Dataset Information

A nested compartmental model to assess the efficacy of paratuberculosis control measures on U.S. dairy farms.

ABSTRACT: Paratuberculosis, also known as Johne's disease (JD), is a chronic contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP). The disease is incurable, fatal and causes economic losses estimated to exceed 200 million dollars to the U.S. dairy industry annually. Several preventive and control measures have been recommended; however, only a few of these measures have been validated empirically. Using a nested compartmental (NC) modeling approach, the main objective of this research was to identify the best combination of control and preventive measures that minimizes the prevalence and incidence of JD and the risk of MAP occurrence in a dairy herd. The NC model employs both MAP transmission estimates and data on pen movement of cattle on a dairy to quantify the effectiveness of control and preventive measures. To obtain reasonable ranges of parameter values for between-pen movements, the NC model was fitted to the movement data of four typical California dairy farms. Using the estimated ranges of the movement parameters and those of JD from previous research, the basic reproduction number was calculated to measure the risk of MAP occurrence in each pen environment as well as the entire dairy. Although the interventions evaluated by the NC model were shown to reduce the infection, no single measure alone was capable of eradicating the infection. The numerical simulations suggest that a combination of test and cull with more frequent manure removal is the most effective method in reducing incidence, prevalence and the risk of MAP occurrence. Other control measures such as limiting calf-adult cow contacts, raising calves in a disease-free herd or colostrum management were less effective.

SUBMITTER: Konboon M

PROVIDER: S-EPMC6168138 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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A nested compartmental model to assess the efficacy of paratuberculosis control measures on U.S. dairy farms.

Konboon Malinee M Bani-Yaghoub Majid M Pithua Patrick O PO Rhee Noah N Aly Sharif S SS

PloS one 20181002 10

Paratuberculosis, also known as Johne's disease (JD), is a chronic contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP). The disease is incurable, fatal and causes economic losses estimated to exceed 200 million dollars to the U.S. dairy industry annually. Several preventive and control measures have been recommended; however, only a few of these measures have been validated empirically. Using a nested compartmental (NC) modeling approach, the main objective of this re ...[more]

PMID: 30278041

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Project description:Various measures have been advocated for the control of Johne's disease (caused by Mycobacterium avium subsp. paratuberculosis, MAP) in different countries. Farmers' compliance has been reported to be variable depending on disease prevalence and incentives to participate in control programs. After the prevalence of MAP shedding and risk factors for within-herd spread of MAP were assessed in 17 Swiss cattle herds (10 dairy and 7 beef), general and herd-specific recommendations were given to the farmers to reduce MAP transmission within the herd. Participation in the study and implementation of control measures were voluntary, no financial incentives were provided for the realization of control measures. After a 3-year period of monitored observation including biannual farm visits and discussion of the situation, the implementation of the recommended control measures and their effect on prevalence of MAP shedding were evaluated. Implementation of recommended general and farm-specific control measures was only partially realized. Neither the number of animals tested positive (before or during the study) nor the farmers' knowledge about paratuberculosis were significantly associated with their compliance for the implementation of management changes. The apparent within-herd prevalence remained constant despite limited implementation of control measures, and no particular group of control measures was found to be associated with changes in prevalence. Farmers' compliance for the implementation of control measures to reduce the impact of Johne's disease in infected farms was very limited under Swiss farming conditions in the frame of voluntary participation in a research project. These results indicate that the losses associated with paratuberculosis in Swiss dairy and beef operations are not estimated to be high enough by the farmers to justify important efforts for control measures, and that incentives may be necessary to achieve efficient implementation of such measures.

Project description:BackgroundEndometritis is a prevalent uterine disease in postpartum cows. The disease reduces fertility performance and milk yield, and subsequently, productivity and profitability of dairy farms. The reduction in performance is associated with considerable economic losses on dairy farms. Smallholder farmers are likely to incur considerable economic losses from the disease where they lack knowledge of effective prevention and control measures for the disease. This study used farmer's perspectives to determine the effectiveness of different management interventions (MIs) for endometritis prevention and control on smallholder farms in Rwanda practicing dairy zero-grazing. The best-worst scaling (BWS) choice method was applied that relied on past 1 year recall data obtained from 154 farmers. These farmers were identified through snowball sampling in a cross-sectional study.ResultsOf the 20 MIs evaluated, 12 scored highly for effectiveness. The top four most effective are: avoiding sharing equipment with neighbouring farms (45.5%), consulting animal health service provider about disease treatment (31.8%), keeping cows in a clean and dry shed (26.7%), and selecting sires based on calving ease (26.6%). The MIs considered least effective were: maintaining clean transition cow housing (35.1%), removal of fetal membrane immediately after passing (33.1%), disinfecting the equipment used in calving assistance before and after use (32.5%), and selecting sires with low percent stillbirths (29.2%).ConclusionThis study has demonstrated the application of BWS object case method in understanding the MIs that farmers consider are most effective in the prevention and control of endometritis disease in the dairy herds. The MIs are on-farm biosecurity and hygiene, seeking veterinary services for disease treatment and selecting sires for ease of calving. These MIs should be considered for prioritization in extension services and research to continuously improve and enhance their practical application on smallholder dairy farms.

Project description:BackgroundA 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.ResultsA 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.ConclusionsThe 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.

Project description:Hepatitis E virus (HEV) genotype 3 is a prevalent zoonotic pathogen in European pig farms, posing a significant public health risk primarily through the foodborne route. The study aimed to identify effective biosecurity measures for controlling HEV transmission on pig farms, addressing a critical gap in current knowledge. Utilizing a cross-sectional design, fecal samples from gilts, dry sows, and fatteners were collected on 231 pig farms of all farm types across nine European countries. Real-time RT-PCR was employed to test these samples for HEV. Simultaneously, a comprehensive biosecurity questionnaire captured data on various potential measures to control HEV. The dependent variable was HEV risk, categorized as lower or higher based on the percentage of positive pooled fecal samples on each farm (25% cut-off). The data were analyzed using generalized linear models (one for finisher samples and one for all samples) with a logit link function with country and farm type as a priori fixed factors. The results of the final multivariable models identified key biosecurity measures associated with lower HEV risk, which were the use of a hygienogram in the breeding (OR: 0.06, p = 0.001) and/or fattening area after cleaning (OR: 0.21, p = 0.019), the presence of a quarantine area (OR: 0.29, p = 0.025), testing and/or treating purchased feed against Salmonella (OR: 0.35, p = 0.021), the presence of other livestock species on the farm, and having five or fewer persons in charge of the pigs. Contrary to expectations, some biosecurity measures were associated with higher HEV risk, e.g., downtime of 3 days or longer after cleaning in the fattening area (OR: 3.49, p = 0.005) or mandatory handwashing for farm personnel when changing barn sections (OR: 3.4, p = 0.026). This novel study unveils critical insights into biosecurity measures effective in controlling HEV on European pig farms. The identification of both protective and risk-associated measures contributes to improving strategies for managing HEV and underscores the complexity of biosecurity in pig farming.

Dataset Information

A nested compartmental model to assess the efficacy of paratuberculosis control measures on U.S. dairy farms.

Publications

A nested compartmental model to assess the efficacy of paratuberculosis control measures on U.S. dairy farms.

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