@article{jolley_love_frey_lanzas_2023, title={Impacts of the <scp>COVID</scp>‐19 pandemic on antimicrobial use in companion animals in an academic veterinary hospital in North Carolina}, volume={70}, ISSN={1863-1959 1863-2378}, url={http://dx.doi.org/10.1111/zph.13040}, DOI={10.1111/zph.13040}, abstractNote={Abstract}, number={5}, journal={Zoonoses and Public Health}, publisher={Wiley}, author={Jolley, Ashlan and Love, William and Frey, Erin and Lanzas, Cristina}, year={2023}, month={Apr}, pages={393–402} }
 @article{love_wang_lanzas_2022, title={Identifying patient-level risk factors associated with non-beta-lactam resistance outcomes in invasive MRSA infections in the United States using chain graphs}, volume={4}, ISSN={["2632-1823"]}, DOI={10.1093/jacamr/dlac068}, abstractNote={Abstract}, number={4}, journal={JAC-ANTIMICROBIAL RESISTANCE}, author={Love, William J. and Wang, C. Annie and Lanzas, Cristina}, year={2022}, month={Jul} }
 @article{cazer_al-mamun_kaniyamattam_love_booth_lanzas_grohn_2020, title={Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining (vol 10, 687, 2019)}, volume={11}, ISSN={["1664-302X"]}, DOI={10.3389/fmicb.2020.01359}, abstractNote={[This corrects the article DOI: 10.3389/fmicb.2019.00687.].}, journal={FRONTIERS IN MICROBIOLOGY}, author={Cazer, Casey L. and Al-Mamun, Mohammad A. and Kaniyamattam, Karun and Love, William J. and Booth, James G. and Lanzas, Cristina and Grohn, Yrjo T.}, year={2020}, month={Jun} }
 @article{moisa_aly_lehenbauer_love_rossitto_van eenennaam_trombetta_bortoluzzi_hulbert_2019, title={Association of plasma haptoglobin concentration and other biomarkers with bovine respiratory disease status in pre-weaned dairy calves}, volume={31}, ISSN={["1943-4936"]}, DOI={10.1177/1040638718807242}, abstractNote={ We conducted a nested, case-control study of pre-weaned dairy calves ( n = 477; 4 California dairy farms) to assess the association between bovine respiratory disease (BRD) and hematologic biomarkers, including plasma haptoglobin (Hp) and plasma bactericide (PB). At each location, heifer or bull dairy calves were observed 2–4 times per week until confirmed as BRD-positive using parallel interpretation of thoracic ultrasound examination and auscultation. In addition, control calves were enrolled after being confirmed as BRD-negative using ultrasound and auscultation. Complete blood counts (CBC), PB, and Hp concentrations were measured. Hp values were higher in calves with confirmed BRD than in controls ( p < 0.01). The area under the curve (AUC) for the various biomarkers was obtained from the corresponding receiver operating characteristic curves. The AUC for Hp was 0.68, a value greater than those for PB or the remaining CBC parameters, indicating that Hp may be the most useful biomarker of BRD in pre-weaned dairy calves. The cutoff value for Hp was 0.195 g/L. }, number={1}, journal={JOURNAL OF VETERINARY DIAGNOSTIC INVESTIGATION}, author={Moisa, Sonia J. and Aly, Sharif S. and Lehenbauer, Terry W. and Love, William J. and Rossitto, Paul V. and Van Eenennaam, Alison L. and Trombetta, Sophia C. and Bortoluzzi, Eduarda M. and Hulbert, Lindsey E.}, year={2019}, month={Jan}, pages={40–46} }
 @article{zawack_love_lanzas_booth_grohn_2019, title={Estimation of multidrug resistance variability in the National Antimicrobial Monitoring System}, volume={167}, ISSN={["1873-1716"]}, url={https://doi.org/10.1016/j.prevetmed.2019.03.006}, DOI={10.1016/j.prevetmed.2019.03.006}, abstractNote={Multidrug resistance is a serious problem raising the specter of infections for which there is no treatment. One of the most important tools in combating multidrug resistance is large scale monitoring programs, because they track resistance over large geographic areas and time scales. This large scope, however, can also introduce variability into the data. The primary monitoring program in the United States is the National Antimicrobial Resistance Monitoring System (NARMS). This study examines the variability of a previously identified resistance pattern in Escherichia coli among ampicillin, gentamicin, sulfisoxazole, and tetracycline using samples isolated from chicken during the years 2004 to 2006 and 2008 to 2012. 2007 is excluded because sulfisozaxole resistance was not measured at slaughter that year. To assess variability in this resistance pattern susceptibility/resistance contingency tables were constructed for each of the 15 combinations of the 4 drugs for each of the years. For each table, variability across the years was assessed at the full table multinomial level as a measure of general variability of the resistance pattern and at the level of the highest order interaction term in a log-linear model of the table as a measure of variability in that particular component of the resistance pattern. A power analysis using the traditional asymptotic normal approximation and one using a Dirichlet-multinomial simulation were carried out to determine the effect of variation on ability to detect nonzero highest order loglinear model terms and the validity of the normal approximation in carrying out such tests. All tables exhibit overdispersion at the multinomial level and in their highest order model parameters. The normal approximation performs well for large sample sizes, low levels of dispersion, and small log-linear model parameters. The approximation breaks down as dispersion or the log linear model parameter grows or sample size shrinks. Taken together these analyses indicate that the level of variability in the NARMS dataset makes it difficult to detect multidrug resistance patterns at the current level of sample collection. In order to better control this dispersion NARMS could collect more variables on each of the samples.}, journal={PREVENTIVE VETERINARY MEDICINE}, author={Zawack, Kelson and Love, Will J. and Lanzas, Cristina and Booth, James G. and Grohn, Yrjo T.}, year={2019}, month={Jun}, pages={137–145} }
 @article{maier_love_karle_dubrovsky_williams_champagne_anderson_rowe_lehenbauer_van eenennaam_et al._2019, title={Management factors associated with bovine respiratory disease in preweaned calves on California dairies: The BRD 100 study}, volume={102}, ISSN={["1525-3198"]}, DOI={10.3168/jds.2018-14773}, abstractNote={
 ABSTRACT
 
 The objective of this cross-sectional study was to determine how management practices on California dairies may be associated with bovine respiratory disease (BRD) in preweaned calves. A convenience sample of 100 dairies throughout California, providing a study population of 4,636 calves, were visited between May 2014 and April 2016. During each farm visit, in-person interviews with the herd manager or calf caretaker were conducted to collect information about herd demographics, maternity pen, colostrum and calf management, herd vaccinations, and dust abatement. A random sample of preweaned calves was identified and evaluated for the presence of BRD using a standardized tool. A survey-adjusted generalized linear mixed model with a logit link function was fitted with calf as the unit of analysis and dairy as the random effect. Mean study herd size (±SE) was 1,718 (±189.9) cows. Survey-adjusted estimates of breed types in the sample were 81.6% (±0.6) Holstein, 13.1% (±0.4) Jersey, and 5.3% (±0.5) crossbred or other purebred breeds, and calf sex proportions were 73.8% (±1.0) female and 26.2% (±1.0) male. Overall survey-adjusted BRD prevalence in the study herds was 6.91% (±0.69). Housing factors positively associated with BRD were metal hutches compared with wood hutches [odds ratio (OR) = 11.19; 95% confidence interval (CI) = 2.80–44.78], calf-to-calf contact in calves >75 d of age (OR = 9.95, 95% CI = 1.50–65.86), feeding Holstein calves <2.84 L of milk or replacer per day (OR = 7.16, 95% CI = 1.23–41.68), and lagoon water used for flushing manure under hutches compared with no flush (OR = 12.06, 95% CI = 1.93–75.47). Providing extra shade over hutches (OR = 0.08; 95% CI = 0.02–0.37), feeding calves at least 90% saleable milk (OR = 0.27, 95% CI = 0.13–0.54) or pasteurized milk (OR = 0.10; 95% CI = 0.03–0.36), and feeding >5.68 L of milk or replacer per day to Jersey calves (OR = 0.04; 95% CI = 0.01–0.28) were negatively associated with BRD. Our study identified management practices on California dairies with variability and that may contribute to differences in BRD prevalence, which will be incorporated into a risk-assessment tool to control and prevent BRD in preweaned dairy calves.
 
}, number={8}, journal={JOURNAL OF DAIRY SCIENCE}, author={Maier, G. U. and Love, W. J. and Karle, B. M. and Dubrovsky, S. A. and Williams, D. R. and Champagne, J. D. and Anderson, R. J. and Rowe, J. D. and Lehenbauer, T. W. and Van Eenennaam, A. L. and et al.}, year={2019}, month={Aug}, pages={7288–7305} }
 @article{karle_maier_love_dubrovsky_williams_anderson_van eenennaam_lehenbauer_aly_2019, title={Regional management practices and prevalence of bovine respiratory disease in California's preweaned dairy calves}, volume={102}, ISSN={["1525-3198"]}, DOI={10.3168/jds.2018-14775}, abstractNote={The objective of this cross-sectional study was to estimate the prevalence of bovine respiratory disease (BRD) in California preweaned dairy calves and identify management practices that are associated with BRD. A convenience sample of 100 dairies in the 3 distinct dairy regions of California was surveyed. Regions evaluated were Northern California (NCA), northern San Joaquin Valley (NSJV), and greater Southern California (GSCA). A questionnaire on calf management practices and demographic information was administered via in-person interviews at each dairy and a random sample of preweaned calves was evaluated using the California BRD scoring system on the same day. Prevalence of BRD varied between the 3 dairy regions: 9.30% in NCA, 4.51% in NSJV, and 7.35% in GSCA. Breed was not associated with BRD prevalence at the statewide level, but differences in prevalence were observed between breeds across the regions with a higher prevalence in NCA for Jerseys and in GSCA for Holsteins, compared with NSJV. Prevalence of BRD was not different between organic and conventional dairies. Colostrum management practices, including heat treatment and feeding colostrum from multiparous cows, varied by region and were associated with lower BRD prevalence. Calves housed in group pens, a practice observed primarily in NCA, had a higher BRD prevalence than those in individual housing. Feeding salable milk was also more common in NCA and was associated with lower BRD prevalence. Ground and road surfaces adjacent to the calf raising area were also variable by region, and paved surfaces were associated with lower BRD prevalence. Management practices associated with BRD varied across the state and may be addressed to inform the adoption and implementation of potentially protective management decisions on California dairies and other regions with similar dairy systems.}, number={8}, journal={JOURNAL OF DAIRY SCIENCE}, author={Karle, B. M. and Maier, G. U. and Love, W. J. and Dubrovsky, S. A. and Williams, D. R. and Anderson, R. J. and Van Eenennaam, A. L. and Lehenbauer, T. W. and Aly, S. S.}, year={2019}, month={Aug}, pages={7583–7596} }
 @article{cazer_al-mamun_kaniyamattam_love_booth_lanzas_grohn_2019, title={Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining}, volume={10}, ISSN={["1664-302X"]}, url={https://doi.org/10.3389/fmicb.2019.00687}, DOI={10.3389/fmicb.2019.00687}, abstractNote={Using multiple antimicrobials in food animals may incubate genetically-linked multidrug-resistance (MDR) in enteric bacteria, which can contaminate meat at slaughter. The U.S. National Antimicrobial Resistance Monitoring System tested 14,418 chicken-associated Escherichia coli between 2004 and 2012 for resistance to 15 antimicrobials, resulting in >32,000 possible MDR patterns. We analyzed MDR patterns in this dataset with association rule mining, also called market-basket analysis. The association rules were pruned with four quality measures resulting in a <1% false-discovery rate. MDR rules were more stable across consecutive years than between slaughter and retail. Rules were decomposed into networks with antimicrobials as nodes and rules as edges. A strong subnetwork of beta-lactam resistance existed in each year and the beta-lactam resistances also had strong associations with sulfisoxazole, gentamicin, streptomycin and tetracycline resistances. The association rules concur with previously identified E. coli resistance patterns but provide significant flexibility for studying MDR in large datasets.}, journal={FRONTIERS IN MICROBIOLOGY}, author={Cazer, Casey L. and Al-Mamun, Mohammad A. and Kaniyamattam, Karun and Love, William J. and Booth, James G. and Lanzas, Cristina and Grohn, Yrjo T.}, year={2019}, month={Apr} }
 @article{zawack_love_lanzas_booth_grohn_2018, title={Inferring the interaction structure of resistance to antimicrobials}, volume={152}, ISSN={["1873-1716"]}, url={https://doi.org/10.1016/j.prevetmed.2018.02.007}, DOI={10.1016/j.prevetmed.2018.02.007}, abstractNote={The growth of antimicrobial resistance presents a significant threat to human and animal health. Of particular concern is multi-drug resistance, as this increases the chances an infection will be untreatable by any antibiotic. In order to understand multi-drug resistance, it is essential to understand the association between drug resistances. Pairwise associations characterize the connectivity between resistances and are useful in making decisions about courses of treatment, or the design of drug cocktails. Higher-order associations, interactions, which tie together groups of drugs can suggest commonalities in resistance mechanism and lead to their identification. To capture interactions, we apply log-linear models of contingency tables to analyze publically available data on the resistance of Escheresia coli isolated from chicken and turkey meat by the National Antimicrobial Resistance Monitoring System. Standard large sample and conditional exact testing approaches for assessing significance of parameters in these models breakdown due to structured patterns inherent to antimicrobial resistance. To address this, we adopt a Bayesian approach which reveals that E. coli resistance associations can be broken into two subnetworks. The first subnetwork is characterized by a hierarchy of β-lactams which is consistent across the chicken and turkey datasets. Tier one in this hierarchy is a near equivalency between amoxicillin-clavulanic acid, ceftriaxone and cefoxitin. Susceptibility to tier one then implies susceptibility to ceftiofur. The second subnetwork is characterized by more complex interactions between a variety of drug classes that vary between the chicken and turkey datasets.}, journal={PREVENTIVE VETERINARY MEDICINE}, author={Zawack, Kelson and Love, Will and Lanzas, Cristina and Booth, James G. and Grohn, Yrjo T.}, year={2018}, month={Apr}, pages={81–88} }
 @article{love_zawack_booth_grohn_lanzas_2016, title={Markov Networks of Collateral Resistance: National Antimicrobial Resistance Monitoring System Surveillance Results from Escherichia coli Isolates, 2004-2012}, volume={12}, ISSN={["1553-7358"]}, url={https://doi.org/10.1371/journal.pcbi.1005160}, DOI={10.1371/journal.pcbi.1005160}, abstractNote={Surveillance of antimicrobial resistance (AMR) is an important component of public health. Antimicrobial drug use generates selective pressure that may lead to resistance against to the administered drug, and may also select for collateral resistances to other drugs. Analysis of AMR surveillance data has focused on resistance to individual drugs but joint distributions of resistance in bacterial populations are infrequently analyzed and reported. New methods are needed to characterize and communicate joint resistance distributions. Markov networks are a class of graphical models that define connections, or edges, between pairs of variables with non-zero partial correlations and are used here to describe AMR resistance relationships. The graphical least absolute shrinkage and selection operator is used to estimate sparse Markov networks from AMR surveillance data. The method is demonstrated using a subset of Escherichia coli isolates collected by the National Antimicrobial Resistance Monitoring System between 2004 and 2012 which included AMR results for 16 drugs from 14418 isolates. Of the 119 possible unique edges, 33 unique edges were identified at least once during the study period and graphical density ranged from 16.2% to 24.8%. Two frequent dense subgraphs were noted, one containing the five β-lactam drugs and the other containing both sulfonamides, three aminoglycosides, and tetracycline. Density did not appear to change over time (p = 0.71). Unweighted modularity did not appear to change over time (p = 0.18), but a significant decreasing trend was noted in the modularity of the weighted networks (p < 0.005) indicating relationships between drugs of different classes tended to increase in strength and frequency over time compared to relationships between drugs of the same class. The current method provides a novel method to study the joint resistance distribution, but additional work is required to unite the underlying biological and genetic characteristics of the isolates with the current results derived from phenotypic data.}, number={11}, journal={PLOS COMPUTATIONAL BIOLOGY}, publisher={Public Library of Science (PLoS)}, author={Love, William J. and Zawack, Kelson A. and Booth, James G. and Grohn, Yrjo T. and Lanzas, Cristina}, editor={Tanaka, Mark M.Editor}, year={2016}, month={Nov} }
 @article{zawack_li_booth_love_lanzas_grohm_2016, title={Monitoring Antimicrobial Resistance in the Food Supply Chain and Its Implications for FDA Policy Initiatives}, volume={60}, ISSN={["1098-6596"]}, DOI={10.1128/aac.00688-16}, abstractNote={ABSTRACT}, number={9}, journal={ANTIMICROBIAL AGENTS AND CHEMOTHERAPY}, author={Zawack, Kelson and Li, Min and Booth, James G. and Love, Will and Lanzas, Cristina and Grohm, Yrjo T.}, year={2016}, month={Sep}, pages={5302–5311} }