A deterministic and stochastic simulation model for intra-herd paratuberculosis transmission

Detection of Low MAP Shedder Prevalence in Large Free-Stall Dairy Herds by Repeated Testing of Environmental Samples and Pooled Milk Samples

Simple Summary

Paratuberculosis is a disease which affects ruminants worldwide. Many countries have implemented certification and monitoring systems to control the disease, particularly in dairy herds. Monitoring herds certified as paratuberculosis non-suspect is an important component of paratuberculosis herd certification programs. The challenge is to detect the introduction or reintroduction of the infectious agent as early as possible with reasonable efforts but high certainty. In our study, we evaluated different low-cost testing schemes in herds where the share of infected animals was low, resulting in a low within-herd prevalence of animals shedding the bacteria that causes paratuberculosis in their feces. The test methods used were repeated pooled milk samples and fecal samples from the barn environment. Our study showed that numerous repetitions of different samples are necessary to monitor such herds with sufficiently high certainty. In the case of herds with a very low prevalence, our study showed that a combination of different sampling approaches is required.

Abstract

An easy-to-use and affordable surveillance system is crucial for paratuberculosis control. The use of environmental samples and milk pools has been proven to be effective for the detection of Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds, but not for monitoring dairy herds certified as MAP non-suspect. We aimed to evaluate methods for the repeated testing of large dairy herds with a very low prevalence of MAP shedders, using different sets of environmental samples or pooled milk samples, collected monthly over a period of one year in 36 herds with known MAP shedder prevalence. Environmental samples were analyzed by bacterial culture and fecal PCR, and pools of 25 and 50 individual milk samples were analyzed by ELISA for MAP-specific antibodies. We estimated the cumulative sensitivity and specificity for up to twelve sampling events by adapting a Bayesian latent class model and taking into account the between- and within-test correlation. Our study revealed that at least seven repeated samplings of feces from the barn environment are necessary to achieve a sensitivity of 95% in herds with a within-herd shedder prevalence of at least 2%. The detection of herds with a prevalence of less than 2% is more challenging and, in addition to numerous repetitions, requires a combination of different samples.

Predicting Positive ELISA Results in Dairy Herds with a Preferred Status in a Paratuberculosis Control Program

Dairy herds participating in the Dutch milk quality assurance program for paratuberculosis are assigned a herd status on the basis of herd examinations by ELISA of individual serum or milk samples, followed by an optional confirmatory fecal PCR. Test-negative herds are assigned Status A; the surveillance of these herds consists of biennial herd examinations. Farmers falsely believing that their Status A herds are Map-free may inadvertently refrain from preventive measures. Therefore, we aimed to develop a predictive model to alert Status A farmers at increased risk of future positive ELISA results. Using data of 8566 dairy herds with Status A in January 2016, two logistic regression models were built, with the probabilities of ≥1 or ≥2 positive samples from January 2017–June 2019 as dependent variables, and province, soil type, herd size, proportion of cattle born elsewhere, time since previous positive ELISA results, and the 95th percentile of the S/P ratios in 2015–2016, as explanatory variables. As internal validation, both models were applied to predict positive ELISA results from January 2019–June 2021, in 8026 herds with Status A in January 2019. The model predicting ≥1 positive sample had an area under the receiver-operating-characteristics curve of 0.76 (95% CI: 0.75, 0.77). At a cut-off predicted probability πc = 0.40, 25% of Status A herds would be alerted with positive and negative predictive values of 0.52 and 0.83, respectively. The model predicting ≥2 positive samples had lower positive, but higher negative, predictive values. This study indicates that discrimination of Status A herds with high and low risks of future positive ELISA results is feasible. This might stimulate farmers with the highest risks to take additional measures to control any undetected Map infections.

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.

Control of paratuberculosis: who, why and how. A review of 48 countries

Paratuberculosis, a chronic disease affecting ruminant livestock, is caused by Mycobacterium avium subsp. paratuberculosis (MAP). It has direct and indirect economic costs, impacts animal welfare and arouses public health concerns. In a survey of 48 countries we found paratuberculosis to be very common in livestock. In about half the countries more than 20% of herds and flocks were infected with MAP. Most countries had large ruminant populations (millions), several types of farmed ruminants, multiple husbandry systems and tens of thousands of individual farms, creating challenges for disease control. In addition, numerous species of free-living wildlife were infected. Paratuberculosis was notifiable in most countries, but formal control programs were present in only 22 countries. Generally, these were the more highly developed countries with advanced veterinary services. Of the countries without a formal control program for paratuberculosis, 76% were in South and Central America, Asia and Africa while 20% were in Europe. Control programs were justified most commonly on animal health grounds, but protecting market access and public health were other factors. Prevalence reduction was the major objective in most countries, but Norway and Sweden aimed to eradicate the disease, so surveillance and response were their major objectives. Government funding was involved in about two thirds of countries, but operations tended to be funded by farmers and their organizations and not by government alone. The majority of countries (60%) had voluntary control programs. Generally, programs were supported by incentives for joining, financial compensation and/or penalties for non-participation. Performance indicators, structure, leadership, practices and tools used in control programs are also presented. Securing funding for long-term control activities was a widespread problem. Control programs were reported to be successful in 16 (73%) of the 22 countries. Recommendations are made for future control programs, including a primary goal of establishing an international code for paratuberculosis, leading to universal acknowledgment of the principles and methods of control in relation to endemic and transboundary disease. An holistic approach across all ruminant livestock industries and long-term commitment is required for control of paratuberculosis.

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.

Incidence of fecal excretion of Mycobacterium avium subsp. paratuberculosis in dairy cows before and after the enrolment in the Québec voluntary program

Paratuberculosis is a chronic and contagious enteric disease of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP). This disease of worldwide distribution is responsible for significant economic losses and the bacteria itself has been linked to human Crohn's disease. Paratuberculosis control programs focus on reducing MAP transmission by implementing better management practices that target infection routes. In Québec, a Voluntary Paratuberculosis Prevention and Control Program (QVPPCP) was launched in 2007. The objectives of this prospective cohort study were threefold. The first was to describe the changes in the incidence of fecal excretion of MAP in cows born before and after farm enrolment in the QVPPCP. The second was to estimate the impact of the risk of within-herd transmission of MAP (measured by the risk assessment score (RAS)) on the incidence of fecal excretion of MAP. And the third was to evaluate the impact of calf rearing practices on the incidence of fecal excretion of MAP. Eighteen MAP-positive herds were visited annually from 2011 to 2015. At each visit, individual fecal samples from all adult cows were collected. MAP was cultured using liquid media and an automated system. A risk assessment questionnaire was completed upon enrolment in the QVPPCP and at each visit. The RAS of the farm was attributed to each cow according to its birthdate. Cox proportional hazards models were used to estimate the hazard ratios (HR) for the exposure variables. Herd clustering was taken into account using robust standard errors. A total of 2158 cows were included (cohort born before n=919; cohort born after n=1239). The incidence and hazard of fecal excretion were significantly lower for the cohort-after than the cohort-before (incidence rate ratio=0.38; 95% CI: 0.18-0.78 and HR=0.48; 95% CI: 0.23-0.98). The HR of fecal excretion for cows exposed to a high RAS was 2.20 times (95% CI: 1.21-3.99) that of cows exposed to a low RAS. Poor calving cow hygiene (HR=3.41; 95% CI: 1.40-8.31) and contact between pre-weaned heifers and adult cows or their feces were significantly associated with an increased hazard of fecal excretion of MAP (HR=2.66; 95% CI: 1.08-6.56). Our results suggest that enrolment in the QVPPCP reduces the risk of MAP fecal excretion. They support the hypothesis that contact between calves and adult cows or their feces increases MAP transmission. The incidence results also suggest that MAP prevalence could be reduced to low levels regardless of initial MAP prevalence.

Epidemiological and economic consequences of purchasing livestock infected with Mycobacterium avium subsp. paratuberculosis

Background

Paratuberculosis (PTB) is a chronic disease which may lead to reduced milk yield, lower animal welfare and death in cattle. The causative agent is Mycobacterium avium subsp. paratuberculosis (MAP). The economic consequences are particularly important incentives in the control and eradication of the infection.

One strategy to control PTB in a herd is to purchase animals from farms with a low risk of MAP infection. We wanted to investigate the epidemiological and economic consequences of buying livestock from different supplier farms of low, medium or high risk, as well as farms with unknown status. We also wanted to estimate the probability of spontaneous fadeout if the farmer of an initially MAP-free herd bought a specified number of infected animals in a single year, or continually bought infected animals. This was achieved through simulation modeling, and the effects of consistently introducing one, five or ten infected animals annually into an initially infection-free herd was also modeled.

Results

Our findings show that once infected, a farm can relatively safely purchase animals from other low and medium-risk farms without experiencing an increase in the prevalence, highlighting the importance of certification programmes. Furthermore, farms free of MAP are highly susceptible and cannot purchase more than a small number of animals per year without having a high risk of being infected. The probability of spontaneous fadeout after 10 years was 82% when introducing a single infected animal into an initially MAP-free herd. When purchasing ten infected animals, this probability was 46%. The continual purchase of infected animals resulted in very low probabilities of spontaneous fadeout.

Conclusions

We demonstrated that MAP-free farms can purchase a small number of animals, preferably from certified farms, each year and still remain free of MAP. Already infected farms have little risk of increasing the prevalence on a farm when purchasing animals from other farms.

Modelling of paratuberculosis spread between dairy cattle farms at a regional scale

Mycobacterium avium subsp. paratuberculosis (Map) causes Johne's disease, with large economic consequences for dairy cattle producers worldwide. Map spread between farms is mainly due to animal movements. Locally, herd size and management are expected to influence infection dynamics. To provide a better understanding of Map spread between dairy cattle farms at a regional scale, we describe the first spatio-temporal model accounting simultaneously for population and infection dynamics and indirect local transmission within dairy farms, and between-farm transmission through animal trade. This model is applied to Brittany, a French region characterized by a high density of dairy cattle, based on data on animal trade, herd size and farm management (birth, death, renewal, and culling) from 2005 to 2013 for 12,857 dairy farms. In all simulated scenarios, Map infection highly persisted at the metapopulation scale. The characteristics of initially infected farms strongly impacted the regional Map spread. Network-related features of incident farms influenced their ability to contaminate disease-free farms. At the herd level, we highlighted a balanced effect of the number of animals purchased: when large, it led to a high probability of farm infection but to a low persistence. This effect was reduced when prevalence in initially infected farms increased. Implications of our findings in the current enzootic situation are that the risk of infection quickly becomes high for farms buying more than three animals per year. Even in regions with a low proportion of infected farms, Map spread will not fade out spontaneously without the use of effective control strategies.

Back to the real world: connecting models with data

Mathematical models for infectious disease are often used to improve our understanding of infection biology or to evaluate the potential efficacy of intervention programs. Here, we develop a mathematical model that aims to describe infection dynamics of Mycobacterium avium subspecies paratuberculosis (MAP). The model was developed using current knowledge of infection biology and also includes some components of MAP infection dynamics that are currently still hypothetical. The objective was to show methods for parameter estimation of state transition models and to connect simulation models with detailed real life data. Thereby making model predictions and results of simulations more reflective and predictive of real world situations. Longitudinal field data from a large observational study are used to estimate parameter values. It is shown that precise data, including molecular diagnostics on the obtained MAP strains, results in more precise and realistic parameter estimates. It is argued that modeling of infection disease dynamics is of great value to understand the patho-biology, epidemiology and control of infectious diseases. The quality of conclusions drawn from model studies depend on two key issues; first, the quality of biology that has gone in the process of developing the model structure; second the quality of the data that go into the estimation of the parameters and the quality and quantity of the data that go into model validation. The more real world data that are used in the model building process, the more likely that modeling studies will provide novel, innovative and valid results.

Modeling tuberculosis dynamics, detection and control in cattle herds

Epidemiological models are key tools for designing and evaluating detection and control strategies against animal infectious diseases. In France, after decades of decrease of bovine tuberculosis (bTB) incidence, the disease keeps circulating. Increasing prevalence levels are observed in several areas, where the detection and control strategy could be adapted. The objective of this work was to design and calibrate a model of the within-herd transmission of bTB. The proposed model is a stochastic model operating in discrete-time. Three health states were distinguished: susceptible, latent and infected. Dairy and beef herd dynamics and bTB detection and control programs were explicitly represented. Approximate Bayesian computation was used to estimate three model parameters from field data: the transmission parameter when animals are inside (β_inside) and outside (β_outside) buildings, and the duration of the latent phase. An independent dataset was used for model validation. The estimated median was 0.43 [0.16–0.84] month⁻¹ for β_inside and 0.08 [0.01–0.32] month⁻¹ for β_outside. The median duration of the latent period was estimated 3.5 [2]–[8] months. The sensitivity analysis showed only minor influences of fixed parameter values on these posterior estimates. Validation based on an independent dataset showed that in more than 80% of herds, the observed proportion of animals with detected lesions was between the 2.5% and 97.5% percentiles of the simulated distribution. In the absence of control program and once bTB has become enzootic within a herd, the median effective reproductive ratio was estimated to be 2.2 in beef herds and 1.7 in dairy herds. These low estimates are consistent with field observations of a low prevalence level in French bTB-infected herds.

Accounting for uncertainty in model-based prevalence estimation: paratuberculosis control in dairy herds

Background

A common approach to the application of epidemiological models is to determine a single (point estimate) parameterisation using the information available in the literature. However, in many cases there is considerable uncertainty about parameter values, reflecting both the incomplete nature of current knowledge and natural variation, for example between farms. Furthermore model outcomes may be highly sensitive to different parameter values. Paratuberculosis is an infection for which many of the key parameter values are poorly understood and highly variable, and for such infections there is a need to develop and apply statistical techniques which make maximal use of available data.

Results

A technique based on Latin hypercube sampling combined with a novel reweighting method was developed which enables parameter uncertainty and variability to be incorporated into a model-based framework for estimation of prevalence. The method was evaluated by applying it to a simulation of paratuberculosis in dairy herds which combines a continuous time stochastic algorithm with model features such as within herd variability in disease development and shedding, which have not been previously explored in paratuberculosis models. Generated sample parameter combinations were assigned a weight, determined by quantifying the model’s resultant ability to reproduce prevalence data. Once these weights are generated the model can be used to evaluate other scenarios such as control options. To illustrate the utility of this approach these reweighted model outputs were used to compare standard test and cull control strategies both individually and in combination with simple husbandry practices that aim to reduce infection rates.

Conclusions

The technique developed has been shown to be applicable to a complex model incorporating realistic control options. For models where parameters are not well known or subject to significant variability, the reweighting scheme allowed estimated distributions of parameter values to be combined with additional sources of information, such as that available from prevalence distributions, resulting in outputs which implicitly handle variation and uncertainty. This methodology allows for more robust predictions from modelling approaches by allowing for parameter uncertainty and combining different sources of information, and is thus expected to be useful in application to a large number of disease systems.

Impact of imperfect Mycobacterium avium subsp. paratuberculosis vaccines in dairy herds: a mathematical modeling approach

The objective of this study was to investigate the potential impacts of imperfect Mycobacterium avium subsp. paratuberculosis (MAP) vaccines on the dynamics of MAP infection in US dairy herds using a mathematical modeling approach. Vaccine-based control programs have been implemented to reduce the prevalence of MAP infection in some dairy herds; however, MAP vaccines are imperfect. Vaccines can provide partial protection for susceptible calves, reduce the infectiousness of animals shedding MAP, lengthen the latent period of infected animals, slow the progression from low shedding to high shedding in infectious animals, and reduce clinical disease. To quantitatively study the impacts of imperfect MAP vaccines, we developed a deterministic multi-group vaccination model and performed global sensitivity analyses. Our results explain why MAP vaccination might have a beneficial, negligible, or detrimental effect in the reduction of prevalence and show that vaccines that are beneficial to individual animals may not be useful for a herd-level control plan. The study suggests that high efficacy vaccines that are aimed at reducing the susceptibility of the host are the most effective in controlling MAP transmission. This work indicates that MAP vaccination should be integrated into a comprehensive control program that includes test-and-cull intervention and improved calf rearing management.

Predicting fadeout versus persistence of paratuberculosis in a dairy cattle herd for management and control purposes: a modelling study

Epidemiological models enable to better understand the dynamics of infectious diseases and to assess ex-ante control strategies. For Mycobacterium avium subsp. paratuberculosis (Map), possible transmission routes have been described, but Map spread in a herd and the relative importance of the routes are currently insufficiently understood to prioritize control measures. We aim to predict early after Map introduction in a dairy cattle herd whether infection is likely to fade out or persist, when no control measures are implemented, using a modelling approach. Both vertical transmission and horizontal transmission via the ingestion of colostrum, milk, or faeces present in the contaminated environment were modelled. Calf-to-calf indirect transmission was possible. Six health states were represented: susceptible, transiently infectious, latently infected, subclinically infected, clinically affected, and resistant. The model was partially validated by comparing the simulated prevalence with field data. Housing facilities and contacts between animals were specifically considered for calves and heifers. After the introduction of one infected animal in a naive herd, fadeout occurred in 66% of the runs. When Map persisted, the prevalence of infected animals increased to 88% in 25 years. The two main transmission routes were via the farm's environment and in utero transmission. Calf-to-calf transmission was minor. Fadeout versus Map persistence could be differentiated with the number of clinically affected animals, which was rarely above one when fadeout occurred. Therefore, early detection of affected animals is crucial in preventing Map persistence in dairy herds.

Invited review: modeling within-herd transmission of Mycobacterium avium subspecies paratuberculosis in dairy cattle: a review

Epidemiological models have been developed to test hypotheses on Mycobacterium avium ssp. paratuberculosis (Map) transmission in a herd, and to compare different paratuberculosis control strategies and alternatives for certification-and-surveillance schemes. The models are simplified representations of existing biological processes tailored to the questions they are intended to answer. Such models depend on available knowledge about the underlying processes, notably in relation to pathogen transmission. All decisions relating to integration of specific aspects of the herd structure and transmission mechanisms as well as modeling objective will influence model behavior and simulation results. This paper examines assumptions on pathogen transmission and risk mitigation represented in 8 epidemiological models of within-herd Map transmission in dairy cattle. We describe available models' structure and examine them in the context of current knowledge about host infection and pathogen transmission pathways. We investigate how population structure and herd management are modeled with regard to their influence on contact structure and pathogen transmission. We show that assumptions about routes of transmission and their contribution within a herd vary greatly among models. Gaps of knowledge that are pivotal to defining transmission equations and parameters, such as variation of susceptibility with age and variability of pattern of shedding, are identified. Quantitative estimates of this incomplete information should be targeted by future research. Existing models could be improved by considering indirect transmission via the environment taking account of Map survival and contact structure between animals in a herd, and by including calf-to-calf transmission, which has recently been proven as being important.