Presence of Mycobacterium avium subs. paratuberculosis DNA in milk used to feed calves in Portugal

2017 ◽  
Vol 84 (2) ◽  
pp. 124-127 ◽  
Author(s):  
Célia Leão ◽  
Ana Botelho ◽  
Elisabete Martins ◽  
Carla Aguiar ◽  
Inês Rebelo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Transmission ◽  
Dairy Farms ◽  
Mitigation Strategies ◽  
Male And Female ◽  
Milk Samples ◽  
Single Origin ◽  
Waste Milk ◽  
Potential Risks ◽  
Bulk Tank

This Technical Research communication describes results of a study aimed at detecting the presence of Map in milk fed to calves, and identifying possible risk factors for that presence. A questionnaire was performed on 37 dairy farms and waste milk samples were collected on 3 occasions separated by a minimum of 1 week. For farms not feeding waste milk, bulk tank milk samples were collected instead. A real time PCR for the detection of the IS900 sequence was performed for the detection of Map. A majority of farms (89·2%) fed waste milk, with only one pasteurising the milk before feeding it to calves. Results of the PCR showed that 51·5% of the farms that were feeding waste milk had a positive result for Map on that milk. None of the studied risk factors were significantly associated with the presence of Map in milk samples, possibly due to the small number of farms entering the study. However, the prevalence of positive samples for Map on PCR was 3·5 times higher for farms that bought in animals from a single origin and 1·9 times higher for farms that bought from multiple farms, when compared with closed farms. Having a calving area for multiple cows also increased the risk of a positive Map result by 1·5 when compared with single pens. The risk of having a positive Map result on waste milk was 1·6 times higher for farms feeding that milk to male calves and 1·4 for farms feeding to both male and female calves, when compared with farms not feeding waste milk. This study highlights paratuberculosis as one of the potential risks of feeding waste milk to calves, and the need for mitigation strategies to be in place to avoid unnecessary disease transmission.

Characterization of the microbiota and resistome of bulk tank milk samples from Prince Edward Island dairy farms

2021 ◽  
Author(s):  
Landon M.C. Warder ◽  
Enrique Doster ◽  
Jennifer K. Parker ◽  
Paul S. Morley ◽  
J.T. McClure ◽  
...  
Keyword(s):  
Prince Edward Island ◽  
Dairy Farms ◽  
Bulk Tank Milk ◽  
Milk Samples ◽  
Bulk Tank

Occurrence of aflatoxin M1 in bovine milk and associated risk factors among dairy farms of Punjab, India

2021 ◽  
pp. 1-10
Author(s):  
H. Thukral ◽  
P. Dhaka ◽  
J. Singh Bedi ◽  
R. Singh Aulakh
Keyword(s):  
Risk Factors ◽  
European Union ◽  
Bovine Milk ◽  
Dairy Farms ◽  
Buffalo Milk ◽  
Cow Milk ◽  
Milk Samples ◽  
Significant Difference ◽  
Associated Risk Factors ◽  
Mean Concentration

Aflatoxin M1 (AFM1) contamination in milk and milk products may pose a major public health concern. The present cross-sectional study was aimed to estimate the prevalence of AFM1 in bovine milk across all districts of Punjab, India and to identify the associated animal and farm level risk factors. A total of 402 milk samples (266 cow milk and 136 buffalo milk) were analysed using commercial ELISA and representative samples were confirmed using HPLC-FLD. The results revealed that 56.2 and 13.4% of the milk samples exceeded the maximum levels of the European Union, i.e. 0.05 μg/l and Food Safety and Standards Authority of India (FSSAI), i.e. 0.5 μg/l for AFM1 in milk, respectively. On analysis of species variation, buffalo milk (prevalence: 56.6%; mean concentration: 0.42±0.9 μg/l) was found to have higher AFM1 levels than cow milk (prevalence: 56.0%; mean concentration: 0.19±0.3 μg/l), with statistically significant difference between mean concentrations (P<0.01) and non-significant difference between AFM1 prevalence (P=0.91). Furthermore, milk from commercial dairy farms (prevalence: 64.7%; mean concentration: 0.34±0.65 μg/l) was found to be more contaminated than from household dairy establishments (prevalence: 47.8%; mean concentration: 0.19±0.65 μg/l). The risk factors ‘above average milk yield/day’ (odds ratio (OR): 2.4) and ‘poor animal hygiene’ (OR: 1.9) were identified at animal level, and ‘intensive dairy farming’ (OR: 3.1) and ‘animal feed without aflatoxin binder’ (OR: 4.7) as farm level risk factors for AFM1 excretion above maximum levels of European Union in milk. Among cow breeds, the milk from ‘non-descript’ breed (OR: 11.5) was found to be most contaminated with AFM1 and the least from Jersey breed (OR: 1.0). The present study highlighted the presence of AFM1 in milk samples; therefore, regular monitoring of AFM1 in milk is required so that high risk regions and associated risk factors can be addressed appropriately.

scholarly journals Haptoglobin and serum amyloid A in relation to the somatic cell count in quarter, cow composite and bulk tank milk samples

2007 ◽  
Vol 74 (2) ◽  
pp. 198-203 ◽  
Author(s):  
Maria Åkerstedt ◽  
Karin Persson Waller ◽  
Åse Sternesjö
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Serum Amyloid A ◽  
Dairy Farms ◽  
Serum Amyloid ◽  
Bulk Tank Milk ◽  
Amyloid A ◽  
Milk Samples ◽  
Bulk Tank

Milk somatic cell count (SCC) is the gold standard in diagnosis of subclinical mastitis, and is also an important parameter in quality programmes of dairy cooperatives. As routine SCC analysis is usually restricted to central laboratories, much effort has been invested in the search for alternative biomarkers of mastitis and milk quality, including the presence in the milk of the acute phase proteins (APP), haptoglobin (Hp) and serum amyloid A (SAA). The aim of this study was to investigate relationships between Hp, SAA and SCC in quarter, cow composite, and bulk tank milk samples. Cows (n=165), without any clinical signs of disease or abnormalities in the milk or udder, from three different dairy farms, were used. Cow composite milk samples from all cows delivering milk at the sampling occasion were taken once in each herd. In one of the farms, representative quarter milk samples (n=103) from 26 cows were also collected. In addition, bulk tank milk samples from 96 dairy farms were included in the study. Samples were analysed for Hp, SAA and SCC, and relationships between the parameters were evaluated at quarter, cow and tank milk levels using Chi-square analysis. Milk samples were categorized according to their SCC, and the presence, or no presence, of SAA and Hp, based on the detection limits of the screening methods (0·3 mg/l and 1·0 mg/l for SAA and Hp, respectively). Hp and SAA were found in milk at quarter, cow composite and bulk tank levels. A large proportion (53%) of the animals had detectable milk concentrations of APP, and SAA was detected more frequently, and at higher concentrations than Hp, regardless of sample type. SAA was detected in as many as 82% of the bulk tank milk samples. Significant relationships were found between Hp, SAA and SCC at quarter and cow composite milk levels, but only between SAA and SCC at bulk tank milk level. Detectable levels of APP were more common at high SCC.

COMPARISONS OF MASTITIS SCREENING TEST RESULTS FROM QUARTER, BUCKET AND BULK MILK SAMPLES1,2

1967 ◽  
Vol 30 (1) ◽  
pp. 7-12 ◽  
Author(s):  
D. S. Postle
Keyword(s):  
Test Scores ◽  
Screening Test ◽  
Dairy Farms ◽  
Screening Tests ◽  
Test Results ◽  
Milk Samples ◽  
Bulk Milk ◽  
Leukocyte Counts ◽  
Bulk Tank ◽  
One Year

Summary Milk from four dairy farms in southern Wisconsin was examined over a period of one year in a study that was undertaken: (a) to determine the agreement between results of mastitis screening tests when applied to bulk, bucket and quarter milk samples; (b) to determine the relative efficiencies of five mastitis screening tests using direct microscopic leukocyte counts as a standard, and (c) to examine the quality, as determined by leukocyte content and screening test results, of the milk from all quarters contributing to the bulk tank on each farm. Most screening tests examined, when applied to quarter milk samples, gave a higher correlation with direct microscopic leukocyte counts than when applied to either bucket or bulk milk samples. Similarly, efficiency ratings of screening tests applied to quarter samples were higher than those for the same tests applied to bulk samples. Three of the four farms examined maintained bulk tank milk screening test scores that failed to suggest the presence of milk from a substantial number of quarters that were shedding abnormal numbers of leukocytes.

scholarly journals Iodine content in bulk tank milk samples in relation to dairy farm size

2014 ◽  
Vol 83 (10) ◽  
pp. S9-S13 ◽  
Author(s):  
Lenka Vorlová ◽  
Lucia Hodulová ◽  
Ivana Borkovcová ◽  
Hana Přidalová ◽  
Romana Kostrhounová ◽  
...  
Keyword(s):  
Dairy Farm ◽  
Iodine Content ◽  
Dairy Farms ◽  
Raw Milk ◽  
Farm Size ◽  
Milk Samples ◽  
Significant Difference ◽  
Organic Dairy ◽  
Bulk Tank ◽  
Organic Dairy Farms

The aim of this study was to compare the iodine content in raw milk from organic and conventional dairy farms of different sizes. Milk samples were collected between 2012 and 2013, and the iodine content was determined by a Sandell-Kolthoff reaction after dry alkaline digestion of the milk samples. Comparing the iodine content in raw milk samples from small sized dairy farms (116.76 ± 46.29 μg/l) and large sized dairy farms (173.70 ± 35.42 μg/l), a significant difference in iodine content was observed (P ≤ 0.05). The lowest values were found in small and medium dairy farms, 45.30 μg/l and 40.46 μg/l, respectively. High variability (112.92 ± 94.74 μg/l) in the iodine content was detected in raw milk from medium sized dairy farms. When considering milk samples from organic dairy farms (119.29 μg /l ± 40.37) vs. conventional dairy farms (136.55 μg/l ± 42.91), no significant difference was detected. These results indicate higher iodine content in milk from large dairy farms regardless of conventional or organic farming methods.

scholarly journals Prevalence of Coxiella burnetii in cows’ and ewes’ bulk tank milk samples from selected dairy farms of Central Italy

2017 ◽  
Vol 16 (4) ◽  
pp. 673-676 ◽  
Author(s):  
Fabrizia Guidi ◽  
Annalisa Petruzzelli ◽  
Floriana Ciarrocchi ◽  
Anna Duranti ◽  
Andrea Valiani ◽  
...  
Keyword(s):  
Coxiella Burnetii ◽  
Central Italy ◽  
Dairy Farms ◽  
Bulk Tank Milk ◽  
Milk Samples ◽  
Bulk Tank

scholarly journals 1214. Household Transmission of Febrile Illness Measured by Smartphone-Connected Thermometers, United States, 2016-2021

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S697-S697
Author(s):  
Danielle Bloch ◽  
John Zicker ◽  
Hannah Somhegyi ◽  
Patrick Philips ◽  
Inder Singh ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Transmission ◽  
Rank Correlation ◽  
Febrile Illness ◽  
Incidence Rates ◽  
Mitigation Strategies ◽  
Health Board ◽  
Secondary Transmission ◽  
Targeted Interventions ◽  
Household Transmission

Abstract Background Understanding household transmission dynamics of infectious diseases can help develop mitigation strategies. Traditional methods of population-level disease surveillance do not capture household transmission. Data collected from smartphone-connected thermometers that can differentiate among individuals in a household can be used to study these characteristics. Using this technology, we estimated the household secondary attack rate (SAR) of febrile illness, assessed its correlation with CDC-reported influenza-like illness (ILI) and COVID-19 case incidence, and identified risk factors for secondary transmission. Methods We conducted a retrospective cohort study among 596,096 febrile illness index cases recorded from August 1, 2016 to January 20, 2021 in households with two or more individuals in all 50 states. Fevers were measured using the Kinsa Smart Thermometer and mobile device app. Secondary cases were defined as household members who recorded a fever 1–10 days after an index case. We calculated SAR prior to and during the COVID-19 pandemic within the study period, and assessed correlation to ILI and COVID-19 case incidence using Spearman’s rank correlation coefficient. Bivariate and multivariable mixed logistic regression models were used to identify risk factors for secondary transmission. Results SAR in the pre-COVID-19 period was 5.9% (95% CI: 5.8%–6.0%) during flu season (November to April), and 3.7% (95% CI: 3.6%–3.7%) in flu off-season, and weekly SAR was significantly correlated with ILI reported from CDC (ρ=0.84, p&lt; 0.001). Secondary transmission was 40% more likely to occur in households where the index case’s initial temperature was ≥ 39.1°C. During the COVID-19 period, SAR was 3.3% (95% CI: 3.3%–3.4%), and daily SAR was significantly correlated with national daily COVID-19 incidence rates (ρ=0.86, p&lt; 0.001). Households in census tracts with &gt;50% essential workforce were 50% more likely to experience secondary transmission. Conclusion Household SAR was highly correlated with ILI and COVID-19 cases. Capturing household transmission of febrile illness through routine public health surveillance may identify risk factors for infectious disease transmission, allowing for more targeted interventions. Disclosures Danielle Bloch, MPH, Kinsa Health (Employee, Shareholder) John Zicker, MS, Kinsa Health (Employee, Shareholder) Hannah Somhegyi, PhD, Kinsa Health (Employee, Shareholder) Patrick Philips, n/a, Kinsa Health (Employee, Shareholder) Inder Singh, n/a, Kinsa Health (Board Member, Employee, Shareholder) Amy Daitch, PhD, Kinsa Health (Employee, Shareholder)

scholarly journals A survey of management practices on Irish dairy farms with emphasis on risk factors for Johne’s disease transmission

2014 ◽  
Vol 67 (1) ◽  
Author(s):  
Aideen E Kennedy ◽  
Eugene F O’Doherty ◽  
Noel Byrne ◽  
Jim O’Mahony ◽  
E M Kennedy ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Transmission ◽  
Management Practices ◽  
Dairy Farms ◽  
Johne's Disease ◽  
Johne’S Disease
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