Many pathogens spread via environmental transmission, without requiring host-to-host direct contact. While models for environmental transmission exist, many are simply constructed intuitively with structures analogous to standard models for direct transmission. As model insights are generally sensitive to the underlying model assumptions, it is important that we are able understand the details and consequences of these assumptions. We construct a simple network model for an environmentally-transmitted pathogen and rigorously derive systems of ordinary differential equations (ODEs) based on different assumptions. We explore two key assumptions, namely homogeneity and independence, and demonstrate that relaxing these assumptions can lead to more accurate ODE approximations. We compare these ODE models to a stochastic implementation of the network model over a variety of parameters and network structures, demonstrating that with fewer restrictive assumptions we are able to achieve higher accuracy in our approximations and highlighting more precisely the errors produced by each assumption. We show that less restrictive assumptions lead to more complicated systems of ODEs and the potential for unstable solutions. Due to the rigour of our derivation, we are able to identify the reason behind these errors and propose potential resolutions.
}, number={2}, journal={MATHEMATICAL BIOSCIENCES AND ENGINEERING}, author={Davies, Kale and Lenhart, Suzanne and Day, Judy and Lloyd, Alun L. and Lanzas, Cristina}, year={2022}, pages={1637–1673} }
@article{das_igoe_lenhart_luong_lanzas_lloyd_odoi_2022, title={Geographic disparities and determinants of COVID-19 incidence risk in the greater St. Louis Area, Missouri (United States)}, volume={17}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0274899}, abstractNote={BackgroundEvidence seems to suggest that the risk of Coronavirus Disease 2019 (COVID-19) might vary across communities due to differences in population characteristics and movement patterns. However, little is known about these differences in the greater St Louis Area of Missouri and yet this information is useful for targeting control efforts. Therefore, the objectives of this study were to investigate (a) geographic disparities of COVID-19 risk and (b) associations between COVID-19 risk and socioeconomic, demographic, movement and chronic disease factors in the Greater St. Louis Area of Missouri, USA.}, number={9}, journal={PLOS ONE}, author={Das, Praachi and Igoe, Morganne and Lenhart, Suzanne and Luong, Lan and Lanzas, Cristina and Lloyd, Alun L. and Odoi, Agricola}, year={2022}, month={Sep} }
@article{igoe_das_lenhart_lloyd_luong_tian_lanzas_odoi_2022, title={Geographic disparities and predictors of COVID-19 hospitalization risks in the St. Louis Area, Missouri (USA)}, volume={22}, ISSN={["1471-2458"]}, DOI={10.1186/s12889-022-12716-w}, abstractNote={Abstract}, number={1}, journal={BMC PUBLIC HEALTH}, author={Igoe, Morganne and Das, Praachi and Lenhart, Suzanne and Lloyd, Alun L. and Luong, Lan and Tian, Dajun and Lanzas, Cristina and Odoi, Agricola}, year={2022}, month={Feb} }
@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{farthing_lanzas_2021, title={Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach}, volume={37}, ISSN={["1878-0067"]}, DOI={10.1016/j.epidem.2021.100524}, abstractNote={Nonpharmaceutical interventions for minimizing indoor SARS-CoV-2 transmission continue to be critical tools for protecting susceptible individuals from infection, even as effective vaccines are produced and distributed globally. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission during discrete events taking place in a single room within a sub-day time frame, and used it to compare effects of four interventions on reducing secondary SARS-CoV-2 attack rates during a superspreading event by simulating a well-known case study. We found that preventing people from moving within the simulated room and efficacious mask usage appear to have the greatest effects on reducing infection risk, but multiple concurrent interventions are required to minimize the proportion of susceptible individuals infected. Social distancing had little effect on reducing transmission if individuals were randomly relocated within the room to simulate activity-related movements during the gathering. Furthermore, our results suggest that there is potential for ventilation airflow to expose susceptible people to aerosolized pathogens even if they are relatively far from infectious individuals. Maximizing the vertical aerosol removal rate is paramount to successful transmission-risk reduction when using ventilation systems as intervention tools.}, journal={EPIDEMICS}, author={Farthing, Trevor S. and Lanzas, Cristina}, year={2021}, month={Dec} }
@article{farthing_lanzas_2021, title={Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: an agent-based modeling approach}, volume={1}, url={https://doi.org/10.1101/2021.01.21.21250240}, DOI={10.1101/2021.01.21.21250240}, abstractNote={Abstract}, publisher={Cold Spring Harbor Laboratory}, author={Farthing, Trevor S. and Lanzas, Cristina}, year={2021}, month={Jan} }
@article{farthing_dawson_sanderson_seger_lanzas_2021, title={Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission}, volume={8}, ISSN={["2054-5703"]}, url={https://doi.org/10.1098/rsos.210328}, DOI={10.1098/rsos.210328}, abstractNote={
Enteric microparasites like
Escherichia coli
use multiple transmission pathways to propagate within and between host populations. Characterizing the relative transmission risk attributable to host social relationships and direct physical contact between individuals is paramount for understanding how microparasites like
E. coli
spread within affected communities and estimating colonization rates. To measure these effects, we carried out commensal
E. coli
transmission experiments in two cattle (
Bos taurus
) herds, wherein all individuals were equipped with real-time location tracking devices. Following transmission experiments in this model system, we derived temporally dynamic social and contact networks from location data. Estimated social affiliations and dyadic contact frequencies during transmission experiments informed pairwise accelerated failure time models that we used to quantify effects of these sociobehavioural variables on weekly
E. coli
colonization risk in these populations. We found that sociobehavioural variables alone were ultimately poor predictors of
E. coli
colonization in feedlot cattle, but can have significant effects on colonization hazard rates (
p
≤ 0.05). We show, however, that observed effects were not consistent between similar populations. This work demonstrates that transmission experiments can be combined with real-time location data collection and processing procedures to create an effective framework for quantifying sociobehavioural effects on microparasite transmission.
}, number={10}, journal={ROYAL SOCIETY OPEN SCIENCE}, author={Farthing, Trevor S. and Dawson, Daniel E. and Sanderson, Mike W. and Seger, Hannah and Lanzas, Cristina}, year={2021}, month={Oct} }
@article{love_wang_lanzas_2021, title={Identifying patient-level risk factors associated with non-β-lactam resistance outcomes in invasive methicillin-resistant Staphylococcus aureus infections in the United States using chain graphs}, volume={11}, url={https://doi.org/10.1101/2021.11.12.21266278}, DOI={10.1101/2021.11.12.21266278}, abstractNote={ABSTRACT}, publisher={Cold Spring Harbor Laboratory}, author={Love, William J. and Wang, Christine A. and Lanzas, Cristina}, year={2021}, month={Nov} }
@article{dawson_rasmussen_peng_lanzas_2021, title={Inferring environmental transmission using phylodynamics: a case-study using simulated evolution of an enteric pathogen}, volume={18}, ISSN={["1742-5662"]}, url={https://doi.org/10.1098/rsif.2021.0041}, DOI={10.1098/rsif.2021.0041}, abstractNote={Indirect (environmental) and direct (host–host) transmission pathways cannot easily be distinguished when they co-occur in epidemics, particularly when they occur on similar time scales. Phylodynamic reconstruction is a potential approach to this problem that combines epidemiological information (temporal, spatial information) with pathogen whole-genome sequencing data to infer transmission trees of epidemics. However, factors such as differences in mutation and transmission rates between host and non-host environments may obscure phylogenetic inference from these methods. In this study, we used a network-based transmission model that explicitly models pathogen evolution to simulate epidemics with both direct and indirect transmission. Epidemics were simulated according to factorial combinations of direct/indirect transmission proportions, host mutation rates and conditions of environmental pathogen growth. Transmission trees were then reconstructed using the phylodynamic approach SCOTTI (structured coalescent transmission tree inference) and evaluated. We found that although insufficient diversity sets a lower bound on when accurate phylodynamic inferences can be made, transmission routes and assumed pathogen lifestyle affected pathogen population structure and subsequently influenced both reconstruction success and the likelihood of direct versus indirect pathways being reconstructed. We conclude that prior knowledge of the likely ecology and population structure of pathogens in host and non-host environments is critical to fully using phylodynamic techniques.}, number={179}, journal={JOURNAL OF THE ROYAL SOCIETY INTERFACE}, author={Dawson, Daniel and Rasmussen, David and Peng, Xinxia and Lanzas, Cristina}, year={2021}, month={Jun} }
@article{sulyok_fox_ritchie_lanzas_lenhart_day_2021, title={Mathematically modeling the effect of touch frequency on the environmental transmission of Clostridioides difficile in healthcare settings}, volume={340}, ISSN={["1879-3134"]}, DOI={10.1016/j.mbs.2021.108666}, abstractNote={Clostridioides difficile, formerly Clostridium difficile, is the leading cause of infectious diarrhea and one of the most common healthcare acquired infections in United States hospitals. C. difficile persists well in healthcare environments because it forms spores that can survive for long periods of time and can be transmitted to susceptible patients through contact with contaminated hands and fomites, objects or surfaces that can harbor infectious agents. Fomites can be classified as high-touch or low-touch based on the frequency they are contacted. The mathematical model in this study investigates the relative contribution of high-touch and low-touch fomites on new cases of C. difficile colonization among patients of a hospital ward. The dynamics of transmission are described by a system of ordinary differential equations representing four patient population classes and two pathogen environmental reservoirs. Parameters that have a significant effect on incidence, as determined by a global sensitivity analysis, are varied in stochastic simulations of the system to identify feasible strategies to prevent disease transmission. Results indicate that on average, under one-quarter of asymptomatically colonized patients are exposed to C. difficile via low-touch fomites. In comparison, over three-quarters of colonized patients are colonized through high-touch fomites, despite additional cleaning of high-touch fomites. Increased contacts with high-touch fomites increases the contribution of these fomites to the incidence of colonized individuals and decreasing the duration of a hospital visit reduces the amount of pathogen in the environment. Thus, enhanced efficacy of disinfection upon discharge and extra cleaning of high-touch fomites, reduced contact with high-touch fomites, and higher discharge rates, among other control measures, could lead to a decrease in the incidence of colonized individuals.}, journal={MATHEMATICAL BIOSCIENCES}, author={Sulyok, Cara Jill and Fox, Lindsey and Ritchie, Hannah and Lanzas, Cristina and Lenhart, Suzanne and Day, Judy}, year={2021}, month={Oct} }
@article{machado_farthing_andraud_nunes lopes_lanzas_2021, title={Modelling the role of mortality-based response triggers on the effectiveness of African swine fever control strategies}, volume={10}, ISSN={["1865-1682"]}, url={https://doi.org/10.1111/tbed.14334}, DOI={10.1111/tbed.14334}, abstractNote={African swine fever (ASF) is considered the most impactful transboundary swine disease. In the absence of effective vaccines, control strategies are heavily dependent on mass depopulation and shipment restrictions. Here, we developed a nested multiscale model for the transmission of ASF, combining a spatially explicit network model of animal shipments with a deterministic compartmental model for the dynamics of two ASF strains within 3 km × 3 km pixels in one Brazilian state. The model outcomes are epidemic duration, number of secondary infected farms and pigs, and distance of ASF spread. The model also shows the spatial distribution of ASF epidemics. We analyzed quarantine-based control interventions in the context of mortality trigger thresholds for the deployment of control strategies. The mean epidemic duration of a moderately virulent strain was 11.2 days, assuming the first infection is detected (best-case scenario), and 15.9 days when detection is triggered at 10% mortality. For a highly virulent strain, the epidemic duration was 6.5 days and 13.1 days, respectively. The distance from the source to infected locations and the spatial distribution was not dependent on strain virulence. Under the best-case scenario, we projected an average number of infected farms of 23.77 farms and 18.8 farms for the moderate and highly virulent strains, respectively. At 10% mortality-trigger, the predicted number of infected farms was on average 46.27 farms and 42.96 farms, respectively. We also demonstrated that the establishment of ring quarantine zones regardless of size (i.e. 5 km, 15 km) was outperformed by backward animal movement tracking. The proposed modelling framework provides an evaluation of ASF epidemic potential, providing a ranking of quarantine-based control strategies that could assist animal health authorities in planning the national preparedness and response plan.}, journal={TRANSBOUNDARY AND EMERGING DISEASES}, publisher={Wiley}, author={Machado, Gustavo and Farthing, Trevor S. and Andraud, Mathieu and Nunes Lopes, Francisco Paulo and Lanzas, Cristina}, year={2021}, month={Oct} }
@article{farthing_lanzas_2021, title={When can we stop wearing masks? Agent-based modeling to identify when vaccine coverage makes nonpharmaceutical interventions for reducing SARS-CoV-2 infections redundant in indoor gatherings}, volume={4}, url={https://doi.org/10.1101/2021.04.19.21255737}, DOI={10.1101/2021.04.19.21255737}, abstractNote={Abstract}, publisher={Cold Spring Harbor Laboratory}, author={Farthing, Trevor S. and Lanzas, Cristina}, year={2021}, month={Apr} }
@article{farthing_dawson_sanderson_lanzas_2020, title={Accounting for space and uncertainty in real‐time location system‐derived contact networks}, url={https://doi.org/10.1002/ece3.6225}, DOI={10.1002/ece3.6225}, abstractNote={Abstract}, journal={Ecology and Evolution}, author={Farthing, Trevor S. and Dawson, Daniel E. and Sanderson, Michael W. and Lanzas, Cristina}, year={2020}, month={Jun} }
@article{garabed_jolles_garira_lanzas_gutierrez_rempala_2020, title={Multi-scale dynamics of infectious diseases}, volume={10}, url={https://doi.org/10.1098/rsfs.2019.0118}, DOI={10.1098/rsfs.2019.0118}, abstractNote={To address the challenge of multiscale dynamics of infectious diseases, the Mathematical Biosciences Institute organized a workshop at The Ohio State University to bring together scientists from a variety of disciplines to share expertise gained through looking at infectious diseases across different scales. The researchers at the workshop, held in April 2018, were specifically looking at three model systems: foot-and-mouth disease, vector-borne diseases and enteric diseases. Although every multiscale model must be necessarily derived from a multiscale system, not every multiscale system has to lead to multiscale models. These three model systems seem to have produced a variety of both multiscale and integrated single-scale mechanistic models that have developed their own strengths and particular challenges. Here, we present papers from some of the workshop participants to show the breadth of the field.}, number={1}, journal={Interface Focus}, publisher={The Royal Society}, author={Garabed, Rebecca B. and Jolles, Anna and Garira, Winston and Lanzas, Cristina and Gutierrez, Juan and Rempala, Grzegorz}, year={2020}, month={Feb}, pages={20190118} }
@article{lanzas_davies_erwin_dawson_2020, title={On modelling environmentally transmitted pathogens}, volume={10}, url={https://doi.org/10.1098/rsfs.2019.0056}, DOI={10.1098/rsfs.2019.0056}, abstractNote={Many pathogens are able to replicate or survive in abiotic environments. Disease transmission models that include environmental reservoirs and environment-to-host transmission have used a variety of functional forms and modelling frameworks without a clear connection to pathogen ecology or space and time scales. We present a conceptual framework to organize microparasites based on the role that abiotic environments play in their lifecycle. Mean-field and individual-based models for environmental transmission are analysed and compared. We show considerable divergence between both modelling approaches when conditions do not facilitate well mixing and for pathogens with fast dynamics in the environment. We conclude with recommendations for modelling environmentally transmitted pathogens based on the pathogen lifecycle and time and spatial scales of the host–pathogen system under consideration.}, number={1}, journal={Interface Focus}, author={Lanzas, Cristina and Davies, Kale and Erwin, Samantha and Dawson, Daniel}, year={2020}, month={Feb} }
@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{lashnits_dawson_breitschwerdt_lanzas_2019, title={Ecological and Socioeconomic Factors Associated with Bartonella henselae Exposure in Dogs Tested for Vector-Borne Diseases in North Carolina}, volume={19}, ISSN={1530-3667 1557-7759}, url={http://dx.doi.org/10.1089/vbz.2018.2397}, DOI={10.1089/vbz.2018.2397}, abstractNote={Bartonella henselae is a zoonotic vector-borne pathogen affecting both humans and dogs. Little is known about the epidemiology of B. henselae in dogs, including risk factors associated with exposure. The objectives of this study were to map the current distribution of B. henselae in dogs in North Carolina (NC) and to identify ecological and socioeconomic factors influencing B. henselae seroreactivity. Results from 4446 B. henselae serology samples from dogs in NC submitted by veterinarians for clinical diagnostic testing to the North Carolina State University College of Veterinary Medicine Vector Borne Disease Diagnostic Laboratory between January 1, 2004 and December 31, 2015 were retrospectively reviewed. These results were used to generate a map of B. henselae seroreactivity. To account for sparsely sampled areas, statistical smoothing using head banging and areal interpolation kriging was performed. Using previously described risk factors for exposure to canine tick-borne diseases, eight multivariable logistic regression models based on biologically plausible hypotheses were tested, and a final model was selected using an Akaike's Information Criterion weighted-average approach. Seroreactivity among dogs tested for vector-borne disease was variable across the state: higher along the southern/eastern coastal plains and eastern Piedmont, and lower in the western mountains. Of 25 explanatory factors considered, the model combining demographic, socioeconomic, climatic, and land use variables fits best. Based on this model, female intact sex and increasing percentage of the county with low-intensity development and evergreen forest were associated with higher seroreactivity. Conversely, moderate development, increasing median household income, and higher temperature range and relative humidity were associated with lower seroreactivity. This model could be improved, however, by including local and host-scale factors that may play a significant role in dogs' exposure.}, number={8}, journal={Vector-Borne and Zoonotic Diseases}, publisher={Mary Ann Liebert Inc}, author={Lashnits, Erin W. and Dawson, Daniel E. and Breitschwerdt, Edward and Lanzas, Cristina}, year={2019}, month={Aug}, pages={582–595} }
@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{chen_lanzas_lee_zenarosa_arif_dulin_2019, title={Metapopulation Model from Pathogen's Perspective: A Versatile Framework to Quantify Pathogen Transfer and Circulation between Environment and Hosts}, volume={9}, ISSN={["2045-2322"]}, DOI={10.1038/s41598-018-37938-0}, abstractNote={Abstract}, journal={SCIENTIFIC REPORTS}, author={Chen, Shi and Lanzas, Cristina and Lee, Chihoon and Zenarosa, Gabriel L. and Arif, Ahmed A. and Dulin, Michael}, year={2019}, month={Feb} }
@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{dawson_farthing_sanderson_lanzas_2019, title={Transmission on empirical dynamic contact networks is influenced by data processing decisions}, volume={26}, ISSN={["1755-4365"]}, url={https://doi.org/10.1016/j.epidem.2018.08.003}, DOI={10.1016/j.epidem.2018.08.003}, abstractNote={Dynamic contact data can be used to inform disease transmission models, providing insight into the dynamics of infectious diseases. Such data often requires extensive processing for use in models or analysis. Therefore, processing decisions can potentially influence the topology of the contact network and the simulated disease transmission dynamics on the network. In this study, we examine how four processing decisions, including temporal sampling window (TSW), spatial threshold of contact (SpTh), minimum contact duration (MCD), and temporal aggregation (daily or hourly) influence the information content of contact data (indicated by changes in entropy) as well as disease transmission model dynamics. We found that changes made to information content by processing decisions translated to significant impacts to the transmission dynamics of disease models using the contact data. In particular, we found that SpTh had the largest independent influence on information content, and that some output metrics (R0, time to peak infection) were more sensitive to changes in information than others (epidemic extent). These findings suggest that insights gained from transmission modeling using dynamic contact data can be influenced by processing decisions alone, emphasizing the need to carefully consideration them prior to using contact-based models to conduct analyses, compare different datasets, or inform policy decisions.}, journal={EPIDEMICS}, publisher={Elsevier BV}, author={Dawson, Daniel E. and Farthing, Trevor S. and Sanderson, Michael W. and Lanzas, Cristina}, year={2019}, month={Mar}, pages={32–42} }
@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{dawson_keung_napoles_vella_chen_sanderson_lanzas_2018, title={Investigating behavioral drivers of seasonal Shiga-Toxigenic Escherichia Coli (STEC) patterns in grazing cattle using an agent-based model}, volume={13}, ISSN={["1932-6203"]}, url={http://europepmc.org/articles/PMC6179278}, DOI={10.1371/journal.pone.0205418}, abstractNote={The causes of seasonal variability in pathogen transmission are not well understood, and have not been comprehensively investigated. In an example for enteric pathogens, incidence of Escherichia coli O157 (STEC) colonization in cattle is consistently higher during warmer months compared to cooler months in various cattle production systems. However, actual mechanisms for this seasonality remain elusive. In addition, the influence of host (cattle) behavior on this pattern has not been thoroughly considered. To that end, we constructed a spatially explicit agent-based model that accounted for the effect of temperature fluctuations on cattle behavior (direct contact among cattle and indirect between cattle and environment), as well as its effect on pathogen survival in the environment. We then simulated the model in a factorial approach to evaluate the hypothesis that temperature fluctuations can lead to seasonal STEC transmission dynamics by influencing cattle aggregation, grazing, and drinking behaviors. Simulation results showed that higher temperatures increased the frequency at which cattle aggregated under shade in pasture, resulting in increased direct contact and transmission of STEC between individual cattle, and hence higher incidence over model simulations in the warm season. In contrast, increased drinking behavior during warm season was not an important transmission pathway. Although sensitivity analyses suggested that the relative importance of direct vs. indirect (environmental) pathways depend to upon model parameterization, model simulations indicated that factors influencing cattle aggregation, such as temperature, were likely strong drivers of transmission dynamics of enteric pathogens.}, number={10}, journal={PLOS ONE}, author={Dawson, Daniel E. and Keung, Jocelyn H. and Napoles, Monica G. and Vella, Michael R. and Chen, Shi and Sanderson, Michael W. and Lanzas, Cristina}, year={2018}, month={Oct} }
@article{chen_lenhart_day_lee_dulin_lanzas_2018, title={Pathogen transfer through environment-host contact: an agent-based queueing theoretic framework}, volume={35}, ISSN={["1477-8602"]}, url={https://doi.org/10.1093/imammb/dqx014}, DOI={10.1093/imammb/dqx014}, abstractNote={Queueing theory studies the properties of waiting queues and has been applied to investigate direct host-to-host transmitted disease dynamics, but its potential in modelling environmentally transmitted pathogens has not been fully explored. In this study, we provide a flexible and customizable queueing theory modelling framework with three major subroutines to study the in-hospital contact processes between environments and hosts and potential nosocomial pathogen transfer, where environments are servers and hosts are customers. Two types of servers with different parameters but the same utilization are investigated. We consider various forms of transfer functions that map contact duration to the amount of pathogen transfer based on existing literature. We propose a case study of simulated in-hospital contact processes and apply stochastic queues to analyse the amount of pathogen transfer under different transfer functions, and assume that pathogen amount decreases during the inter-arrival time. Different host behaviour (feedback and non-feedback) as well as initial pathogen distribution (whether in environment and/or in hosts) are also considered and simulated. We assess pathogen transfer and circulation under these various conditions and highlight the importance of the nonlinear interactions among contact processes, transfer functions and pathogen demography during the contact process. Our modelling framework can be readily extended to more complicated queueing networks to simulate more realistic situations by adjusting parameters such as the number and type of servers and customers, and adding extra subroutines.}, number={3}, journal={MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA}, author={Chen, Shi and Lenhart, Suzanne and Day, Judy D. and Lee, Chihoon and Dulin, Michael and Lanzas, Cristina}, year={2018}, month={Sep}, pages={409–425} }
@article{phenotypical resistance correlation networks for 10 non-typhoidal salmonella subpopulations in an active antimicrobial surveillance programme._2018, url={https://doi.org/10.1017/S0950268818000833}, DOI={10.1017/s0950268818000833}, abstractNote={Abstract}, journal={Epidemiology and infection}, year={2018}, month={Apr} }
@article{fletcher_erwin_lanzas_theriot_2018, title={Shifts in the Gut Metabolome and Clostridium difficile Transcriptome throughout Colonization and Infection in a Mouse Model}, volume={3}, ISSN={["2379-5042"]}, url={http://europepmc.org/articles/PMC5874438}, DOI={10.1128/msphere.00089-18}, abstractNote={
Clostridium difficile
is a bacterial pathogen of global significance that is a major cause of antibiotic-associated diarrhea. Antibiotics deplete the indigenous gut microbiota and change the metabolic environment in the gut to one favoring
C. difficile
growth. Here we used metabolomics and transcriptomics to define the gut environment after antibiotics and during the initial stages of
C. difficile
colonization and infection. We show that amino acids, in particular, proline and branched-chain amino acids, and carbohydrates decrease in abundance over time and that
C. difficile
gene expression is consistent with their utilization by the bacterium
in vivo
. We employed an integrated approach to analyze the metabolome and transcriptome to identify associations between metabolites and transcripts. This highlighted the importance of key nutrients in the early stages of colonization, and the data provide a rationale for the development of therapies based on the use of bacteria that specifically compete for nutrients that are essential for
C. difficile
colonization and disease.
}, number={2}, journal={MSPHERE}, author={Fletcher, Joshua R. and Erwin, Samantha and Lanzas, Cristina and Theriot, Casey M.}, year={2018} }
@misc{grohn_carson_lanzas_pullum_stanhope_volkova_2017, title={A proposed analytic framework for determining the impact of an antimicrobial resistance intervention}, volume={18}, ISSN={["1475-2654"]}, url={https://doi.org/10.1017/S1466252317000019}, DOI={10.1017/s1466252317000019}, abstractNote={Abstract}, number={1}, journal={ANIMAL HEALTH RESEARCH REVIEWS}, author={Grohn, Yrjo T. and Carson, Carolee and Lanzas, Cristina and Pullum, Laura and Stanhope, Michael and Volkova, Victoriya}, year={2017}, month={Jun}, pages={1–25} }
@article{bintz_lenhart_lanzas_2017, title={Antimicrobial Stewardship and Environmental Decontamination for the Control of Clostridium difficile Transmission in Healthcare Settings}, volume={79}, ISSN={["1522-9602"]}, url={http://europepmc.org/articles/PMC5495002}, DOI={10.1007/s11538-016-0224-7}, abstractNote={We implement an agent-based model for Clostridium difficile transmission in hospitals that accounts for several processes and individual factors including environmental and antibiotic heterogeneity in order to evaluate the efficacy of various control measures aimed at reducing environmental contamination and mitigating the effects of antibiotic use on transmission. In particular, we account for local contamination levels that contribute to the probability of colonization and we account for both the number and type of antibiotic treatments given to patients. Simulations illustrate the relative efficacy of several strategies for the reduction of nosocomial colonizations and nosocomial diseases.}, number={1}, journal={BULLETIN OF MATHEMATICAL BIOLOGY}, author={Bintz, Jason and Lenhart, Suzanne and Lanzas, Cristina}, year={2017}, month={Jan}, pages={36–62} }
@article{lanzas_2017, title={Arresting Contagion: Science, Policy, and Conflicts Over Animal Disease Control. By Alan L. Olmstead and Paul W. Rhode. Cambridge (Massachusetts): Harvard University Press. $49.95. xi + 465 p.; ill.; index. ISBN: 978-0-674-72877-6. 2015.}, volume={92}, ISSN={0033-5770 1539-7718}, url={http://dx.doi.org/10.1086/694941}, DOI={10.1086/694941}, abstractNote={Previous articleNext article No AccessHistory, Philosophy, and Ethics of BiologyArresting Contagion: Science, Policy, and Conflicts Over Animal Disease Control. By Alan L. Olmstead and Paul W. Rhode. Cambridge (Massachusetts): Harvard University Press. $49.95. xi + 465 p.; ill.; index. ISBN: 978-0-674-72877-6. 2015.Cristina LanzasCristina LanzasPopulation Health & Pathobiology, North Carolina State University, Raleigh, North Carolina Search for more articles by this author Population Health & Pathobiology, North Carolina State University, Raleigh, North CarolinaPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Quarterly Review of Biology Volume 92, Number 4December 2017 Published in association with Stony Brook University Article DOIhttps://doi.org/10.1086/694941 Views: 32Total views on this site For permission to reuse, please contact [email protected]PDF download Crossref reports no articles citing this article.}, number={4}, journal={The Quarterly Review of Biology}, publisher={University of Chicago Press}, author={Lanzas, Cristina}, year={2017}, month={Dec}, pages={456–457} }
@article{park_skaar_jirtle_hoyo_2017, title={Epigenetics, obesity and early-life cadmium or lead exposure}, volume={9}, ISSN={["1750-192X"]}, DOI={10.2217/epi-2016-0047}, abstractNote={Obesity is a complex and multifactorial disease, which likely comprises multiple subtypes. Emerging data have linked chemical exposures to obesity. As organismal response to environmental exposures includes altered gene expression, identifying the regulatory epigenetic changes involved would be key to understanding the path from exposure to phenotype and provide new tools for exposure detection and risk assessment. In this report, we summarize published data linking early-life exposure to the heavy metals, cadmium and lead, to obesity. We also discuss potential mechanisms, as well as the need for complete coverage in epigenetic screening to fully identify alterations. The keys to understanding how metal exposure contributes to obesity are improved assessment of exposure and comprehensive establishment of epigenetic profiles that may serve as markers for exposures.}, number={1}, journal={EPIGENOMICS}, author={Park, Sarah S. and Skaar, David A. and Jirtle, Randy L. and Hoyo, Cathrine}, year={2017}, month={Jan}, pages={57–75} }
@inbook{fleming-davies_jabbari_robertson_asih_lanzas_lenhart_theriot_2017, title={Mathematical Modeling of the Effects of Nutrient Competition and Bile Acid Metabolism by the Gut Microbiota on Colonization Resistance Against Clostridium difficile}, ISBN={9783319603025 9783319603049}, ISSN={2364-5733 2364-5741}, url={http://dx.doi.org/10.1007/978-3-319-60304-9_8}, DOI={10.1007/978-3-319-60304-9_8}, abstractNote={Clostridium difficile is the leading cause of infectious diarrhea in hospitals and one of the most common healthcare associated infections. Antibiotics alter the normal gut microbiota and facilitate the colonization of enteric pathogens such as C. difficile. Our objective is to elucidate the role of bile acids and other mechanisms in providing colonization resistance against C. difficile. We formulated and analyzed differential equation models for microbial interactions in the gut and bile acid dynamics, as well as a combined model including both mechanisms. Our analysis indicates that bile acids do not prevent C. difficile colonization, but they regulate the onset of C. difficile colonization and growth after antibiotic perturbation. These results have implications in the development of novel ways to inhibit C. difficile infection.}, booktitle={Association for Women in Mathematics Series}, publisher={Springer International Publishing}, author={Fleming-Davies, Arietta and Jabbari, Sara and Robertson, Suzanne L. and Asih, Tri Sri Noor and Lanzas, Cristina and Lenhart, Suzanne and Theriot, Casey M.}, year={2017}, pages={137–161} }
@article{stephenson_lanzas_lenhart_day_2017, title={Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission}, volume={75}, ISSN={["1432-1416"]}, url={http://europepmc.org/articles/PMC5643219}, DOI={10.1007/s00285-017-1133-6}, abstractNote={The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.}, number={6-7}, journal={JOURNAL OF MATHEMATICAL BIOLOGY}, author={Stephenson, Brittany and Lanzas, Cristina and Lenhart, Suzanne and Day, Judy}, year={2017}, month={Dec}, pages={1693–1713} }
@article{kwon_lanzas_reske_hink_seiler_bommarito_burnham_dubberke_2016, title={An Evaluation of Food as a Potential Source for Clostridium difficile Acquisition in Hospitalized Patients}, volume={37}, ISSN={["1559-6834"]}, url={http://europepmc.org/articles/PMC5421383}, DOI={10.1017/ice.2016.218}, number={12}, journal={INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY}, author={Kwon, Jennie H. and Lanzas, Cristina and Reske, Kimberly A. and Hink, Tiffany and Seiler, Sondra M. and Bommarito, Kerry M. and Burnham, Carey-Ann D. and Dubberke, Erik R.}, year={2016}, month={Dec}, pages={1401–1407} }
@article{chen_sanderson_lee_cernicchiaro_renter_lanzas_2016, title={Basic Reproduction Number and Transmission Dynamics of Common Serogroups of Enterohemorrhagic Escherichia coli}, volume={82}, ISSN={["1098-5336"]}, DOI={10.1128/aem.00815-16}, abstractNote={ABSTRACT}, number={18}, journal={APPLIED AND ENVIRONMENTAL MICROBIOLOGY}, author={Chen, Shi and Sanderson, Michael W. and Lee, Chihoon and Cernicchiaro, Natalia and Renter, David G. and Lanzas, Cristina}, year={2016}, month={Sep}, pages={5612–5620} }
@article{chen_lanzas_2016, title={Distinction and connection between contact network, social network, and disease transmission network}, volume={131}, ISSN={["1873-1716"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84978375309&partnerID=MN8TOARS}, DOI={10.1016/j.prevetmed.2016.07.002}, abstractNote={In this paper we discuss the distinction and connection between three closely related networks in animal ecology and epidemiology studies: the contact, social, and disease transmission networks. We provide a robust theoretical definition and interpretation of these three networks, demonstrate that social and disease transmission networks can be derived as spanning subgraphs of contact network, and show examples based on real-world high-resolution cattle contact structure data. Furthermore, we establish a modeling framework to track potential disease transmission dynamics and construct transmission network based on the observed animal contact network.}, journal={PREVENTIVE VETERINARY MEDICINE}, author={Chen, Shi and Lanzas, Cristina}, year={2016}, month={Sep}, pages={8–11} }
@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{lanzas_chen_2016, title={Mathematical modeling tools to study preharvest food safety}, volume={4}, number={4}, journal={Microbiology Spectrum}, author={Lanzas, C. and Chen, S.}, year={2016} }
@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} }
@article{lanzas_chen_2015, title={Complex system modelling for veterinary epidemiology}, volume={118}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84921458136&partnerID=MN8TOARS}, DOI={10.1016/j.prevetmed.2014.09.012}, abstractNote={The use of mathematical models has a long tradition in infectious disease epidemiology. The nonlinear dynamics and complexity of pathogen transmission pose challenges in understanding its key determinants, in identifying critical points, and designing effective mitigation strategies. Mathematical modelling provides tools to explicitly represent the variability, interconnectedness, and complexity of systems, and has contributed to numerous insights and theoretical advances in disease transmission, as well as to changes in public policy, health practice, and management. In recent years, our modelling toolbox has considerably expanded due to the advancements in computing power and the need to model novel data generated by technologies such as proximity loggers and global positioning systems. In this review, we discuss the principles, advantages, and challenges associated with the most recent modelling approaches used in systems science, the interdisciplinary study of complex systems, including agent-based, network and compartmental modelling. Agent-based modelling is a powerful simulation technique that considers the individual behaviours of system components by defining a set of rules that govern how individuals (“agents”) within given populations interact with one another and the environment. Agent-based models have become a recent popular choice in epidemiology to model hierarchical systems and address complex spatio-temporal dynamics because of their ability to integrate multiple scales and datasets.}, number={2-3}, journal={Preventive Veterinary Medicine}, author={Lanzas, C. and Chen, S.}, year={2015}, pages={207–214} }
@article{chen_ilany_white_sanderson_lanzas_2015, title={Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?}, volume={10}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84939158760&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0129253}, abstractNote={Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.}, number={6}, journal={PLOS ONE}, author={Chen, Shi and Ilany, Amiyaal and White, Brad J. and Sanderson, Michael W. and Lanzas, Cristina}, year={2015}, month={Jun} }
@article{aguilar-bonavides_sanchez-arias_lanzas_2014, title={Accurate prediction of major histocompatibility complex class II epitopes by sparse representation via ℓ 1-minimization}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84920830114&partnerID=MN8TOARS}, DOI={10.1186/1756-0381-7-23}, abstractNote={The major histocompatibility complex (MHC) is responsible for presenting antigens (epitopes) on the surface of antigen-presenting cells (APCs). When pathogen-derived epitopes are presented by MHC class II on an APC surface, T cells may be able to trigger an specific immune response. Prediction of MHC-II epitopes is particularly challenging because the open binding cleft of the MHC-II molecule allows epitopes to bind beyond the peptide binding groove; therefore, the molecule is capable of accommodating peptides of variable length. Among the methods proposed to predict MHC-II epitopes, artificial neural networks (ANNs) and support vector machines (SVMs) are the most effective methods. We propose a novel classification algorithm to predict MHC-II called sparse representation via ℓ 1-minimization.We obtained a collection of experimentally confirmed MHC-II epitopes from the Immune Epitope Database and Analysis Resource (IEDB) and applied our ℓ 1-minimization algorithm. To benchmark the performance of our proposed algorithm, we compared our predictions against a SVM classifier. We measured sensitivity, specificity abd accuracy; then we used Receiver Operating Characteristic (ROC) analysis to evaluate the performance of our method. The prediction performance of MHC-II epitopes of the ℓ 1-minimization algorithm was generally comparable and, in some cases, superior to the standard SVM classification method and overcame the lack of robustness of other methods with respect to outliers. While our method consistently favoured DPPS encoding with the alleles tested, SVM showed a slightly better accuracy when "11-factor" encoding was used.ℓ 1-minimization has similar accuracy than SVM, and has additional advantages, such as overcoming the lack of robustness with respect to outliers. With ℓ 1-minimization no model selection dependency is involved.}, journal={BioData Mining}, author={Aguilar-Bonavides, C. and Sanchez-Arias, R. and Lanzas, C.}, year={2014} }
@article{lanzas_dubberke_2014, title={Effectiveness of screening hospital admissions to detect asymptomatic carriers of Clostridium difficile: A modeling evaluation}, volume={35}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84904406665&partnerID=MN8TOARS}, DOI={10.1086/677162}, abstractNote={ObjectiveBoth asymptomatic and symptomatic Clostridium difficile carriers contribute to new colonizations and infections within a hospital, but current control strategies focus only on preventing transmission from symptomatic carriers. Our objective was to evaluate the potential effectiveness of methods targeting asymptomatic carriers to control C. difficile colonization and infection (CDI) rates in a hospital ward: screening patients at admission to detect asymptomatic C. difficile carriers and placing positive patients into contact precautions.}, number={8}, journal={Infection Control and Hospital Epidemiology}, author={Lanzas, C. and Dubberke, E.R.}, year={2014}, pages={1043–1050} }
@article{chen_white_sanderson_amrine_ilany_lanzas_2014, title={Highly dynamic animal contact network and implications on disease transmission}, volume={4}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84897033007&partnerID=MN8TOARS}, DOI={10.1038/srep04472}, abstractNote={Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2).}, journal={Scientific Reports}, author={Chen, S. and White, B.J. and Sanderson, M.W. and Amrine, D.E. and Ilany, A. and Lanzas, C.}, year={2014} }
@article{volkova_lu_lanzas_grohn_2013, title={Evaluating targets for control of plasmid-mediated antimicrobial resistance in enteric commensals of beef cattle: A modelling approach}, volume={141}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84885085642&partnerID=MN8TOARS}, DOI={10.1017/S0950268812002993}, abstractNote={SUMMARY}, number={11}, journal={Epidemiology and Infection}, author={Volkova, V.V. and Lu, Z. and Lanzas, C. and Grohn, Y.T.}, year={2013}, pages={2294–2312} }
@article{magombedze_ngonghala_lanzas_2013, title={Evalution of the "Iceberg Phenomenon" in Johne's Disease through Mathematical Modelling}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84886007728&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0076636}, abstractNote={Johne's disease (JD) is a chronic, enteric disease in ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP). Disease progression follows four distinct stages: silent, subclinical, clinical and advanced. Available diagnostic tests have poor sensitivity and cannot detect early stages of the infection; as a result, only animals in the clinical and advanced stages, which represent the tip of the ‘iceberg’, are identified through testing. The Iceberg Phenomenon is then applied to provide estimates for JD prevalence. For one animal in the advanced stage, it is assumed that there are one to two in the clinical stage, four to eight in the subclinical stage, and ten to fourteen in the silent stage. These ratios, however, are based on little evidence. To evaluate the ratios, we developed a deterministic ordinary differential equation model of JD transmission and disease progression dynamics. When duration periods associated with the natural course of the disease progression are used, the above ratios do not hold. The ratios used to estimate JD prevalence need to be further investigated.}, number={10}, journal={PLoS ONE}, author={Magombedze, G. and Ngonghala, C.N. and Lanzas, C.}, year={2013} }
@article{chen_sanderson_lanzas_2013, title={Investigating effects of between- and within-host variability on Escherichia coli O157 shedding pattern and transmission}, volume={109}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84874225403&partnerID=MN8TOARS}, DOI={10.1016/j.prevetmed.2012.09.012}, abstractNote={Healthy cattle and their environment are the reservoir for the human pathogen Escherichia coli O157. In E. coli O157 epidemiology, supershedders have been loosely defined as cattle that shed high concentrations of E. coli O157 (≥ 10(4)colony-forming cells (CFU)/g of feces) at a single (or multiple) cross-section in time. Due to the variability in the pathogen shedding level among animals (between-host variability), as well as fluctuations in the level shed by a single animal (within-host variability), it is difficult to interpret fecal bacteria distributions, as well as to parse the relative contribution of between- and within-host variability to the observed shedding patterns at the pen level. We developed an agent-based model that integrates individual animal data on temporal fecal shedding dynamics with pen-level E. coli O157 transmission to study how the temporal (and aggregation) patterns of E. coli O157 shedding loads and prevalence arise at the pen level. We demonstrated that even without between-host variability, the prevalence of animals with concentration of E. coli O157 in feces that exceeds 10(4)CFU/g is similar to that observed in cross-sectional field data. Both within-host and between-host variability can generate supershedders.}, number={1-2}, journal={Preventive Veterinary Medicine}, author={Chen, S. and Sanderson, M. and Lanzas, C.}, year={2013}, pages={47–57} }
@article{modelling dynamics of plasmid-gene mediated antimicrobial resistance in enteric bacteria using stochastic differential equations_2013, volume={3}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84883338707&partnerID=MN8TOARS}, DOI={10.1038/srep02463}, abstractNote={The ubiquitous commensal bacteria harbour genes of antimicrobial resistance (AMR), often on conjugative plasmids. Antimicrobial use in food animals subjects their enteric commensals to antimicrobial pressure. A fraction of enteric Escherichia coli in cattle exhibit plasmid-gene mediated AMR to a third-generation cephalosporin ceftiofur. We adapted stochastic differential equations with diffusion approximation (a compartmental stochastic mathematical model) to research the sources and roles of stochasticity in the resistance dynamics, both during parenteral antimicrobial therapy and in its absence. The results demonstrated that demographic stochasticity among enteric E. coli in the occurrence of relevant events was important for the AMR dynamics only when bacterial numbers were depressed during therapy. However, stochasticity in the parameters of enteric E. coli ecology, whether externally or intrinsically driven, contributed to a wider distribution of the resistant E. coli fraction, both during therapy and in its absence, with stochasticities in individual parameters interacting in their contribution.}, journal={Scientific Reports}, year={2013} }
@article{chen_sanderson_white_amrine_lanzas_2013, title={Temporal-spatial heterogeneity in animal-environment contact: Implications for the exposure and transmission of pathogens}, volume={3}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84887267839&partnerID=MN8TOARS}, DOI={10.1038/srep03112}, abstractNote={Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental bacteria concentrations at different areas. The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment. Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.}, journal={Scientific Reports}, author={Chen, S. and Sanderson, M.W. and White, B.J. and Amrine, D.E. and Lanzas, C.}, year={2013} }
@article{volkova_lanzas_lu_gröhn_2012, title={Mathematical model of plasmid-mediated resistance to ceftiofur in commensal enteric escherichia coli of cattle}, volume={7}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84861214053&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0036738}, abstractNote={Antimicrobial use in food animals may contribute to antimicrobial resistance in bacteria of animals and humans. Commensal bacteria of animal intestine may serve as a reservoir of resistance-genes. To understand the dynamics of plasmid-mediated resistance to cephalosporin ceftiofur in enteric commensals of cattle, we developed a deterministic mathematical model of the dynamics of ceftiofur-sensitive and resistant commensal enteric Escherichia coli (E. coli) in the absence of and during parenteral therapy with ceftiofur. The most common treatment scenarios including those using a sustained-release drug formulation were simulated; the model outputs were in agreement with the available experimental data. The model indicated that a low but stable fraction of resistant enteric E. coli could persist in the absence of immediate ceftiofur pressure, being sustained by horizontal and vertical transfers of plasmids carrying resistance-genes, and ingestion of resistant E. coli. During parenteral therapy with ceftiofur, resistant enteric E. coli expanded in absolute number and relative frequency. This expansion was most influenced by parameters of antimicrobial action of ceftiofur against E. coli. After treatment (>5 weeks from start of therapy) the fraction of ceftiofur-resistant cells among enteric E. coli, similar to that in the absence of treatment, was most influenced by the parameters of ecology of enteric E. coli, such as the frequency of transfer of plasmids carrying resistance-genes, the rate of replacement of enteric E. coli by ingested E. coli, and the frequency of ceftiofur resistance in the latter.}, number={5}, journal={PLoS ONE}, author={Volkova, V.V. and Lanzas, C. and Lu, Z. and Gröhn, Y.T.}, year={2012} }
@article{epidemiological model for clostridium difficile transmission in healthcare settings_2011, volume={32}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79957940848&partnerID=MN8TOARS}, DOI={10.1086/660013}, abstractNote={Objective.Recent outbreaks ofClostridium difficileinfection (CDI) have been difficult to control, and data indicate that the importance of different sources of transmission may have changed. Our objectives were to evaluate the contributions of asymptomatic and symptomatic C.difficilecarriers to new colonizations and to determine the most important epidemiological factors influencing C.difficiletransmission.}, number={6}, journal={Infection Control and Hospital Epidemiology}, year={2011}, pages={553–561} }
@article{lanzas_lu_gröhn_2011, title={Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-78651278394&partnerID=MN8TOARS}, DOI={10.1089/fpd.2010.0643}, abstractNote={Foodborne diseases are a significant health-care and economic burden. Most foodborne pathogens are enteric pathogens harbored in the gastrointestinal tract of farm animals. Understanding the transmission of foodborne pathogens and the dissemination of antimicrobial resistance at the farm level is necessary to design effective control strategies at preharvest. Mathematical models improve our understanding of pathogen dynamics by providing a theoretical framework in which factors affecting transmission and control of the pathogens can be explicitly considered. In this review, we aim to present the principles underlying the mathematical modeling of foodborne pathogens and antimicrobial resistance at the farm level to a broader audience.}, number={1}, journal={Foodborne Pathogens and Disease}, author={Lanzas, C. and Lu, Z. and Gröhn, Y.T.}, year={2011}, pages={1–10} }
@article{dubberke_haslam_lanzas_bobo_burnham_gröhn_tarr_2011, title={The ecology and pathobiology of Clostridium difficile infections: An interdisciplinary challenge}, volume={58}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-78651362977&partnerID=MN8TOARS}, DOI={10.1111/j.1863-2378.2010.01352.x}, abstractNote={Summary}, number={1}, journal={Zoonoses and Public Health}, author={Dubberke, E.R. and Haslam, D.B. and Lanzas, C. and Bobo, L.D. and Burnham, C.-A.D. and Gröhn, Y.T. and Tarr, P.I.}, year={2011}, pages={4–20} }
@article{lanzas_ayscue_ivanek_gröhn_2010, title={Model or meal? Farm animal populations as models for infectious diseases of humans}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-75749090456&partnerID=MN8TOARS}, DOI={10.1038/nrmicro2268}, abstractNote={In recent decades, theory addressing the processes that underlie the dynamics of infectious diseases has progressed considerably. Unfortunately, the availability of empirical data to evaluate these theories has not grown at the same pace. Although laboratory animals have been widely used as models at the organism level, they have been less appropriate for addressing issues at the population level. However, farm animal populations can provide empirical models to study infectious diseases at the population level.}, number={2}, journal={Nature Reviews Microbiology}, author={Lanzas, C. and Ayscue, P. and Ivanek, R. and Gröhn, Y.T.}, year={2010}, pages={139–148} }
@article{lanzas_warnick_james_wright_wiedmann_gröhn_2010, title={Transmission dynamics of a multidrug-resistant salmonella typhimurium outbreak in a dairy farm}, volume={7}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-77950555929&partnerID=MN8TOARS}, DOI={10.1089/fpd.2009.0411}, abstractNote={Cattle are recognized as an important source of foodborne Salmonella causing human illness, particularly for antimicrobial-resistant strains. The transmission dynamics of multidrug-resistant (MDR) Salmonella after the onset of a clinical outbreak in a dairy farm has been rarely monitored. The early transmission of a pathogen influences the outbreak size and persistence of the pathogen at the farm level and, therefore, how long the herd represents a risk for Salmonella zoonotic transmission. The objective of this study was to describe the transmission dynamics of MDR Salmonella Typhimurium after the onset of a clinical outbreak in a dairy herd. For that purpose, fecal shedding and serological response to MDR Salmonella were monitored in a longitudinal study conducted in a dairy herd after a few cases of salmonellosis, and a stochastic transmission model was developed to predict Salmonella persistence at the pen level. The outbreak was limited to five clinical cases, and only 18 animals out of 500 cows shed Salmonella in feces. The longest shedder was culture-positive for Salmonella for at least 68 days. The isolates (n = 27) were represented by four pulsed-field gel electrophoresis patterns; three patterns were similar. With one exception, isolates were resistant to nine or more antimicrobial drugs. Simulations of the transmission model indicated that approximately 50% of the outbreaks were likely to die out within 20 days after the first animal was infected. The simulation studies indicated that salmonellosis outbreaks with few clinical cases were likely due to the extinction of the pathogen in the premises in the early phase of the outbreaks. Small population size and group structure within the farm decrease the on-farm persistence of the pathogen.}, number={4}, journal={Foodborne Pathogens and Disease}, author={Lanzas, C. and Warnick, L.D. and James, K.L. and Wright, E.M. and Wiedmann, M. and Gröhn, Y.T.}, year={2010}, pages={467–474} }
@article{seo_lanzas_tedeschi_pell_fox_2009, title={Development of a mechanistic model to represent the dynamics of particle flow out of the rumen and to predict rate of passage of forage particles in dairy cattle}, volume={92}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-68949208454&partnerID=MN8TOARS}, DOI={10.3168/jds.2006-799}, abstractNote={A mechanistic and dynamic model was developed to represent physiological aspects of particle dynamics in the reticulo-rumen (RR) and to predict rate of passage out of the RR (Kp) of forage particles quantitatively. The model consists of 2 conceptual pools with 3 spatial compartments of particles; the compartment the particle enters is based on functional specific gravity (FSG). The model assumes 2 major pressure gradient-driven flows of particles out of the RR through the reticulo-omasal orifice between 2 consecutive primary reticular contractions. One is associated with the second phase of primary reticular contraction and involves propulsion of particles in the vicinity of the honeycomb structure of the reticulum from the RR. The second flow involves movement of particles in the reticulum without selection by size. Particle outflow rate was assumed to be proportional to liquid outflow rate. The passage coefficient, defined as the ratio of particle to liquid outflow rate, was estimated for each particle group by an equation derived from the probability of passage based on FSG and particle size. Particles retained on a 1.18-mm screen were defined as large particles. When the model was evaluated with 41 observations in an independent database, it explained 66% of the variation in observed Kp of forage particles with a root mean square prediction error of 0.009. With 16 observations that also included measurements of liquid passage rate, the model explained 81 and 86% of the variation in observed Kp liquid and Kp forage, respectively. An analysis of model predictions using a database with 455 observations indicated that the assumptions underlying the model seemed to be appropriate to describe the dynamics of forage particle flow out of the RR. Sensitivity analysis showed that probability of a particle being in the pool likely to escape is most critical in the passage of large forage particles, whereas the probability of being in the reticulum as well as in the likely to escape pool is important in the passage of small forage and concentrate particles. The FSG of a particle is more important in determining the fate of a particle than its size although they are correlated, especially for forage particles. We conclude that this model can be used to understand the factors that affect the dynamics of particle flow out of the RR and predict Kp of particles out of the RR in dairy cattle.}, number={8}, journal={Journal of Dairy Science}, author={Seo, S. and Lanzas, C. and Tedeschi, L.O. and Pell, A.N. and Fox, D.G.}, year={2009}, pages={3981–4000} }
@article{ayscue_lanzas_ivanek_gröhn_2009, title={Modeling on-farm Escherichia coli O157:H7 population dynamics}, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-67650763409&partnerID=MN8TOARS}, DOI={10.1089/fpd.2008.0235}, abstractNote={Escherichia coli O157:H7 is a potentially fatal foodborne pathogen with a putative reservoir for human infection in feedlot cattle. In order to more effectively identify targets for intervention strategies, we aimed to (1) assess the role of various feedlot habitats in E. coli O157:H7 propagation and (2) provide a framework for examining the relative contributions of animals and the surrounding environment to observed pathogen dynamics. To meet these goals we developed a mathematical model based on an ecological metapopulation framework to track bacterial population dynamics inside and outside the host. We used E. coli O157:H7 microbiological and epidemiological literature to characterize E. coli O157:H7 habitats at the pen level and account for E. coli O157:H7 population processes in water troughs, feedbunks, cattle hosts, and pen floors in the model. Simulations indicated that E. coli O157:H7 was capable of maintaining viable populations in the feedlot without net growth in the cattle gastrointestinal tract, suggesting E. coli O157:H7 may not always act as an obligate parasite. Water troughs and contaminated pen floors appeared to be particularly influential sources driving E. coli O157:H7 population dynamics and thus would serve as prime environmental targets for interventions to effectively reduce the E. coli O157:H7 load at the pen level.}, number={4}, journal={Foodborne Pathogens and Disease}, author={Ayscue, P. and Lanzas, C. and Ivanek, R. and Gröhn, Y.T.}, year={2009}, pages={461–470} }
@article{lanzas_broderick_fox_2008, title={Improved feed protein fractionation schemes for formulating rations with the cornell net carbohydrate and protein system}, volume={91}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-57749117028&partnerID=MN8TOARS}, DOI={10.3168/jds.2008-1440}, abstractNote={Adequate predictions of rumen-degradable protein (RDP) and rumen-undegradable protein (RUP) supplies are necessary to optimize performance while minimizing losses of excess nitrogen (N). The objectives of this study were to evaluate the original Cornell Net Carbohydrate Protein System (CNCPS) protein fractionation scheme and to develop and evaluate alternatives designed to improve its adequacy in predicting RDP and RUP. The CNCPS version 5 fractionates CP into 5 fractions based on solubility in protein precipitant agents, buffers, and detergent solutions: A represents the soluble nonprotein N, B1 is the soluble true protein, B2 represents protein with intermediate rates of degradation, B3 is the CP insoluble in neutral detergent solution but soluble in acid detergent solution, and C is the unavailable N. Model predictions were evaluated with studies that measured N flow data at the omasum. The N fractionation scheme in version 5 of the CNCPS explained 78% of the variation in RDP with a root mean square prediction error (RMSPE) of 275 g/d, and 51% of the RUP variation with RMSPE of 248 g/d. Neutral detergent insoluble CP flows were overpredicted with a mean bias of 128 g/d (40% of the observed mean). The greatest improvements in the accuracy of RDP and RUP predictions were obtained with the following 2 alternative schemes. Alternative 1 used the inhibitory in vitro system to measure the fractional rate of degradation for the insoluble protein fraction in which A = nonprotein N, B1 = true soluble protein, B2 = insoluble protein, C = unavailable protein (RDP: R(2) = 0.84 and RMSPE = 167 g/d; RUP: R(2) = 0.61 and RMSPE = 209 g/d), whereas alternative 2 redefined A and B1 fractions as the non-amino-N and amino-N in the soluble fraction respectively (RDP: R(2) = 0.79 with RMSPE = 195 g/d and RUP: R(2) = 0.54 with RMSPE = 225 g/d). We concluded that implementing alternative 1 or 2 will improve the accuracy of predicting RDP and RUP within the CNCPS framework.}, number={12}, journal={Journal of Dairy Science}, author={Lanzas, C. and Broderick, G.A. and Fox, D.G.}, year={2008}, pages={4881–4891} }
@article{the effect of heterogeneous infectious period and contagiousness on the dynamics of salmonella transmission in dairy cattle_2008, volume={136}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-54049121463&partnerID=MN8TOARS}, DOI={10.1017/S0950268807000209}, abstractNote={SUMMARY}, number={11}, journal={Epidemiology and Infection}, year={2008}, pages={1496–1510} }
@article{the risk and control of salmonella outbreaks in calf-raising operations: a mathematical modeling approach_2008, volume={39}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-55549086869&partnerID=MN8TOARS}, DOI={10.1051/vetres:2008038}, abstractNote={Salmonellosis in calves has economic and welfare implications, and serves as a potential source of human infections. Our objectives were to assess the risk of Salmonella spread following its introduction into a herd of pre-weaned calves and to evaluate the efficacy of control strategies to prevent and control outbreaks. To meet these objectives, we developed a model of Salmonella transmission within a pre-weaned group of calves based on a well documented outbreak of salmonellosis in a calf-raising operation and other literature. Intervention scenarios were evaluated in both deterministic and stochastic versions of the model. While the basic reproduction number (R0) was estimated to be 2.4, simulation analysis showed that more than 60% of the invasions failed after the introduction of a single index case. With repeated introduction of index cases, the probability of Salmonella spread was close to 1, and the tested control strategies were insufficient to prevent transmission within the group. The most effective strategies to control ongoing outbreaks were to completely close the rearing operation to incoming calves, to increase the proportion of admitted calves that were immunized (>75%), and to assign personnel and equipment to groups of calves.}, number={6}, journal={Veterinary Research}, year={2008} }
@article{lanzas_sniffen_seo_tedeschi_fox_2007, title={A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants}, volume={136}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-34447095486&partnerID=MN8TOARS}, DOI={10.1016/j.anifeedsci.2006.08.025}, abstractNote={Balancing ruminant diets for appropriate levels and types of dietary carbohydrates (CHO) is necessary to maximize production while assuring the health of the animals. Several feed fractions (i.e., volatile fatty acids (VFA), lactate, sugars, starch) are now being measured in some commercial feed laboratories and this information may assist in better formulating diets. A CHO fractionation scheme based on ruminal degradation characteristics needed for nutritional models is described and its impact on predictions with the Cornell Net Carbohydrate and Protein System (CNCPS) is assessed. Dietary CHO are divided into eight fractions: the CA1 is volatile fatty acids (VFA), CA2 is lactic acid, CA3 is other organic acids, CA4 is sugars, CB1 is starch, CB2 is soluble fiber, CB3 is available neutral detergent fiber (NDF), and CC is unavailable NDF. A Monte Carlo analysis was conducted with an example lactating dairy cow ration to compare the original CNCPS CHO scheme (CA = sugars and organic acids, CB1 = starch and soluble fiber, CB2 = available NDF, CC = unavailable NDF) with the developed CHO scheme. A database was used to obtain distributions and correlations of the feed inputs used in the schemes for the ingredients of the ration (corn and grass silages, high moisture corn, soybean meal, and distillers’ grains). The CHO fractions varied in a decreasing order as VFAs, soluble fiber, lactic acid, sugar, NDF, starch, and total non-fiber carbohydrates (NFC). Use of the expanded scheme in the CNCPS decreased the microbial CP production, which was sensitive (standard regression coefficient in parenthesis) to corn silage starch (0.55), grass silage NDF rate (0.46), high moisture corn grain starch rate (0.44), and corn silage NDF rate (0.33). Predicted ruminal NFC digestibility remained similar. The expanded CHO scheme provides a more appropriate feed description to account for variation in changes in silage quality and diet NFC composition. However, to fully account for differences in feed CHO utilization, further improvements in the methodology used to estimate the fractions and their corresponding degradation rates, inclusion of dietary factors in dry matter intake predictions, and prediction of ruminal VFA production and pH are necessary.}, number={3-4}, journal={Animal Feed Science and Technology}, author={Lanzas, C. and Sniffen, C.J. and Seo, S. and Tedeschi, L.O. and Fox, D.G.}, year={2007}, pages={167–190} }
@article{seo_lanzas_tedeschi_fox_2007, title={Development of a mechanistic model to represent the dynamics of liquid flow out of the rumen and to predict the rate of passage of liquid in dairy cattle}, volume={90}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-34247890082&partnerID=MN8TOARS}, number={2}, journal={Journal of Dairy Science}, author={Seo, S. and Lanzas, C. and Tedeschi, L.O. and Fox, D.G.}, year={2007}, pages={840–855} }
@article{lanzas_fox_pell_2007, title={Digestion kinetics of dried cereal grains}, volume={136}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-34447104787&partnerID=MN8TOARS}, DOI={10.1016/j.anifeedsci.2006.09.004}, abstractNote={Grain fermentability largely determines the feed value of grains for ruminants. Our objective was to evaluate the variation in kinetics of gas production of cereal grains and the relationship among gas production, chemical composition and feed value. Eighteen barley, 99 corn, 23 sorghum, and 57 wheat samples were fermented in vitro for 48 h. Gas production was measured with a computerized system and an exponential model was fitted to the data. The impact of the variation in composition and kinetics on the feed value of grains in feedlot rations was assessed with the Cornell Net Carbohydrate and Protein System (CNCPS). Fractional gas rates were significantly different between grains (P<0.001), with a mean and S.D. of 0.24 (0.029) h−1 for barley (n = 20), 0.15 (0.026) h−1 for corn (n = 98), 0.06 (0.016) h−1 for sorghum (n = 23) and 0.26 (0.039) h−1 for wheat (n = 57). Fermentation rates were more variable than the chemical components. Fractional rates were poorly correlated with chemical composition within grain with the highest correlations for acid detergent insoluble crude protein (ADICP) (r = −0.31, P<0.01) and ADF (r = −0.27, P<0.01) for corn and neutral detergent insoluble crude protein (NDICP) (r = 0.35, P<0.05) for wheat. The impact of the variation in composition and kinetics on the feed value of grains in feedlot rations was assessed. The CNCPS predicted a maximal variation of <2.1 MJ/day and <60 g/day in metabolizable energy (ME) and metabolizable protein (MP) supply from grains, respectively. For sorghum, the fermentation rate was predicted to be a major determinant of the site of starch fermentation. A detailed evaluation of feed values for grains needs to include information on rates of fermentation.}, number={3-4}, journal={Animal Feed Science and Technology}, author={Lanzas, C. and Fox, D.G. and Pell, A.N.}, year={2007}, pages={265–280} }
@article{lanzas_tedeschi_seo_fox_2007, title={Evaluation of protein fractionation systems used in formulating rations for dairy cattle}, volume={90}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-35748969906&partnerID=MN8TOARS}, number={1}, journal={Journal of Dairy Science}, author={Lanzas, C. and Tedeschi, L.O. and Seo, S. and Fox, D.G.}, year={2007}, pages={507–521} }
@article{seo_tedeschi_lanzas_schwab_fox_2006, title={Development and evaluation of empirical equations to predict feed passage rate in cattle}, volume={128}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-33646143985&partnerID=MN8TOARS}, DOI={10.1016/j.anifeedsci.2005.09.014}, abstractNote={Empirical equations were developed to accurately predict passage rate (Kp) in ration formulation models for all classes of dairy and beef cattle. The database was comprised of studies that used external markers, and 553, 195 and 766 treatment means were used to develop the Kp equations for forages, concentrates and liquid, respectively. A random coefficients model that used each study effect as a random variable was used to select statistically significant input variables to predict rate of passage. The parameters of the variables were estimated using ordinary least square method. The equations developed were: Kp forage = (2.365 + 0.0214FpBW + 0.0734CpBW + 0.069FDMI)/100; Kp concentrate = (1.169 + 0.1375FpBW + 0.1721CpBW)/100 and Kp liquid = (4.524 + 0.0223FpBW + 0.2046CpBW + 0.344FDMI)/100, where Kp is the passage rate, h−1; FpBW the forage DMI as a proportion of BW, g/kg; CpBW the concentrate DMI as a proportion of BW and FDMI is the forage DMI, kg. These Kp equations for forages, concentrates and liquid explained 87%, 95% and 94%, respectively of the variation in passage rates in the database used in equation development after adjustment for random study effect. These and other published equations were evaluated with an independent database. In this evaluation, the R2 of the new equations were 0.39, 0.40 and 0.25 for prediction of the passage of forages, concentrates and liquid, respectively, which was higher than the R2 of the previously published equations by 0.03–0.19, 0.01–0.14, and 0.04–0.16 for forages, concentrates and liquid, respectively. The root mean square prediction error (RMSPE) was reduced by 3–22%, 2–33%, and 4–31% in the prediction of Kp of forages, concentrates and liquid, respectively, with the new equations. These new empirical equations are suitable for predicting passage rate in cattle, but predictability overall is still low and increases in the accuracy of predicting passage rates requires development of a mechanistic model that accounts for more biologically important variables affecting passage rate (e.g. physical property of particles, water intake and flux, and within day variation in intake).}, number={1-2}, journal={Animal Feed Science and Technology}, author={Seo, S. and Tedeschi, L.O. and Lanzas, C. and Schwab, C.G. and Fox, D.G.}, year={2006}, pages={67–83} }