region of Pakistan (17) shows how difficult it can be to extinguish a rinderpest outbreak in the modern era without ongoing vigilance of vaccine quality and communication and education of appropriate hygienic measures to the afflicted population. Fortunately, the inaccessibility of the region, relatively low cattle population densities, and potentially the mild pathogenicity of the viral strain, kept this outbreak confined over the 18 months it took to effectively respond and extinguish this epidemic. Nevertheless, > 80% mortality rates were noted in most affected regions (17).

While some of the more dramatic epidemics were due to strains of high virulence and high reproductive number (R0), both R0 and virulence vary across rinderpest strains. Endemic propagation of rinderpest leads to the dominance of milder strains of the virus with both lower virulence and R0 (18–20). Estimates of R0 over the different strains range from 1.2 to ∼5 (19).

#### 2. METHODS

To facilitate exploration of the effects of different disease parameters and the utility of a variety of mitigations, the model has been implemented as an interactive application using the Shiny package of R. The code can be found at https://github.com/ pfenimore/rinderpest.

#### 2.1. Disease Progression

For clarity, the disease progression model is first described for a single, well-mixed geographical area without spatial spread. **Figure 1** is a schematic of this disease progression with vaccination; culling is omitted. The corresponding differential equations governing the deterministic model, with culling included, are Equations 1–8. β is the transmission parameter with units of inverse time. The subscripts for disease progression rates are the starting and ending states, e.g., kIH is the rate of going from the infectious and mildly ill state, I, to the seriously ill state, H. The rate susceptibles move to the vaccination-given category is kV. Cattle in states S, E, I, and H can be culled (not shown in **Figure 1**). The rate of culling from state H is kHc. The total number of live cattle is N.

$$\frac{d\mathcal{S}}{dt} = -\beta \frac{(I+H)}{N} \mathcal{S} - k\_V \mathcal{S} - k\_{\mathcal{S}c} \mathcal{S} \tag{1}$$

$$\frac{dE}{dt} = \beta \frac{(I+H)}{N} (\mathbb{S} + V\_{\mathbb{S}}) - k\_{El}E - k\_{Ec}E \tag{2}$$

$$\frac{dI}{dt} = k\_{EI}E - k\_{IR}I - k\_{IH}I - k\_{Ic}I \tag{3}$$

$$\frac{dH}{dt} = k\_{\rm H}I - k\_{\rm HD}H - k\_{\rm Hc}H - k\_{\rm HR}H \tag{4}$$

$$\frac{dD}{dt} = k\_{HD}H + k\_{Sc}S + k\_{Ec}E + k\_{Ic}I + k\_{Hc}H \tag{5}$$

$$\frac{dR}{dt} = k\_{IR}I + k\_{HR}H \tag{6}$$

$$\frac{dV\_{\mathcal{g}}}{dt} = k\_{V}\mathcal{S} - \beta \frac{(I+H)}{N} V\_{\mathcal{g}} - k\_{V\_{\mathcal{g}}V\_{m}} V\_{\mathcal{g}} \tag{7}$$

$$\frac{dV\_m}{dt} = k\_{V\_\mathcal{S}V\_m} V\_\mathcal{S} \tag{8}$$

#### 2.2. Values of Disease Progression Parameter

Incubation period is defined as the time between inoculation and virus secretion. Rinderpest virus can be shed a day or two before the onset of fever (21), but the level is low and shedding occurs

only in a minority of animals (20). Consequently, the incubation period is taken as the time from inoculation to onset of fever. Rossiter and James give a value of 5.6 days (20). States I and H are both infectious, with I denoting the non-specific, nonsevere stages of disease and H denoting severe disease. State H is defined as the infectious period after onset of characteristic mouth lesions.  For cattle with a virulent strain, these lesions become common roughly 3–5 days after fever onset (21).

Disease progression has varied between locales where the virus was present (19). In **Table 1**, the parameters used for our simulation of the 1994 Pakistan epidemic are shown along with parameters for two of the last lineages to be eradicated (19). Lineage-1 was considered to be of moderate virulence and was at one time widespread in Africa. Lineage-2 caused mild disease and was also present in Somalia. The values for time spent in states I and H in **Table 1** are set to be similar to the total time spent in state I in the SEIR model of Mariner et al. (19) for lineages 1 and 2. Mouth lesions last 3 or more days (21), however, for less virulent strains a minority of animals (∼20%) do not develop mouth lesions (20). Consequently, the extra time in the infectious state of the less virulent strains is assigned to state I rather than state H. The fraction of rinderpest infected cattle that die varies greatly with strain, increasing from ∼2 to ∼90% with virulence (20).

#### 2.3. Geographic Spread

Geographic spread is primarily modeled as being due to the movements of cattle and people directly caring for the animals. Spread to market locations can be modeled also. Only for the model of the outbreak in Pakistan is movement along roads modeled. In this section, the methods for modeling spread due to everyday activities as well as to market locations are described.

After initial incidence at a point location, disease spread is implemented on a geographic grid of cattle population with the center block containing the initial point of incidence. Geographic spread of disease is approximated as a force of infection communicating between geographical compartments. The population does not move between compartments (i.e., population grid elements). For illustrative purposes, a simple

TABLE 1 | Rinderpest disease progression parameters.

geographic grid with 25 blocks is shown on the left in **Figure 2**. (Note: only the grid is shown, population values are not). For the disease to spread out of the initial geographic block, some of the healthy animals in surrounding geographic blocks must be exposed to rinderpest virus. The form of the spatial spread is assumed to be similar to that of foot and mouth disease (FMD) which, as another animal disease affecting livestock, has similar spread mechanisms. The ability of FMD to spread from one location to another is known to decay rapidly with distance when movements of animals between farms and to markets is highly restricted (22, 23). We approximate this decay as exponential with distance and an example of this transmission kernel is shown on the left in **Figure 2**. For each block a one dimensional column in the contact-availability array is computed. In this example, a 25 by 25 matrix, A, is generated.

The contact-availability, A(i, j), of virus from an infectious population of animals in block j, to animals in block i is controlled by the exponentially decaying transmission kernel. Therefore, the spatial extent of the receiving block must be taken into account. This is done approximately as shown below,

$$A(i,j) \propto \int\_{r(i,j)-\mathrm{b}/2}^{r(i,j)+\mathrm{b}/2} e^{-\varkappa/\mathrm{d}} d\varkappa = 2\mathrm{d}e^{-r(i,j)/\mathrm{d}}\sinh(\frac{\mathrm{b}}{2\mathrm{d}}) \tag{9}$$

where b is the size of a square block as defined in **Figure 2 (left)**, r(i, j) is the center-to-center separation of blocks i and j, and d is the characteristic length of the exponentially decaying transmission kernel and has a value of 3 in **Figure 2 (right)**.

For r(i, i) = 0, the contact-availability is

$$A(i,i) \propto 2\mathbf{d}(1 - e^{-\mathbf{b}/(2\mathbf{d})}) \tag{10}$$

The total contact availability of an animal should not depend on grid size, b. We also assume that total contact availability is independent of d and normalize it to 1. Therefore, we need,

$$\sum\_{i=1}^{n} A(i,j) \le 1\tag{11}$$

where n is the number of blocks in the grid. Pn i=1 A(i, j) will be less than one if there is significant availability outside of the geographically modeled region. To facilitate normalization of the contact availability matrix, A(i, j), the simulations should be setup such that the transmission kernel for the center box decays to approximately 0 at the edges of the modeled region. In practice, if the smallest dimension of the modeled region is 2w, w ≫ d. Therefore, the sum of all elements of the contact-availability matrix for the center block, j = c, is used to normalize the contact-availability matrix.

$$\sum\_{i=1}^{n} A(i, \mathbf{c}) = \sum\_{i \neq c} 2de^{-r(i, \mathbf{c})/\mathbf{d}} \sinh(\frac{\mathbf{b}}{2\mathbf{d}}) + 2\mathbf{d} (1 - e^{-\mathbf{b}/(2\mathbf{d})}) \tag{12}$$

In addition to the non-directional spread described above, directional spread is also implemented; a location of a feed-lot, or market can be specified. The fraction of infectious spread that is directional, fD, is also specified by the user. If there is only one location that is a gathering point, e.g., a feedlot, then, a long distance contact availability array, Di,j can be defined as,

$$D(i = \text{feedlot}, j) = f\_D \quad D(i \neq \text{feedlot}, j) = 0 \tag{13}$$

More generally,

$$\sum\_{i=1}^{n} D(i,j) = f\_D \tag{14}$$

The total contact availability matrix is then,

$$T(i,j) = (1 - f\_D)A(i,j) + D(i,j) \tag{15}$$

and

$$\sum\_{i=1}^{n} T(i, j) = (1 - f\_D) \sum\_{i=1}^{n} A(i, j) + \sum\_{i=1}^{n} D(i, j)$$

$$= (1 - f\_D) \sum\_{i=1}^{n} A(i, j) + f\_D \le 1 \tag{16}$$

a distance, x, away. The width of the geographic boxes, b, is 10 and the decay of the transmission kernel is 3.

#### 2.4. Mitigations

Several mitigations are implemented by time-dependent adjustment of rates in Equations 1–8; transmission control, vaccination, and culling. Mitigation implementation times are referenced to the time of disease identification. The disease is identified when the number of cases supersedes a set number specified by the user.

Transmission control reduces the interactions of virusfrom infectious cattle- with healthy cattle. It is implemented as a reduction of β. This mitigation can represent, for example, keeping animals in different stalls (i.e., short range movement control) or improved hygiene by the people caring for the animals. The fraction of spread that is due to long range (directional) movement can be reduced. This could represent a ban on the transport of animals to feed-lots or markets.

Vaccination or culling is performed within user defined rings around each block containing symptomatic animals (states I, and H, but not E). The assumption is that once rinderpest has been detected, farmers and veterinarians will be on the lookout for animals with early symptoms. The list of geographical blocks where vaccination or culling is desired is updated once a day.

The number of vaccine doses which can be given in a day, Vd, is a user input. In scenarios for which there is not enough vaccine to vaccinate all of the healthy population within a given radius of symptomatic cattle, an equal fraction of cattle are vaccinated in each of the chosen geographic blocks.

The rate for vaccination in a specific location is kV(i), where i is the index for a geographic box. In a time step, ts , with units of days, the number of doses available is Vdts . The total number of cattle available for vaccination, St , is the sum of all susceptible cattle in the region chosen for vaccination. The number of doses administered in a geographic box, i, is then VdtsS(i)/St . We assume that vaccination rates are much faster than the rate at which animals get sick and that culling and vaccination do not occur simultaneously in the same location. The expression for kV(i) assumes that S(i) decays exponentially with decay constant kV(i). The change in susceptibles, 1S(i), equals the number of doses administered and is given in Equation (17).

$$V\_d t\_s \mathcal{S}(i) / \mathcal{S}\_t = \Delta \mathcal{S}(i) = \mathcal{S}(i) (1 - e^{-k\_V(i)t\_i}) \tag{17}$$

Therefore,

$$k\_V(i) = \log(1 - V\_d t\_s / \mathcal{S}\_t) / t\_s. \tag{18}$$

However, if the total number of doses available in a time step is greater than the number of susceptibles needing vaccination, i.e., Vdts/St > 1, this formula fails. In that case, we choose to leave an insignificant fraction of a susceptible unvaccinated. Then

$$S(i)e^{-k\_V(i)t\_s} = 0.0001 \qquad \text{and} \qquad k\_V(i) = -\log(0.0001/S(i))/t\_s \tag{19}$$

As with vaccination, culling can be performed in and around geographic blocks that have a symptomatic population including infectious and/or very ill animals. The user has the choice of culling all seriously ill animals (state H), all infectious animals (states I and H), or all animals in states S, E, I, and H. When there are not enough resources to cull all of the chosen animals, the choice of which animals to cull is done analogously to the methods for vaccination.

#### 2.5. Governing Equations

In the geographically-resolved simulation with transmission control, the governing equations for box (grid element) i are given below where cm is the fractional reduction in β due to mitigation, and r is the fractional reduction in directional spread. We assume that cattle in state H are too sick to move around and hence do not infect cattle in other geographic areas.

$$\frac{d\mathbf{S}(i)}{dt} = -k(i)\mathbf{S}(i) - k\_V(i)\mathbf{S}(i) - k\_{\mathbf{S}c}(i)\mathbf{S}(i) \tag{20}$$

$$\frac{dV\_{\mathcal{S}}(i)}{dt} = k\nu(i)\mathcal{S}(i) - k(i)V\_{\mathcal{S}}(i) - k\_{V\_{\mathcal{S}}V\_{m}}V\_{\mathcal{S}} \tag{21}$$

$$\frac{dV\_m(i)}{dt} = k\_{V\_\mathcal{g}V\_m} V\_\mathcal{g}(i) \tag{22}$$

$$\frac{dE(i)}{dt} = k(i)(S(i) + V\_{\mathcal{g}}(i)) - k\_{El}(i)E(i) - k\_{Ec}(i)E(i) \tag{23}$$

$$\frac{dI(i)}{dt} = k\_{EI}(i)E(i) - k\_{IR}I(i) - k\_{HI}I(i) - k\_{Ic}(i)I(i) \tag{24}$$

$$\frac{dH(i)}{dt} = k\_{IH}I(i) - k\_{HD}H(i) - k\_{HR}H(i) - k\_{HC}(i)H(i) \tag{25}$$

$$\frac{dD(i)}{dt} = k\_{HD}H(i) + k\_{\text{Sc}}(i)\text{S}(i) + k\_{\text{Ec}}(i)E(i) + k\_{\text{Hc}}(i)H(i) \tag{26}$$

$$\frac{dR(i)}{dt} = k\_{IR}I(i) + k\_{HR}H(i) \tag{27}$$

where,

$$k(i) = c\_m \beta \frac{1}{N(i)} \sum\_{j=1}^{n} [(1 - rf\_D)A(i, j) + rD(i, j)]I(j) + H(i) \tag{28}$$

and

$$k\_{EI}(i) = \begin{cases} k\_{EI}, & \text{if } E(i) > 0.3/(26km^2) \\ 0, & E(i) \le 0.3/(26km^2) \end{cases} \tag{29}$$

#### 2.6. Deterministic Computational Method

The rate coefficients, kIR, kIH, kHD, kHR do not vary with geographic location. kEI(i), however, depends on location. If the exposed population of cattle is less than a threshold value in a grid element, i, then kEI(i) is set to 0 in that block and there is no disease progression. Accumulation into E(i) however can continue and may lead to disease progression in the grid element at a later time. This restriction on disease progression prevents a miniscule amount of infection from sparking a new location of incidence. **Figure 3** demonstrates that the threshold population needed for disease progression in a grid element can have a large effect on whether mitigations are effective. The value of the threshold population was chosen by matching results of hybrid (section 2.7) and deterministic simulations as discussed in section 2.9.

Linearization of the contagion term in Equation 28 allows us to solve Equations 20–27 as a stepwise eigenvalue problem. We integrated the time-dependent dynamics this way because thresholding the accumulation of initial cases in a geographical cell (Equation 29) makes the net system dynamics integrodifferential, obviating proofs of robustness for standard ODE solvers. The eigenvalue solution – in contrast to standard (polynomial) differential equation solvers, has a compact, welldefined inverse Laplace transform, preserving the rate-process structure of most terms in the epidemic model.

Because the k(i) are not constant during each time step, trapezoidal integration is used to improve the approximation. Approximate values of I, H and N at the end of the time step are first determined using kstart. These values are then used to determine kend. The values for all states at the end of the time step are then calculated using k = (kend + kstart)/2.

#### 2.7. Hybrid Deterministic-Stochastic Computational Method

Disease progression for geographic boxes in which the number of infected animals is <50 is performed stochastically using Gillespie's τ -leap method (24). For example, to calculate the S → E transition, k(i) is calculated using Equation 28, then the number of animals transitioning from S → E is calculated by sampling a Poisson distribution with λ = k(i)S(i)ts , where ts is the time step. The other transitions are calculated analogously.

#### 2.8. Initial Conditions

Initial cattle population data are from the Food and Agriculture Organization of the United Nations (25).

A single case of a disease does not always lead to an epidemic. The hybrid method captures this variability when started with a single exposed animal. The goal of this work is to determine what happens when an epidemic is started due to release of rinderpest virus. Therefore, the simulations start with a sufficient number of cases so that rinderpest is very likely to progress for several weeks. The number of starting cases is below the detection threshold that can trigger user specified mitigations. The relative number of cases in each state is based on the disease progression parameters. Specifically lineage-1 is started with 6 animals in state E, 2 in state I, and 1 in state H. Lineage 2 is started with 3 animals in state E, 2 in state I and 2 in state H. When the Pakistan 1994 parameters are used, the simulation is started with 3 animals in E, 2 in I and 1 in H.

#### 2.9. Setting the Timestep and Exposed Population Density Threshold

The timestep for the solution of the differential equations has to be set so that nearly identical answers are obtained if any shorter time step is used. Cumulative cases were simulated using different time steps for the lineage-1 and lineage-2 disease transmission and progression parameters in **Table 5** and for two population densities. The agreement between the hybrid simulations, which use a stochastic computation when the number of diseased animals in a grid element is small, and the wholly deterministic simulations is quite good over this large range of parameters as shown in **Figure 4**. For time steps of 0.02 and 0.05 days the deterministic results are within the errors of the hybrid simulation results. Therefore, the threshold population density needed in the exposed state of 0.3 exposed cattle per 26 km2 is used for all deterministic simulations. The deterministic results show very little change over a range of 0.01–0.2 day time steps, with the biggest difference in results being 0.36%. Consequently, a time step of 0.2 days is used when deterministic simulations are run. A time step of 0.05 days is used when hybrid simulations are used.

#### 3. RESULTS

#### 3.1. Simulating Historical Outbreaks 3.1.1. 1994 Rinderpest Outbreak in Pakistan

A severe epidemic of rinderpest afflicted northern Pakistan in 1994–1995 (17). The disease was recognized during the first 6 months of the epidemic. At least 40,000 animals died and possibly red curve.

as many as 50,000, approximately 7,000 of which died in the first 5 months. The first reported case was in Parri, a village south of Gilgit, in March 1994. Morbidity rates were near 100% in villages where animals were not vaccinated. The Pakistani government confirmed that the disease was rinderpest in August. Vaccination also began in August, but some of the vaccine used was later found to be subpotent and many vaccinated animals were afflicted by rinderpest. By October, rinderpest was prevalent in the upper Indus watershed including the Hunza and Gilgit valleys1 (17). The FAO and European Union then provided nearly 4 million vaccine doses. However, due to the onset of winter and poor road conditions, only limited vaccination was TABLE 2 | Pakistan Rinderpest outbreak 1994–1995: Parameters.

\*Assuming the epidemic started in the beginning of March.

performed. A final vaccination effort was started in April 1995. The outbreak ended in a village to the west, Khaplu, in November 1995 (17).

In the 1994 Pakistan outbreak, the infection moved along the roads as cattle were taken to market or to relatives. Therefore long distance movement was modeled by having the epidemic moving along the roads. The road data were taken from the OpenStreetMap project2 . The cattle trade in this region is directional, with cattle rarely traveling south from the junction of the Gilgit with the Indus river (personal communication, Paul Rossiter). Consequently, southern movement of the epidemic along roads south of this junction was forbidden in the simulation.

For the first ∼160 days of the simulation, March–August of 1994, no vaccination is performed in accordance with known facts about the epidemic. Subsequently, vaccination is performed at a rate of 200 effective cattle vaccinations per day with a

1The World Without Rinderpest. Available online at: http://www.fao.org/docrep/ 003/w3246e/W3246E06.htm (Accessed February 2016).

2Available online at: http://download.geofabrik.de (Accessed January 16, 2016).

vaccination ring of 30 km to simulate the use of subpotent vaccine. When more effective vaccine did arrive, winter had set in and only limited vaccination was performed. Consequently, we continue at a rate of 200 effective vaccinations per day until the simulation ends in mid-winter.

Short range, isotropic movement was modeled with an exponentially decaying function with a decay constant of 1.5 km. Movement along the roads was always in a distance range of 28– 42 km. The percentage of disease spread occurring via the road network is initially 0.5%. However starting in September 1994, the amount of long distance spread is reduced by a factor of 5 under the hypothesis that if people couldn't move around very well to vaccinate cattle, the virus was not spread long distances either. Parameters are summarized in **Table 2**. Gridded cattle population data from the Food and Agriculture Organization of the United Nations (25) were reduced by a factor of 1.3 to account for the increase in population between 1994 and 2005 (26).

With so many cattle in the area dying it is expected that hygiene would be improved even before confirmation that the disease was rinderpest and the commencement of vaccination. However, reports from the time indicate that hygiene was generally poor (17). Consequently, β is reduced by 20% only 30 days before vaccination is begun.

The results of the simulation are consistent with known features of the epidemic. After week 20 of the simulation, i.e., in August 1994, ∼7,300 cattle are dead consistent with the ∼7,000 reported by Rossiter (17). Furthermore, **Figure 5** shows that rinderpest was prevalent in the Hunza and Gilgit valleys as reported. At the end of the 41st simulation week, there are ∼42,500 dead animals consistent with an end number of ∼50,000 or less in Nov. of 1995 following a summer of effective vaccination. Therefore, geographical and temporal spread are satisfied simultaneously with reasonable parameterization.

#### 3.1.2. Fremantle, Australia: Control by Culling and Quarantine

The 1923 outbreak in Fremantle, Australia near Perth was controlled by culling and quarantine (10). To roughly model this

#### TABLE 3 | Fremantle parameters.

\*Rounded to the nearest hundred. And still increasing.

outbreak, a rinderpest epidemic starting just north of Fremantle was simulated. Since no specific information is available on the value of β, we assumed β = 1 as a stringent test of whether the epidemic could be extinguished with culling and transmission control. Mitigations began 2 days after disease detection. Culling was performed at a total rate of 1,500 animals per day with the culling radius set at 7 km and a 1 day delay between animals becoming infectious and when they are culled. Quarantine was modeled as a factor of 2 reduction in transmission. The parameters are in **Table 3**. The starting cattle population in **Figure 6** shows that the population density is low with most of the cattle in a very localized region.

Culling alone was able to extinguish the epidemic as shown in **Table 4**. With the addition of quarantine (50% transmission reduction), the epidemic was extinguished with fewer dead cattle. This level of transmission reduction alone does not end the epidemic. Without culling, the outbreak would continue and many more cattle would die after the 10 week simulation period. In the 1923 outbreak, ∼3,000 animals were culled. This smaller number of culls is likely due to the lower animal population in 1923.

#### 3.2. Simulation of Rinderpest Virus Release in a Naïve Population

Nine regions around the world with varying population densities were modeled to understand potential epidemics resulting from the introduction of rinderpest into a naive population. The ¨ regions were chosen to have relatively uniform population densities and a few examples are shown in **Figure 7**.

Rinderpest varies in virulence (20), consequently simulations were performed with several parameter sets. Parameters of the strain in the 1994 Pakistan outbreak and lineage 1 and 2 from Mariner et al. (19) are shown in **Table 5**. For all simulations the characteristic distance for spreading was 1.3 km and the characteristic time for the vaccine to become effective was 5 days.

#### 3.2.1. Uncontrolled Release

Cumulative case counts at the end of simulations are shown as a function of population density in **Figure 8**. Simulations with lineage-1 parameters were run for 5 weeks, while simulations with lineage-2 parameters were recorded for 5 and 30 weeks. When case counts are low as for the 5 week simulations using lineage-2, the results are nearly independent of initial populations because S/N is approximately 1 (See Equations 20, 28, 23). However, when case counts rise and S/N falls in the lower population regions, a strong dependence on population density is seen; the lineage-1 results at 5 weeks and the lineage-2 results at 30 weeks in **Figure 8**.

Before rinderpest is detected it could spread to locations distant from the original outbreak. This type of spread occurred in the 2001 FMD outbreak (27). Once rinderpest is detected, we assume that long distance movement of cattle will be banned (and stopped). Nonetheless, the initial spread leads to a more rapidly progressing epidemic. The open circle in **Figure 8** demonstrates this increase at 5 weeks for lineage-1 parameters when 1% of the spread is to long distance locations until long distance movements are stopped 2 days after rinderpest is detected.

A final input to investigate is the characteristic distance of spread, d. Increasing d from 1.3 to 2 km increases the number of cases (after the start phase of the simulations) as shown in **Figure 9**. This increase is greater for areas with lower populations. This population dependence can be explained as the increased spread providing a larger susceptible population. The variation in the general trends are due to the fact that these real world populations are not homogeneous.

#### 3.2.2. Effects of Mitigations

Three mitigations are modeled: reduction in transmission, vaccination, and culling. As discussed in the historical perspective section, transmission can be reduced by better hygiene and by movement control. These measures can slow an epidemic, but do not extinguish it. Vaccination and culling both have the potential to extinguish an epidemic, but the the details of implementation

TABLE 5 | Simulation starting parameters.

are critical to both the success of the effort and the final impact of the epidemic. In the following we look at how the efficacy of mitigation is affected both by controllable parameters such as the number of vaccinations per day as well as by uncontrollable parameters such as population density and characteristic spread distance. Results are presented only for lineage-1 because the results are a more stringent test of a mitigations efficacy.

#### **<IP_ADDRESS>. Vaccination**

In the simulations, 10,000 doses were assumed to be available each day and the vaccination radius is set to 6 km. Vaccination started 7 days after the disease was identified which occurred after only 5 cattle showed clear signs of rinderpest. The length of time needed to extinguish the epidemic, the cumulative cases and the number of cattle immunized are given in **Table 6** for several different regions with varying average cattle population densities. Ending an epidemic solely by vaccination is more difficult in higher population density regions. For the highest population densities, these vaccination conditions were not sufficient to stop the epidemic. If highly effective transmission reduction, begun only 1 day after disease identification, is combined with these vaccination conditions, then the epidemic can be extinguished as shown on the right of **Table 6**.

The effect on epidemic progression of the start time for vaccination was studied. **Figure 10A** shows that for a region with a cattle density of roughly 68 cattle/km2 , the number of cattle immunized goes up rapidly with the delay in starting vaccination until the available 10,000 doses/day is not enough to control the epidemic. For a population density of 126 cattle/km2 which was shown as not controlled in **Table 6**, the epidemic can be controlled if the start delay is reduced from 7 to 5 days. The length of the epidemic is reduced further as the delay is decreased. For a population density of 150 cattle/km2 the epidemic can only be brought under control by vaccination alone if vaccination begins after a nearly impossible delay of only 2 days after detection. Clearly, the delay in starting vaccination is a critical parameter.

All the results thus far concerning vaccination have been obtained using a characteristic spread distance of 1.3 km. While this parameter can not necessarily be controlled as part of a mitigation, it is important to know how stable our results are to the variety of geographical spread conditions which may occur in different parts of the world. **Table 7** contains results for a spread distance of 2 km for the geographic area having an average population density of 68 cattle/km2 . With this increase in geographic spread, the epidemic can no longer be controlled by the same vaccination parameters used to obtain the results in **Table 6**. Rather, both the number of available doses and the radius around active cases where vaccination is performed must be increased.

#### **<IP_ADDRESS>. Vaccination with transmission reduction**

With extensive movement controls transmission of highly infectious diseases can be reduced by roughly a factor of 2 as was shown for FMD in an analysis of the 2001 outbreak (23). The right three columns of **Table 6** show that it is possible to extinguish a rinderpest epidemic with vaccination under nearly ideal circumstances; (i) the disease was identified when only 5 cattle had become seriously ill and before any infected animals were transported and the disease spread to distant locations, (ii) effective vaccination was begun 7 days after disease identification and veterinarians were able to vaccinate when and where needed, (iii) hygiene and movement control reduced transmission by a

long distance spread for lineage-1 at 5 weeks. The red open circle in (A) corresponds to results with the 1% spread to the four long distance locations shown in (B).

factor of 2 one day after disease identification. However, if some of the circumstances are not ideal, such as the disease spreading before identification and a delay in starting vaccination then the outbreak may not be extinguished. Even in a location of medium population density (68 cattle/km2 ) more resources are needed for greater vaccination delay and with a long enough delay the epidemic can not be controlled as shown in **Figure 10B**.

#### **<IP_ADDRESS>. Culling**

The potential to stop the lineage-1 strain of rinderpest by culling was examined for several areas with different population densities using the parameters from **Table 5**. The maximum rate of killing cattle was assumed to be 10,000 per day and cattle were culled regardless of disease state. The area of the geographic bins was reduced by a factor of 4 for this work, so that the radius of culls around an infectious grid element could be examined at higher resolution. In the initial examination of culling for control, the culling radius was set at 3 km, culling was started 7 days after the epidemic was detected, and the time between an animal becoming infectious and the start of culling in that grid element and the surrounding elements defined by the cull radius was set at 2 days. The left side of **Table 8** shows that culling with these fairly optimal parameters does not stop the epidemic in areas with high cattle population. When very effective transmission reduction is achieved starting only 1 day after disease detection, then culling can stop the epidemic albeit with large numbers of dead cattle that were never sick.

**Figure 11** demonstrates that the delay between when the first animal in a grid element becomes infectious and when animals in that grid element and the specified surrounding area are culled is a critical parameter determining how many animals must be culled before epidemic extinction. An increase in this local delay increases the number of animals that must be culled in order to extinguished the epidemic increases. Furthermore, in the presence of initial long distance spread, **Figure 11B**, the epidemic can not be controlled if the delay between when the animals become infectious and when animals in that grid element are culled is 2 days or longer.

The radius of culling around locations with identified cases is a very important practical parameter. Owners of livestock generally do not want to have their apparently healthy animals slaughtered. Culling only locations where animals are sick can extinguish low transmissibility strains such as lineage-2 (results not shown), but not high transmissibility strains such as lineage-1. However, even for the high transmissibility strains, the culling radius around identified locations with infected animals does not need to be large for the relatively small characteristic distances of spread likely to hold for livestock (especially under movement restrictions). A characteristic spread distance of 2 km is used in the investigations of culling radius and an area of 1◦ × 1.5◦ was modeled. The effects of increasing the cull radius depend critically on the delay between disease identification and culling as well as on slaughter and disposal resources. **Table 9** shows results for both a 7 day initial delay combined with a 3 day local delay, and a 3 day initial delay combined with a 4 day local delay. For these two scenarios different cull radii and limitations on

#### TABLE 6 | Extinguishing lineage-1 epidemics by vaccination.

\*Rounded to nearest thousand.

\*\*Rounded to nearest hundred.

NCThe epidemic is not controlled within 15 weeks.

extinguished. (A) No long distance spread and no transmission reduction. (B) Long distance spread is allowed to the locations shown in Figure 8B until 1 day after disease detection. Transmission is reduced by a factor of 2 also 1 day after disease detection.

available culling resources are considered. If an attempt is made to expand the culling area, but resources are inadequate to cull the entire area, then the number of dead animals can actually increase with "mitigation" if areas with infectious animals are not culled. If sufficient resources are available to cull the entire chosen area each day, then otherwise uncontrollable epidemics can be extinguished or reductions in the number of dead animals can be achieved. A consequence of this result is that a large cull radius is more important at the start of an epidemic when fewer resources are needed.

# 4. DISCUSSION

#### 4.1. Decision Support

Most epidemics begin with exponential growth until either there is a depletion of the susceptible population or control measures are put in place. A general scenario for incidence, cumulative cases and dead is shown in **Figure 12**. The first mitigation to be implemented for any disease is usually transmission TABLE 7 | Effects of vaccination radius and available doses for a characteristic spread distance of 2 km and average population density of 68 cattle/km2 .

\*Not controlled at 15 weeks.

reduction, often through better hygiene or separation of animals. Subsequently, either culling or vaccination is needed.

The 2001 European FMD epidemic provides insight into the practicalities of culling that are likely to arise if rinderpest were to escape from the lab. Nearly 600,000 cattle were slaughtered as a disease control measure in England (28). Based on the epidemic progression (28) and the dates when culling was performed on farms contiguous to infected farms, we estimate that the majority of culling took place over a 6 week period from about March 11th to April 29th and that on average 10,000 cattle were

#### TABLE 8 | Extinguishing epidemics by culling.

\*Rounded to nearest thousand.

\*\*Rounded to nearest hundred.

NCNot Controlled.

FIGURE 11 | For a fairly uniform population density of 68 cattle/km2 , the number of cattle that must be killed to extinguish an epidemic with culling depends on the delay between when the cattle at a location become infected and when they are killed. (A) No long distance spread and no transmission reduction. Area modeled is 0.8 × 0.8 degrees. (B) Long distance spread is allowed to the locations shown in Figure 8B until 1 day after disease detection. The epidemic can not be extinguished if the delay between when the cattle at a location become infected and when they are killed is 2 days or more. Area modeled is 1.3 × 2 degrees.

TABLE 9 | Number of dead cattle for different culling scenarios\* using a fairly uniform population density of 68 cattle/km2 .

\*The characteristic distance of spread was 2 km instead of 1.3 km as was used for most of the simulations.

culled per day. Both the Netherlands and the United Kingdom experienced difficulties in safely disposing of the carcasses (28, 29). Furthermore, there was significant resistance to culling from farmers (30).

In this work concerning rinderpest, the high culling rates of the FMD epidemic were used (10,000 /day). Even with an extremely rapid start of 5 days after disease detection, culling is unable to extinguish highly contagious epidemics at the highest

population densities. When culling does extinguish a weeks-tomonths old epidemic, the result can be hundreds of thousands of dead cattle that were never sick.

Vaccination has the advantages of being more farmer-friendly and has no carcass disposal problems, but requires a large ready supply of effective vaccine and a means to administer it. Simulations were performed assuming 10,000 vaccinations could be performed per day. This rate is not sufficient to stop epidemics of highly virulent rinderpest in the highest cattle population areas on earth. Only in combination with highly effective hygiene control that cuts transmission in half can vaccination end epidemics in these types of scenarios. The assumption of a 50% reduction in β is based on analysis of the 2001 FMD epidemic (23). However, this large reduction may not always be achievable (17).

The presented simulations of rinderpest epidemics in naïve populations demonstrate the importance of several skills and mitigation resources. (1) The rapid detection of a rinderpest outbreak. (2) The ability to stop the movement of cattle and prevent any (further) spread to distant locations. (3) The implementation of better zoosanitary hygiene and animal isolation. If vaccination is to be used to stop an epidemic, then the ability to start an effective vaccination program of up to 10,000 animals per day on only a few days notice is needed. If culling is to end the epidemic then other resources are needed; the ability to slaughter and dispose of up to 10,000 animals per day on short (1–2 days) notice including the ability to slaughter animals on proximate sites where no animals have been diagnosed.

History demonstrates that an outbreak of a serious and highly transmissible disease such as rinderpest is likely to have severe economic and sociological consequences. As noted in section 1.1, the rinderpest outbreak in the late nineteenth century caused famine amongst the Masai people of Africa (11). Livestock have considerable social value in some parts of sub-Saharan Africa as described by Catley et al. (31). Other parts of the world are not immune from the socio-economic consequences of livestock disease. The 2001 outbreak of FMD, another serious and highly transmissable livestock disease, caused economic hardship both for farmers with herds affected by infection and/or culling as well as for otherwise unaffected farms due to movement and trade restrictions (32). The epidemic was very costly with the UK Department of Environment Food and Rural Affairs (DEFRA) spending >£3 billion (33).

## 4.2. Comparison of Our Techniques to Other Modeling Methods

There is a significant body of work modeling the geographical spread of infectious disease. Much of the early work focused on spread between isolated cities and these models are sometimes referred to as metapopulation and/or patch models (34–36). However, in many areas of the world, human and animal populations are fairly contiguous and a model of well separated cites or farms is not appropriate. There is a large body of research on which transport model is best under which conditions (37, 38) and a conceptual analysis of process-driven (i.e., mechanistic) modeling frameworks has been published (39). Our rectangular tiling of population and spatial spread kernel are both simple to implement and understand. As noted in Mancy et al. (39), when working at the research–policy interface non-complex models have advantages if they can be implemented without sacrificing accuracy. Additionally, there is evidence that the exponentially decaying spread kernel is appropriate from the 2001 foot and mouth disease outbreak (22, 23).

This combination of gridded population data and a spatial transmission kernel has been previously used in modeling the spatio-temporal spread of epidemics. For example, models incorporating airline transport over the entire world have been developed (40, 41). The effects of pixel size in the grid have been investigated using a stochastic SIR model (42). A model of Rift Valley fever (43) and a model of rinderpest in the US (44) used deterministic progression and spread within "counties" combined with stochastic spread between "counties."

One of the challenges for deterministic models is constructing realistic spatially explicit models (45). The model presented here addresses that challenge without the considerable computational cost and large data requirements of agent-based models, nor the infinite spectrum of approximate eigenvalues in a non-linear partial differential equation. Our deterministic simulation can be run in seconds for an area of 88 × 88 km on a laptop computer. Therefore, effects of a variety of mitigations can be analyzed rapidly. A screen shot of the graphical interface is shown at the end of this paper (**Appendix**).

# 5. CONCLUSIONS

The described simulation methods can model the time course of historical data using the known mitigation methods and disease progression parameters. Additionally, the time-dependence of the geographic extent of the simulated epidemic compared with the known extent of the historical outbreaks provides significant further constraint of the model. This geographically-resolved epimodel, developed using historical data, provides information for present-day decision-support.

Mitigation of a rinderpest outbreak without serious or even devastating effects on human society depends on disease recognition when case numbers are still small, and requires a response in a few days or 1–2 weeks depending on the transmissibility of the virus and the cattle population density. Even large-scale, effective vaccination within a week of noticing 5 cattle seriously ill with rinderpest in the worlds densest cattle population areas will not eliminate the epidemic on a timescale of weeks to months for the most virulent strains. The outbreak of a virulent strain in an area of dense but reasonably common cattle population would lead to hundreds of thousands of dead cattle assuming a nearly optimal response. Mitigation of epidemics involving less virulent strains should be possible with culling or vaccination, particularly when combined with transmission reduction. Responding to an epidemic requires resources and constant preparation including; an established and highly functional veterinary infrastructure, resources for carcass disposal and a large stockpile of effective vaccines. The perceived benefit from continued storage of rinderpest virus must be considered in the context of consequences due to a potential release of an already eradicated disease.

#### REFERENCES

#### AUTHOR CONTRIBUTIONS

BM and PF had the original idea for the basic structure of the epidemiological model. They also wrote the first version of the code. JM has taken the original code and made substantial revisions to both the underlying mathematical structure and to the interface based on discussions with PF, CM, and BM. CM has made critical inputs regarding the inner workings of the algorithm.

#### ACKNOWLEDGMENTS

We would especially like to thank Dr. Paul Rossiter (UN/FAO) for his assistance with this work. His extensive knowledge of rinderpest was important in the development and testing of the model. We extend gracious thanks to Dr. Samia Metwally (UN/FAO) for inviting one of us, BM, to multinational forums discussing current storage and consolidation of rinderpest virus where we were permitted to present our results. We thank Aalder Dekker (UN/FAO) for feedback on early versions of the tool described in this paper. We thank Jeanne Fair for instigating the collaboration with the UN/FAO. Finally, Dennis DeRiggi's (Institute for Defense Analysis) feedback on the code and methods are also gratefully acknowledged. This work is supported in part by the U.S Defense Threat Reduction Agency through DTRA10027-13794 project CB10093, NSF/DEB SEES Grant CHE-1314029, and Los Alamos National Laboratory LDRD 20150090DR.

**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 Mourant, Fenimore, Manore and McMahon. This is an openaccess 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.

# Pathogenesis of *Mycobacterium bovis* infection: the Badger Model As a Paradigm for Understanding Tuberculosis in Animals

*Eamonn Gormley\* and Leigh A. L. Corner*

*School of Veterinary Medicine, University College Dublin, Dublin, Ireland*

Tuberculosis in animals is caused principally by infection with *Mycobacterium bovis* and the potential for transmission of infection to humans is often the fundamental driver for surveillance of disease in livestock and wild animals. However, with such a vast array of species susceptible to infection, it is often extremely difficult to gain a detailed understanding of the pathogenesis of infection––a key component of the epidemiology in all affected species. This is important because the development of disease control strategies in animals is determined chiefly by an understanding of the epidemiology of the disease. The most revealing data from which to formulate theories on pathogenesis are that observed in susceptible hosts infected by natural transmission. These data are gathered from detailed studies of the distribution of gross and histological lesions, and the presence and distribution of infection as determined by highly sensitive bacteriology procedures. The information can also be used to establish the baseline for evaluating experimental model systems. The European badger (*Meles meles*) is one of a very small number of wild animal hosts where detailed knowledge of the pathogenesis of *M. bovis* infection has been generated from observations in natural-infected animals. By drawing parallels from other animal species, an experimental badger infection model has also been established where infection of the lower respiratory tract mimics infection and the disease observed in natural-infected badgers. This has facilitated the development of diagnostic tests and testing of vaccines that have the potential to control the disease in badgers. In this review, we highlight the fundamental principles of how detailed knowledge of pathogenesis can be used to evaluate specific intervention strategies, and how the badger model may be a paradigm for understanding pathogenesis of tuberculosis in any affected wild animal species.

Keywords: tuberculosis, *Mycobacterium bovis*, badgers, pathogenesis, infection, vaccination

#### INTRODUCTION

The presence of tuberculosis in wild animals has attracted scientific attention primarily because they are implicated in transmission of infection to livestock and other economically important species, and the risk of zoonotic transmission to humans. In Ireland and the UK, the European badger (*Meles meles*) is the principal wild animal species involved (1, 2). Elsewhere, wild boar (*Sus scrofa*) (3), goats (*Capra hircus*) (4) and species of deer, notably red deer (*Cervus elaphus*), fallow (*Dama dama*),

#### *Edited by:*

*Javier Bezos, Complutense University of Madrid, Spain*

#### *Reviewed by:*

*Andrew William Byrne, Agri Food and Biosciences Institute, United Kingdom Bernat Pérez De Val, Centre de Recerca en Sanitat Animal, Spain*

> *\*Correspondence: Eamonn Gormley<EMAIL_ADDRESS>
#### *Specialty section:*

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

*Received: 27 October 2017 Accepted: 27 December 2017 Published: 15 January 2018*

#### *Citation:*

*Gormley E and Corner LAL (2018) Pathogenesis of Mycobacterium bovis Infection: the Badger Model As a Paradigm for Understanding Tuberculosis in Animals. Front. Vet. Sci. 4:247. doi: 10.3389/fvets.2017.00247*

and roe deer (*Capreolus capreolus*) are affected in continental Europe (5). In New Zealand, the brushtail possum (*Trichosurus vulpecula*) is the key species affected (6). In North America, whitetailed deer (*Odocoileus virginianus)* (7) elk (*Cervus canadensis*) (8) and bison (*Bison bison*) (9) are among the known reservoirs of infection. In Africa, many species of outstanding conservation merit are infected, posing a threat to the survival of local populations (10). With limited resources available to conduct surveillance programs, the gathering of basic information to develop an understanding of pathogenesis is rarely undertaken in natural-infected hosts. A key reason is often the physical size of the animal and the volume of tissues and specimens required to ensure maximum sensitivity and specificity of diagnostic procedures. Added problems include the availability of suitable samples and the potential for bias arising from misinterpretation of data because sampling is only from advanced disease cases or from cases identified by imperfect diagnostic tests.

There has been much written about the value of laboratory animals as surrogates in studying tuberculosis (11). This is mainly in the context of human tuberculosis where there is a drive to understand the host–pathogen interactions in great detail with a view to developing new therapies and vaccines (12). Those involved in trying to study the disease in a particular species are often reliant on information generated from laboratory animals, which may or may not be particularly relevant. Other than providing insights into pathogenesis at the animal level, laboratory animal models cannot contribute substantially toward understanding the epidemiology of human or animal tuberculosis at a population level. With the exception of the most commonly used laboratory animals, progress has also been hindered by the almost universal lack of reagents for specific animal species: this has constrained the development of diagnostic tests and limited the ability to understand how animals might respond to vaccines.

Nevertheless, animal models have been used extensively in tuberculosis research and proved invaluable in improving the understanding of pathogenesis and defining the subtle interactions between the pathogen and the host immune system (13, 14). The mouse model has been particularly useful and has revealed detailed functional information on many aspects of the host immunological responses to infection (15). The relative costs involved, the wide availability of immunological reagents, and the development of genetically modified lines have made the mouse model the pragmatic choice for many laboratories. However, the mouse is not considered to be a natural host for tuberculosis and study results often differ depending on the mouse strain used (16). This can be a cause for concern when extrapolating to different species. Other animal models including rabbits, guinea pigs, zebrafish, non-human primates, and cattle (a natural host of *M. bovis*) are all subject to the same constraints when applying the interpretation of the results across species (11). Notwithstanding the availability of reagents and the logistics and welfare of housing animals, there may be differences in the host response influenced by, for example, route of infection and pathogenesis. This all poses particular challenges for the study of tuberculosis in more exotic natural susceptible hosts and particular care needs to be taken to translate the results of studies from one model animal to another species. Key to this is deciding which pieces of information are relevant to the target species and how this can be used to develop a complete picture of the pathogenesis of infection. In Ireland, we have compared natural and experimental *M. bovis* infection models of badgers with a uniform level of postmortem examination, histology, and bacteriology. This has provided a unique opportunity to evaluate and gain insights into pathogenesis in both model systems.

#### TUBERCULOSIS IN BADGERS

The involvement of badgers in the epidemiology of tuberculosis in cattle is well established in Ireland and the UK (1, 17). Results from the four area badger removal trial in Ireland and the Randomized Badger Culling Trial (RBCT) in England provided evidence of a positive effect of badger culling on incidence rates of tuberculosis in associated cattle herds (18, 19). Arising from these studies, current policies to eradicate the disease are largely focused on surveillance testing of cattle supplemented with badger population control measures in areas of Ireland and England considered as high risk for cross-species transmission (1, 20). Analysis of *M. bovis* prevalence rates in approximately 5,000 badgers culled in Ireland in response to tuberculosis breakdowns in cattle herds has revealed a decrease in the overall prevalence from 26 to 11% between 2007 and 2011 (21). Nevertheless, large-scale culling is considered to be unsustainable in the long term, although it is recognized in Ireland, the UK, and other countries that eradication of tuberculosis in cattle is unlikely if the infection reservoir of *M. bovis* infection in badgers, and maybe other maintenance species, is not adequately addressed (22–24). The development of a vaccination strategy targeted at badgers is judged as a potentially feasible option; a key objective of vaccination is to reduce the transmission rate of infection within the badger population by reducing the level of susceptibility to infection or to alter the pathology of the infection in vaccinated badgers where protection is less than 100% to the extent that it decreases the rate of excretion of *M. bovis* and transmission to cattle (25). Until relatively recently there was limited detailed information relating to susceptibility of badgers to tuberculosis, and whether they were capable of resisting *M. bovis* infection through the generation of protective immune responses. A considerable body of research work has been carried out in Ireland and the UK to gain a greater understanding of the disease in badgers with the objective to develop and implement a vaccination strategy for badger populations (26). A critical step in this development stage is establishing a model system that closely mimics the natural infection state in free-living populations.

## PATHOGENESIS OF TUBERCULOSIS IN BADGERS

Insights into the pathogenesis and a baseline for the evaluation of experimental infection studies have been gained in badgers to a degree not previously undertaken in any other natural-infected species (27). Badgers are considered to be highly susceptible to *M. bovis* infection (28). As in many species, tuberculosis is principally a respiratory disease in badgers but in a naturalinfected population there appears to be a second route of transmission by contamination of bite wounds, which is less prevalent but still significant. Pulmonary infection is established following inhalation of infectious aerosols and this leads to protracted progression toward a clinical state of disease (29). Aerosol infection results in a chronic disease and infected animals can express a variety of disease states ranging from latent subclinical infection (i.e., no visibly detectable lesions or clinical manifestations of disease) to moderate disease (with size-limited pulmonary and extrapulmonary lesions) and to severe overt disease with generalized pathology. In the majority of aerosol-infected badgers, however, infection remains latent and the proportion of badgers that develop generalized disease is small (29, 30). By contrast, bite wound infection results in a more rapid and progressive infection with typically generalized infection and lesions (29, 31). Despite the absence of lesions in the majority of infected animals, badgers with any state of infection may pose a risk of transmission to susceptible hosts where there is close and frequent contact.

More refined insights into the pathology of disease have been revealed from detailed postmortem studies of culled badgers (31, 32). The sequence of events in the pathogenesis, including the early dissemination of infection from the lungs, is best demonstrated when the distribution of infection in the badgers is examined in a broad repertoire of anatomical sites (**Figure 1**). Gross visible lesions are commonly found in the thoracic cavity (lungs, tracheobronchial and mediastinal lymph nodes), with the head and body lymph nodes the most frequently affected extrathoracic sites. Visible lesions are scarce in the abdominal cavity; however, a broad range of tissues and organs may be infected. In badgers presenting with only a single site of infection, the distribution pattern is much the same as that in badgers with multiple infection sites. This could signify that host–pathogen interactions during the initial stages postinfection, rather than tissue predisposition, dissemination, or progression of disease, govern the infection distribution. Tuberculosis can also develop when bite wounds become infected with saliva containing infective bacilli. The spectrum of infected bite wounds can range from circumscribed subcutaneous granulomas, lacerated wounds

examined for gross lesions, and samples for histological/bacteriological examination during systematic detailed postmortem of natural-infected wild badgers. Reproductive tract tissues (not shown) were also examined (31).

draining abscesses, to large open ulcerated areas devoid of skin. The pathogenesis of infection following bite wound contamination differs from that after aerosol infection in that there is rapid progression of infection, a greater number of lesions, and wider distribution and severity of infection (27).

The presence of discrete tuberculous granulomas is the characteristic of infection in badgers as also occurs in other reservoir hosts including cattle (33), possums (34), and ferrets (35). These are composed largely of epithelioid cells, macrophages, and sporadic lymphocytes. Lesions are typically cellular and proliferative to a large extent, with limited necrosis, mineralization, or fibrosis (29, 36–38). Histologically, there is a wide variety in the size and structure of lesions present in an animal, and even in individual tissues (**Figure 2**). As the severity and size of lesions increase and the granulomas expands, the central mass of epithelioid cells increase and are enclosed by a peripheral rim of lymphocytes with the outer layer composed of macrophages and neutrophils, bounded by a narrow uneven fibroblast layer. As the infection progresses, lesions coalesce and may form large areas of necrosis

Figure 2 | Photomicrographs illustrating (A) three granulomas of varying size indicated by white arrowheads in a hyperplastic/reactive lymph node of a badger; (B) higher magnification image of one of these granulomas. Hematoxylin and eosin stains, magnification ×20 (A) and ×100 (B).

and caseastion, sometimes associated with mineralization. The presence of acid-fast bacilli (AFB) becomes more common as the area of necrosis increases and then may be extracellular. In lung lesions, there may be erosion of bronchi and bronchioles walls, and AFB may be present in cellular debris in the lumina.

The specific immunological responses to infection with *M. bovis* can also offer important insights into key aspects of pathogenesis. However, measurement of these responses in badgers or other wild animals can be problematic not only because of a lack of reagents but also the requirement to repeatedly capture and collect samples from animals. In an experimental setting, this is feasible and it is possible to monitor changes in responses as the infection progresses (39, 40) As in all species studied, the predominant early specific immune response following *M. bovis* infection of badgers is T cell-mediated (CMI), leading to proliferation of T lymphocytes, secretion of interleukin-2 (IL-2) and release of pro-inflammatory cytokines including interferon-γ (IFN-γ) (41–43). The responses can be measured *ex vivo* following antigenic stimulation of blood or purified peripheral blood monocytes with tuberculin or the specific mycobacterial antigens ESAT-6/CFP10 cocktail. Where longitudinal studies have been conducted in wild badgers, the strength of the initial IFN-γ responses correlates with the progression of infection (44). Serological responses are associated with a later stage of infection when visible lesions are likely to be present and severity of disease is high (45). The immune-dominant serological antigen is restricted to the mycobacterial antigen MPB83, although the sensitivity of detection of antibodies recognizing this antigen is relatively low across the full spectrum of infection severity (46, 47). The innate immune response to infection with tuberculosis is regulated through the activity of macrophages; the key cells that are permissive for the growth of intracellular mycobacteria. Activated macrophages produce reactive nitrogen intermediates that are directly inhibitory for the growth of a wide range of intracellular organisms including *M. tuberculosis* (48) and *M. bovis* BCG (49). Nitric oxide (NO) is produced through oxidation of L-arginine (50) in a reaction catalyzed by an inducible nitric oxide synthase (iNOS) (51). However, studies in badgers have revealed that blood monocytederived macrophages do not produce NO or upregulate iNOS expression following *in vitro* activation of macrophages (52). This intriguing finding might imply that badgers should lack the ability to control infection *via* the innate response, though there is no strong pathological evidence to support this.

#### EXPERIMENTAL INFECTION MODELS IN BADGERS

While the use of natural-infected animals has proved invaluable for investigating pathology across the broad spectrum of disease ranging from early infection to clinical disease, experimental models have the advantage of allowing study of the kinetics of disease progression and immunological responses starting from a fixed dose and a fixed point of time (28, 39, 40). This can facilitate reproduction of disease in a format necessary for the development of diagnostic tests and for evaluating vaccines. In order to understand fundamental aspects of pathogenesis, the experimental model needs to be framed around relevant infection routes, and plausible challenge doses that are reflective of natural transmission. The profile of infection that is generated should also be characteristic and consistent within the recognized spectrum of the naturally occurring disease. Principally, this requires evenness in the profile of lesion development and distribution of infection as found in natural *M. bovis* infection. In developing the badger infection model for tuberculosis in Ireland, the key factors that were considered to achieve this end were the choice of *M. bovis* strain, route of infection, the infective dose, and the kinetics of infection. The strain of *M. bovis* used for experimental infection was first isolated from a lesion in a clinically diseased badger (28). Spoligotyping revealed that the strain type was common in both infected badgers and cattle. In an initial study, the infective doses used were <10 colony forming units (CFU) (low dose), ~100 CFU (medium dose), and ~3,000 CFU (high dose) with delivery by the endobronchial route of infection, to mimic the dominant respiratory route of natural infection (28).

The results of this study showed that badgers were very susceptible to infection: all of the badgers had established infection across each of the doses used when animals were euthanized at 17 weeks postinfection (28). The results also demonstrated that the dose of *M. bovis* had a little effect on the distribution of infection but as the dose increased so did the rate of disease progression. There was a consistent profile of infection among the groups exposed to each dose according to the measures employed: distribution and number of lesions, severity score of gross lesions, distribution and number of infected tissues, levels of extrathoracic infection, and distribution and number of histological lesions. The inoculation resulted in a variety of infection states, ranging from latency (absence of gross lesions), to gross lesions in the lungs, draining and extrathoracic lymph nodes, and pleura. The experimental infections appeared to mimic the more severe end of the spectrum of lung disease found in naturalinfected badgers in that pulmonary lesions ranged from 1- to 2-mm diameter discrete tubercles, to extensive miliary lesions, with consolidation and pervading caseation of lobes (**Figure 3**). Cavitation and liquefaction were not seen (37).

The CMI responses, as determined by antigen stimulation of peripheral blood mononuclear cells (PBMCs) with bovine purified protein derivative tuberculin (PPD-B), increased to levels associated with the infective dose and pathology recorded postmortem (39). The badgers infected with the highest dose of *M. bovis* developed the earliest immune responses at 3 weeks postinfection. In addition, the highest infective dose correlated with the most consistent CMI response. In those animals with latent infection the CMI responses were weak and indistinguishable from non-infected control animals over most of the study period. In contrast to the CMI response, the humoral antibody responses of the badgers were intermittent over the time period of the study and not strongly influenced by the dose of *M. bovis*.

The aim of the follow-up study was to describe pathological, bacteriological, and immunological changes over a 24-week infection period using only the high-dose rate (46, 53). Inoculation by

Figure 3 | Experimental infection. Lesions of experimental pulmonary tuberculosis with miliary lesions of a uniform size in the inoculated lobe. In natural-infected badgers typically fewer pulmonary lesions are observed and they vary in size.

the endobronchial route resulted in a non-progressive infection in most of the badgers, with limited dissemination of infection from the thoracic cavity. Where this occurred it was principally to the mesenteric and hepatic lymph nodes. However, there was a lack of uniformity in the progression of disease across time. There was contraction in the distribution of infection from that seen at 6 weeks to that at 12 weeks, but then progression of infection between 12 and 18 weeks but similar results for 18 and 24 weeks. The analysis suggested that changes in the distribution of infection between time points arose from nonuniform development of lesions within badgers and that local resolution of lesions may have also occurred. The CMI responses to PPD-B were first detectable 3 weeks after infection, and over the study period the responses of the PBMC to antigen stimulation with PPD-B and the specific antigen CFP-10 were positively associated with the presence of gross lesions in the infected badgers. There was no evidence of a direct correlation between the strength of the response and the severity or distribution of observed lesions. The serological response was largely restricted to MPB83 across all states of infection. An interesting finding from this study was the generation of immunoglobulin-G (IgG) recognition of MPB83 coincident with the CMI response at 3 weeks postchallenge.

A key feature of the badger experimental model has been the dose-dependent recreation of different states of infection, ranging from latency to clinical disease, all characteristic of natural infection. This is unique among natural hosts of infection in that each state in the badger can be defined by a combination of pathological and immunological parameters. In human tuberculosis, latency (skin test and IFN-γ immunological responses but no clinical or radiographic signs) is significant in the epidemiology of disease (54, 55). Latency is also an important feature in natural-infected badgers where, in a high proportion of infected badgers, infection is not associated with any clinical signs or gross pathology (31). The apparent lack of immunological responses in the natural or experimentally reproduced latency may reflect how the different immune systems control very low levels of infection, or strains of low virulence, e.g., bacillus of Calmette–Guérin (BCG), or may point to differences in pathogenesis of infection in the different hosts (56).

## BCG VACCINATION AND PATHOGENESIS OF DISEASE IN BADGERS

Having established an experimental infection model that mimics the characteristics of moderate-to-severe natural disease, the studies progressed to evaluating BCG vaccine protection using the endobronchial experimental infection model (57, 58). A second objective was to determine if vaccination altered the pathogenesis of disease. The first study examined the effect of vaccination on the distribution of experimental infection. The BCG vaccine was administered in two different ways: subcutaneous injection (~5 × 105 CFU) and application to mucosal membranes (nasal and conjunctival mucosa with total final vaccine dose of 4 × 105 CFU). This latter route of immunization facilitated the delivery of BCG directly to an available mucosal surface, as a proxy route for delivery of an oral vaccine. With this protocol, the BCG was likely to be presented to the immune system *via* lymphoid tissues of the nasal cavity and/or conjunctiva. Inhaled aerosol particles may also have been exposed to the lymphoid tissues of the lower respiratory tract.

Following vaccination and endobronchial challenge (~104 CFU *M. bovis*) infection was established in all vaccinates and in all of the control group. Compared with the controls, vaccinates had fewer sites of infection, sites of extrathoracic infection, and sites with gross lesions. In the group vaccinated by the subcutaneous routes, all these measures were lower than for those vaccinated by the mucosal route. Vaccination also altered the distribution of gross lesions following challenge with no extrathoracic gross lesions in the vaccinates. These effects were more pronounced for the subcutaneous group. It was 2 weeks after *M. bovis* challenge that the subcutaneous vaccinated group responded to PPD-B, whereas the remaining groups responded from 4 weeks postchallenge. Over the period of infection, the highest immune responses were recorded in the non-vaccinated/infected control group. The immune profiles observed also associated with lesion severity scores measured at postmortem in all groups. Vaccination was also expressed by a significant delay in seroconversion to MPB83, which correlated with the levels of severity of the disease in all groups. From an immunological perspective, an intriguing finding was the lack of CMI activity in response to vaccination, as measured by IFN-γ production. This has been found in other captive badger studies and there is evidence that it correlates positively with the dose of vaccine delivered (59). It is tempting to speculate that this lack of CMI activity following vaccination is mechanistically related to the absence of similar responses in latent-infected badgers. In both cases, it might suggest that innate T cells play a prominent role for limiting multiplication of bacilli and maintaining them at low numbers. In recent years, there is growing evidence of non-specific protective effects generated by vaccination with BCG and other live vaccines (60). It is thought to be mediated by cross-reactivity of T-cell responses to related and unrelated pathogens, and/or by "trained immunity" whereby the innate immune system is modified by epigenetic programming following initial exposure, in order to increase resistance to reinfection (61, 62). The repeated exposure of badgers to environmental mycobacteria may provide the conditions necessary for training of the innate immune system to maintain subsequent exposure to *M. bovis* as a latent infection in most cases, and to limit the requirement of a CMI response in response to BCG vaccination.

Further studies examined the effect of oral BCG vaccination (endo-esophageal instillation of ~108 CFU BCG encapsulated in a lipid formulation) on protective effect and the distribution of infection after experimental challenge (63, 64). The predominant effect of BCG vaccination was seen as a reduction in the severity and number of gross lesions, decreased mycobacterial load in the lungs, and reduced number of sites of infection. However, vaccination did not alter the thoracic–extrathoracic pattern of infection. The CMI responses recorded in each of the vaccine groups were consistent with protection when expressed by pathology severity scores.

The most effective way of validating an experimental vaccination model is to compare it to vaccination of free-living animals in their natural environment. This allows vaccine protection to be assessed in a scenario of natural transmission. It also addresses an inherent limitation of captive animal vaccine studies where the infective dose and time of infection are controlled, leading to a relatively homogenous infection level in all animals from using relatively high-challenge doses. Two vaccine field trials have been carried out in badgers, in the UK and Ireland (65, 66). An injectable BCG vaccine for badgers was used in the UK trial and the results reported a 74% reduction in seropositivity among vaccinated badgers as compared with non-vaccinated badgers (65). Further analysis using a combination of diagnostic tests revealed a decreased risk of cubs testing positive as the proportion of adults vaccinated increased (67). In the Irish study, there was also a clear reduction in the rate of seroconversion among vaccinated badgers as compared with the non-vaccinated badgers, and in those vaccinated animals that did seroconvert, there was a significant time delay to when seroconversion occurred relative to the non-vaccinated badgers (66). The delayed time to seroconversion was consistent with that recorded in the captive badger vaccine studies where vaccine protection was also measured by time to seroconversion following endobronchial *M. bovis* challenge (33). A follow-up analysis using a different serology test confirmed that the proportion of seropositive animals was reduced in the vaccinated population compared with the non-vaccinated animals over the course of the trial (68).

#### BCG VACCINATION AND DISSEMINATION OF INFECTION IN BADGERS

In all of the experimental vaccine studies, the protection levels generated by vaccination with BCG did not prevent establishment of infection; this may have reflected the severity of challenge resulting from endobronchial delivery of virulent *M. bovis*. However, vaccination did not appear to substantially change the pathogenesis of disease. One notable finding of the experimental vaccine protection studies was the level of dissemination of infection from the lung in all infected badgers including vaccinates. The principal measure of vaccine-induced protection was a reduction in the severity of thoracic and extrathoracic lesions rather than a reduction in the wider distribution of infection. The BCG vaccine is known to limit disseminated disease when delivered to children but is less effective in protecting adults against pulmonary disease (69–71). During the early innate stages of the immune response dissemination from the initial site of infection may occur before migration of the mycobacteria to a lymph node stimulates the development of a CMI response (72). Lesion development characteristic of tuberculosis will not commence until a sufficiently potent CMI response is generated, and this may take several weeks, dependent on the potency of the immune response and the severity of the infective dose. In the badger experimental model the average time to detect a measurable CMI response is 2–4 weeks (58, 63). During the period preceding this response, infected macrophages can use the lymphatic system to pass through the draining lymph nodes and circulate throughout the host. When a sufficiently dominant CMI response is induced, infected macrophages can become immobilized in lymph node tissue and further migration is restricted. Lesions can then develop and progress at sites where infected macrophages are resident, including those areas of the lung where infection was initiated. Following vaccination, antigen specific T-cells still take time to accumulate, allowing the infective bacilli to multiply and spread. In the badger model, the earliest time point for measuring postinfection responses is 2 weeks. The data indicate that responses in vaccinates appear around this time point and earlier than in non-vaccinates. Nevertheless, it still allows time for dissemination of infection to occur in the days following establishment of infection, by translocation of infected macrophages *via* the lymphatic system or the blood stream. Local dissemination may occur by movement of infected macrophages within tissues or following accumulation of infected debris in the lymphatics, or blood vessels, airways, renal or gastrointestinal system (29). This may partly explain why vaccination is particularly successful in reducing the severity of disease but has limited impact on distribution of infection.

## EXPERIMENTAL INFECTION MODELS FOR DOMESTIC SPECIES AND WILD ANIMAL TUBERCULOSIS

Studies in natural susceptible hosts and experimental studies in captive natural susceptible hosts are indispensable in advancing the understanding of the pathogenesis of tuberculosis. This in turn can generate confidence in the interpretation of results from experimental vaccine—challenge studies. In many domestic species, e.g., cattle, goats, and deer, the presentation of tuberculosis is similar to that observed in the greater majority of infected humans in that it is a chronic, slowly progressive disease with pathology predominantly confined to the lower respiratory tract, with associated cellular immune responses (73, 74). However, the occurrence and prevalence of latency in these species has not been clearly established and is difficult to identify in either natural-infected or experimentally infected animals.

Many of the pathogenesis studies and infection models developed in livestock and wild animals have been motivated by the desire to develop vaccines to control inter-species spread of tuberculosis (75). With this in mind, development of a reliable experimental infection model is important for a number of reasons including (a) the need to establish infection with an appropriate dose, (b) keeping the dose biologically plausible, (c) obtaining a balance ensuring infection is successful in all animals including vaccinates, (d) ensuring that the infection route used and the pathology generated is at least within the spectrum of the disease in its natural state, and (e) there are appropriate and measurable parameters for quantifying protective immunity.

Unlike laboratory animal model systems, livestock and wild animals are usually natural hosts for infection and are relatively outbred. Therefore, replicating the pathogenesis of natural infection might be confounded by the differing environmental conditions experienced by free-living and captive animals, and also different levels of natural susceptibility to infection. Experimental infection of domestic cattle with low doses of *M. bovis* (102 to 103 CFU) by intratracheal/endobronchial inoculation or by aerosol-generating systems has resulted in lesions similar to those detected in the lungs and associated lymph nodes of natural-infected animals (76, 77). A natural challenge system of housing tuberculosis-free cattle with natural-infected animals has been presented as a biologically plausible challenge system but with a highly variable degree of success (78, 79). Experimental infections using endobronchial (*M. caprae*) or aerosol delivery (*M. bovis*) have been carried out in goats (80, 81). In both cases, the distribution of lesions mimicked those seen in natural infection. Further studies in goats experimentally infected with selected members of the *M. tuberculosis* complex (*M. bovis*, *M. caprae*, *M. tuberculosis*) revealed different clinical outcomes with lesion scores ranking highest with *M. bovis*, then *M. caprae* and *M. tuberculosis* (51). These results highlight a good example of host tropism associated with closely related mycobacterial species. Sheep have also been experimentally infected with *M. caprae* by the endotracheal route resulting in granulomatous caseous and necrotizing lesions in the lung and associated lymph nodes, typically found in natural cases of sheep tuberculosis (82). In addition, there were similar measured immunological, pathological, and bacteriological parameters as found in experimental *M. caprae* infection of goats. In deer naturally infected with *M. bovis*, the distribution of lesions differs from other domestic animals in that lesions are found predominantly in the retropharyngeal lymph nodes followed by lung and thoracic lymph nodes. Experimental infection models in deer routinely target inoculation of the tonsillar crypts to mimic natural infection and lesion distribution (83, 84). Additional studies in white-tailed deer have demonstrated that dissemination from the tonsil is an infrequent event involving low numbers of bacilli (85).

Ferrets (*Mustela Furo*) are susceptible to infection with *M. bovis* and are considered as part of the epidemiology of *M. bovis* transmission in New Zealand (86). As mustelids related to badgers, they offer some advantages as a model animal species in that they are available from licensed suppliers, and are relatively easy to house and maintain in captivity. Experimental infection models have been established where *M. bovis* was delivered to captive ferrets by the oral or aerosol route (35, 87). In both models, infection was found in the thoracic cavity and also in the mesenteric lymph nodes. The mechanism of dissemination from the primary site of infection in both models is not clearly understood. To date, experimental challenge by the endobronchial route has not been reported; this would allow for direct comparison of different aspects of pathogenesis with badgers, which might reveal subtle differences in specific host–pathogen interactions influencing dissemination.

The wild boar (*Sus scrofa*) is considered as a key maintenance host for tuberculosis in Spain with prevalence rates >50% in areas with high-density populations (88). Vaccination is being explored as a potential strategy to control the level of disease in these wild animals. In the first challenge study, a field isolate of *M. bovis* was delivered to boar by the oropharyngeal route using a range of infective doses between 102 and 106 CFU (89). All four challenged wild-boar-developed lesions and severe generalized lesions were observed in two animals exposed to the highest dose: this was not considered typical of the lesion distribution encountered in natural infections.

Routes of infection not observed in natural-infected wild animals have been used in experimental infections to achieve particular outcomes. Such alternative inoculation routes have been used to experimentally infect New Zealand brushtail possums to counter the high susceptibility of these animals to experimental infection and the rapid progression of disease. Delivery of *M. bovis via* conjunctival instillation resulted in established infection in a dose-dependent manner (90). The infection progressed slowly in the possums, generating palpable lesions in superficial lymph node lesions, and widespread distribution of macroscopic and microscopic lesions, all characteristics of the disease in wild, natural-infected possums. Percutaneous inoculation of *M. bovis* suspension into the paws resulted in gross lesions in superficial lymph nodes as is observed in natural-infected possums (91). As with the conjunctival challenge route, percutaneous infection prolonged the postchallenge survival period. However, although these two alternative routes of infection do result in gross lesion distribution as seen in natural-infected wild possums, they significantly underestimate the distribution of infection as seen when more detailed postmortem examination procedures are employed (6). Natural transmission between infected and susceptible captive possums was also investigated as a possible method of evaluating vaccination in captive possums but proved unsuitable (92). The rate of *M. bovis* transmission was lowest when animals were mixed at random; however, transmission increased significantly with mixing of more sociable possums. This indicated that transmission was influenced by the proximity of susceptible and infected possums leading to increased frequency and duration of social interactions.

Though the presence of visible lesions, whether in experimentally infected or in natural-infected animals, can point toward the likely route of natural infection, caution must be taken in interpreting such data when only a limited number of infection parameters are measured. This highlights one of the difficulties when working with relatively large animal species to understand pathogenesis. The sensitivity of detection of infection can be severely compromised in large animals, such as cattle and deer, simply because of the difficulty of detecting small lesions or infection in large organs and lymph nodes (93). This can lead to biases when analysis is based on visible lesion detection. In all animals, there is the possibility of microscopic lesions or small bacteriological loads existing in the carcase but too small to detect, this being an increasing probability as the mass of the animal increases. Sampling from natural-infected populations can also compound this when only animals considered likely to have large lesions, or strong reactors to the skin test are recruited for analysis. The problem here is that it represents a relatively late stage of disease progression and the distribution of lesions may not reflect the early stage of pathogenesis and the likely route of infection.

Even when using natural-infected animals across a broad spectrum of disease, the interpretation can be subjected to bias if insensitive protocols for bacteriology and histology are employed. In studying the disease in natural-infected badgers, we tried to minimize these biases by randomly sampling from the infected population and by using sensitive bacteriological and histological procedures on a predetermined set of 36 tissues covering a wide range of anatomically diverse tissue samples in each animal. In addition, the tissues for bacteriology were collected aseptically so that the bacteriological detection of infection was maximized and tissues were individually cultured for the same reason (31). This intensity of pathological investigation has not been repeated in any other natural-infected animal species but for the badger, at least, it provides a reference point to

#### REFERENCES

compare natural-infected animals with those from experimental infection studies.

#### CONCLUDING REMARKS

The pathological and bacteriological examination of naturalinfected badgers with tuberculosis when using sensitive postmortem examination procedures has provided an important and essential baseline for understanding the pathogenesis and epidemiology of tuberculosis in this species. It has also provided the framework for developing experimental infection studies, which has allowed the evaluation of diagnostic assays and the measurement of vaccine efficacy. There is a growing awareness that *M. bovis* infection is naturally endemic in a diverse range of domestic and wild animals, as well as in humans. Experimentally, at least, it seems that most animal species are susceptible to infection. With the continuous threat of infection spreading from wild animals to livestock and the risk of onward transmission to humans, the continued improvement in knowledge of pathogenesis and epidemiology will serve to lessen the transmission risks into the future.

#### AUTHOR CONTRIBUTIONS

EG and LC contributed equally to this review including critical analysis of published data and preparation of the manuscript.

#### ACKNOWLEDGMENTS

We would like to acknowledge funding and support provided by the Department of Agriculture, Food & the Marine Food (DAFM) for all of the badger studies. We are grateful to Assoc. Professor Joe Cassidy, Paul Stanley, Aidan Kelly, and Brian Cloak for photographic images.

**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 Gormley and Corner. 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) or licensor 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.*

# Preliminary Results Indicate That Inactivated Vaccine against Paratuberculosis Could Modify the Course of Experimental *Mycobacterium bovis* Infection in Calves

#### *Edited by:*

*Julio Alvarez, University of Minnesota, United States*

#### *Reviewed by:*

*Mirinda Van Kleef, ARC OVI, South Africa Andrew William Byrne, Agri Food and Biosciences Institute, United Kingdom*

> *\*Correspondence: Joseba M. Garrido*

<EMAIL_ADDRESS>
#### *†Present address:*

*Ramón A. Juste, SERIDA, Agri-food Research and Development Regional Service, Villaviciosa, Asturias, Spain*

#### *Specialty section:*

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

*Received: 24 July 2017 Accepted: 02 October 2017 Published: 18 October 2017*

#### *Citation:*

*Serrano M, Elguezabal N, Sevilla IA, Geijo MV, Molina E, Juste RA and Garrido JM (2017) Preliminary Results Indicate That Inactivated Vaccine against Paratuberculosis Could Modify the Course of Experimental Mycobacterium bovis Infection in Calves. Front. Vet. Sci. 4:175. doi: 10.3389/fvets.2017.00175*

*Miriam Serrano, Natalia Elguezabal, Iker A. Sevilla, María V. Geijo, Elena Molina, Ramón A. Juste† and Joseba M. Garrido\**

*Animal Health Department, NEIKER-Instituto Vasco de Investigación y Desarrollo Agrario, Bizkaia Science and Technology Park, Derio, Spain*

Although paratuberculosis (PTB) vaccination has been recognized as an effective tool to control the disease, its use has been limited in countries undergoing bovine tuberculosis (bTB) eradication programs because of its interference with the diagnostic techniques. Due to this restraint, little is known about the effect of vaccinating against PTB on the progression of bTB infection. To assess this topic, an experimental infection was carried out including the following three groups of five calves each: non-vaccinated infected with *Mycobacterium bovis* (NVI), vaccinated against PTB infected with *M. bovis* (VI), and vaccinated against PTB non-infected (VNI). The level of infection attending to pathological and bacteriological parameters was evaluated at necropsy in collected tissue samples. Infection was confirmed in all challenged animals being the lung and thoracic regions most affected for all studied parameters. The VI group presented 15.62% less gross lesions in the thoracic region than the NVI, although no significant differences were found. Only one vaccinated animal presented gross lesions in the lung, compared to three non-vaccinated calves. NVI animals showed an average of 1.8 lung lobes with gross lesions whereas in the vaccinated group the average number of affected lobes was 0.2, representing an 89% reduction. Significant differences were not found, although a tendency was observed (*p* = 0.126). Pathological and culture scores showed the same tendency. Vaccination induced a 71.42 and 60% reduction in lesion and culture scores in the lung as well as a 23.75 and 26.66% decline, respectively, in the thoracic region. The VI group showed lower positivity in the rest of the areas for all measured criteria except for the head. In order to reinforce our results, further research on a larger sample size is needed, but the results from this study suggest that PTB vaccination could confer certain degree of protection against bTB infection, supporting the view that PTB vaccination could increase resistance to the main mycobacterioses that affect animals.

Keywords: paratuberculosis, bovine tuberculosis, vaccine, interference, crossed-protection

# INTRODUCTION

Bovine tuberculosis (bTB) and paratuberculosis (PTB) are mycobacterial diseases that have a huge economic impact on cattle, especially on dairy herds (1, 2). Both present a widespread distribution, affecting domestic hosts (3, 4) and wildlife species (5, 6), promoting the successful dissemination of their etiological agents.

Paratuberculosis or Johne's disease is caused by *Mycobacterium avium* subsp. *paratuberculosis* (MAP). Progression of the disease causes a chronic gastrointestinal granulomatous inflammation. Different factors, such as the long incubation period of the disease, fecal-oral route transmission, intermittent excretion periods added to high resistance of mycobacteria in the environment, and limited performance of diagnostic methods, make control of the infection difficult to achieve. PTB vaccination has been proven to restrain the disease in cattle (7), sheep (8), and goats (9). Excretion of bacterial burden is considerably reduced, containing the spread of the infection and therefore diminishing the number of clinical cases (10, 11). Nevertheless, the interference induced by PTB vaccination with the current interpretation criteria (12) of the bTB official diagnostic tests (13) results in the restricted use of PTB vaccination. MAP-based vaccination in cattle is not allowed by the Animal Health Authorities of most countries. Despite the diagnostic interference, a certain degree of containment of the lesion dissemination from the target organs after a bTB infection has been previously reported in PTB-vaccinated goats (14). This suggests that if interference issues are avoided, PTB vaccination can be used for PTB control and might also be beneficial against bTB conferring some degree of protection.

The degree of interference of PTB vaccination with official bTB diagnostic tests has been evaluated previously in cattle (13, 15) and goats (16, 17). Cross-reactivity in the skin test has proven to be limited if the comparative intradermal test is used in bTB-free bovine herds (13). These findings have been based on an exhaustive analysis of results from a vaccine clinical trial under field conditions. To evaluate the effect of PTB vaccination on bTB infection and the interference due with bTB diagnosis, an experimental infection with *Mycobacterium bovis* in bovines previously vaccinated against PTB was performed. Results on interference using alternative diagnostic criteria and specific antigens have been reported in a separate paper (12) while pathological and bacteriological changes associated with vaccination in a bTB experimental infection are the goal of this report.

# MATERIALS AND METHODS

#### Ethics Statement

Animals used in this study had their origin in commercial farms. With the purpose of obtaining data for this trial, calves were submitted to clinical practices standardized and regulated by the European, Spanish and Regional Law and Ethics Committee. The experimental design underwent ethical review and approval by NEIKER's Animal Care and Use Committee and by the Agriculture Department (PARAPATO-1264-BFA).

# Animal Selection

Thirty Friesian calves from 13 different farms in northern Spain were selected in a feedlot. For final selection of animals, absence of previous contact with mycobacteria was considered. IFN-γ release assay (IGRA) with standard tuberculins (A-PPD, B-PPD) as well as with more specific antigens (ESAT-6/CFP10 and Rv3615c) (18) already tested for the diagnosis of bTB was the assay used for this purpose. The first blood sampling was carried out at week 0, at the age of 2 months. After the blood samples were collected, 20 randomly selected animals were vaccinated subcutaneously in the dewlap with 1 ml of a heat-inactivated vaccine (Silirum® CZV, Pontevedra, Spain) and 10 remained unvaccinated. In order to reassure the absence of previous contact with *M. bovis* or other mycobacteria, blood samplings at the feedlot were repeated twice, at weeks 4 and 12. Finally 10 vaccinated and five non-vaccinated animals with negative results for IGRA and without evident pathologies were selected and transported to the biosafety level 3 (BSL-3) facilities in NEIKER where three groups of five animals each were formed.

## *M. bovis* Challenge

A 2-week adaptation period was established for the calves after their arrival at the BSL-3 facilities. At week 18 post-vaccination, five vaccinated and five non-vaccinated animals were challenged by the endotracheal route with 106 colony-forming units (CFUs) of a *M*. *bovis* field isolate suspended in 2 ml of phosphate-buffered saline after intramuscular sedation with Xylazine (10 mg/50 kg). The *M. bovis* challenging isolate was spoligotype SB0339 according to the *M. bovis* Spoligotype Database website (http://www. mbovis.org). The final experimental groups were as follows: PTB vaccinated and *M. bovis* infected (VI), PTB vaccinated and *M. bovis* non-infected (VNI), and PTB non-vaccinated and *M. bovis* infected (NVI).

#### Postmortem Studies

The animals were slaughtered at week 14 post-infection in three consecutive days, five calves per day. Upon sedation with XILAGESIC® 2% (10 mg/50 kg lw) (Laboratorios Calier, S.A., Barcelona, Spain), animals were euthanized by an intravenous injection of T61 (4–6 ml/50 kg) (Intervet International GMBH, Unterschleissheim, Germany). Complete necropsy was performed although special focus was set on the respiratory system. All tissue specimens were individually collected and processed for pathological and microbiological analysis. Collected tissues per region included were: head [tonsils, nasal turbinate, and parotid and retropharyngeal and mandibular lymph nodes (LNs)], thorax (tracheal, tracheobronchial, mediastinal, pulmonary, and prescapular LNs), lung (right and left cranial and caudal lobes and medium and accessory lobes), abdomen (liver, spleen, and hepatic LNs), and others (prefemoral LNs).

#### Gross Pathology

All tissues were visually inspected for lesions compatible with TB infection. Scoring of lesions according to Palmer et al. (19) was performed independently by two researchers, and the mean value of both scores was used. Briefly, the scoring system for lung was as follows: 0: no visible gross lesion, 1: no visible external gross lesion but internal detected after splicing, 2: less than five lesions smaller than 10 mm, 3: over five lesions smaller than 10 mm, 4: more than one lesion bigger than 10 mm, and 5: gross confluent lesions. In the case of LNs, scoring was as follows: 0: no visible gross lesions, 1: focal lesions of 1–2 mm, 2: a lot of small foci, and 3: extended lesions. Once scores were assigned to each lesion, total and regional scores per animal were calculated by adding them.

#### Bacterial Culture

Bacterial tissue culture was performed as described previously (20). Briefly, 2 g of tissue samples were homogenized in 10 ml of sterile distilled water. Five milliliters of the suspension was decontaminated and processed for liquid culture in BBL MGIT tubes supplemented with BBL MGIT PANTA and BACTEC MGIT growth supplement (Becton Dickinson, Franklin Lakes, NJ, USA) following manufacturer's instructions. BBL MGIT tubes were incubated for 42 days in a BACTEC MGIT 960 System. The remaining 5 ml were decontaminated in hexadecyl-pyridinium chloride 0.75% (w/v) for 12–18 h for solid culture. After a 5 min centrifugation step at 2,500 × *g*, pellets were cultured in Coletsos tubes (bioMérieux SAF-69280 Marcy l'Etoile France) at 37°C during 4 months.

Once the MGIT incubation period finished, DNA extraction was performed on culture from all positive tubes and some negative tubes. PCR was carried out subsequently to confirm that growth was due to *M. bovis* (21).

After the incubation period for solid culture was completed, colonies were visualized under a stereoscope and scraped for DNA extraction and *M. tuberculosis* complex PCR confirmation (21). All isolates were confirmed as *M. bovis* SB0339 by spoligotyping (22). A culture score was defined in order to categorize the infection level of each tissue. In this case, scores were as follows: 0: no growth, 1: less than 10 colonies, 2: between 10 and 50 colonies, and 3: over 50 colonies (20).

A tissue was considered positive for culture when it gave a positive result by solid culture, liquid culture, or both.

#### Statistical Analysis

Reduction by vaccination was calculated by the formula (1 − VI/ NVI) × 100 for each of the following parameters: solid culture score, number of positive tissues by culture, gross lesion score, and number of affected areas by gross pathology.

For the analysis, the number of tissues with positive cultures, with bTB compatible gross lesion and the solid culture and lesion scores, was calculated per area and animal. Differences in the degree of pathology and bacterial burden (lesion scores and culture scores) were compared using the Mann–Whitney *U*-test. Differences in the number of affected tissues by gross pathology and culture were assessed using Student's paired two-sample *t*-test, whereas Fisher's exact test was used for proportions of animals with lesions. Spearman's correlation test was applied to assess the association between culture and gross pathology results. In all cases, significance of the differences among groups for all variables was accepted at *p* < 0.05.

# RESULTS

#### Clinical Signs

All animals included in the study went through the whole experiment, and no adverse reactions were reported after vaccination or challenge. No clinical signs of bTB such as wasting and coughing were observed in any of the animals after challenge. Infection of all challenged animals was confirmed by bacteriological and pathological analysis. The VNI group did not present gross lesions compatible with bTB or culture-positive tissues.

#### Postmortem Analysis

Detailed pathology results from the infected groups of the study are shown in **Table 1**. The thoracic region and lung were the areas presenting a higher number of affected tissues and the NVI presented slightly higher scores as expected. Culture results from the infected groups of the study are shown in **Table 2**. In this case, again thorax and lung were the most affected areas, although the VI group only presented one animal with one positive tissue. The analysis has been focused separately on head, thorax, and lung as well as on the total where all areas of the animal have been considered. The analysis of number of tissues presenting pathology and culture positive results is shown in **Table 3**.

In the thoracic region, the NVI group presented a mean of 6.4 LNs with gross lesions with a minimum of two and a maximum of 10 affected LNs in each animal compared to the VI group with an average of 5.4 LNs affected with a minimum of two and a maximum of nine affected LNs. Significant differences among groups were not observed (*p* = 0.643). However, the reduction due to vaccination was of 15.62%.

Of the six lung lobes evaluated, the NVI group presented an average of 1.8 lobes with gross lesions with a minimum of zero and a maximum of five affected lobes per animal, much higher than the mean of 0.2 affected lobes found in the VI group, which had a minimum of zero and a maximum of one affected lobes. Although significant differences were not observed between the number of affected lobes, the tendency should be considered (*t*-test, *p* = 0.126). This represents an 89% reduction due to vaccination. Only one animal (1/5, 20%) from the VI group presented lesions in the lung compared to three animals (3/5, 60%) from the NVI group (Fisher's test; *p* = 0.189).

The number of affected tissues was always lower in the VI group than in the NVI groups except for the area that compromised the head. In this case, two animals presented gross lesions, one in one tissue and another in two in the VI group, whereas the NVI group presented one animal with gross lesions in two tissues. Tissue culture positivity was also slightly higher in the head in the VI group where an average of 1.4 ± 0.4 tissues with detectable bacteria was observed compared to the mean of 1 ± 0.55 tissues in the NVI group. In the VI group, four animals presented positive tissue culture (4/5, 80%) compared to three in the NVI group (3/5, 60%).

Pathology and culture scores were always lower in the VI group than in the NVI group (**Table 4** and **Figure 1**) except for the head where lesion scores were slightly higher in the VI group (0.6 ± 0.4 vs. 0.4 ± 0.4). In any case, significant differences were

#### TABLE 1 | Tissues with tuberculosis compatible lesions in the infected groups of the study.

*VI, vaccinated infected; NVI, non-vaccinated infected; LN, lymph node.*

*One LN affected (right or left): dotted; two LNs affected (both right and left or two of three, cranial, caudal, or medial): light gray; three LNs affected (cranial, caudal, and medial): dark gray.*

*Lesion score is the sum of the scores of all tissues.*

TABLE 2 | Tissues with positive culture results in the infected groups of the study.

*VI, vaccinated infected; NVI, non-vaccinated infected; LN, lymph node.*

*MGIT culture positive: dotted; solid culture positive: light gray; both MGIT and solid culture positive: dark gray.*

*Culture score is the sum of the scores of all tissues.*

not observed among analyzed areas. However, reductions in lung of 71.42 and 60% in lesion and culture scores, respectively, and of 23.75 and 26.66% in the vaccinated group for the same parameters in thorax should be noted.

Correlation between both diagnostic methods considering number of affected tissues was best fit in lung (*r* = 0.988, *p* < 0.0001), followed by head (*r* = 0.746, *p* = 0.013), total (*r* = 0.667, *p* = 0.035), and thorax (*r* = 0.655, *p* = 0.04).

#### DISCUSSION

Although the efficacy of PTB vaccination has been repeatedly demonstrated (7, 11, 18, 23), its use has been restricted due to the cross-reactivity with current bTB diagnostic methods. Interference issues have probably led to the lack of knowledge on the effect of PTB vaccination in the development of bTB infection. This is the first study examining this topic in bovines under experimental conditions.

In this particular experimental setting, all animals became infected regardless of their vaccination status showing positive culture results and macroscopic lesions compatible with bTB. In both groups, thorax and lung were the most affected areas. The majority of tissue sites affected by infection in terms of lesion development or bacterial colonization, as well as the highest lesion and culture scores appeared in these two areas. However, PTB vaccination seemed to induce a moderate protective

TABLE 3 | Gross pathology and bacteriology analysis considering number of affected tissues per area.

*NVI, non-vaccinated infected; VI, vaccinated infected; R, reduction due to vaccination.*

*NVI, non-vaccinated infected; VI, vaccinated infected; R, reduction due to vaccination.*

response against *M. bovis* challenge, which led to a reduction of the pathological and bacteriological results in both areas of the VI group. The effect of vaccination was most evident in the lung as seen by the fact that only one animal (1/5, 20%) of the VI group presented lesions and detectable bacteria in this area compared to the NVI group where three animals were affected (3/5, 60%). Same tendency was observed in the remaining studied areas except for the head, where the protective effect was not evident. Although differences among groups were not statistically significant and only tendencies have been observed, the degree of protection observed can be considered biologically relevant. To reinforce the appealing results obtained from this first trial, it would be necessary to carry out further studies with a larger sample size.

These results suggest that a certain degree of heterologous protection against *M. bovis* infection takes place after PTB vaccination, and although the protection conferred is probably not enough to impede the establishment of the disease or prevent horizontal transmission within a herd, it may contain the infection to some extent. Results from this experiment indicate that this containment would clearly benefit the lung (60–89% reduction in lesions and bacterial burden) since reduction due to vaccination in the thoracic region was less notorious and absent in the head area. This may be important considering that the main excretion route of *M. bovis* is through the respiratory system, and therefore, the reduction of the bacterial load in the lung may lead to a reduction of this figure in the environment.

These findings partially agree with the results obtained by Pérez de Val et al. (14) in goats after PTB vaccination and subsequent challenge with *M. bovis* where, lesions in vaccinated goats appeared only in the lung and corresponding LNs whereas non-vaccinated animals showed an increased dissemination frequency of the lesions. In that case (14), goats were challenged through the endobronchial route and, therefore, infection progressed mainly affecting the lower respiratory tract. In another study in goats in which the transthoracic route was used, lesions were mainly located in lung and mediastinic and mesenteric LNs (24). In our study, thorax was the primary focus and extrathoracic and extrapulmonary dissemination of bacteria to the upper respiratory tract or head area (retropharyngeal, mandibular, parotid LNs, and nasal turbinate) occurred in four animals of the VI group and three animals of the NVI group. This could be due to a pulmonary dissemination to the head by mycobacterial shedding in the tracheobronchial secretions and subsequent ingestion as hypothesized in previous reports (25). Bacteria and gross lesions were detected in spleen of one animal of the NVI group, whereas only gross lesions were observed in spleen and liver of one animal of the VI group indicating that systemic circulation of mycobacteria had occurred.

Added to the route, the challenging dose can be crucial for the pathological outcome of the infection. In previous studies in goats (14, 24, 25), animals were challenged with lower doses of *Mycobacterium caprae* (102 –1.5 × 103 CFUs), but as stated before in those studies, the inoculum was directly deposited into the lung. The selected dose (106 CFU) and infection route (endotracheal) may be responsible for the wider spreading of the lesions in our study. This high dose was applied to guarantee infection for vaccine evaluation. In any case, considering the fact that in experimental conditions the bacterial load administered for challenge is most probably many logs higher than the amount of *M. bovis* that an animal will be in contact with in field conditions

it could be expected that higher protection levels would be observed in these cases.

Positive correlations were found between pathological and bacteriological techniques as expected. These were best fit in the lung, area that poses the most noticeable partial protective effect by the vaccine.

The results presented here suggest that vaccination against PTB modifies the course of experimental bTB infection by decreasing the severity of the lesions and the bacterial burden. Although our results are not conclusive, they support the view that mycobacterial vaccines could potentially be useful tools for disease control in specific settings where vaccination does not interfere with eradication programs.

# ETHICS STATEMENT

With the purpose of obtaining data for this trial, calves were submitted to clinical practices standardized and regulated by the European, Spanish and Regional Law and Ethics Committee. The experimental design underwent ethical review and approval

# REFERENCES

by NEIKER's Animal Care and Use Committee and by the Agriculture Department (PARAPATO-1264-BFA).

# AUTHOR CONTRIBUTIONS

RJ, JG, and IS conceived the study. MS, EM, MG, IS, and NE carried out the laboratory work. RJ, NE, and MS compiled and analyzed the data. MS, NE, and IS collated the results. MS, NE, IS, and JG drafted the preliminary manuscript. All authors participated in the review and the editing of the final draft and also read and approved its final version.

# ACKNOWLEDGMENTS

This study was supported with funds from the Departamento de Economía e Infraestructuras of the Basque Government (OFS2008001) and by Ministerio de Economía, Industria y Competitividad of the Spanish Government (AGL2008- 05820-C02-01/GAN and AGL2014-56305-C3-3-R). MS acknowledges support from the Departamento de Educación of the Basque Government (PRE\_2016\_2\_0155).

and ESAT-6/CFP10 specificity. *Prev Vet Med* (2010) 96:161–9. doi:10.1016/j. prevetmed.2010.06.007

**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 © 2017 Serrano, Elguezabal, Sevilla, Geijo, Molina, Juste and Garrido. 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) or licensor 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.*