Antimicrobial resistance patterns of Campylobacter from feedlot cattle

Aims: This study examined 448 Campylobacter strains isolated in 1999 and 2000 from US feedlot cattle for resistance to 12 antimicrobials. Methods and Results: Isolates were tested for antimicrobial susceptibility using the E-test method. Approximately 60% (n = 267) were resistant to one or more antimicrobials, and 19·6% (n = 88) were resistant to two or more antimicrobials. Of the Campylobacter jejuni isolates, 49·1% (n = 187) were resistant to tetracycline, 10·2% (n = 39) were resistant to nalidixic acid, 8·4% were resistant to trimethoprim/sulfamethoxazole, and 1·8% (n = 7) were resistant to ciprofloxacin. Resistance to any of the other eight antimicrobials was 1·3% or less, but 14·4% (n = 55) were resistant to two or more antimicrobials. In the Campylobacter coli group, 65·7% (n = 44) were resistant to tetracycline, 52·2% (n = 35) were resistant to trimethoprim/sulfamethoxazole, 22·4% (n = 15) were resistant to nalidixic acid, and 9·0% (n = 6) were resistant to ciprofloxacin. Resistance to any of the remaining eight antimicrobials was 3·0% or less, although 49·3% (n = 33) were resistant to two or more antimicrobials. Conclusions: Although antimicrobials are widely used in US feedlot cattle production, our results demonstrate generally low levels of resistance to a broad range of commonly used antimicrobials relative to other recent studies. Significance and Impact of the Study: Resistance data on Campylobacter isolated from this major US livestock commodity is lacking. This overview enhances current knowledge and provides a basis for further studies

Antimicrobial resistance patterns of Campylobacter from feedlot cattle

Aims: This study examined 448 Campylobacter strains isolated in 1999 and 2000 from US feedlot cattle for resistance to 12 antimicrobials. Methods and Results: Isolates were tested for antimicrobial susceptibility using the E-test method. Approximately 60% (n = 267) were resistant to one or more antimicrobials, and 19·6% (n = 88) were resistant to two or more antimicrobials. Of the Campylobacter jejuni isolates, 49·1% (n = 187) were resistant to tetracycline, 10·2% (n = 39) were resistant to nalidixic acid, 8·4% were resistant to trimethoprim/sulfamethoxazole, and 1·8% (n = 7) were resistant to ciprofloxacin. Resistance to any of the other eight antimicrobials was 1·3% or less, but 14·4% (n = 55) were resistant to two or more antimicrobials. In the Campylobacter coli group, 65·7% (n = 44) were resistant to tetracycline, 52·2% (n = 35) were resistant to trimethoprim/sulfamethoxazole, 22·4% (n = 15) were resistant to nalidixic acid, and 9·0% (n = 6) were resistant to ciprofloxacin. Resistance to any of the remaining eight antimicrobials was 3·0% or less, although 49·3% (n = 33) were resistant to two or more antimicrobials. Conclusions: Although antimicrobials are widely used in US feedlot cattle production, our results demonstrate generally low levels of resistance to a broad range of commonly used antimicrobials relative to other recent studies. Significance and Impact of the Study: Resistance data on Campylobacter isolated from this major US livestock commodity is lacking. This overview enhances current knowledge and provides a basis for further studies

Salmonella prevalence and antimicrobial resistance in swine from 5 US states from 2003 to 2005

The Collaboration in Animal Health and Food Safety Epidemiology (CAHFSE), a USDA joint program of ARS, APHIS, and FSIS was established to track food borne pathogens and monitor animal health issues. Fecal samples (n=9020) were collected and cultured for Salmonella from pens of pigs near slaughter weight (generally~ 22 weeks old) from swine farms in five U.S. states. A prevalence of 8.0, 10.1, and 8.5% was observed in 2003, 2004, and 2005, respectively The top 10 serotypes accounted for 94% of the total Salmonella isolates with S. Derby (45%), S. Typhimurium var. 5- (15%), and S Heidelberg (9%) comprising the top three serotypes each year. Salmonella Give was found in 8% of samples in 2003, 3% of samples m 2004, but was not found in the top 10% of ISolates m 2005. The percentage of Salmonella isolates that were susceptible to all of the 16 antimicrobials tested increased from 6% in 2003 to 15% in 2005. At the same time, the percentage of isolates resistant to 10 or more antimicrobials increased from 1% to 15%. The increase in multiple drug resistance was coincident with an increase in the percentage of S. Derby isolates. Overall, frequency of resistance to individual antimicrobials was relatively stable from 2003 to 2005 and observed differences were related to changes in serotypes over time, which highlights the importance of reporting resistance data by individual serotype. CAHFSE provides a mechanism to monitor changes in serotypes of Salmonella as well as antimicrobial resistance patterns over time

Salmonella serotypes from 1997-2003 NARMS swine diagnostic, on-farm, and slaughter samples

The veterinary component of the National Antimicorbial Resistance Monitoring System (NARMS) identified 8527 Salmonella isolates from swine samples in the years 1997-2003. Fifty-one Salmonella serotypes were identified from 3147 diagnostic, 2138 on-farm, and 3246 slaughter samples

Antimicrobial resistance in Salmonella from 1997-2003 NARMS swine samples

A total of 3246 swine slaughter and 3147 swine diagnostic Salmonella isolates from the National Antimicrobial Resistance Monitoring System (NARMS) for the years 1997-2003 were tested for antimicrobial resistance. No resistance was detected in any Salmonella isolates for ciprofloxacin or amikacin. For all other antimicrobics tested, more resistance was observed in diagnostic isolates compared to slaughter isolates

Antimicrobial susceptibility of salmonella isolates from swine

The emergence of antimicrobial resistance among bacteria is of growing concern to practitioners and producers. Problems associated with the emergence of resistance include treatment failure, prolonged shedding, and the development oflong term carriage of the resistant bacteria in the host. The emergence of resistance among Salmonella species is particularly worrisome as it is a zoonotic agent and is ubiquitous in nature

Serotypes and Antimicrobial Resistance in Salmonella Isolates from Swine, NARMS-EB 1997-2000

The National Antimicrobial Resistance Monitoring System (NARMS) was developed in 1996 as a collaborative effort between the FDA, USDA, and CDC to monitor antimicrobial resistance development in enteric organisms in humans and animals. Salmonella was selected as the sentinel organism

National antimicrobial resistance monitoring system: Results for swine

Use of antimicrobics has increased in both human and veterinary medicine. This is due in part to the availability of the antimicrobics and the efficacy they impart in control of certain infectious diseases. However, use of antimicrobics can lead to the development of resistance to the antirnicrobics. Antimicrobial resistance can diminish effectiveness and may even render an antimicrobic ineffective as a therapeutic. Although use may result in a portion of bacteria that are resistant, the exact fate of this population in terms of persistence and transmission has been difficult to determine. Use panerns in veterinary medicine (therapeutic versus preventive versus growth promotion use) also complicates the picture. Additionally, while transmission of resistant bacteria from animals to humans occurs, it has been difficult to assess the extent to which this occurs and the impact transmission has on actual dissemination of resistant populations

Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: Review of current approaches

BACKGROUND: Emerging animal and zoonotic diseases and increasing international trade have resulted in an increased demand for veterinary surveillance systems. However, human and financial resources available to support government veterinary services are becoming more and more limited in many countries world-wide. Intuitively, issues that present higher risks merit higher priority for surveillance resources as investments will yield higher benefit-cost ratios. The rapid rate of acceptance of this core concept of risk-based surveillance has outpaced the development of its theoretical and practical bases. DISCUSSION: The principal objectives of risk-based veterinary surveillance are to identify surveillance needs to protect the health of livestock and consumers, to set priorities, and to allocate resources effectively and efficiently. An important goal is to achieve a higher benefit-cost ratio with existing or reduced resources. We propose to define risk-based surveillance systems as those that apply risk assessment methods in different steps of traditional surveillance design for early detection and management of diseases or hazards. In risk-based designs, public health, economic and trade consequences of diseases play an important role in selection of diseases or hazards. Furthermore, certain strata of the population of interest have a higher probability to be sampled for detection of diseases or hazards. Evaluation of risk-based surveillance systems shall prove that the efficacy of risk-based systems is equal or higher than traditional systems; however, the efficiency (benefit-cost ratio) shall be higher in risk-based surveillance systems. SUMMARY: Risk-based surveillance considerations are useful to support both strategic and operational decision making. This article highlights applications of risk-based surveillance systems in the veterinary field including food safety. Examples are provided for risk-based hazard selection, risk-based selection of sampling strata as well as sample size calculation based on risk considerations

A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels

<p>Abstract</p> <p>Background</p> <p>In recent years, computer simulation models have supported development of pandemic influenza preparedness policies. However, U.S. policymakers have raised several <it>concerns </it>about the practical use of these models. In this review paper, we examine the extent to which the current literature already addresses these <it>concerns </it>and identify means of enhancing the current models for higher operational use.</p> <p>Methods</p> <p>We surveyed PubMed and other sources for published research literature on simulation models for influenza pandemic preparedness. We identified 23 models published between 1990 and 2010 that consider single-region (e.g., country, province, city) outbreaks and multi-pronged mitigation strategies. We developed a plan for examination of the literature based on the concerns raised by the policymakers.</p> <p>Results</p> <p>While examining the concerns about the adequacy and validity of data, we found that though the epidemiological data supporting the models appears to be adequate, it should be validated through as many updates as possible during an outbreak. Demographical data must improve its interfaces for access, retrieval, and translation into model parameters. Regarding the concern about credibility and validity of modeling assumptions, we found that the models often simplify reality to reduce computational burden. Such simplifications may be permissible if they do not interfere with the performance assessment of the mitigation strategies. We also agreed with the concern that social behavior is inadequately represented in pandemic influenza models. Our review showed that the models consider only a few social-behavioral aspects including contact rates, withdrawal from work or school due to symptoms appearance or to care for sick relatives, and compliance to social distancing, vaccination, and antiviral prophylaxis. The concern about the degree of accessibility of the models is palpable, since we found three models that are currently accessible by the public while other models are seeking public accessibility. Policymakers would prefer models scalable to any population size that can be downloadable and operable in personal computers. But scaling models to larger populations would often require computational needs that cannot be handled with personal computers and laptops. As a limitation, we state that some existing models could not be included in our review due to their limited available documentation discussing the choice of relevant parameter values.</p> <p>Conclusions</p> <p>To adequately address the concerns of the policymakers, we need continuing model enhancements in critical areas including: updating of epidemiological data during a pandemic, smooth handling of large demographical databases, incorporation of a broader spectrum of social-behavioral aspects, updating information for contact patterns, adaptation of recent methodologies for collecting human mobility data, and improvement of computational efficiency and accessibility.</p