Search

The goals of the present study were to use data from the first national longitudinal study of students in collegiate recovery programs (CRPs) to 1) provide an updated characterization of CRP students, with respect to demographics and past problem severity; 2) characterize current psychosocial functioning and examine changes in functioning over time; and 3) examine the impact of COVID-19 on CRP students. Data came from a longitudinal cohort study focused on the impact of CRPs on participating students’ success initiated in fall 2020. Four-year universities and community colleges with CRPs were invited to be partners on this project. Three cohorts of participants were recruited. All participants who completed the baseline survey (N = 334) were invited to complete follow-up surveys. The sample was composed of mostly White, cisgender undergraduate students with an average age of 29 years at baseline. CRP students generally reported challenging personal and academic histories, including high levels of polysubstance use and substance problem severity. They evidenced high levels of current psychosocial functioning. Recovery-related functioning (i.e., recovery capital, quality of life) was generally high at baseline and decreased slightly over time. COVID-19 represented a substantial source of stress for many CRP students, impacting some individuals’ abstinence. These results from the first national longitudinal study of CRP students parallel findings from other cross-sectional and/or CRP-specific studies and provide novel insights into the stability of recovery functioning. These results can advance our understanding and characterization of the national CRP student population, with the ability to examine recovery-related constructs over time.

Additional file 1. Percentage of Covariates Selected in Bootstrap Re-fitted Models

Welfare costs of a potential food shock were estimated by disseminating information to milk drinkers on the prevalence of Mycobacterium avium sub. paratuberculosis (MAP) in the U.S. milk supply, its potential linkage to Crohn’s disease in humans, and subsequent government intervention to minimize MAP in the milk supply. We found that 19.6% of milk consumers exposed to MAP information would stop milk consumption at current market prices, and that only 5% of those would return to their original milk consumption levels after the government intervention. Societal costs of the food shock after the intervention were estimated at $18.2 billion., International Journal on Food System Dynamics, Vol 11, No 5 (2020)

Supplemental material, DA2_Manuscript_SupplementaryFigurev2_xyz337630d6ac5bd for Examining the Relationship Between Low Birth Weight Occurrence and Passive Measures of Environmental Arsenic by Census Tract in Escambia and Santa Rosa Counties, Florida by Maya Scott-Richardson, Marilyn O’Hara Ruiz and Rebecca L Smith in Environmental Health Insights

Chronic livestock diseases cause large financial loss and affect the animal health and welfare. Controlling these diseases mostly requires precise information on both individual animal and population dynamics to inform farmer’s decision. Mathematical models provide opportunities to test different control and elimination options rather implementing them in real herds, but these models require valid 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 in the US. 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 a MAP infection was integrated on top of it. 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 suggested a reduction in MAP but no elimination was observed. Overall, this research not only provides a complete model for MAP infection dynamics in a cattle herd, but also offers a method for estimating parameter by fitting IBM models.

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.

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.

Endemic diseases can be counted among the most serious sources of losses for livestock production. In dairy farms in particular, one of the most common diseases is Johne's disease, caused by Mycobacterium avium ssp. paratuberculosis (MAP). Infection with MAP causes direct costs because it affects milk production, but it has also been suspected to increase the risk of clinical mastitis (CM) among infected animals. This might contribute to further costs for farmers. We asked whether MAP infection represents a risk factor for CM and, in particular, whether CM occurrences were more common in MAP-infected animals. Our results, obtained by survival analysis, suggest that MAP-infected cows had an increased probability of experiencing CM during lactation. These results highlight the need to account for the interplay of infectious diseases and other health conditions in economic and epidemiological modeling. In this case, accounting for MAP-infected cows having an increased CM occurrence might have nonnegligible effects on the estimated benefit of MAP control.

Paratuberculosis, or Johne's disease (JD), is a chronic enteric disease of ruminants infected by Mycobacterium avium subsp. paratuberculosis (MAP) that causes a significant financial loss in dairy industry. To reduce prevalence and transmission in dairy herds infected with MAP, control programs have been implemented, including test-based culling, improved calf rearing management, and vaccination. The important issue of preventing MAP invasion into a MAP-free herd has been less investigated, however. The objective of this study was to examine whether vaccination was able to prevent MAP invasion in dairy cattle using a stochastic simulation approach. We developed a MAP vaccination model in which calves were vaccinated with a vaccine that is both imperfect in reducing the susceptibility of the host ('leaky') and that does not successfully immunize all calves ('failure in take'). Probability of MAP persistence and the number of infected animals in herds were computed for both control and vaccinated herds over a ten-year period after introduction of an initial infected heifer. Global parameter sensitivity analyses were performed to find the most influential parameters for MAP invasion. Our results show that vaccination of calves is effective in preventing MAP invasion, provided that the vaccine is of high efficacy in both reduction of susceptibility and 'take' effects; however, there is still a small chance (10 years) due to vertical transmission. This study indicates that reduction in the transmission rate of high shedders (>50 CFU), the number of infected heifers initially introduced to herds, and vertical transmission are important to further decrease the probability of MAP becoming endemic and the overall number of infected animals in endemic herds. The simulation work is useful for designing vaccination programs aimed at preventing MAP invasion in MAP-free herds.

In the dairy industry, Johne's disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (MAP) is one of the major investigated diseases. To date, researchers have suggested some control strategies for JD, such as test-and-cull based herd management, isolated calf rearing management, and vaccinations. Due to the slow progressing nature of MAP, tests with low diagnostic test sensitivity and specificity, and economic limitations, implementing these strategies has not resulted in elimination of MAP from farms. To date, no study has integrated detailed dairy herd dynamics with different MAP transmission routes. We have developed an individual-based dairy herd model by incorporating basic herd dynamics in a closed herd environment where no new animals have been bought from outside. The model considered three age groups of animals: calves, heifers and adults. It includes sequential life events of a dairy animal and such key dynamic processes of the dairy herd as lactation cycle, calving, voluntary waiting period, insemination, pregnancy, dry-off period and calf and heifer rearing. After initially validating that the model reproduced typical herd dynamics, it was extended by incorporating MAP infection dynamics, where each individual adult animal belonged to one of four infection compartments: susceptible, latent, low shedding and high shedding. The model includes two disease transmission routes: horizontal transmission (i.e., fecal-oral) and vertical transmission (i.e., in utero infection). The results confirm that this model can simulate a realistic dairy herd and that inclusion of the above-mentioned dynamic processes provides useful information about individual infected animals to farmers. Access to the individual animal information offers more validity to assessment of appropriate control strategies for an endemically MAP infected herd. This model can serve as an accurate and novel tool not only to better understand MAP dynamics, but is also valuable as an individual based system of a typical dairy herd that can be applied to other research questions.

The objective of this study was to determine the economic value of obtaining timely and more accurate clinical mastitis (CM) test results for optimal treatment of cows. Typically CM is first identified when the farmer observes recognisable outward signs. Further information of whether the pathogen causing CM is Gram-positive, Gram-negative or other (including no growth) can be determined by using on-farm culture methods. The most detailed level of information for mastitis diagnostics is obtainable by sending milk samples for culture to an external laboratory. Knowing the exact pathogen permits the treatment method to be specifically targeted to the causation pathogen, resulting in less discarded milk. The disadvantages are the additional waiting time to receive test results, which delays treating cows, and the cost of the culture test. Net returns per year (NR) for various levels of information were estimated using a dynamic programming model. The Value of Information (VOI) was then calculated as the difference in NR using a specific level of information as compared to more detailed information on the CM causative agent. The highest VOI was observed where the farmer assumed the pathogen causing CM was the one with the highest incidence in the herd and no pathogen specific CM information was obtained. The VOI of pathogen specific information, compared with non-optimal treatment of Staphylococcus aureus where recurrence and spread occurred due to lack of treatment efficacy, was $20.43 when the same incorrect treatment was applied to recurrent cases, and $30.52 when recurrent cases were assumed to be the next highest incidence pathogen and treated accordingly. This indicates that negative consequences associated with choosing the wrong CM treatment can make additional information cost-effective if pathogen identification is assessed at the generic information level and if the pathogen can spread to other cows if not treated appropriately.

Longitudinal data from 3 commercial dairy herds in the northeast United States, collected from 2004 to 2011, were analyzed to determine the effect of Mycobacterium avium ssp. paratuberculosis (MAP) infection status and progression path on milk production. Disease status, as indicated by MAP test results, was determined through quarterly ELISA serum testing, biannual fecal culture, and culture of tissues and feces at slaughter. Milk production data were collected from the Dairy Herd Information Association. Animals with positive MAP test results were categorized, based on test results over the full course of the study, as high path (at least one high-positive culture) or low path (at least one positive culture or ELISA). The cumulative numbers of positive ELISA and culture results were recorded. The effects of both MAP infection path, status, and number of positive tests on milk production were analyzed using a mixed linear model with an autocorrelation random effect structure. Low- and high-path animals produced more milk before their first positive test than always-negative animals, especially high-path animals. Although mean production decreased after a first positive test, low-path animals were shown to recover some productivity. High-path animals continued to exhibit a decrease in milk production, especially after their first high-positive fecal culture. These results show that not all animals that test positive for MAP will have long-term production losses. Milk production decreased significantly with each additional positive test. Ultimately, production loss appeared to be a function of MAP infection progression.

Longitudinal data from 3 commercial dairy herds in the northeast United States, collected from 2004 to 2011, were analyzed to determine the effect of Mycobacterium avium ssp. paratuberculosis (MAP) infection status and progression path on milk production. Disease status, as indicated by MAP test results, was determined through quarterly ELISA serum testing, biannual fecal culture, and culture of tissues and feces at slaughter. Milk production data were collected from the Dairy Herd Information Association. Animals with positive MAP test results were categorized, based on test results over the full course of the study, as high path (at least one high-positive culture) or low path (at least one positive culture or ELISA). The cumulative numbers of positive ELISA and culture results were recorded. The effects of both MAP infection path, status, and number of positive tests on milk production were analyzed using a mixed linear model with an autocorrelation random effect structure. Low- and high-path animals produced more milk before their first positive test than always-negative animals, especially high-path animals. Although mean production decreased after a first positive test, low-path animals were shown to recover some productivity. High-path animals continued to exhibit a decrease in milk production, especially after their first high-positive fecal culture. These results show that not all animals that test positive for MAP will have long-term production losses. Milk production decreased significantly with each additional positive test. Ultimately, production loss appeared to be a function of MAP infection progression.

Replaced with revised version of paper 06/08/11.

A conceptual framework for an infectious disease control model for livestock is developed and empirically applied to evaluate the economic and epidemiological consequences of various controls for Johne's disease in dairy herds. The empirical results show that control of the disease will significantly improve dairy producers' profitability in infected herds., Replaced with revised version of paper 06/08/11.

Infectious diseases play a critical role in determining the profitability of individual farms and maintaining the viability of livestock industries, international trade, and trade policies. Thus, it is critical to analyze the economic consequences of infectious diseases, and the effects of producer strategies to control or eliminate diseases in a cost efficient approach. Also, important is the goal to rally support for the development of public disease control programs. This study examined the long-term feasibility and effectiveness of various producer strategies to prevent and control Johne’s disease in dairy herds, an infectious and incurable disease which has significant economic repercussions for the dairy industry. There are few previous studies available on the economic aspects of Johne’s disease and there remains a knowledge gap with regard to the economics of the disease and the economic justification of the disease controls associated with the biological characteristics of the disease. This study contributes to this body of knowledge. We constructed an optimal control model integrating the biology of animals and disease into an economic framework to estimate the best control method in terms of maximizing an individual farm’s profit and minimizing disease elimination periods. Our results show that any Johne’s disease control method yields a higher net present value compared to no control. Implementing a single control strategy can control the disease, but a combination of control strategies in different categories is the most profitable and effective way to reduce the infection rate in a disease-infected herd. The results of the study are directly applicable to managing this disease on US dairy farms and contribute to controlling a high-priority pathogen in an important industry.

Infectious diseases play a critical role in determining the profitability of individual farms and maintaining the viability of livestock industries, international trade, and trade policies. Thus, it is critical to analyze the economic consequences of infectious diseases, and the effects of producer strategies to control or eliminate diseases in a cost efficient approach. Also, important is the goal to rally support for the development of public disease control programs. This study examined the long-term feasibility and effectiveness of various producer strategies to prevent and control Johne’s disease in dairy herds, an infectious and incurable disease which has significant economic repercussions for the dairy industry. There are few previous studies available on the economic aspects of Johne’s disease and there remains a knowledge gap with regard to the economics of the disease and the economic justification of the disease controls associated with the biological characteristics of the disease. This study contributes to this body of knowledge. We constructed an optimal control model integrating the biology of animals and disease into an economic framework to estimate the best control method in terms of maximizing an individual farm’s profit and minimizing disease elimination periods. Our results show that any Johne’s disease control method yields a higher net present value compared to no control. Implementing a single control strategy can control the disease, but a combination of control strategies in different categories is the most profitable and effective way to reduce the infection rate in a disease-infected herd. The results of the study are directly applicable to managing this disease on US dairy farms and contribute to controlling a high-priority pathogen in an important industry.