The mean incidence and prevalence values were extremely low due to the fact that the model simulations assumed that only one super-shedder adult cow and another infected adult cow were introduced into the herd in pen 10 and pen 8, respectively and followed for 10 years. Similar results were obtained when small numbers of infected cows and supershedders were introduced into a herd of 10,000 cows. This indicates that the illustrated results are consistent for small numbers of infectious cows and supper shedders initially introduced to the herd. In the population of adult cows, controls 2 & 4a, 2 & 4b, 3 & 4b, 5 & 4b, 4a & 4b , and all controls combined result in a MAP prevalence of 0.52%. Measures 4a or 4b are common to all the adult cattle effective control measures. Hence an effective way to reduce MAP prevalence in the adult cow population is test and cull of test-positive cattle. However, control 4a was more effective than 4b resulting in a MAP prevalence of 0.61% and 0.98%, respectively. Table 10 shows the number of weekly incidence and the mean MAP prevalence for the most effective triple combination control measures and all of the control measures by the end of year 10 for calves and heifers were 5 & 4a & 4b ; and for adult cows is seen with 3 & 4a & 4b . Simulating all the control measures results in the mean MAP prevalence by year 10 in calves and heifers of 0.009% and in adult cows 1.04%.The simulation results indicate that no single control measure was sufficient to prevent increase in incidence of JD; however, Control 4b resulted in the best single control measure. The most effective combination of binary control measures was produced by controls 4a annual test and cull of adult cows and 4b . The overall risk of MAP occurrence was substantially reduced when test and cull was combined with intensive enclosure cleaning to reduce MAP concentration in the environment.

Particularly, the best triple control measures resulted when combining Controls 3, 4a and 4b, dry racks for weed which combined increased scraping of fecal slurry on solid surfaces in the dairy and /or power washing by 10-fold to reduce the environmental pathogen load, while also testing and culling dry-off cows on weekly basis and adult cattle annually. A farm that employs all control measures or a combination of these three control measures has the minimum risk of JD occurrence. It also has extremely prevalence and incidence provided that the number of infectious cow and supper shedder added to the herd is very small . Finally, it should be noted that these results can be expected if the dairy manager adheres to a cattle movement pattern between pens which maintains a degree of isolation between calves and cows and within the cow population as illustrated in the Cattle Movement diagram. Purposefully moving cattle between pens in a prescribed sequence changes the contact patterns between susceptible and infected cows beyond the assumption of random mixing inherent in infectious disease models. Cattle movement management is integral to the effectiveness of MAP control measures and changes to this system can modify the anticipated success of the control measures.Modeling JD with effects of vaccination has been addressed in previous works . In the present study, we did not investigate the effects of vaccination in our modeling and numerical simulations. Previous research has shown that exposure to MAP vaccines or M. aviumantigens can result in false positive tuberculosis tests, which is a concern for herds in TB free states and specifically those that commonly transport cattle across state lines. Furthermore, no vaccine has been developed to fully protect calves. There is currently no available approved treatment in food animals once an animal has contracted the MAP infection. For such reasons vaccinating against MAP is not widely practiced and hence was not considered in the current model.

In the present work we assumed that the amount of shedding in the calf population does not sustainably influence the transmission dynamics of JD, i.e., γC = 0 for pen 1 . Nevertheless, this could be oversimplifying assumption in cases that the shedding rate is greater than a critical value. Although the simulation result indicate that test and cull can be an effective control measure, there are two major concerns regarding test and cull. First, test and cull result is an immediate economic loss, which may not be recovered for a long period. Second, diagnostic tests to identify infected cows often have low sensitivities and are often costly to apply routinely. Therefore, the efficacy of test and cull substantially varies based on the frequency and sensitivity of the test. There are simulating models and field studies that aim to determine the optimal culling rate in different herds based on the long term profitability of the control measure. However, more data and model simulations are needed to develop reliable, effective and profitable JD control programs. It should be noted that the data related to this study is from California dairies. Hence, the outcomes of current study may not necessarily apply to non-intensive dairy systems elsewhere in the US and the world. However, for dairies that manage cows in housing units and groups similar to the study dairies our findings may apply in terms of effectiveness of control measures and what may be expected in reduction of MAP transmission. Another limitation of the current study as with other mathematical modeling studies and specifically those modeling MAP transmission is the lack of precise transmission rates and other inputs needed by the model. Such model inputs require specifically designed studies that can limit variability and target the specific rate of interest. However, MAP’s chronicity increases the duration of such studies which may translate to increase in cost in addition to prolonged duration of studies and potential for loss of follow up of study animals given other competing risks. To address these limitations, the current study identified several key assumptions that can be justified to utilize ranges of transmission rates from previous works .Investigating the optimal use of the cattle movement model with additional controls can benefit from these findings as the data shows that test and cull strategies seem to give the best outcome for R0. When test and cull is applied in pens 7 through 14 we see the most desirable outcome. While the primary goal of this work was to determine the efficacy of control measures using a NC model applied to JD on dairy farms, such models could also be employed to explore impacts on other animals and potentially applied to other diseases.Antimicrobial resistance is a growing concern for food safety and public health globally. Both humans and animals share similar antimicrobial drugs; hence, the judicious use of antimicrobials by both veterinary and human medicine is important to reduce the risk of AMR in enteric bacteria. The administration of therapeutic and prophylactic antimicrobial drugs in animals can be at the individual animal or at the group level. Improper or excessive use of antimicrobials can lead to the development of AMR and multidrug resistance in dairy cows and calves, which could potentially result in the accumulation of bacterial AMR genes within livestock and throughout the farm environment. Modern dairy production systems can be composed of multiple inter-connected cattle production stages, with each stage characterized by unique management practices. Production status, disease conditions, and health status within the cattle groups, and patterns of and governing regulations for antimicrobial usage vary with these stages of production. The distribution of AMR genes in dairy farm settings has not been fully characterized due to the complexity of resistome in dairy production systems and different bacterial communities for different stages of production throughout the farm environment.

According to USDA’s Animal and Plant Health Inspection Service, antimicrobial use in dairy cattle production is classified as three stages of dairy production consisting of preweaned heifers, weaned heifers, and cows and treatment of digestive problems, respiratory infections, mastitis, lameness, and reproductive problems. In general, commercial racks the most frequent antimicrobials used in dairy cattle are tetracyclines, beta-lactams, cephalosporins, and florfenicols. Excessive selective pressures with high antimicrobial concentrations of relevant enteric bacteria can result in a high probability for selection, survival, and dissemination of AMR genes in the environment . Although AMR genes are frequently detected in bacteria from dairy cattle feces, far less is known about the relative abundance of resistance in cattle at different production stages. These knowledge gaps of the ecological connectivity of AMR reservoirs in relation to their microbial communities, and AMR gene transmission pathways within and between dairy cattle at different production stages hamper our efforts to minimize the emergence and persistence of AMR. Whole-genome sequencing and bio-informatics approaches are increasingly used to systemically characterize AMR genes in bacteria from livestock including dairy cattle. The State of California has been the primary dairy producer in the US since 1993, contributing to 18.5% of US milk production. In 2017, dairy cows in California accounted for greater than 20% of the entire dairy population in the US. The overarching goal of this study was to characterize AMR genes in commensal bacteria from cattle at different production stages to generate data that can support future efforts to target AMR control efforts on the farms. Our objectives were to identify AMR genes in Escherichia coli and Enterococcus spp. from cattle at different production stages, contrast AMR phenotypes with the presence or absence of these bacterial AMR genes and identify production stages that have higher risks of spreading AMR genes within the farm environment.The purpose of our study was in part to characterize the overall resistance profile of fecal E. coli and Enterococcus from cattle at different production stages. Based on the resistance genes detected from the ResFinder database , genes conferring resistance to tetracycline, sulphonamide, and aminoglycoside were the main resistance genes in E. coli. This finding was similar to a previous study of AMR in E. coli isolated from dairy cattle, which found E. coli was mostly resistant to tetracycline followed by florfenicol , ampicillin , and chloramphenicol. For Enterococcus spp., resistance to macrolide was the main resistance gene identified in the ResFinder database . In terms of resistance genes identified from the CARD database, 100% of E. coli isolates had genes resistant to over 15 classes of antimicrobials, and 77.6% of Enterococcus isolates had genes resistant to three classes of antimicrobials. Due to the differences in availability and settings of genes between the ResFinder and CARD databases, it was not surprising that resistance genes in E. coli and Enterococcus identified from the two databases were not identical. Interesting, the two databases were consistent in the detection of tetracycline, aminoglycoside, and phenicol as major resistant genes in E. coli and macrolide and aminoglycoside as major resistant genes in Enterococcus. With respect to the major resistance in E. coli and Enterococcus , tetracycline is one of the commonly used antimicrobials in food animal production in the US and Europe, frequently for digestive conditions. Tetracycline is normally used for the treatment of respiratory diseases in food-producing animals in the US. Tetracycline-resistant bacteria, especially non-pathogenic or commensal bacteria, may play a major role as bacterial reservoirs for AMR and MDR, both within cattle populations and for the general dairy farm environment given the ubiquity of manure in these production systems. In general, macrolides and lincosamides are used for the treatment of bacterial infection, especially in mastitis cows, and for growth promotion in food-producing animals. Macrolides are also used in combination with aminoglycosides to treat mastitis in dairy cattle in some European countries, while lincosamides are mainly used in the US in dairy cattle production. We did not collect information on antimicrobial use for this study;hence, we were unable to assess the relationships between the occurrence of AMR genes and antimicrobial use on the farm. However, many studies have indicated that the use of antimicrobials in food-producing animals including dairy cows can lead to increases in AMR and MDR bacteria on livestock farms. In future studies, it would be interesting to further investigate the relationships between AMR and patterns of antimicrobial use at different production stages.Enterococcus spp. are known to cause mastitis in dairy cattle. A previous study revealed that Enterococcus spp. isolates from fecal samples from 122 dairy cattle operations were resistant to lincomycin , followed by flavomycin , and tetracycline.