Modeling of Mycobacterium avium subsp. paratuberculosis dynamics in a dairy herd: An individual based approach

Investigating effective testing strategies for the control of Johne's disease in western Canadian cow-calf herds using an agent-based simulation model

Johne's disease is an insidious infectious disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's disease can have important implications for animal welfare and risks causing economic losses in affected herds due to reduced productivity, premature culling and replacement, and veterinary costs. Despite the limited accuracy of diagnostic tools, testing and culling is the primary option for controlling Johne's disease in beef herds. However, evidence to inform specific test and cull strategies is lacking. In this study, a stochastic, continuous-time agent-based model was developed to investigate Johne's disease and potential control options in a typical western Canadian cow-calf herd. The objective of this study was to compare different testing and culling scenarios that included varying the testing method and frequency as well as the number and risk profile of animals targeted for testing using the model. The relative effectiveness of each testing scenario was determined by the simulated prevalence of cattle shedding MAP after a 10-year testing period. A second objective was to compare the direct testing costs of each scenario to identify least-cost options that are the most effective at reducing within-herd disease prevalence. Whole herd testing with individual PCR at frequencies of 6 or 12 months were the most effective options for reducing disease prevalence. Scenarios that were also effective at reducing prevalence but with the lowest total testing costs included testing the whole herd with individual PCR every 24 months and testing the whole herd with pooled PCR every 12 months. The most effective method with the lowest annual testing cost per unit of prevalence reduction was individual PCR on the whole herd every 24 months. Individual PCR testing only cows that had not already been tested 4 times also ranked well when considering both final estimated prevalence at 10 years and cost per unit of gain. A more in-depth economic analysis is needed to compare the cost of testing to the cost of disease, taking into account costs of culling, replacements and impacts on calf crops, and to determine if testing is an economically attractive option for commercial cow-calf operations.

Reviewing age-structured epidemiological models of cattle diseases tailored to support management decisions: Guidance for the future

Mechanistic simulation models are being increasingly used as tools to assist with animal health decision-making in the cattle sector. We reviewed scientific literature for studies reporting age-structured cattle management models in application to infectious diseases. Our emphasis was on papers dedicated to support decision making in the field. In this systematic review we considered 1290 manuscripts and identified 76 eligible studies. These are based on 52 individual models from 10 countries addressing 9 different pathogens. We provide an overview of these models and present in detail their theoretical foundations, design paradigms and incorporated processes. We propose a structure of the characteristics of cattle disease models using three main features: [1] biological processes, [2] farming-related processes and [3] pathogen-related processes. It would be of benefit if future cattle disease models were to follow this structure to facilitate science communication and to allow increased model transparency.

Quantifying transmission of Mycobacterium avium subsp. paratuberculosis among group-housed dairy calves

Johne’s disease (JD) is a chronic enteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP), with control primarily aimed at preventing new infections among calves. The aim of the current study was to quantify calf-to-calf transmission of MAP among penmates in an experimental trial. Newborn Holstein bull calves (n = 32) were allocated into pens of 4, with 2 inoculated (IN) calves and 2 calves that were contact exposed (CE). Calves were group-housed for 3 months, with frequent collection of fecal and blood samples and tissue collection after euthanasia. The basic reproduction ratio (R₀) was estimated using a final size (FS) model with a susceptible-infected model, based on INF-γ ELISA and tissue culture followed by qPCR. In addition, the transmission rate parameter (β) for new shedding events was estimated using a general linearized method (GLM) model with a susceptible-infected-susceptible model based on culture, followed by qPCR, of fecal samples collected during group housing. The R₀ was derived for IN and CE calves separately, due to a difference in susceptibility, as well as differences in duration of shedding events. Based on the FS model, interferon-γ results from blood samples resulted in a R₀^IG of 0.90 (0.24, 2.59) and tissue culture resulted in a R₀^T of 1.36 (0.45, 3.94). Based on the GLM model, the R₀ for CE calves to begin shedding (R₀^CE) was 3.24 (1.14, 7.41). We concluded that transmission of MAP infection between penmates occurred and that transmission among calves may be an important cause of persistent MAP infection on dairy farms that is currently uncontrolled for in current JD control programs.

Assessment of the bovine tuberculosis elimination protocol in the United States

In this study, we analyzed the performance of the USDA's bovine tuberculosis (bTB) elimination protocol in a 1,000-cow closed dairy herd using an agent-based simulation model under different levels of initial bTB infection. We followed the bTB test sensitivity and specificity values used by the USDA in its model assessment. We estimated the net present value over a 20-yr horizon for a bTB-free milking herd and for bTB-infected herds following the USDA protocol. We estimated the expected time to identify the infection in the herd once it is introduced, its elimination time, the reproductive number (R₀), and effective reproduction number (R_e) under the USDA protocol. The optimal number of consecutive negative whole-herd tests (WHT) needed to declare a herd bTB-free with a 95% confidence under different bTB prevalence levels was derived. Our results support the minimum number of consecutive negative WHT required by the USDA protocol to declare a herd bTB-free; however, the number of consecutive negative WHT needed to eliminate bTB in a herd depends on the sensitivity and specificity of the tests. The robustness of the protocol was analyzed under conservative bTB test parameters from the literature. The cost of implementing the USDA protocol when 1 infected heifer is introduced in a 1,000-cow dairy herd is about $1,523,161. The average time until detection and the time required to eliminate bTB-infected animals from the herd, after 1 occult animal is introduced in the herd, were 735 and 119 d, respectively.

A data-driven individual-based model of infectious disease in livestock operation: A validation study for paratuberculosis

Chronic livestock diseases cause large financial loss and affect animal health and welfare. Controlling these diseases mostly requires precise information on both individual animal and population dynamics to inform the farmer’s decisions, but even successful control programmes do by no means assure elimination. Mathematical models provide opportunities to test different control and elimination options rather than implementing them in real herds, but these models require robust parameter estimation and validation. Fitting these models to data is a difficult task due to heterogeneities in livestock processes. In this paper, we develop an infectious disease modeling framework for a livestock disease (paratuberculosis) that is caused by Mycobacterium avium subsp. paratuberculosis (MAP). Infection with MAP leads to reduced milk production, pregnancy rates, and slaughter value and increased culling rates in cattle and causes significant economic losses to the dairy industry. These economic effects are particularly important motivations in the control and elimination of MAP. In this framework, an individual-based model (IBM) of a dairy herd was built and MAP infection dynamics was integrated. Once the model produced realistic dynamics of MAP infection, we implemented an evaluation method by fitting it to data from three dairy herds from the Northeast region of the US. The model fitting exercises used least-squares and parameter space searching methods to obtain the best-fitted values of selected parameters. The best set of parameters were used to model the effect of interventions. The results show that the presented model can complement real herd statistics where the intervention strategies suggest a reduction in MAP prevalence without elimination. Overall, this research not only provides a complete model for MAP infection dynamics in a dairy herd but also offers a method for estimating parameters by fitting IBM models.

Expanding behavior pattern sensitivity analysis with model selection and survival analysis

Background

Sensitivity analysis is an essential step in mathematical modeling because it identifies parameters with a strong influence on model output, due to natural variation or uncertainty in the parameter values. Recently behavior pattern sensitivity analysis has been suggested as a method for sensitivity analyses on models with more than one mode of output behavior. The model output is classified by behavior mode and several behavior pattern measures, defined by the researcher, are calculated for each behavior mode. Significant associations between model inputs and outputs are identified by building linear regression models with the model parameters as independent variables and the behavior pattern measures as the dependent variables. We applied the behavior pattern sensitivity analysis to a mathematical model of tetracycline-resistant enteric bacteria in beef cattle administered chlortetracycline orally. The model included 29 parameters related to bacterial population dynamics, chlortetracycline pharmacokinetics and pharmacodynamics. The prevalence of enteric resistance during and after chlortetracycline administration was the model output. Cox proportional hazard models were used when linear regression assumptions were not met.

Results

We have expanded the behavior pattern sensitivity analysis procedure by incorporating model selection techniques to produce parsimonious linear regression models that efficiently prioritize input parameters. We also demonstrate how to address common violations of linear regression model assumptions. Finally, we explore the semi-parametric Cox proportional hazards model as an alternative to linear regression for situations with censored data. In the example mathematical model, the resistant bacteria exhibited three behaviors during the simulation period: (1) increasing, (2) decreasing, and (3) increasing during antimicrobial therapy and decreasing after therapy ceases. The behavior pattern sensitivity analysis identified bacterial population parameters as high importance in determining the trajectory of the resistant bacteria population.

Conclusions

Interventions aimed at the enteric bacterial population ecology, such as diet changes, may be effective at reducing the prevalence of tetracycline-resistant enteric bacteria in beef cattle. Behavior pattern sensitivity analysis is a useful and flexible tool for conducting a sensitivity analysis on models with varied output behavior, enabling prioritization of input parameters via regression model selection techniques. Cox proportional hazard models are an alternative to linear regression when behavior pattern measures are censored or linear regression assumptions cannot be met.

Control measures to prevent the increase of paratuberculosis prevalence in dairy cattle herds: an individual-based modelling approach

Paratuberculosis, a gastrointestinal disease caused by Mycobacterium avium subsp. paratuberculosis (Map), can lead to severe economic losses in dairy cattle farms. Current measures are aimed at controlling prevalence in infected herds, but are not fully effective. Our objective was to determine the most effective control measures to prevent an increase in adult prevalence in infected herds. We developed a new individual-based model coupling population and infection dynamics. Animals are characterized by their age (6 groups) and health state (6 states). The model accounted for all transmission routes and two control measures used in the field, namely reduced calf exposure to adult faeces and test-and-cull. We defined three herd statuses (low, moderate, and high) based on realistic prevalence ranges observed in French dairy cattle herds. We showed that the most relevant control measures depend on prevalence. Calf management and test-and-cull both were required to maximize the probability of stabilizing herd status. A reduced calf exposure was confirmed to be the most influential measure, followed by test frequency and the proportion of infected animals that were detected and culled. Culling of detected high shedders could be delayed for up to 3 months without impacting prevalence. Management of low prevalence herds is a priority since the probability of status stabilization is high after implementing prioritized measures. On the contrary, an increase in prevalence was particularly difficult to prevent in moderate prevalence herds, and was only feasible in high prevalence herds if the level of control was high.

Evaluating the impact of transmission mode, calibration level and farmer compliance in simulation models of paratuberculosis in dairy herds

Simulation models can predict the outcome of different strategies for the control and eradication of paratuberculosis (PTB) in dairy herds. Two main transmission modes have previously been used to simulate the spread of PTB: direct (contact between animals) and indirect (through the environment). In addition, previous models were calibrated to either low or high within-herd prevalence levels, which we refer to as normal and low hygiene levels, respectively. We simulated both direct and indirect transmission with the same model in both normal and low hygiene level scenarios. The effectiveness of a test-and-cull strategy was dependent on the calibration level of the simulation model, and eradication occurred less frequently with the more biologically plausible indirect transmission mode. The results were compared to within-herd prevalence records from 314 dairy herds. The prevalence in 50% of the herds varied less than 0.9% per year on average, and less than 4% in 90% of the herds. We therefore conclude that the normal-hygiene scenario best describes most dairy herds in Denmark. Finally, we simulated different levels of farmer compliance with a test-and-cull strategy and found that a 60% compliance level was not sufficient to reach eradication within 10 years.

An agent-based model evaluation of economic control strategies for paratuberculosis in a dairy herd

This paper uses an agent-based simulation model to estimate the costs associated with Mycobacterium avium ssp. paratuberculosis (MAP), or Johne's disease, in a milking herd, and to determine the net benefits of implementing various control strategies. The net present value (NPV) of a 1,000-cow milking herd is calculated over 20 yr, parametrized to a representative US commercial herd. The revenues of the herd are generated from sales of milk and culled animals. The costs include all variable and fixed costs necessary to operate a representative 1,000-cow milking herd. We estimate the NPV of the herd with no MAP infection, under an expected endemic infection distribution with no controls, and under an expected endemic infection distribution with various controls. The initial number of cows in a herd with an endemic MAP infection is distributed as 75% susceptible, 13% latent, 9% low MAP shedding, and 3% high MAP shedding. Control strategies include testing using ELISA and fecal culture tests and culling of cows that test positive, and culling based on observable milk production decrease. Results show that culling cows based on test results does not increase the herd's NPV and in most cases decreases NPV due to test costs as well as false positives and negatives with their associated costs (e.g., culling healthy cows and keeping infected cows). Culling consistently low producing cows when MAP is believed to be present in the herd produces higher NPV over the strategy of testing and culling MAP infected animals, and over the case of no MAP control.

Evaluation of fecal shedding and antibody response in dairy cattle infected with paratuberculosis using national surveillance data in Japan

Paratuberculosis or Johne's disease (JD), is a chronic infectious disease causing intractable diarrhea in cattle, which leads to less productivity, such as decreased milk yield, and lower daily weight gain. As a control measure against JD in cattle, national serological surveillance has been conducted in Japan since 1998. To conduct modeling studies that are useful to evaluate the effectiveness of control measures against JD, reliable parameter values, such as length of time from infection to the start of fecal shedding or antibody expression, are especially important. These parameters in the Japanese cattle population are assumed to be different from those in other countries with a higher prevalence of JD or in experimental infection settings; therefore, they must be estimated for the cattle population in Japan. Data from national surveillance conducted in Tokachi District, Hokkaido Prefecture, were used for this study. Using data from JD diagnostic tests for all cattle in Tokachi District between 1998 and 2014, all testing histories for infected animals were estimated as the number of tested cattle and positive cattle at each age of month for both fecal and antibody tests. A deterministic mathematical model for JD development, from infection to fecal shedding and antibody expression in infected cattle, was constructed to obtain the probability of testing positive when applied to both fecal and antibody tests at a given age. Likelihood was obtained from these estimated test results and best values for parameters were obtained using the Markov Chain Monte-Carlo method. Fifty-five percent of infected cattle were projected to have a transient shedding period, which was estimated to start 12 months after infection and last for 4 months. Persistent shedding was projected to occur in all infected cattle, and estimated to begin 7-84 months from infection. Following persistent shedding, antibody expression was estimated to start 7 months later. These values are useful for developing models to evaluate the status of JD infection and the effectiveness of control measures in the Japanese cattle population.

Which phenotypic traits of resistance should be improved in cattle to control paratuberculosis dynamics in a dairy herd: a modelling approach

Paratuberculosis is a worldwide disease causing production losses in dairy cattle herds. Variability of cattle response to exposure to Mycobacterium avium subsp. paratuberculosis (Map) has been highlighted. Such individual variability could influence Map spread at larger scale. Cattle resistance to paratuberculosis has been shown to be heritable, suggesting genetic selection could enhance disease control. Our objective was to identify which phenotypic traits characterising the individual course of infection influence Map spread in a dairy cattle herd. We used a stochastic mechanistic model. Resistance consisted in the ability to prevent infection and the ability to cope with infection. We assessed the effect of varying (alone and combined) fourteen phenotypic traits characterising the infection course. We calculated four model outputs 25 years after Map introduction in a naïve herd: cumulative incidence, infection persistence, and prevalence of infected and affected animals. A cluster analysis identified influential phenotypes of cattle resistance. An ANOVA quantified the contribution of traits to model output variance. Four phenotypic traits strongly influenced Map spread: the decay in susceptibility with age (the most effective), the quantity of Map shed in faeces by high shedders, the incubation period duration, and the required infectious dose. Interactions contributed up to 12% of output variance, highlighting the expected added-value of improving several traits simultaneously. Combinations of the four most influential traits decreased incidence to less than one newly infected animal per year in most scenarios. Future genetic selection should aim at improving simultaneously the most influential traits to reduce Map spread in cattle populations.

Use of an Individual-based Model to Control Transmission Pathways of Mycobacterium avium Subsp. paratuberculosis Infection in Cattle Herds

Johne’s disease (JD) is a chronic enteric disease in cattle caused by Mycobacterium avian subsp. paratuberculosis (MAP). Eradicating JD is a difficult task due to the long incubation period of MAP, inefficient diagnostic tests, and delayed clinical signs. Effective control strategies can help farmers to reduce prevalence, but those most acceptable to farmers combine specific information about lactation performance and testing results, which existing models do not provide. This paper presents an individual-based model of MAP infection dynamics and assesses the relative performance of the applied alternative control strategies. The base dairy herd model included the daily life events of a dairy cow and reflects several current dairy management processes. We then integrated MAP infection dynamics into the model. The model adopted four different test-based control strategies based on risk-based culling decisions and three hygiene scenarios. The model tracked the source of each infection and quantified the efficacy of each control strategy in reducing the risks of different transmission routes. The results suggest that risk-based culling can reduce prevalence compared with no control, but cannot eliminate the infection. Overall, this work provides not only a valuable tool to investigate MAP transmission dynamics but also offers adaptability to model similar infectious diseases.

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): paratuberculosis

Paratuberculosis has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on the eligibility of paratuberculosis to be listed, Article 9 for the categorisation of paratuberculosis according to disease prevention and control rules as in Annex IV and Article 8 on the list of animal species related to paratuberculosis. The assessment has been performed following a methodology composed of information collection and compilation, expert judgement on each criterion at individual and, if no consensus was reached before, also at collective level. The output is composed of the categorical answer, and for the questions where no consensus was reached, the different supporting views are reported. Details on the methodology used for this assessment are explained in a separate opinion. According to the assessment performed, paratuberculosis can be considered eligible to be listed for Union intervention as laid down in Article 5(3) of the AHL. The disease would comply with the criteria in Sections 3, 4 and 5 of Annex IV of the AHL, for the application of the disease prevention and control rules referred to in points (c), (d) and (e) of Article 9(1). The animal species to be listed for paratuberculosis according to Article 8(3) criteria are several species of mammals and birds as susceptible species and some species of the families Bovidae, Cervidae and Leporidae as reservoirs.

Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows

Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP) in feces and infect other animals. Farmers identify the infectious animals through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where frequent testing results in lower revenue. When we look at the probability of eradication, then it is correlated with the testing frequency and the target prevalence during the control phase. The probability of eradication is low in the low hygiene herd, and a test-and-cull strategy should probably not be the primary strategy in this herd. Based on this study we suggest that, in order to control MAP, the standard Danish dairy farm should use an adaptive strategy where a short sampling interval of three months is used when the estimated true prevalence is above 1%, and otherwise use a long sampling interval of one year.