@article{seger_sanderson_white_lanzas_2024, title={Analysis of within-pen and between-pen fenceline temporal contact networks in confined feedlot cattle}, volume={227}, ISSN={["1873-1716"]}, DOI={10.1016/j.prevetmed.2024.106210}, abstractNote={Though contact networks are important for describing the dynamics for disease transmission and intervention applications, individual animal contact and barriers between animal populations, such as fences, are not often utilized in the construction of these models. The objective of this study was to use contact network analysis to quantify contacts within two confined pens of feedlot cattle and the shared "fenceline" area between the pens at varying temporal resolutions and contact duration to better inform the construction of network-based disease transmission models for cattle within confined-housing systems. Two neighboring pens of feedlot steers were tagged with Real-Time Location System (RTLS) tags. Within-pen contacts were defined with a spatial threshold (SpTh) of 0.71 m and a minimum contact duration (MCD) of either 10 seconds (10 s), 30 seconds (30 s), or 60 seconds (60 s). For the fenceline network location readings were included within an area extending from 1 m on either side of the shared fence. "Fenceline" contacts could only occur between a steer from each pen. Static, undirected, weighted contact networks for within-pen networks and the between-pen network were generated for the full study duration and for daily (24-h), 6-h period, and hourly networks to better assess network heterogeneity. For the full study duration network, the two within-pen networks were densely homogenous. The within-pen networks showed more heterogeneity when smaller timescales (6-h period and hourly) were applied. When contacts were defined with a MCD of 30 s or 60 s, the total number of contacts seen in each network decreased, indicating that most of the contacts observed in our networks may have been transient passing contacts. Cosine similarity was moderate and stable across days for within pen networks. Of the 90 total tagged steers between the two pens, 86 steers (46 steers from Pen 2 and 40 steers from Pen 3) produced at least one contact across the shared fenceline. The total network density for the network created across the shared fenceline between the two pens was 17%, with few contacts at shorter timescales and for MCD of 30 s or 60 s. Overall, the contact networks created here from high-resolution spatial and temporal contact observation data provide estimates for a contact network within commercial US feedlot pens and the contact network created between two neighboring pens of cattle. These networks can be used to better inform pathogen transmission models on social contact networks.}, journal={PREVENTIVE VETERINARY MEDICINE}, author={Seger, H. L. and Sanderson, M. W. and White, B. J. and Lanzas, C.}, year={2024}, month={Jun} }
 @article{lacy_khan_nath_das_igoe_lenhart_lloyd_lanzas_odoi_2024, title={Geographic disparities and predictors of COVID-19 vaccination in Missouri: a retrospective ecological study}, volume={12}, ISSN={["2296-2565"]}, DOI={10.3389/fpubh.2024.1329382}, abstractNote={BackgroundLimited information is available on geographic disparities of COVID-19 vaccination in Missouri and yet this information is essential for guiding efforts to improve vaccination coverage. Therefore, the objectives of this study were to (a) investigate geographic disparities in the proportion of the population vaccinated against COVID-19 in Missouri and (b) identify socioeconomic and demographic predictors of the identified disparities.MethodsThe COVID-19 vaccination data for time period January 1 to December 31, 2021 were obtained from the Missouri Department of Health. County-level data on socioeconomic and demographic factors were downloaded from the 2020 American Community Survey. Proportions of county population vaccinated against COVID-19 were computed and displayed on choropleth maps. Global ordinary least square regression model and local geographically weighted regression model were used to identify predictors of proportions of COVID-19 vaccinated population.ResultsCounties located in eastern Missouri tended to have high proportions of COVID-19 vaccinated population while low proportions were observed in the southernmost part of the state. Counties with low proportions of population vaccinated against COVID-19 tended to have high percentages of Hispanic/Latino population (p = 0.046), individuals living below the poverty level (p = 0.049), and uninsured (p = 0.015) populations. The strength of association between proportion of COVID-19 vaccinated population and percentage of Hispanic/Latino population varied by geographic location.ConclusionThe study findings confirm geographic disparities of proportions of COVID-19 vaccinated population in Missouri. Study findings are useful for guiding programs geared at improving vaccination coverage and uptake by targeting resources to areas with low proportions of vaccinated individuals.}, journal={FRONTIERS IN PUBLIC HEALTH}, author={Lacy, Alexanderia and Khan, Md Marufuzzaman and Nath, Nirmalendu Deb and Das, Praachi and Igoe, Morganne and Lenhart, Suzanne and Lloyd, Alun L. and Lanzas, Cristina and Odoi, Agricola}, year={2024}, month={Mar} }
 @article{das_igoe_lacy_farthing_timsina_lanzas_lenhart_odoi_lloyd_2024, title={Modeling county level COVID-19 transmission in the greater St. Louis area: Challenges of uncertainty and identifiability when fitting mechanistic models to time-varying processes}, volume={371}, ISSN={["1879-3134"]}, DOI={10.1016/j.mbs.2024.109181}, abstractNote={We use a compartmental model with a time-varying transmission parameter to describe county level COVID-19 transmission in the greater St. Louis area of Missouri and investigate the challenges in fitting such a model to time-varying processes. We fit this model to synthetic and real confirmed case and hospital discharge data from May to December 2020 and calculate uncertainties in the resulting parameter estimates. We also explore non-identifiability within the estimated parameter set. We determine that that death rate of infectious non-hospitalized individuals, the testing parameter and the initial number of exposed individuals are not identifiable based on an investigation of correlation coefficients between pairs of parameter estimates. We also explore how this non-identifiability ties back into uncertainties in the estimated parameters and find that it inflates uncertainty in the estimates of our time-varying transmission parameter. However, we do find that R0 is not highly affected by non-identifiability of its constituent components and the uncertainties associated with the quantity are smaller than those of the estimated parameters. Parameter values estimated from data will always be associated with some uncertainty and our work highlights the importance of conducting these analyses when fitting such models to real data. Exploring identifiability and uncertainty is crucial in revealing how much we can trust the parameter estimates.}, journal={MATHEMATICAL BIOSCIENCES}, author={Das, Praachi and Igoe, Morganne and Lacy, Alexanderia and Farthing, Trevor and Timsina, Archana and Lanzas, Cristina and Lenhart, Suzanne and Odoi, Agricola and Lloyd, Alun L.}, year={2024}, month={May} }
 @article{deb_timsina_lenhart_foster_lanzas_2024, title={Quantifying trade-offs between therapeutic efficacy and resistance dissemination for enrofloxacin dose regimens in cattle}, volume={14}, ISSN={["2045-2322"]}, DOI={10.1038/s41598-024-70741-8}, abstractNote={Abstract The use of antimicrobial drugs in food-producing animals contributes to the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dynamics of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli : 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-FDA-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed non-FDA-approved scenario (7.5 mg/kg, two doses 24 h apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli . Overall, the scenarios that decrease P. multocida , including resistant P. multocida did not coincide with those that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis suggests that bacterial populations were the most sensitive to drug conversion factors into plasma ( $${\beta}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>β</mml:mi> </mml:math> ), elimination of the drug from the colon ( $$\vartheta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϑ</mml:mi> </mml:math> ), fifty percent sensitive bacteria ( P. multocida ) killing effect ( $${\text{L}}_{\text{s50}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mtext>L</mml:mtext> <mml:mtext>s50</mml:mtext> </mml:msub> </mml:math> ), fifty percent of bacteria ( E. coli ) above ECOFF killing effect ( $${\text{C}}_{\text{r50}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mtext>C</mml:mtext> <mml:mtext>r50</mml:mtext> </mml:msub> </mml:math> ), and net drug transfer rate in the lung ( $$\gamma$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>γ</mml:mi> </mml:math> ) parameters.}, number={1}, journal={SCIENTIFIC REPORTS}, author={Deb, Liton Chandra and Timsina, Archana and Lenhart, Suzanne and Foster, Derek and Lanzas, Cristina}, year={2024}, month={Sep} }
 @article{erwin_fletcher_sweeney_theriot_lanzas_2023, title={Distilling Mechanistic Models From Multi-Omics Data}, url={https://doi.org/10.1101/2023.09.06.556597}, DOI={10.1101/2023.09.06.556597}, abstractNote={AbstractHigh-dimensional multi-omics data sets are increasingly accessible and now routinely being generated as part of medical and biological experiments. However, the ability to infer mechanisms of these data remains low due to the abundance of confounding data. The gap between data generation and interpretation highlights the need for strategies to harmonize and distill complex multi-omics data sets into concise, mechanistic descriptions. To this end, a four-step analysis approach for multiomics data is herein demonstrated, comprising: filling missing data and harmonizing data sources, inducing sparsity, developing mechanistic models, and interpretation. This strategy is employed to generate a parsimonious mechanistic model from high-dimensional transcriptomics and metabolomics data collected from a murine model ofClostridioides difficileinfection. This approach highlighted the role of the Stickland reactor in the production of toxins during infection, in agreement with recent literature. The methodology present here is demonstrated to be feasible for interpreting multi-omics data sets and it, to the authors knowledge, one of the first reports of a successful implementation of such a strategy.}, author={Erwin, Samantha and Fletcher, Joshua R. and Sweeney, Daniel C. and Theriot, Casey M. and Lanzas, Cristina}, year={2023}, month={Sep} }
 @article{farthing_jolley_nickel_hill_stwalley_reske_kwon_olsen_burnham_dubberke_et al._2023, title={Early coronavirus disease 2019 (COVID-19) pandemic effects on individual-level risk for healthcare-associated infections in hospitalized patients}, volume={6}, ISSN={["1559-6834"]}, DOI={10.1017/ice.2023.83}, abstractNote={AbstractObjective:We compared the individual-level risk of hospital-onset infections with multidrug-resistant organisms (MDROs) in hospitalized patients prior to and during the coronavirus disease 2019 (COVID-19) pandemic. We also quantified the effects of COVID-19 diagnoses and intrahospital COVID-19 burden on subsequent MDRO infection risk.Design:Multicenter, retrospective, cohort study.Setting:Patient admission and clinical data were collected from 4 hospitals in the St. Louis area.Patients:Data were collected for patients admitted between January 2017 and August 2020, discharged no later than September 2020, and hospitalized ≥48 hours.Methods:Mixed-effects logistic regression models were fit to the data to estimate patients’ individual-level risk of infection with MDRO pathogens of interest during hospitalization. Adjusted odds ratios were derived from regression models to quantify the effects of the COVID-19 period, COVID-19 diagnosis, and hospital-level COVID-19 burden on individual-level hospital-onset MDRO infection probabilities.Results:We calculated adjusted odds ratios for COVID-19–era hospital-onset Acinetobacter spp., P. aeruginosa and Enterobacteriaceae spp infections. Probabilities increased 2.64 (95% confidence interval [CI], 1.22–5.73) times, 1.44 (95% CI, 1.03–2.02) times, and 1.25 (95% CI, 1.00–1.58) times relative to the prepandemic period, respectively. COVID-19 patients were 4.18 (95% CI, 1.98–8.81) times more likely to acquire hospital-onset MDRO S. aureus infections.Conclusions:Our results support the growing body of evidence indicating that the COVID-19 pandemic has increased hospital-onset MDRO infections.}, journal={INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY}, author={Farthing, Trevor S. and Jolley, Ashlan and Nickel, Katelin B. and Hill, Cherie and Stwalley, Dustin and Reske, Kimberly A. and Kwon, Jennie H. and Olsen, Margaret A. and Burnham, Jason P. and Dubberke, Erik R. and et al.}, year={2023}, month={Jun} }
 @article{deb_jara_lanzas_2023, title={Early evaluation of the Food and Drug Administration (FDA) guidance on antimicrobial use in food animals on antimicrobial resistance trends reported by the National Antimicrobial Resistance Monitoring System (2012-2019)}, volume={17}, ISSN={["2352-7714"]}, url={http://europepmc.org/abstract/med/37448772}, DOI={10.1016/j.onehlt.2023.100580}, abstractNote={Antimicrobial resistance (AMR) is one of the biggest challenges to global public health. To address this issue in the US, governmental agencies have implemented system-wide guidance frameworks and recommendations aimed at reducing antimicrobial use. In particular, the Food and Drug Administration (FDA) prohibited the extra-label use of cephalosporins in food animals in 2012 and issued the guidance for industry (GFI) #213 about establishing a framework to phase out the use of all medically relevant drugs for growth promotion in 2012. Also in 2015, the FDA implemented veterinary feed directive (VFD) drug regulations (GFI# 120) to control the use of certain antimicrobials. To assess the potential early effects of these FDA actions and other concurrent antimicrobial stewardship actions on AMR in the food chain, we compared the patterns of the phenotypic (minimum inhibitory concentration (MIC) and percentage of resistance) and genotypic resistances for selected antimicrobials before and after 2016 across different enteric pathogen species, as reported by the National Antimicrobial Resistance Monitoring System (NARMS). Most of the antimicrobials analyzed at the phenotypic level followed a downward trend in MIC after implementing the guidance. Although, most of those changes were less than one 1-fold dilution. On the other hand, compared to MIC results, the results based on phenotypic resistance prevalence evidenced higher differences in both directions between the pre- and post-guidance implementation period. Also, we did not find relevant differences in the presence of AMR genes between pre- and post-VFD drug regulations. We concluded that the FDA guidance on antimicrobial use has not led to substantial reductions in antimicrobial drug resistance yet.}, journal={ONE HEALTH}, author={Deb, Liton Chandra and Jara, Manuel and Lanzas, Cristina}, year={2023}, month={Dec} }
 @article{davies_lenhart_day_lloyd_lanzas_2022, title={Extensions of mean-field approximations for environmentally-transmitted pathogen networks}, volume={20}, ISSN={["1551-0018"]}, DOI={10.3934/mbe.2023075}, abstractNote={<abstract><p>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.</p></abstract>}, 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{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={AbstractAntimicrobial resistance (AMR) in bacterial pathogens reduces the effectiveness of these drugs in both human and veterinary medicine, making judicious antimicrobial use (AMU) an important strategy for its control. The COVID‐19 pandemic modified operations in both human and veterinary healthcare delivery, potentially impacting AMU. The goal of this research is to quantify how antimicrobial drug prescribing practices for companion animals in an academic veterinary hospital changed during the pandemic. A retrospective study was performed using prescribing data for dogs and cats collected from the NC State College of Veterinary Medicine (NCSU‐CVM) pharmacy, which included prescriptions from both the specialty referral hospital and primary care services. Records (n = 31,769) for 34 antimicrobial drugs from 2019–2020—before and during the pandemic‐related measures at the NCSU‐CVM—were compared. The prescribed antimicrobials' importance was categorized using the FDA's Guidance for Industry (GFI #152), classifying drugs according to medical importance in humans. A proportional odds model was used to estimate the probability of more important antimicrobials being administered in patients seen during the pandemic versus before (i.e., critically important vs. highly important vs. important). Rates of AMU per week and per patient visit were also compared. During the pandemic, cumulative antimicrobials prescribed per week were significantly decreased in most services for dogs. Weekly rates for Highly Important antimicrobials were also significantly lower in dogs. For important and critically important antimicrobials, rates per week were significantly decreased in various services overall. Rates of antimicrobial administration per patient visit were significantly increased for Highly Important drugs. Patients in the internal medicine, dermatology, and surgery services received significantly more important antimicrobials during the pandemic than before, while cardiology patients received significantly less. These results suggest that the pandemic significantly impacted prescribing practices of antimicrobials for companion animals in this study.}, 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{lacy_igoe_das_farthing_lloyd_lanzas_odoi_lenhart_2023, title={Modeling impact of vaccination on COVID-19 dynamics in St. Louis}, volume={17}, ISSN={["1751-3766"]}, DOI={10.1080/17513758.2023.2287084}, abstractNote={The region of St. Louis, Missouri, has displayed a high level of heterogeneity in COVID-19 cases, hospitalization, and vaccination coverage. We investigate how human mobility, vaccination, and time-varying transmission rates influenced SARS-CoV-2 transmission in five counties in the St. Louis area. A COVID-19 model with a system of ordinary differential equations was developed to illustrate the dynamics with a fully vaccinated class. Using the weekly number of vaccinations, cases, and hospitalization data from five counties in the greater St. Louis area in 2021, parameter estimation for the model was completed. The transmission coefficients for each county changed four times in that year to fit the model and the changing behaviour. We predicted the changes in disease spread under scenarios with increased vaccination coverage. SafeGraph local movement data were used to connect the forces of infection across various counties.}, number={1}, journal={JOURNAL OF BIOLOGICAL DYNAMICS}, author={Lacy, Alexanderia and Igoe, Morganne and Das, Praachi and Farthing, Trevor and Lloyd, Alun L. and Lanzas, Cristina and Odoi, Agricola and Lenhart, Suzanne}, year={2023}, month={Dec} }
 @misc{lanzas_jara_tucker_curtis_2022, title={A review of epidemiological models of Clostridioides difficile transmission and control (2009e2021)}, volume={74}, ISSN={["1095-8274"]}, url={https://doi.org/10.1016/j.anaerobe.2022.102541}, DOI={10.1016/j.anaerobe.2022.102541}, abstractNote={Clostridioides difficile is the leading cause of infectious diarrhea and one of the most common healthcare-acquired infections worldwide. We performed a systematic search and a bibliometric analysis of mathematical and computational models for Clostridioides difficile transmission. We identified 33 publications from 2009 to 2021. Models have underscored the importance of asymptomatic colonized patients in maintaining transmission in health-care settings. Infection control, antimicrobial stewardship, active testing, and vaccination have often been evaluated in models. Despite active testing and vaccination being not currently implemented, they are the most commonly evaluated interventions. Some aspects of C. difficile transmission, such community transmission and interventions in health-care settings other than in acute-care hospitals, remained less evaluated through modeling.}, journal={ANAEROBE}, publisher={Elsevier BV}, author={Lanzas, Cristina and Jara, Manuel and Tucker, Rachel and Curtis, Savannah}, year={2022}, month={Apr} }
 @article{mahmud_wallace_reske_alvarado_muenks_rasmussen_burnham_lanzas_dubberke_dantas_2022, title={Epidemiology of Plasmid Lineages Mediating the Spread of Extended-Spectrum Beta-Lactamases among Clinical Escherichia coli}, volume={8}, ISSN={["2379-5077"]}, url={https://doi.org/10.1128/msystems.00519-22}, DOI={10.1128/msystems.00519-22}, abstractNote={
            The increasing incidence of nosocomial infections with extended-spectrum beta-lactamase (ESBL)-producing
            Escherichia coli
            represents a significant threat to public health, given the limited treatment options available for such infections. The rapid ESBL spread is suggested to be driven by localization of the resistance genes on conjugative plasmids.
          }, journal={MSYSTEMS}, author={Mahmud, Bejan and Wallace, Meghan A. and Reske, Kimberly A. and Alvarado, Kelly and Muenks, Carol E. and Rasmussen, David A. and Burnham, Carey-Ann D. and Lanzas, Cristina and Dubberke, Erik R. and Dantas, Gautam}, editor={Marshall, Christopher W.Editor}, year={2022}, month={Aug} }
 @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.MethodsData on COVID-19 incidence and chronic disease hospitalizations were obtained from the Department of Health and Missouri Hospital Association, respectively. Socioeconomic and demographic data were obtained from the 2018 American Community Survey while population mobility data were obtained from the SafeGraph website. Choropleth maps were used to identify geographic disparities of COVID-19 risk and several sociodemographic and chronic disease factors at the ZIP Code Tabulation Area (ZCTA) spatial scale. Global negative binomial and local geographically weighted negative binomial models were used to investigate associations between ZCTA-level COVID-19 risk and socioeconomic, demographic and chronic disease factors.ResultsThere were geographic disparities found in COVID-19 risk. Risks tended to be higher in ZCTAs with high percentages of the population with a bachelor’s degree (p<0.0001) and obesity hospitalizations (p<0.0001). Conversely, risks tended to be lower in ZCTAs with high percentages of the population working in agriculture (p<0.0001). However, the association between agricultural occupation and COVID-19 risk was modified by per capita between ZCTA visits. Areas that had both high per capita between ZCTA visits and high percentages of the population employed in agriculture had high COVID-19 risks. The strength of association between agricultural occupation and COVID-19 risk varied by geographic location.ConclusionsGeographic disparities of COVID-19 risk exist in the St. Louis area and are associated with sociodemographic factors, population movements, and obesity hospitalization risks. The latter is particularly concerning due to the growing prevalence of obesity and the known immunological impairments among obese individuals. Therefore, future studies need to focus on improving our understanding of the relationships between COVID-19 vaccination efficacy, obesity and waning of immunity among obese individuals so as to better guide vaccination regimens and reduce disparities.}, 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
                Background
                There is evidence of geographic disparities in COVID-19 hospitalization risks that, if identified, could guide control efforts. Therefore, the objective of this study was to investigate Zip Code Tabulation Area (ZCTA)-level geographic disparities and identify predictors of COVID-19 hospitalization risks in the St. Louis area.
              
                Methods
                Hospitalization data for COVID-19 and several chronic diseases were obtained from the Missouri Hospital Association. ZCTA-level data on socioeconomic and demographic factors were obtained from the American Community Survey. Geographic disparities in distribution of COVID-19 age-adjusted hospitalization risks, socioeconomic and demographic factors as well as chronic disease risks were investigated using choropleth maps. Predictors of ZCTA-level COVID-19 hospitalization risks were investigated using global negative binomial and local geographically weighted negative binomial models.
              
                Results
                COVID-19 hospitalization risks were significantly higher in ZCTAs with high diabetes hospitalization risks (p < 0.0001), COVID-19 risks (p < 0.0001), black population (p = 0.0416), and populations with some college education (p = 0.0005). The associations between COVID-19 hospitalization risks and the first three predictors varied by geographic location.
              
                Conclusions
                There is evidence of geographic disparities in COVID-19 hospitalization risks that are driven by differences in socioeconomic, demographic and health-related factors. The impacts of these factors vary by geographical location implying that a ‘one-size-fits-all’ approach may not be appropriate for management and control. Using both global and local models leads to a better understanding of geographic disparities. These findings are useful for informing health planning to identify geographic areas likely to have high numbers of individuals needing hospitalization as well as guiding vaccination efforts.
              }, 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
               
                  Background
                  MRSA is one of the most common causes of hospital- and community-acquired infections. MRSA is resistant to many antibiotics, including β-lactam antibiotics, fluoroquinolones, lincosamides, macrolides, aminoglycosides, tetracyclines and chloramphenicol.
               
               
                  Objectives
                  To identify patient-level characteristics that may be associated with phenotype variations and that may help improve prescribing practice and antimicrobial stewardship.
               
               
                  Methods
                  Chain graphs for resistance phenotypes were learned from invasive MRSA surveillance data collected by the CDC as part of the Emerging Infections Program to identify patient level risk factors for individual resistance outcomes reported as MIC while accounting for the correlations among the resistance traits. These chain graphs are multilevel probabilistic graphical models (PGMs) that can be used to quantify and visualize the complex associations among multiple resistance outcomes and their explanatory variables.
               
               
                  Results
                  Some phenotypic resistances had low connectivity to other outcomes or predictors (e.g. tetracycline, vancomycin, doxycycline and rifampicin). Only levofloxacin susceptibility was associated with healthcare-associated infections. Blood culture was the most common predictor of MIC. Patients with positive blood culture had significantly increased MIC of chloramphenicol, erythromycin, gentamicin, lincomycin and mupirocin, and decreased daptomycin and rifampicin MICs. Some regional variations were also observed.
               
               
                  Conclusions
                  The differences in resistance phenotypes between patients with previous healthcare use or positive blood cultures, or from different states, may be useful to inform first-choice antibiotics to treat clinical MRSA cases. Additionally, we demonstrated multilevel PGMs are useful to quantify and visualize interactions among multiple resistance outcomes and their explanatory variables.
               }, 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={AbstractIntervention strategies for minimizing indoor SARS-CoV-2 transmission are often based on anecdotal evidence because there is little evidence-based research to support them. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission, and used it to compare effects of four interventions on reducing individual-level SARS-CoV-2 transmission risk by simulating a well-known case study. We found that imposing movement restrictions 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 move 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 rates of aerosol removal is the key to successful transmission-risk reduction when using ventilation systems as intervention tools.Article Summary LineImposing mask usage requirements, group size restrictions, duration limits, and social distancing policies can have additive, and in some cases multiplicative protective effects on SARS-CoV-2 infection risk during indoor events.}, 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={ABSTRACTMethicillin-resistant Staphylococcus aureus (MRSA) is one of the most common causes of hospital- and community-acquired infections. MRSA is resistant to many antibiotics, including ß-lactam antibiotics, fluoroquinolones, lincosamides, macrolides, aminoglycosides, tetracyclines, and chloramphenicol. Graphical models such as chain graphs can be used to quantify and visualize the interactions among multiple resistant outcomes and their explanatory variables. In this study, we analyzed MRSA surveillance data collected by the Centers for Disease Control and Prevention (CDC) as part of the Emerging Infections Program (EIP) using chain graphs with the objective of identifying risk factors for individual phenotypic resistance outcomes (reported as minimum inhibitory concentration, MIC) while considering the correlations among themselves. Some phenotypic resistances have low connectivity to other outcomes or predictors (e.g. tetracycline, vancomycin, doxycycline, and rifampin). Levofloxacin was the only resistant associated with healthcare use. Blood culture was the most common predictor of MIC. Patients with positive blood culture had significantly increased MIC to chloramphenicol, erythromycin, gentamicin, lincomycin, and mupirocin, and decreased daptomycin and rifampin MICs. Chain graphs show the unique and common risk factors associated with resistance outcomes.}, 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={AbstractAs vaccination efforts to combat the COVID-19 pandemic are ramping up worldwide, there are rising concerns that individuals will begin to eschew nonpharmaceutical interventions for preventing SARS-CoV-2 transmission and attempt to return to pre-pandemic normalcy before vaccine coverage levels effectively mitigate transmission risk. In the U.S.A., some governing bodies have already weakened or repealed guidelines for nonpharmaceutical intervention use, despite a recent spike in national COVID-19 cases and majority population of unvaccinated individuals. Recent modeling suggests that repealing nonpharmaceutical intervention guidelines too early into vaccine rollouts will lead to localized increases in COVID-19 cases, but the magnitude of nonpharmaceutical intervention effects on individual-level SARS-CoV-2 infection risk in fully- and partially-vaccinated populations is unclear. We use a previously-published agent-based model to simulate SARS-CoV-2 transmission in indoor gatherings of varying durations, population densities, and vaccination coverage levels. By simulating nonpharmaceutical interventions in some gatherings but not others, we were able to quantify the difference in SARS-CoV-2 infection risk when nonpharmaceutical interventions were used, relative to scenarios with no nonpharmaceutical interventions. We found that nonpharmaceutical interventions will often reduce secondary attack rates, especially during brief interactions, and therefore there is no definitive vaccination coverage level that makes nonpharmaceutical interventions completely redundant. However, the reduction effect on absolute SARS-CoV-2 infection risk conferred by nonpharmaceutical interventions is likely proportional to COVID-19 prevalence. Therefore, if COVID-19 prevalence decreases in the future, nonpharmaceutical interventions will likely still confer protective effects but potential benefits may be small enough to remain within “effectively negligible” risk thresholds.}, 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


Point data obtained from real‐time location systems (RTLSs) can be processed into animal contact networks, describing instances of interaction between tracked individuals. Proximity‐based definitions of interanimal “contact,” however, may be inadequate for describing epidemiologically and sociologically relevant interactions involving body parts or other physical spaces relatively far from tracking devices. This weakness can be overcome by using polygons, rather than points, to represent tracked individuals and defining “contact” as polygon intersections.

We present novel procedures for deriving polygons from RTLS point data while maintaining distances and orientations associated with individuals' relocation events. We demonstrate the versatility of this methodology for network modeling using two contact network creation examples, wherein we use this procedure to create (a) interanimal physical contact networks and (b) a visual contact network. Additionally, in creating our networks, we establish another procedure to adjust definitions of “contact” to account for RTLS positional accuracy, ensuring all true contacts are likely captured and represented in our networks.

Using the methods described herein and the associated R package we have developed, called contact, researchers can derive polygons from RTLS points. Furthermore, we show that these polygons are highly versatile for contact network creation and can be used to answer a wide variety of epidemiological, ethological, and sociological research questions.

By introducing these methodologies and providing the means to easily apply them through the contact R package, we hope to vastly improve network‐model realism and researchers' ability to draw inferences from RTLS data.

}, journal={Ecology and Evolution}, author={Farthing, Trevor S. and Dawson, Daniel E. and Sanderson, Michael W. and Lanzas, Cristina}, year={2020}, month={Jun} }
 @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={AbstractMetapopulation models have been primarily explored in infectious disease epidemiology to study host subpopulation movements and between-host contact structures. They also have the potential to investigate environmental pathogen transferring. In this study, we demonstrate that metapopulation models serve as an ideal modeling framework to characterize and quantify pathogen transfer between environment and hosts. It therefore unifies host, pathogen, and environment, collectively known as the epidemiological triad, a fundamental concept in epidemiology. We develop a customizable and generalized pathogen-transferring model where pathogens dwell in and transferring (via contact) between environment and hosts. We analyze three specific case studies: pure pathogen transferring without pathogen demography, source-sink dynamics, and pathogen control via external disinfection. We demonstrate how pathogens circulate in the system between environment and hosts, as well as evaluate different controlling efforts for healthcare-associated infections (HAIs). For pure pathogen transferring, system equilibria can be derived analytically to explicitly quantify long-term pathogen distribution in the system. For source-sink dynamics and pathogen control via disinfection, we demonstrate that complete eradication of pathogens can be achieved, but the rates of converging to system equilibria differ based on specific model parameterization. Direct host-host pathogen transferring and within-host dynamics can be future directions of this modeling framework by adding specific modules.}, 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{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_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{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={AbstractAntimicrobials play a critical role in treating cases of invasive non-typhoidal salmonellosis (iNTS) and other diseases, but efficacy is hindered by resistant pathogens. Selection for phenotypical resistance may occur via several mechanisms. The current study aims to identify correlations that would allow indirect selection of increased resistance to ceftriaxone, ciprofloxacin and azithromycin to improve antimicrobial stewardship. These are medically important antibiotics for treating iNTS, but these resistances persist in non-TyphiSalmonellaserotypes even though they are not licensed for use in US food animals. A set of 2875Salmonella entericaisolates collected from animal sources by the National Antimicrobial Resistance Monitoring System were stratified in to 10 subpopulations based on serotype and host species. Collateral resistances in each subpopulation were estimated as network models of minimum inhibitory concentration partial correlations. Ceftriaxone sensitivity was correlated with otherβ-lactam resistances, and less commonly resistances to tetracycline, trimethoprim-sulfamethoxazole or kanamycin. Azithromycin resistance was frequently correlated with chloramphenicol resistance. Indirect selection for ciprofloxacin resistance via collateral selection appears unlikely. Density of the ACSSuT subgraph resistance aligned well with the phenotypical frequency. The current study identifies several important resistances in iNTS serotypes and further research is needed to identify the causative genetic correlations.}, 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={AbstractAntimicrobial use (AMU) is increasingly threatened by antimicrobial resistance (AMR). The FDA is implementing risk mitigation measures promoting prudent AMU in food animals. Their evaluation is crucial: the AMU/AMR relationship is complex; a suitable framework to analyze interventions is unavailable. Systems science analysis, depicting variables and their associations, would help integrate mathematics/epidemiology to evaluate the relationship. This would identify informative data and models to evaluate interventions. This National Institute for Mathematical and Biological Synthesis AMR Working Group's report proposes a system framework to address the methodological gap linking livestock AMU and AMR in foodborne bacteria. It could evaluate how AMU (and interventions) impact AMR. We will evaluate pharmacokinetic/dynamic modeling techniques for projecting AMR selection pressure on enteric bacteria. We study two methods to model phenotypic AMR changes in bacteria in the food supply and evolutionary genotypic analyses determining molecular changes in phenotypic AMR. Systems science analysis integrates the methods, showing how resistance in the food supply is explained by AMU and concurrent factors influencing the whole system. This process is updated with data and techniques to improve prediction and inform improvements for AMU/AMR surveillance. Our proposed framework reflects both the AMR system's complexity, and desire for simple, reliable conclusions.}, 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{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} }
 @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{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{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}, abstractNote={OBJECTIVETo determine whetherClostridium difficileis present in the food of hospitalized patients and to estimate the risk of subsequent colonization associated withC. difficilein food.METHODSThis was a prospective cohort study of inpatients at a university-affiliated tertiary care center, May 9, 2011–July 12, 2012. Enrolled patients submitted a portion of food from each meal. Patient stool specimens and/or rectal swabs were collected at enrollment, every 3 days thereafter, and at discharge, and were cultured forC. difficile. Clinical data were reviewed for evidence of infection due toC. difficile.A stochastic, discrete event model was developed to predict exposure toC. difficilefrom food, and the estimated number of new colonization events from food exposures per 1,000 admissions was determined.RESULTSA total of 149 patients were enrolled and 910 food specimens were obtained. Two food specimens from 2 patients were positive forC. difficile(0.2% of food samples; 1.3% of patients). Neither of the 2 patients was colonized at baseline withC. difficile. Discharge colonization status was available for 1 of the 2 patients and was negative. Neither was diagnosed withC. difficileinfection while hospitalized or during the year before or after study enrollment. Stochastic modeling indicated contaminated hospital food would be responsible for less than 1 newly colonized patient per 1,000 hospital admissions.CONCLUSIONSThe recovery ofC. difficilefrom the food of hospitalized patients was rare. Modeling suggests hospital food is unlikely to be a source ofC. difficileacquisition.Infect Control Hosp Epidemiol2016;1401–1407}, 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{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{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
          
            Understanding the transmission dynamics of pathogens is essential to determine the epidemiology, ecology, and ways of controlling enterohemorrhagic
            Escherichia coli
            (EHEC) in animals and their environments. Our objective was to estimate the epidemiological fitness of common EHEC strains in cattle populations. For that purpose, we developed a Markov chain model to characterize the dynamics of 7 serogroups of enterohemorrhagic
            Escherichia coli
            (O26, O45, O103, O111, O121, O145, and O157) in cattle production environments based on a set of cross-sectional data on infection prevalence in 2 years in two U.S. states. The basic reproduction number (
            R
            0
            ) was estimated using a Bayesian framework for each serogroup based on two criteria (using serogroup alone [the O-group data] and using O serogroup, Shiga toxin gene[s], and intimin [
            eae
            ] gene together [the EHEC data]). In addition, correlations between external covariates (e.g., location, ambient temperature, dietary, and probiotic usage) and prevalence/
            R
            0
            were quantified.
            R
            0
            estimates varied substantially among different EHEC serogroups, with EHEC O157 having an
            R
            0
            of >1 (∼1.5) and all six other EHEC serogroups having an
            R
            0
            of less than 1. Using the O-group data substantially increased
            R
            0
            estimates for the O26, O45, and O103 serogroups (
            R
            0
            > 1) but not for the others. Different covariates had distinct influences on different serogroups: the coefficients for each covariate were different among serogroups. Our modeling and analysis of this system can be readily expanded to other pathogen systems in order to estimate the pathogen and external factors that influence spread of infectious agents.
          
          
            IMPORTANCE
            In this paper we describe a Bayesian modeling framework to estimate basic reproduction numbers of multiple serotypes of Shiga toxin-producing
            Escherichia coli
            according to a cross-sectional study. We then coupled a compartmental model to reconstruct the infection dynamics of these serotypes and quantify their risk in the population. We incorporated different sensitivity levels of detecting different serotypes and evaluated their potential influence on the estimation of basic reproduction numbers.
          }, 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{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} }
 @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
          
            In response to concerning increases in antimicrobial resistance (AMR), the Food and Drug Administration (FDA) has decided to increase veterinary oversight requirements for antimicrobials and restrict their use in growth promotion. Given the high stakes of this policy for the food supply, economy, and human and veterinary health, it is important to rigorously assess the effects of this policy. We have undertaken a detailed analysis of data provided by the National Antimicrobial Resistance Monitoring System (NARMS). We examined the trends in both AMR proportion and MIC between 2004 and 2012 at slaughter and retail stages. We investigated the makeup of variation in these data and estimated the sample and effect size requirements necessary to distinguish an effect of the policy change. Finally, we applied our approach to take a detailed look at the 2005 withdrawal of approval for the fluoroquinolone enrofloxacin in poultry water. Slaughter and retail showed similar trends. Both AMR proportion and MIC were valuable in assessing AMR, capturing different information. Most variation was within years, not between years, and accounting for geographic location explained little additional variation. At current rates of data collection, a 1-fold change in MIC should be detectable in 5 years and a 6% decrease in percent resistance could be detected in 6 years following establishment of a new resistance rate. Analysis of the enrofloxacin policy change showed the complexities of the AMR policy with no statistically significant change in resistance of both
            Campylobacter jejuni
            and
            Campylobacter coli
            to ciprofloxacin, another second-generation fluoroquinolone.
          }, 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.MethodsWe developed an agent-based transmission model for C. difficile that incorporates screening and contact precautions for asymptomatic carriers in a hospital ward. We simulated scenarios that vary according to screening test characteristics, colonization prevalence, and type of strain present at admission.ResultsIn our baseline scenario, on average, 42% of CDI cases were community-onset cases. Within the hospital-onset (HO) cases, approximately half were patients admitted as asymptomatic carriers who became symptomatic in the ward. On average, testing for asymptomatic carriers reduced the number of new colonizations and HO-CDI cases by 40%–50% and 10%–25%, respectively, compared with the baseline scenario. Test sensitivity, turnaround time, colonization prevalence at admission, and strain type had significant effects on testing efficacy.ConclusionsTesting for asymptomatic carriers at admission may reduce both the number of new colonizations and HO-CDI cases. Additional reductions could be achieved by preventing disease in patients who are admitted as asymptomatic carriers and developed CDI during the hospital stay.}, 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={SUMMARYEnteric commensal bacteria of food animals may serve as a reservoir of genes encoding antimicrobial resistance (AMR). The genes are often plasmidic. Different aspects of bacterial ecology can be targeted by interventions to control plasmid-mediated AMR. The field efficacy of interventions remains unclear. We developed a deterministic mathematical model of commensalEscherichia coliin its animate and non-animate habitats within a beef feedlot's pen, with someE. colihaving plasmid-mediated resistance to the cephalosporin ceftiofur. We evaluated relative potential efficacy of within- or outside-host biological interventions delivered throughout rearing depending on the targeted parameter of bacterial ecology. Most instrumental in reducing the fraction of resistant entericE. coliat steer slaughter age were interventions acting on the entericE. coliand capable of either ‘plasmid curing’E. coli, or lowering maximumE. colinumbers or the rate of plasmid transfer in this habitat. Also efficient was to increase the regular replacement of entericE. coli. Lowering replication rate of resistantE. colialone was not an efficient intervention target.}, 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{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{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 (≥104 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 104 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{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.Design, Setting, and Patients.Retrospective cohort study of all patients admitted to medical wards at a large tertiary care hospital in the United States in the calendar year 2008.Methods.Data from six medical wards and published literature were used to develop a compartmental model of C.difficiletransmission. Patients could be in one of five transition states in the model: resistant to colonization (R), susceptible to colonization (S), asymptomatically colonized without protection against CDI (C-), asymptomatically colonized with protection against CDI (C+), and diseased (ie, with CDI; D).Results.The contributions of C-, C+, and D patients to new colonizations were similar. The simulated basic reproduction number ranged from 0.55 to 1.99, with a median of 1.04. These values suggest that transmission within the ward alone from patients with CDI cannot sustain new C.difficilecolonizations and therefore that the admission of colonized patients plays an important role in sustaining transmission in the ward. The epidemiological parameters that ranked as the most influential were the proportion of admitted C-patients and the transmission coefficient for asymptomatic carriers.Conclusion.Our study underscores the need to further evaluate the role of asymptomatically colonized patients in C.difficiletransmission in healthcare settings.}, 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 Clostridium difficile is a well recognized pathogen of humans and animals. Although C. difficile was first identified over 70 years ago, much remains unknown in regards to the primary source of human acquisition and its pathobiology. These deficits in our knowledge have been intensified by dramatic increases in both the frequency and severity of disease in humans over the last decade. The changes in C. difficile epidemiology might be due to the emergence of a hypervirulent stain of C. difficile, ageing of the population, altered risk of developing infection with newer medications, and/or increased exposure to C. difficile outside of hospitals. In recent years, there have been numerous reports documenting C. difficile contamination of various foods, and reports of similarities between strains that infect animals and strains that infect humans as well. The purposes of this review are to highlight the many challenges to diagnosing, treating, and preventing C. difficile infection in humans, and to stress that collaboration between human and veterinary researchers is needed to control this pathogen.}, 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_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{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={Although small-animal models have been very useful for the investigation of diseases, disease transmission is difficult to study in these models. Lanzas and colleagues describe how farm animals can be used to study transmission of diseases and how they allow for the design of transmission models. 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{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={SUMMARYThe objective of this study was to address the impact of heterogeneity of infectious period and contagiousness onSalmonellatransmission dynamics in dairy cattle populations. We developed three deterministic SIR-type models with two basic infected stages (clinically and subclinically infected). In addition, model 2 included long-term shedders, which were defined as individuals with low contagiousness but long infectious period, and model 3 included super-shedders (individuals with high contagiousness and long infectious period). The simulated dynamics, basic reproduction number (R0) and critical vaccination threshold were studied. Clinically infected individuals were the main force of infection transmission for models 1 and 2. Long-term shedders had a small impact on the transmission of the infection and on the estimated vaccination thresholds. The presence of super-shedders increasesR0and decreases the effectiveness of population-wise strategies to reduce infection, making necessary the application of strategies that target this specific group.}, 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_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{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{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} }