1. Fleming-Davies A., Jabbari, S., Robertson, S. Sri Noor Asih, T., Lanzas, CLenhart, 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: Layton A., Miller L. (eds) Women in Mathematical Biology. Association for Women in Mathematics Series, vol 8. Springer, Cham [link]
  2. Grohn, Y.T., Carson, C., Lanzas, C., Pullum, L., Stanhope, M.J., and Volkova, V. 2017.A proposed analytic framework for determining the impact of an antimicrobial resistance intervention. Animal Health Research Reviews. In press.[link]
  3. 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. doi:10.1007/s00285-017-1133-6 [link]
  4. 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: 36-62 [link]


  1. Love, W., Zawack, K., Booth, J.G., Grohn, Y.T., Lanzas, C. 2016. Markov networks of collateral antibiotic resistance: National antimicrobial resistance monitoring system surveillance results from Escherichia coli isolates, 2004-2013. PLoS Computational Biology,12: e1005160 [link]
  2. Lanzas, C. Chen, S. 2016. Mathematical modeling tools to study preharvest food safety. Microbiology Spectrum, 4 [link]
  3. Kwon, J., Lanzas, C., Reske, K., Hink, T., Seiler, S., Bommarito, K., Burnham, C., Dubberke, E. 2016. The role of food as a potential source of Clostridium difficile acquisition in hospitalized patients. Infection Control and Hospital Epidemiology. In press. [link]
  4. Chen, S., Sanderson, M., Lee, C., Cernicchiaro, N., Renter, D., Lanzas., C. 2016. Basic reproduction number and transmission dynamics of common serogroups of enterohemorrhagic Escherichia coli. Applied and Environmental Microbiology. 82:5612-5620 [link]
  5. Zawack, K.,  Li, M., Booth, J.G., Love, W., Lanzas, C., Gröhn. 2016. Monitoring antimicrobial resistance in the food supply chain and its implications for FDA policy initiatives. Antimicrobial Agents and Chemotherapy. 602:5302-5311 [link]
  6. Chen and Lanzas, C. 2016. Distinction and connection between contact network, social network and disease transmission network. Preventive Veterinary Medicine, 131,8-11 [link] 


  1. 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: e0129253 [link]
  2. Lanzas, C., and Chen, S. 2015. Complex system modeling for veterinary epidemiology. Preventive Veterinary Medicine, 118: 207-214 [link]


  1. Aguilar-Bonavides, C., Sanchez-Arias, R., Lanzas, C. 2014. Major Histocompatibility Complex Class II Epitope Accurate Prediction by Sparse Representation. BioData Minding, 7:23 [link]
  2. Lanzas, C and Dubberke, E. 2014. Effectiveness of screening hospital admissions for colonization in reducing Clostridium difficile transmission: a modeling evaluation. Infection Control and Hospital Epidemiology, 35: 1043-1050 [link]
  3. Chen, S., White, B., Sanderson, M., Amrine, D., Ilany, A., Lanzas, C. 2014. A highly dynamic animal contact network and implications on disease transmission. Nature Scientific Reports, 4: 4472. [link]


  1. Chen, S., Sanderson, M., White, B., Amrine, D., Lanzas, C. 2013. Temporal-spatial heterogeneity in animal-environment contact: implications for the exposure and transmission of pathogens. Nature Scientific Reports, 3:3112. [link]
  2. Magombedze, G., Ngonghala, C., Lanzas, C. 2013. Evaluation of the “Iceberg phenomenon” in Johne’s disease through mathematical modelling. PLoS ONE. 8: e76636 [link]
  3. Volkova, V. V., Lu. Z., Lanzas, C., Scott, H.M., Gröhn, Y.T. 2013. Modelling dynamics of plasmid-gene mediated antimicrobial resistance in enteric bacteria using stochastic differential equations. Nature Scientific Reports, 3: 2463 [link]
  4. Volkova, V. V., Lu., Z., Lanzas, C., Gröhn, Y.T. 2013. Evaluating targets for control of plasmid-mediated antimicrobial resistance in enteric commensals of beef cattle: modeling approach. Epidemiology and Infection 141: 2294-2312 [link]
  5. 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: 47-57 [link]


  1. 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: e367 [link]


  1. Lanzas, C., Dubberke, E.R,, Lu, Z., Reske, K.A., Gröhn, Y.T. 2011. Epidemiological model for Clostridium difficile transmission in health care settings. Infection Control and Hospital Epidemiology. 32: 553-561 [link]
  2. 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: 1-10 [link]
  3. Dubberke, E. R., Haslam, D. B., Lanzas, C., Bobo, L. D., Burnham, C. D., Gröhn, Y. T., Tarr. P. I. 2011. The ecology and pathobiology of Clostridium difficile infections: an interdisciplinary challenge. Zoonoses and Public Health, 58: 4-20 [link]


  1. Lanzas, C., Warnick, L. D., James, K. L., Wright, E. M., Wiedmann, M. and Gröhn, Y. T., 2010. Transmission dynamics of a multi-drug resistant Salmonella typhimurium outbreak in a dairy farm. Foodborne Pathogens and Disease, 7: 467-474 [link]
  2. 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, 8:139-148 [link]


  1. Seo, S., Lanzas, C., Tedeschi, L.O., Pell, A., 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: 3981-4000
  2. Ayscue, P., Lanzas, C., Ivanek, R., Gröhn, Y.T., 2009. Modeling on-farm Escherichia coli O157:H7 population dynamics. Foodborne Pathogens and Disease, 6: 461-470


  1. 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, 91:4881-4891
  2. Lanzas, C., Warnick, L.D., Ivanek, R., Ayscue, P., Nydam, D.V., Gröhn, Y.T., 2008. The risk and control of Salmonella outbreaks in calf-raising operations: a mathematical modeling approach. Veterinary Research, 39:61
  3. Lanzas, C., Brien, S., Ivanek, R., Lo, Y., Chapagain, P.P., Ray, K.A., Ayscue, P., Warnick, L.D., Gröhn, Y.T., 2008. The effect of heterogeneous infectious period and contagiousness on the dynamics of Salmonella transmission in dairy cows. Epidemiology and Infection, 136:1496-1510


  1. 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 Technology, 136: 167-190
  2. Lanzas, C., Pell, A.N., Fox, D.G., 2007. Digestion kinetics of dried cereal grains. Animal Feed Science Technology, 136: 265-280
  3. 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 rate of passage of liquid in dairy cattle. Journal Dairy Science, 90: 840-855
  4. Lanzas, C., Seo, S., Tedeschi, L.O., Fox, D.G., 2007. Evaluation of protein fractionation systems used in formulating rations for dairy cattle. Journal Dairy Science, 90: 507-521


  1. 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 Technology, 128: 67-83