Cristina Lanzas

Lacy, A., Khan, M. M., Nath, N. D., Das, P., Igoe, M., Lenhart, S., … Odoi, A. (2024). Geographic disparities and predictors of COVID-19 vaccination in Missouri: a retrospective ecological study. FRONTIERS IN PUBLIC HEALTH, 12. https://doi.org/10.3389/fpubh.2024.1329382

Erwin, S., Fletcher, J. R., Sweeney, D. C., Theriot, C. M., & Lanzas, C. (2023, September 6). Distilling Mechanistic Models From Multi-Omics Data. https://doi.org/10.1101/2023.09.06.556597

Farthing, T. S., Jolley, A., Nickel, K. B., Hill, C., Stwalley, D., Reske, K. A., … Lanzas, C. (2023, June 29). Early coronavirus disease 2019 (COVID-19) pandemic effects on individual-level risk for healthcare-associated infections in hospitalized patients. INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY, Vol. 6. https://doi.org/10.1017/ice.2023.83

Deb, L. C., Jara, M., & Lanzas, C. (2023). 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). ONE HEALTH, 17. https://doi.org/10.1016/j.onehlt.2023.100580

Jolley, A., Love, W., Frey, E., & Lanzas, C. (2023). Impacts of the <scp>COVID</scp>‐19 pandemic on antimicrobial use in companion animals in an academic veterinary hospital in North Carolina. Zoonoses and Public Health, 70(5), 393–402. https://doi.org/10.1111/zph.13040

Lacy, A., Igoe, M., Das, P., Farthing, T., Lloyd, A. L., Lanzas, C., … Lenhart, S. (2023). Modeling impact of vaccination on COVID-19 dynamics in St. Louis. JOURNAL OF BIOLOGICAL DYNAMICS, 17(1). https://doi.org/10.1080/17513758.2023.2287084

Lanzas, C., Jara, M., Tucker, R., & Curtis, S. (2022). [Review of A review of epidemiological models of Clostridioides difficile transmission and control (2009e2021)]. ANAEROBE, 74. https://doi.org/10.1016/j.anaerobe.2022.102541

Mahmud, B., Wallace, M. A., Reske, K. A., Alvarado, K., Muenks, C. E., Rasmussen, D. A., … Dantas, G. (2022, August 22). Epidemiology of Plasmid Lineages Mediating the Spread of Extended-Spectrum Beta-Lactamases among Clinical Escherichia coli (C. W. Marshall, Ed.). MSYSTEMS, Vol. 8. https://doi.org/10.1128/msystems.00519-22

Davies, K., Lenhart, S., Day, J., Lloyd, A. L., & Lanzas, C. (2022). Extensions of mean-field approximations for environmentally-transmitted pathogen networks. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 20(2), 1637–1673. https://doi.org/10.3934/mbe.2023075

Das, P., Igoe, M., Lenhart, S., Luong, L., Lanzas, C., Lloyd, A. L., & Odoi, A. (2022). Geographic disparities and determinants of COVID-19 incidence risk in the greater St. Louis Area, Missouri (United States). PLOS ONE, 17(9). https://doi.org/10.1371/journal.pone.0274899

Igoe, M., Das, P., Lenhart, S., Lloyd, A. L., Luong, L., Tian, D., … Odoi, A. (2022). Geographic disparities and predictors of COVID-19 hospitalization risks in the St. Louis Area, Missouri (USA). BMC PUBLIC HEALTH, 22(1). https://doi.org/10.1186/s12889-022-12716-w

Love, W. J., Wang, C. A., & Lanzas, C. (2022). Identifying patient-level risk factors associated with non-beta-lactam resistance outcomes in invasive MRSA infections in the United States using chain graphs. JAC-ANTIMICROBIAL RESISTANCE, 4(4). https://doi.org/10.1093/jacamr/dlac068

Farthing, T. S., & Lanzas, C. (2021). Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: An agent-based modeling approach. EPIDEMICS, 37. https://doi.org/10.1016/j.epidem.2021.100524

Farthing, T. S., & Lanzas, C. (2021, January 22). Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: an agent-based modeling approach (Vol. 1). Vol. 1. https://doi.org/10.1101/2021.01.21.21250240

Farthing, T. S., Dawson, D. E., Sanderson, M. W., Seger, H., & Lanzas, C. (2021). Combining epidemiological and ecological methods to quantify social effects on Escherichia coli transmission. ROYAL SOCIETY OPEN SCIENCE, 8(10). https://doi.org/10.1098/rsos.210328

Love, W. J., Wang, C. A., & Lanzas, C. (2021, November 14). 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 (Vol. 11). Vol. 11. https://doi.org/10.1101/2021.11.12.21266278

Dawson, D., Rasmussen, D., Peng, X., & Lanzas, C. (2021). Inferring environmental transmission using phylodynamics: a case-study using simulated evolution of an enteric pathogen. JOURNAL OF THE ROYAL SOCIETY INTERFACE, 18(179). https://doi.org/10.1098/rsif.2021.0041

Sulyok, C. J., Fox, L., Ritchie, H., Lanzas, C., Lenhart, S., & Day, J. (2021). Mathematically modeling the effect of touch frequency on the environmental transmission of Clostridioides difficile in healthcare settings. MATHEMATICAL BIOSCIENCES, 340. https://doi.org/10.1016/j.mbs.2021.108666

Machado, G., Farthing, T. S., Andraud, M., Nunes Lopes, F. P., & Lanzas, C. (2021, October 15). Modelling the role of mortality-based response triggers on the effectiveness of African swine fever control strategies. TRANSBOUNDARY AND EMERGING DISEASES, Vol. 10. https://doi.org/10.1111/tbed.14334

Farthing, T. S., & Lanzas, C. (2021, April 27). 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 (Vol. 4). Vol. 4. https://doi.org/10.1101/2021.04.19.21255737

Farthing, T. S., Dawson, D. E., Sanderson, M. W., & Lanzas, C. (2020). Accounting for space and uncertainty in real‐time location system‐derived contact networks. Ecology and Evolution. https://doi.org/10.1002/ece3.6225

Garabed, R. B., Jolles, A., Garira, W., Lanzas, C., Gutierrez, J., & Rempala, G. (2020). Multi-scale dynamics of infectious diseases. Interface Focus, 10(1), 20190118. https://doi.org/10.1098/rsfs.2019.0118

Lanzas, C., Davies, K., Erwin, S., & Dawson, D. (2020). On modelling environmentally transmitted pathogens. Interface Focus, 10(1). https://doi.org/10.1098/rsfs.2019.0056

Cazer, C. L., Al-Mamun, M. A., Kaniyamattam, K., Love, W. J., Booth, J. G., Lanzas, C., & Grohn, Y. T. (2020, June 30). Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining (vol 10, 687, 2019). FRONTIERS IN MICROBIOLOGY, Vol. 11. https://doi.org/10.3389/fmicb.2020.01359

Lashnits, E. W., Dawson, D. E., Breitschwerdt, E., & Lanzas, C. (2019). Ecological and Socioeconomic Factors Associated with Bartonella henselae Exposure in Dogs Tested for Vector-Borne Diseases in North Carolina. Vector-Borne and Zoonotic Diseases, 19(8), 582–595. https://doi.org/10.1089/vbz.2018.2397

Zawack, K., Love, W. J., Lanzas, C., Booth, J. G., & Grohn, Y. T. (2019). Estimation of multidrug resistance variability in the National Antimicrobial Monitoring System. PREVENTIVE VETERINARY MEDICINE, 167, 137–145. https://doi.org/10.1016/j.prevetmed.2019.03.006

Chen, S., Lanzas, C., Lee, C., Zenarosa, G. L., Arif, A. A., & Dulin, M. (2019). Metapopulation Model from Pathogen's Perspective: A Versatile Framework to Quantify Pathogen Transfer and Circulation between Environment and Hosts. SCIENTIFIC REPORTS, 9. https://doi.org/10.1038/s41598-018-37938-0

Cazer, C. L., Al-Mamun, M. A., Kaniyamattam, K., Love, W. J., Booth, J. G., Lanzas, C., & Grohn, Y. T. (2019). Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining. FRONTIERS IN MICROBIOLOGY, 10. https://doi.org/10.3389/fmicb.2019.00687

Dawson, D. E., Farthing, T. S., Sanderson, M. W., & Lanzas, C. (2019). Transmission on empirical dynamic contact networks is influenced by data processing decisions. EPIDEMICS, 26, 32–42. https://doi.org/10.1016/j.epidem.2018.08.003

Zawack, K., Love, W., Lanzas, C., Booth, J. G., & Grohn, Y. T. (2018). Inferring the interaction structure of resistance to antimicrobials. PREVENTIVE VETERINARY MEDICINE, 152, 81–88. https://doi.org/10.1016/j.prevetmed.2018.02.007

Dawson, D. E., Keung, J. H., Napoles, M. G., Vella, M. R., Chen, S., Sanderson, M. W., & Lanzas, C. (2018). Investigating behavioral drivers of seasonal Shiga-Toxigenic Escherichia Coli (STEC) patterns in grazing cattle using an agent-based model. PLOS ONE, 13(10). https://doi.org/10.1371/journal.pone.0205418

Chen, S., Lenhart, S., Day, J. D., Lee, C., Dulin, M., & Lanzas, C. (2018). Pathogen transfer through environment-host contact: an agent-based queueing theoretic framework. MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA, 35(3), 409–425. https://doi.org/10.1093/imammb/dqx014

Phenotypical resistance correlation networks for 10 non-typhoidal Salmonella subpopulations in an active antimicrobial surveillance programme. (2018). Epidemiology and Infection. https://doi.org/10.1017/s0950268818000833

Fletcher, J. R., Erwin, S., Lanzas, C., & Theriot, C. M. (2018). Shifts in the Gut Metabolome and Clostridium difficile Transcriptome throughout Colonization and Infection in a Mouse Model. MSPHERE, 3(2). https://doi.org/10.1128/msphere.00089-18

Grohn, Y. T., Carson, C., Lanzas, C., Pullum, L., Stanhope, M., & Volkova, V. (2017). [Review of A proposed analytic framework for determining the impact of an antimicrobial resistance intervention]. ANIMAL HEALTH RESEARCH REVIEWS, 18(1), 1–25. https://doi.org/10.1017/s1466252317000019

Bintz, J., Lenhart, S., & Lanzas, C. (2017). Antimicrobial Stewardship and Environmental Decontamination for the Control of Clostridium difficile Transmission in Healthcare Settings. BULLETIN OF MATHEMATICAL BIOLOGY, 79(1), 36–62. https://doi.org/10.1007/s11538-016-0224-7

Lanzas, C. (2017). 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. The Quarterly Review of Biology, 92(4), 456–457. https://doi.org/10.1086/694941

Park, S. S., Skaar, D. A., Jirtle, R. L., & Hoyo, C. (2017). Epigenetics, obesity and early-life cadmium or lead exposure. EPIGENOMICS, 9(1), 57–75. https://doi.org/10.2217/epi-2016-0047

Fleming-Davies, A., Jabbari, S., Robertson, S. L., Asih, T. S. N., Lanzas, C., Lenhart, S., & Theriot, C. M. (2017). Mathematical Modeling of the Effects of Nutrient Competition and Bile Acid Metabolism by the Gut Microbiota on Colonization Resistance Against Clostridium difficile. In Association for Women in Mathematics Series (pp. 137–161). https://doi.org/10.1007/978-3-319-60304-9_8

Stephenson, B., Lanzas, C., Lenhart, S., & Day, J. (2017). Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission. JOURNAL OF MATHEMATICAL BIOLOGY, 75(6-7), 1693–1713. https://doi.org/10.1007/s00285-017-1133-6

Kwon, J. H., Lanzas, C., Reske, K. A., Hink, T., Seiler, S. M., Bommarito, K. M., … Dubberke, E. R. (2016). An Evaluation of Food as a Potential Source for Clostridium difficile Acquisition in Hospitalized Patients. INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY, 37(12), 1401–1407. https://doi.org/10.1017/ice.2016.218

Chen, S., Sanderson, M. W., Lee, C., Cernicchiaro, N., Renter, D. G., & Lanzas, C. (2016). Basic Reproduction Number and Transmission Dynamics of Common Serogroups of Enterohemorrhagic Escherichia coli. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 82(18), 5612–5620. https://doi.org/10.1128/aem.00815-16

Chen, S., & Lanzas, C. (2016). Distinction and connection between contact network, social network, and disease transmission network. PREVENTIVE VETERINARY MEDICINE, 131, 8–11. https://doi.org/10.1016/j.prevetmed.2016.07.002

Love, W. J., Zawack, K. A., Booth, J. G., Grohn, Y. T., & Lanzas, C. (2016). Markov Networks of Collateral Resistance: National Antimicrobial Resistance Monitoring System Surveillance Results from Escherichia coli Isolates, 2004-2012. PLOS COMPUTATIONAL BIOLOGY, 12(11). https://doi.org/10.1371/journal.pcbi.1005160

Lanzas, C., & Chen, S. (2016). Mathematical modeling tools to study preharvest food safety. Microbiology Spectrum, 4(4).

Zawack, K., Li, M., Booth, J. G., Love, W., Lanzas, C., & Grohm, Y. T. (2016). Monitoring Antimicrobial Resistance in the Food Supply Chain and Its Implications for FDA Policy Initiatives. ANTIMICROBIAL AGENTS AND CHEMOTHERAPY, 60(9), 5302–5311. https://doi.org/10.1128/aac.00688-16

Lanzas, C., & Chen, S. (2015). Complex system modelling for veterinary epidemiology. Preventive Veterinary Medicine, 118(2-3), 207–214. https://doi.org/10.1016/j.prevetmed.2014.09.012

Chen, S., Ilany, A., White, B. J., Sanderson, M. W., & Lanzas, C. (2015). Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals? PLOS ONE, 10(6). https://doi.org/10.1371/journal.pone.0129253

Aguilar-Bonavides, C., Sanchez-Arias, R., & Lanzas, C. (2014). Accurate prediction of major histocompatibility complex class II epitopes by sparse representation via ℓ 1-minimization. BioData Mining. https://doi.org/10.1186/1756-0381-7-23

Lanzas, C., & Dubberke, E. R. (2014). Effectiveness of screening hospital admissions to detect asymptomatic carriers of Clostridium difficile: A modeling evaluation. Infection Control and Hospital Epidemiology, 35(8), 1043–1050. https://doi.org/10.1086/677162

Chen, S., White, B. J., Sanderson, M. W., Amrine, D. E., Ilany, A., & Lanzas, C. (2014). Highly dynamic animal contact network and implications on disease transmission. Scientific Reports, 4. https://doi.org/10.1038/srep04472

Volkova, V. V., Lu, Z., Lanzas, C., & Grohn, Y. T. (2013). Evaluating targets for control of plasmid-mediated antimicrobial resistance in enteric commensals of beef cattle: A modelling approach. Epidemiology and Infection, 141(11), 2294–2312. https://doi.org/10.1017/S0950268812002993

Magombedze, G., Ngonghala, C. N., & Lanzas, C. (2013). Evalution of the "Iceberg Phenomenon" in Johne's Disease through Mathematical Modelling. PLoS ONE, 8(10). https://doi.org/10.1371/journal.pone.0076636

Chen, S., Sanderson, M., & Lanzas, C. (2013). Investigating effects of between- and within-host variability on Escherichia coli O157 shedding pattern and transmission. Preventive Veterinary Medicine, 109(1-2), 47–57. https://doi.org/10.1016/j.prevetmed.2012.09.012

Modelling dynamics of plasmid-gene mediated antimicrobial resistance in enteric bacteria using stochastic differential equations. (2013). Scientific Reports, 3. https://doi.org/10.1038/srep02463

Chen, S., Sanderson, M. W., White, B. J., Amrine, D. E., & Lanzas, C. (2013). Temporal-spatial heterogeneity in animal-environment contact: Implications for the exposure and transmission of pathogens. Scientific Reports, 3. https://doi.org/10.1038/srep03112

Volkova, V. V., Lanzas, C., Lu, Z., & Gröhn, Y. T. (2012). Mathematical model of plasmid-mediated resistance to ceftiofur in commensal enteric escherichia coli of cattle. PLoS ONE, 7(5). https://doi.org/10.1371/journal.pone.0036738

Epidemiological model for Clostridium difficile transmission in healthcare settings. (2011). Infection Control and Hospital Epidemiology, 32(6), 553–561. https://doi.org/10.1086/660013

Lanzas, C., Lu, Z., & Gröhn, Y. T. (2011). Mathematical modeling of the transmission and control of foodborne pathogens and antimicrobial resistance at preharvest. Foodborne Pathogens and Disease, 8(1), 1–10. https://doi.org/10.1089/fpd.2010.0643

Dubberke, E. R., Haslam, D. B., Lanzas, C., Bobo, L. D., Burnham, C.-A. D., Gröhn, Y. T., & Tarr, P. I. (2011). The ecology and pathobiology of Clostridium difficile infections: An interdisciplinary challenge. Zoonoses and Public Health, 58(1), 4–20. https://doi.org/10.1111/j.1863-2378.2010.01352.x

Lanzas, C., Ayscue, P., Ivanek, R., & Gröhn, Y. T. (2010). Model or meal? Farm animal populations as models for infectious diseases of humans. Nature Reviews Microbiology, 8(2), 139–148. https://doi.org/10.1038/nrmicro2268

Lanzas, C., Warnick, L. D., James, K. L., Wright, E. M., Wiedmann, M., & Gröhn, Y. T. (2010). Transmission dynamics of a multidrug-resistant salmonella typhimurium outbreak in a dairy farm. Foodborne Pathogens and Disease, 7(4), 467–474. https://doi.org/10.1089/fpd.2009.0411

Seo, S., Lanzas, C., Tedeschi, L. O., Pell, A. N., & Fox, D. G. (2009). 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. Journal of Dairy Science, 92(8), 3981–4000. https://doi.org/10.3168/jds.2006-799

Ayscue, P., Lanzas, C., Ivanek, R., & Gröhn, Y. T. (2009). Modeling on-farm Escherichia coli O157:H7 population dynamics. Foodborne Pathogens and Disease, 6(4), 461–470. https://doi.org/10.1089/fpd.2008.0235

Lanzas, C., Broderick, G. A., & Fox, D. G. (2008). Improved feed protein fractionation schemes for formulating rations with the cornell net carbohydrate and protein system. Journal of Dairy Science, 91(12), 4881–4891. https://doi.org/10.3168/jds.2008-1440

The effect of heterogeneous infectious period and contagiousness on the dynamics of Salmonella transmission in dairy cattle. (2008). Epidemiology and Infection, 136(11), 1496–1510. https://doi.org/10.1017/S0950268807000209

The risk and control of Salmonella outbreaks in calf-raising operations: A mathematical modeling approach. (2008). Veterinary Research, 39(6). https://doi.org/10.1051/vetres:2008038

Lanzas, C., Sniffen, C. J., Seo, S., Tedeschi, L. O., & Fox, D. G. (2007). A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants. Animal Feed Science and Technology, 136(3-4), 167–190. https://doi.org/10.1016/j.anifeedsci.2006.08.025

Seo, S., Lanzas, C., Tedeschi, L. O., & Fox, D. G. (2007). 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. Journal of Dairy Science, 90(2), 840–855. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-34247890082&partnerID=MN8TOARS

Lanzas, C., Fox, D. G., & Pell, A. N. (2007). Digestion kinetics of dried cereal grains. Animal Feed Science and Technology, 136(3-4), 265–280. https://doi.org/10.1016/j.anifeedsci.2006.09.004

Lanzas, C., Tedeschi, L. O., Seo, S., & Fox, D. G. (2007). Evaluation of protein fractionation systems used in formulating rations for dairy cattle. Journal of Dairy Science, 90(1), 507–521. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-35748969906&partnerID=MN8TOARS

Seo, S., Tedeschi, L. O., Lanzas, C., Schwab, C. G., & Fox, D. G. (2006). Development and evaluation of empirical equations to predict feed passage rate in cattle. Animal Feed Science and Technology, 128(1-2), 67–83. https://doi.org/10.1016/j.anifeedsci.2005.09.014