Stochastic modelling to assess economic effects of treatment of chronic subclinical mastitis caused by Streptococcus uberis

2007 ◽  
Vol 74 (4) ◽  
pp. 459-467 ◽  
Author(s):  
Wilma Steeneveld ◽  
Jantijn Swinkels ◽  
Henk Hogeveen
Keyword(s):  
Decision Support ◽  
Current Model ◽  
Economic Value ◽  
Stochastic Modelling ◽  
Subclinical Mastitis ◽  
Economic Effects ◽  
Streptococcus Uberis ◽  
Duration Of Infection ◽  
Specific Factors ◽  
On Farm

Chronic subclinical mastitis is usually not treated during the lactation. However, some veterinarians regard treatment of some types of subclinical mastitis to be effective. The goal of this research was to develop a stochastic Monte Carlo simulation model to support decisions around treatment of chronic subclinical mastitis caused by Streptococcus uberis. Factors in the model included the probability of cure after treatment, probability of the cow becoming clinically diseased, transmission of infection to other cows, and physiological effects of the infection. Using basic input parameters for Dutch circumstances, the average economic costs per cow of an untreated chronic subclinical mastitis case caused by Str. uberis in a single quarter from day of diagnosis onwards was €109. With treatment, the average costs were higher (€120). Thus, for the average cow, treatment was not efficient economically. However, the risk of high costs was much higher when cows with chronic subclinical mastitis were not treated. A sensitivity analysis showed that profitability of treatment of chronic subclinical Str. uberis mastitis depended on farm-specific factors (such as economic value of discarded milk) and cow-specific factors (such as day of diagnosis, duration of infection, amount of transmission to other cows and cure rate). Therefore, herd level protocols are not sufficient and decision support should be cow specific. Given the importance of cow-specific factors, information from the current model could be applied to automatic decision support systems.

Evaluation of the udder health status in subclinical mastitis affected dairy cows through bacteriological culture, somatic cell count and thermographic imaging

2015 ◽  
Vol 18 (4) ◽  
pp. 799-805 ◽  
Author(s):  
A. Bortolami ◽  
E. Fiore ◽  
M. Gianesella ◽  
M. Corrò ◽  
S. Catania ◽  
...  
Keyword(s):  
Health Status ◽  
Dairy Cows ◽  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Subclinical Mastitis ◽  
Bacteriological Culture ◽  
Udder Health ◽  
Streptococcus Uberis ◽  
Thermographic Imaging

Abstract Subclinical mastitis in dairy cows is a big economic loss for farmers. The monitoring of subclinical mastitis is usually performed through Somatic Cell Count (SCC) in farm but there is the need of new diagnostic systems able to quickly identify cows affected by subclinical infections of the udder. The aim of this study was to evaluate the potential application of thermographic imaging compared to SCC and bacteriological culture for infection detection in cow affected by subclinical mastitis and possibly to discriminate between different pathogens. In this study we evaluated the udder health status of 98 Holstein Friesian dairy cows with high SCC in 4 farms. From each cow a sample of milk was collected from all the functional quarters and submitted to bacteriological culture, SCC and Mycoplasma spp. culture. A thermographic image was taken from each functional udder quarter and nipple. Pearson’s correlations and Analysis of Variance were performed in order to evaluate the different diagnostic techniques. The most frequent pathogen isolated was Staphylococcus aureus followed by Coagulase Negative Staphylococci (CNS), Streptococcus uberis, Streptococcus agalactiae and others. The Somatic Cell Score (SCS) was able to discriminate (p<0.05) cows positive for a pathogen from cows negative at the bacteriological culture except for cows with infection caused by CNS. Infrared thermography was correlated to SCS (p<0.05) but was not able to discriminate between positive and negative cows. Thermographic imaging seems to be promising in evaluating the inflammation status of cows affected by subclinical mastitis but seems to have a poor diagnostic value.

On-farm culture and pathogen identification: risks and benefits

Livestock ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 268-273
Author(s):  
Al Manning
Keyword(s):  
Clinical Mastitis ◽  
Selective Treatment ◽  
Gram Positive ◽  
Streptococcus Uberis ◽  
High Prevalence ◽  
Implementation Studies ◽  
International Experts ◽  
On Farm ◽  
The Impact ◽  
High Bulk

Selective treatment of clinical mastitis cases based on the results of on-farm culture (OFC) has been suggested by several international experts. It is based on the theory that mastitis cases caused by Gram-negative species has high resolution rates, and those that do not resolve respond poorly to therapy. Several peer-reviewed studies have evaluated the accuracy of different OFC test kits, which are between 60–85% accurate at identifying Gram-positive pathogens. Implementation studies consistently show a reduction in antimicrobial use, although further research across larger populations is needed to assess the impact on mastitis cure. Any OFC protocol should be regularly reviewed with the herd veterinarian. Herds with a high bulk cell count, a high prevalence of Gram-positive pathogens (e.g. Streptococcus uberis), or with a high prevalence of Klebsiella spp. should carefully consider the impact of deferred or withholding treatment on mastitis cure.

scholarly journals Economic Effects of Biofuel Production on States and Rural Communities

2006 ◽  
Vol 38 (2) ◽  
pp. 377-387 ◽  
Author(s):  
Joe L. Parcell ◽  
Patrick Westhoff
Keyword(s):  
Rural Communities ◽  
Ethanol Production ◽  
Economic Effects ◽  
Biofuel Production ◽  
Local Taxes ◽  
Current Production ◽  
Corn Prices ◽  
On Farm ◽  
Production Industry ◽  
Incentive Payments

This study summarizes research on farm-, local-, regional-, and macro-level economic effects of ethanol production. Given current production levels, the ethanol production industry annually employees approximately 3,500 workers, pays out nearly $132 million in worker salaries, generates over $110 million in local taxes, and takes in some $2 billion in government incentive payments. Projections for a 60 million gallon per year ethanol plant indicate an annual increase in corn usage of 21 million bushels, a one-time capitalization of $75 million, an increase in local corn prices of between $0.06/bushel and $0.12/bushel, a 54 direct and a 210 indirect jobs created, an increase in local tax revenues of $1.2 million, a decrease in federal commodity program outlays of $30 million, and an increase in ethanol production incentives (federal only) of around $30.5 million.

An online decision support tool to evaluate ecological weed management strategies

Weed Science ◽  
2019 ◽  
Vol 67 (4) ◽  
pp. 463-473
Author(s):  
Douglas Bessette ◽  
Robyn Wilson ◽  
Christian Beaudrie ◽  
Clayton Schroeder
Keyword(s):  
Decision Support ◽  
Soil Quality ◽  
Weed Management ◽  
Decision Support Tool ◽  
The United States ◽  
Support Tool ◽  
Organic Farmers ◽  
Ecological Weed Management ◽  
On Farm

AbstractWeeds remain the most commonly cited concern of organic farmers. Without the benefit of synthetic herbicides, organic farmers must rely on a host of ecological weed management (EWM) practices to control weeds. Despite EWM’s ability to improve soil quality, the perceived rate of integrated EWM strategy adoption remains low. This low adoption is likely a result of the complexity in designing and evaluating EWM strategies, the tendency for outreach to focus on the risks of EWM strategies rather than their benefits, and a lack of quantitative measures linking the performance of EWM strategies to farmers’ on-farm objectives and practices. Here we report on the development and deployment of an easy-to-use online decision support tool (DST) that aids organic farmers in identifying their on-farm objectives, characterizing the performance of their practices, and evaluating EWM strategies recommended by an expert advisory panel. Informed by the principles of structured decision making, the DST uses multiple choice tasks to help farmers evaluate the short- and long-term trade-offs of EWM strategies, while also focusing their attention on their most important objectives. We then invited organic farmers across the United States, in particular those whose email addresses were registered on the USDA’s Organic Research Integrity Database, to engage the DST online. Results show considerable movement in participants’ (n = 45) preferences from practices focused on reducing weeding costs and labor in the short term to EWM strategies focused on improving soil quality in the long term. Indeed, nearly half of those farmers (48%) who initially ranked a strategy composed of their current practices highest ultimately preferred a better-performing EWM strategy focused on eliminating the weed seedbank over 5 yr.

scholarly journals A decision support tool for rural water supply planning

2020 ◽  
Vol 10 (3) ◽  
pp. 447-457
Author(s):  
Joseph Cook ◽  
Jake Wagner ◽  
Gunnar Newell
Keyword(s):  
Decision Support ◽  
Water Supply ◽  
Current Model ◽  
Decision Support Tool ◽  
Community Members ◽  
Rural Water Supply ◽  
Support Tool ◽  
Rural Water ◽  
Supply Planning ◽  
Using Data

Abstract Over a dozen studies have examined how households who travel to collect water (about one-quarter of humanity) make choices about where and how much to collect. There is little evidence, however, that these studies have informed rural water supply planning in anything but a qualitative way. In this paper, we describe a new web-based decision support tool that planners or community members can use to simulate scenarios such as (1) price, quality, or placement changes of existing sources, (2) the closure of an existing source, or (3) the addition of a new source. We describe the analytical structure of the model and then demonstrate its possibilities using data from a recent study in rural Meru County, Kenya. We discuss some limits of the current model, and encourage readers and practitioners to explore it and suggest ways in which it could be improved or used most effectively.

Comparison of an on-farm point-of-care diagnostic with conventional culture in analysing bovine mastitis samples

2019 ◽  
Vol 86 (2) ◽  
pp. 222-225 ◽  
Author(s):  
Geoff Jones ◽  
Olaf Bork ◽  
Scott A Ferguson ◽  
Andrew Bates
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Point Of Care ◽  
Bacterial Species ◽  
Class Analysis ◽  
Sensitivity Testing ◽  
Milk Samples ◽  
Streptococcus Uberis ◽  
Standard Culture ◽  
On Farm

AbstractThe performance of a new point-of-care diagnostic (Mastatest), an on-farm test designed to identify bacteria and provide antibiotic sensitivity testing information from milk samples, was compared with standard microbiological culture methods. A total of 292 milk samples from clinical mastitis cases in dairy cows on New Zealand dairy farms were examined, and latent class analysis was used to estimate the performance characteristics of both tests. Two hundred and fifty-six samples (87.7%) demonstrated bacterial infection in standard culture, and 269 (92.1%) using the point-of-care diagnostic. The most common bacterial species detected was Streptococcus uberis, found in 195 samples (66.8%) using standard culture and 190 samples (65.1%) using the point-of-care diagnostic. Latent class analysis found no significant differences in test characteristics between the point-of-care diagnostic and standard culture. The estimated sensitivity and specificity of the point-of-care diagnostic against all targets combined were 94.6 and 72.1% respectively; the corresponding estimates for standard culture were 90.5 and 73.9%. Comparison of antibiotic susceptibility testing using the point-of-care diagnostic and the reference method showed similar trends and, in some cases, identical MIC50 and MIC90 values, with at most one antibiotic dilution difference.

Using dairy herd improvement records and clinical mastitis history to identify subclinical mastitis infections at dry-off

2008 ◽  
Vol 75 (2) ◽  
pp. 240-247 ◽  
Author(s):  
Audrey H Torres ◽  
Päivi J Rajala-Schultz ◽  
Fred J DeGraves ◽  
Kent H Hoblet
Keyword(s):  
Dairy Herd ◽  
Cost Effective ◽  
Subclinical Mastitis ◽  
Clinical Mastitis ◽  
Somatic Cell Counts ◽  
Dry Cow Therapy ◽  
Cell Counts ◽  
On Farm ◽  
First 90 Days ◽  
Major Pathogens

Interest in selective dry cow therapy (SDCT) has been increasing owing to concerns over development of antimicrobial resistance. Implementation of SDCT, however, requires a quick and cost-effective on-farm method for identifying cows for treatment and cows that can be left without treatment. The objective of the present study was to evaluate the use of clinical mastitis (CM) history and somatic cell counts (SCC) from monthly Dairy Herd Improvement (DHI) records in identification of infected and uninfected cows at dry-off. A total of 647 Holstein cows were classified as uninfected or infected at dry-off based on CM history and varying number of monthly SCC records (with three different SCC cut-offs). Cows were considered uninfected based on the following criteria: (1) SCC <100 000 cells/ml and no CM during the lactation; (2) SCC <200 000 cells/ml and no CM during the lactation; (3) as criterion two, but additionally a cow was also considered uninfected if it experienced a case of CM during the first 3 months of the lactation and the SCC was <100 000 cells/ml for the rest of the lactation; (4) SCC <300 000 cells/ml and no CM during the lactation; otherwise they were considered infected. Infected and uninfected cows at dry-off were most efficiently identified using three months' SCC records with a threshold of 200 000 cells/ml for cows without CM during the lactation and a threshold of 100 000 cells/ml during the rest of lactation for cows with CM during the first 90 days in milk. Moreover, this criterion also most efficiently identified cows infected with major pathogens only at dry-off. The success of the criteria used for identifying infected and uninfected cows will, however, depend on herd characteristics, such as prevalence of infection and type of pathogens present in the herd.

scholarly journals Use of on-farm data to guide treatment and control mastitis caused by Streptococcus uberis

2016 ◽  
Vol 99 (9) ◽  
pp. 7690-7699 ◽  
Author(s):  
Olivier Samson ◽  
Nicolas Gaudout ◽  
Ellen Schmitt ◽  
Ynte Hein Schukken ◽  
Ruth Zadoks
Keyword(s):  
Streptococcus Uberis ◽  
And Control ◽  
On Farm
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