Fecal shedding of, antimicrobial resistance in, and serologic response to Salmonella Typhimurium in dairy calves

Alexander, Kimberly A.; Warnick, Lorin D.; Cripps, C. J.; McDonough, Patrick L.; Gröhn, Yrjö T.; Reed, Kelly E.; James, Karen L.; Soyer, Yeşim; Ivanek, Renata

doi:10.2460/javma.235.6.739

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…Specifically, S . Dublin was consistently among the top three serotypes in ground beef reported annually by FSIS during 2007–2009 and is among the top ten reported ground beef Salmonella serotypes since 2003 [ 36 ]. Salmonella is known to be host-adapted in cattle, and it is therefore not unexpected to find it in ground beef [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Antimicrobial resistance trends in fecal Salmonella isolates from northern California dairy cattle admitted to a veterinary teaching hospital, 2002-2016

et al. 2018

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Nontyphoidal Salmonella infections contribute to approximately 1.2 million annual illnesses in the United States. Historical and recent outbreaks have been associated with dairy products, ground beef, and direct contact with cattle. Salmonella antimicrobial resistance (AMR) is a serious concern that can reduce successful treatment of infections, increasing recovery time, medical costs, and mortality rates in humans and animals. This highlights the need to track AMR in Salmonella isolated from cattle to improve treatment plans, manage trends in AMR, and prevent future AMR development. A total of 242 Salmonella isolates were retrieved from 9,162 cattle fecal samples submitted to the University of California, Davis Veterinary Medical Teaching Hospital from 2002 to 2016. These isolates were tested for antimicrobial susceptibility using a standardized broth dilution panel. Multidrug resistance (MDR) to three or more classes of antimicrobials was observed in 50.8% of isolates, and the most common MDR pattern was amoxicillin-ampicillin-cefoxitin-ceftiofur-ceftriaxone-chloramphenicol-streptomycin-tetracycline (23.2%). There were significantly greater odds for antimicrobial resistance to aminoglycosides (OR: 2.03, 95% CI: 1.1–3.7), penicillins (OR: 1.87, 95% CI: 1.007–3.5), and tetracyclines (OR: 1.87, 95% CI: 1.017–3.4) for the 2002–2009 period when compared to the 2010–2016 period. The most prevalent MDR serotypes were Newport (100% MDR, n = 52), Typhimurium (100%, n = 20), and Dublin (71% MDR, n = 46). Risk factors associated with higher odds for isolating MDR Salmonella included isolates from calves when compared to adult cattle (OR: 22.0; 95% C.I.: 3.9–125.7), and isolates obtained from cattle suspect of having salmonellosis versus from the infectious disease control surveillance program (OR:13.7; 95%C.I.: 2.8–66.8). Despite a temporal trend for reduced AMR to most antimicrobial drug classes, a lack of this observed in the 2002–2009 period when compared to the 2010–2016 period for important drug classes such as cephalosporins (OR: 1.6, 95% CI: 0.87–3.1), and a trend for temporal increase in resistant to quinolones drugs (P value 0.004) highlight the relevance of AMR surveillance in cattle with Salmonella infections with the aim of targeting future prophylactic interventions.

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Section: Discussionmentioning

confidence: 99%

Antimicrobial resistance trends in fecal Salmonella isolates from northern California dairy cattle admitted to a veterinary teaching hospital, 2002-2016

et al. 2018

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“…In these instances, the population estimates and simulated outbreak parameters shared a sigmoid-like relationship due to the model's ancestral branch estimates: the DTA model usually predicts that all the ancestral branches are one host population, until the majority of the tips are another host population, where all the ancestral branches switch [22]. The correct population parameters were also only estimated when simulating outbreaks with equal intra-population transmission rates and infectious periods, parameters that usually differ between Salmonella host populations [26,27]. However, even in these instances the DTA model inaccurately estimated ancestral host population states and transmission parameters.…”

Section: Discussionmentioning

confidence: 99%

Investigation of the validity of two Bayesian ancestral state reconstruction models for estimating Salmonella transmission during outbreaks

Bloomfield¹,

Vaughan²,

Benschop³

et al. 2019

PLoS ONE

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Ancestral state reconstruction models use genetic data to characterize a group of organisms’ common ancestor. These models have been applied to salmonellosis outbreaks to estimate the number of transmissions between different animal species that share similar geographical locations, with animal host as the state. However, as far as we are aware, no studies have validated these models for outbreak analysis. In this study, salmonellosis outbreaks were simulated using a stochastic Susceptible-Infected-Recovered model, and the host population and transmission parameters of these simulated outbreaks were estimated using Bayesian ancestral state reconstruction models (discrete trait analysis (DTA) and structured coalescent (SC)). These models were unable to accurately estimate the number of transmissions between the host populations or the amount of time spent in each host population. The DTA model was inaccurate because it assumed the number of isolates sampled from each host population was proportional to the number of individuals infected within each host population. The SC model was inaccurate possibly because it assumed that each host population's effective population size was constant over the course of the simulated outbreaks. This study highlights the need for phylodynamic models that can take into consideration factors that influence the characteristics and behavior of outbreaks, e.g. changing effective population sizes, variation in infectious periods, intra-population transmissions, and disproportionate sampling of infected individuals.

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“…In these instances, the population estimates and simulated outbreak parameters shared a sigmoid-like relationship due to the model’s ancestral branch estimates: the DTA model usually predicts that all the ancestral branches are one host population, until the majority of the tips are another host population, where all the ancestral branches switch (11). The correct population parameters were also only estimated when simulating outbreaks with equal intra-population transmission rates and infectious periods, parameters that usually differ between Salmonella host populations (15,16). However, even in these instances the DTA model inaccurately estimated ancestral host population states and transmission parameters.…”

Section: Discussionmentioning

confidence: 99%

Investigation of the validity of two Bayesian ancestral state reconstruction models for estimatingSalmonellatransmission during outbreaks

Bloomfield

Vaughan

Benschop

et al. 2019

Preprint

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Ancestral state reconstruction models use genetic data to characterize a group of organisms’ common ancestor. These models have been applied to salmonellosis outbreaks to estimate the number of transmissions between different animal species that share similar geographical locations, with animal host as the state. However, as far as we are aware, no studies have validated these models for outbreak analysis. In this study, salmonellosis outbreaks were simulated using a stochastic Susceptible-Infected-Recovered model, and the host population and transmission parameters of these simulated outbreaks were estimated using Bayesian ancestral state reconstruction models (discrete trait analysis (DTA) and structured coalescent (SC)). These models were unable to accurately estimate the number of transmissions between the host populations or the amount of time spent in each host population. The DTA model was inaccurate because it assumed the number of isolates sampled from each host population was proportional to the number of individuals infected within each host population. The SC model was inaccurate possibly because it assumed that each host population’s effective population size was constant over the course of the simulated outbreaks. This study highlights the need for phylodynamic models that can take into consideration factors that influence the characteristics and behavior of outbreaks, e.g. changing effective population sizes, variation in infectious periods, intra-population transmissions, and disproportionate sampling of infected individuals.

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Fecal shedding of, antimicrobial resistance in, and serologic response to Salmonella Typhimurium in dairy calves

Abstract: Although the herds differed in serologic response and Salmonella subtype, the duration of fecal shedding among calves was similar between herds.

Cited by 5 publications

References 31 publications

Antimicrobial resistance trends in fecal Salmonella isolates from northern California dairy cattle admitted to a veterinary teaching hospital, 2002-2016

Antimicrobial resistance trends in fecal Salmonella isolates from northern California dairy cattle admitted to a veterinary teaching hospital, 2002-2016

Investigation of the validity of two Bayesian ancestral state reconstruction models for estimating Salmonella transmission during outbreaks

Investigation of the validity of two Bayesian ancestral state reconstruction models for estimatingSalmonellatransmission during outbreaks

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