About

Renata Ivanek, DVM, MS, PhD, is a Professor in the Department of Population Medicine and Diagnostic Sciences at Cornell University College of Veterinary Medicine. Her research integrates expertise in epidemiology, veterinary medicine, public health, mathematical modeling, biostatistics, machine learning, and risk assessment. Her work focuses on identifying and evaluating strategies to control infectious diseases in humans and animals, enhancing antimicrobial stewardship in livestock, and sustainably increasing food safety from farm to table. Additionally, she addresses the technical and ethical challenges of applying artificial intelligence methods in food and veterinary systems, including data governance, standardization, and sharing. Dr. Ivanek holds a Doctor of Veterinary Medicine degree from the Faculty of Veterinary Medicine at the University of Zagreb, an MS in Veterinary Epidemiology from the Royal Veterinary College & London School of Hygiene and Tropical Medicine, and a PhD in Comparative Biomedical Sciences with a concentration in Epidemiology from Cornell University. Her professional experience includes positions at Texas A&M University, where she served as Assistant Professor, Associate Professor, and held a joint appointment in Epidemiology and Biostatistics. Since 2015, she has been a faculty member at Cornell University, where she is a tenured Professor and co-directs the Combined DVM-PhD Degree Program Pathway and the Cornell Institute for Digital Agriculture. Her numerous awards include the Zoetis Award for Veterinary Research Excellence and the SUNY Chancellor's Award for Excellence in Teaching.

Research topics

• Biology
• Environmental science
• Agricultural science
• Biotechnology
• Environmental health
• Medicine
• Business
• Marketing
• Ecology
• Geography
• Microbiology

Selected publications

• Both Season and Equid Type Affect Endogenous Adrenocorticotropic Hormone Concentrations in Healthy Donkeys, Mules and Hinnies in the United States

  Animals · 2026-01-16

  articleOpen access

  Baseline plasma ACTH concentrations are frequently utilized as part of the diagnostic evaluation of equids when PPID is suspected. Baseline ACTH can be impacted by many factors including time of year, i.e., ACTH has generally been found to be elevated during late summer through early autumn in the northern hemisphere. An understanding of ACTH concentrations in healthy equids over the course of a year is useful for the proper interpretation of concentrations in PPID-suspect animals. Previous studies assessing ACTH concentrations in healthy donkeys (Equus asinus) and hybrids (E. asinus × E. caballus) are limited, often utilizing very small numbers, equids from specific and limited geographical regions, limited timeframes or unspecified donkey types (miniature, standard, or mammoth). We aimed to characterize the seasonal variation in baseline ACTH concentrations in healthy miniature donkeys, standard donkeys and hybrids in the United States (US) and to compare those concentrations across these groups. Following outlier removal, 19 standard donkeys (from California (CA), Massachusetts (MA), New York (NY)), 14 miniature donkeys (CA and NY), and 28 hybrids (Texas (TX) and NY) were utilized for analysis. Samples were collected from each equid twice per month from June to November 2019 and once per month from December 2019 through May 2020. The mean ACTH concentration of all equids was higher from mid-August through the end of October compared to the rest of the year (being the highest in the second half of September with the mean (standard deviation) values of 109.6 (52.6), 134.6 (67.4), and 100.8 (189.6) in standard donkeys, miniature donkeys, and hybrids, respectively). Additionally, ACTH concentrations in hybrids were 23% (95% Confidence Interval (CI): 4–38%) and 51% (95% CI: 36–63%) lower than in standard and miniature donkeys, respectively, from mid-August through October. During the rest of the year, hybrids similarly showed 31% (95% CI: 16–43%) and 30% (95% CI: 15–42%) lower ACTH concentrations compared with standard and miniature donkeys, respectively.

  PublisherOA PDFDOI

• Characterizing tilapia cage aquaculture biosecurity and production practices in Lake Victoria, Kenya

  Aquaculture Reports · 2026-04-13

  articleOpen access
  PublisherDOI

• Perceptions of Voluntary Horizontal Confidential Food Safety Data Sharing: An Exploratory Interview Study with Food Industry Leadership

  Research Square · 2026-03-06

  preprintOpen accessSenior author
  PublisherDOI

• Interventions Targeting the Beef Feedlot Environment to Control Antimicrobial Resistance: A Mathematical Modelling Study

  Zoonoses and Public Health · 2026-04-10

  articleOpen accessSenior author

  ABSTRACT Introduction To address concerns about livestock as a source of antimicrobial‐resistant bacteria and genes, there have been many recent efforts worldwide to study prescribing practices, optimal antibiotic use, and alternatives to antibiotic use. However, there is empirical evidence supporting the persistence of antimicrobial resistance genes at high densities in cattle pens for at least 2 years after cattle were removed. Methods We describe a mathematical modelling framework to predict and explore the dynamics of antimicrobial‐resistant enteric bacteria in food‐producing animals and their immediate environments. Using the difference equation based compartmental modelling framework, we algebraically derive a formula for the relative rate of growth of antimicrobial‐resistant enteric bacteria in the environment ( R AMR ). Results We demonstrate that R AMR > 1 (i.e. , growth) of tetracycline‐resistant Escherichia coli in feedlot environments can occur under a range of plausible conditions, even in the absence of antimicrobial use in the feedlot cattle. Our model can reproduce data observed under field conditions showing rapid growth of tetracycline‐resistant E. coli in the environment despite no antimicrobials being used. Finally, we demonstrate that generic hygiene measures such as scraping pen floors are likely to reduce the density of tetracycline‐resistant E. coli in the farm environment considerably, especially in cold climates. Conclusions Farm environments such as beef cattle feedlots may be conducive to persistence or even growth of antimicrobial resistant bacteria under a wide range of plausible conditions, even in the absence of antimicrobial use. The system may be quite resilient, and even stringent cleaning will likely not be sufficient to eliminate resistant bacteria from the environment in some climates, especially where freeze–thaw cycles are uncommon.

  PublisherDOI

• A fluid milk spoilage simulation framework reveals the need for spoilage intervention strategies that account for frequency of bacterial postpasteurization contamination

  Journal of Dairy Science · 2025-07-15 · 2 citations

  articleOpen access

  <h2>ABSTRACT</h2> Postpasteurization contamination (PPC) with gram-negative bacteria and the growth of spore-forming bacteria are major causes of fluid milk spoilage, typically leading to sensory defects when bacterial concentrations exceed 6 log₁₀ cfu/mL. Existing models focus on individual spoilage pathways, limiting their ability to capture the complexity of milk spoilage. To address this, we developed a simulation framework that simultaneously models the growth of both types of bacteria in high-temperature short-time pasteurized milk along a supply chain. Dairy processing plants were categorized into 3 groups based on shelf life of historical fluid milk: long, medium, and short shelf-life plants. We assumed varying initial PPC frequencies for each category, with ranges of 0% to 33% for long, 34% to 66% for medium, and 67% to 100% for short shelf-life plants. Shelf life, defined as when 25% of milk containers exceeded 6 log₁₀ cfu/mL, was predicted as 25, 12, and 8 d for long, medium, and short shelf-life plants, respectively. Our predictions aligned with observed bacterial growth in commercial milk stored at 6°C, with the percentage of milk containers exceeding 6 log₁₀ cfu/mL on d 14 falling within the fifth to 95th percentiles of simulated values. Sensitivity analysis identified key parameters influencing bacterial concentrations at shelf life d 7, 14, and 21 for long, medium, and short shelf-life plants, respectively, guiding intervention strategies. What-if scenario analysis revealed that effective intervention strategies to extend shelf life vary by plant categories. While interventions targeting spore-forming bacteria, such as microfiltration, bactofugation, and improved home storage conditions, extended the shelf life for long shelf-life milk by 3 to 5 d, PPC reduction extended shelf life by 5 and 4 d in medium and short shelf-life plants, respectively. This simulation framework provides a comprehensive spoilage prediction tool to support data-driven decision making for fluid milk processors.

  PublisherOA PDFDOI

• Risk assessment of Escherichia coli O157:H7 along the farm-to-fork fresh-cut romaine lettuce supply chain

  Scientific Reports · 2025-05-20 · 1 citations

  articleOpen accessSenior author

  Outbreaks of Escherichia coli O157:H7 (ECO157) in romaine lettuce remain an ongoing public health concern. Quantitative microbial risk assessment (QMRA) models are key tools for identifying control measures to mitigate foodborne diseases. Here, we introduce a comprehensive QMRA framework along the farm-to-fork fresh-cut romaine lettuce chain, including a novel preharvest difference equation model, to predict annual ECO157 illness cases in the United States and evaluate control strategies. We demonstrated the importance of managing irrigation-related contamination at preharvest to control illness cases. Wildlife intrusions pose lower health risk, followed by runoffs and biological soil amendments of animal origin. When preharvest contamination persists and combines with time-temperature abuses at postharvest, the predicted ECO157 illness cases rise considerably. We showed a broad range of interventions targeting both preharvest and postharvest stages can effectively improve the microbial safety of fresh-cut romaine. The comprehensive practices and interventions explored in this study will aid decision-makers in establishing/enhancing food safety best management practices.

  PublisherOA PDFDOI

• Characterization of biosecurity practices and viral infections on pig farms in Hong Kong

  Preventive Veterinary Medicine · 2025-05-14 · 2 citations

  articleOpen access

  The objectives of this study were to characterize the biosecurity practices implemented on pig farms in Hong Kong and determine the between-farm prevalence of economically important viral pathogens. All active pig farms in Hong Kong (n = 40) were invited to participate in an interview-based survey using a Biocheck-UGent™ questionnaire to evaluate their biosecurity practices. Pen-level oral fluid samples were collected by cotton ropes to detect six target viral pathogens using RT-PCR: porcine reproductive and respiratory virus (PRRSV), porcine circovirus type-2 (PCV-2), swine influenza virus (SIV), porcine delta-coronavirus (PDCoV), porcine epidemic diarrhea virus (PEDV), and transmissible gastroenteritis virus (TGEV). Eighteen farms (45 %) accepted our invitation and participated in this study. Biosecurity practices were found to be inadequate in many areas, with an average overall score of 50.1 ± 9.4 (mean ± SD). The study farms scored higher for external biosecurity (56.4 ± 8.6) than internal biosecurity practices (43.9 ± 12.1). Among external biosecurity subcategories, breeding pig and semen purchase scored highest (93.2), while visitors and farmworkers scored lowest (23.5). In internal biosecurity, the disease management subcategory received the highest score (66.7). Only two external biosecurity subcategories, breeding pig and semen purchase (93.2), and farm location (70) exceeded the global average scores. Key deficiencies were identified in biosecurity protocols for visitors and workers, hygiene standards for feed, water, and equipment supplies, and measures to prevent disease transmission between compartments (farrowing, nursery, and finishing units). Over 90 % of participating farms implemented vaccination programs for PRRSV, PCV-2, porcine parvovirus (PPV), pseudorabies virus (PRV), and classical swine fever virus (CSFV) while no farms vaccinated against SIV, and vaccination for swine coronaviruses was sporadic. All target viruses except TGEV were detected at the farm level. The between-farm prevalences among the 18 study farms were PRRSV-2 (94.4 %), PRRSV-1 (38.9 %), PCV-2 (83.3 %), SIV (55.6 %), PDCoV (16.7 %), and PEDV (5.6 %). We provided comprehensive baseline information on the biosecurity practices of pig farms for the first time in Hong Kong. We identified critical areas of biosecurity for improvement and offered tailored recommendations to help the producers implement more effective prevention and control strategies for infectious diseases within and between farms.

  PublisherDOI

• Correction: Risk assessment of Escherichia coli O157:H7 along the farm-to-fork fresh-cut romaine lettuce supply chain

  Scientific Reports · 2025-08-06

  erratumOpen accessSenior author
  PublisherOA PDFDOI

• Farm-to-consumer quantitative microbial risk assessment model for <i>Listeria monocytogenes</i> on fresh-cut cantaloupe

  medRxiv · 2025-03-03

  preprintOpen accessSenior author

  ABSTRACT Cantaloupe contamination with the foodborne pathogen Listeria monocytogenes (LM) may occur along the supply chain. We developed a quantitative microbial risk assessment (QMRA) model for LM on cantaloupe along the fresh-cut supply chain and evaluated potential risk reduction strategies. The developed model starts at harvest and includes conditions during transportation from field to intermediate facility (packinghouse or cooling facility), handling at the intermediate facility, transportation to the fresh-cut facility, storage pre-processing at the fresh-cut facility, processing and handling at the fresh-cut facility, as well as conditions during distribution, retail, transportation to home, and home storage. The model was simulated to (i) provide an estimate of LM concentration in a single serving (134 g) and (ii) estimate annual illnesses and deaths in the United States attributed to LM contaminated fresh-cut cantaloupe. The baseline model predicted the median risk of listeriosis per serving in general and susceptible populations was 1.4 × 10 −12 and 6.4 × 10 −11 , respectively. The median (5 th , 95 th percentiles) predicted number of illnesses and deaths annually attributed to fresh-cut cantaloupe were 0 (0, 1070) and 0 (0, 264), respectively. Time and temperature conditions post-packaging, and the initial number of LM at harvest had the greatest impacts on LM per contaminated serving and the number of annual illnesses; the initial LM levels at harvest and cross-contamination parameters at the fresh-cut facility had the greatest impacts on prevalence of contaminated servings. Assessment of interventions demonstrated that reducing temperature and/or time conditions post-packaging can be an effective risk reduction strategy. Overall, the developed tool estimates the risk associated with the consumption of LM contaminated fresh-cut cantaloupe and facilitates the identification and assessment of potential risk reduction strategies across the supply chain.

  PublisherOA PDFDOI

• Integration of mathematical modeling and economics approaches to evaluate strategies for control of Salmonella Dublin in a heifer-raising operation

  PLoS ONE · 2025-10-16 · 1 citations

  articleOpen accessSenior authorCorresponding

  Salmonella Dublin infections in heifer-raising operations (HROs) cause animal health and economic losses for these operations and represent a pathogen source for dairy farms obtaining replacement heifers from HROs. To improve control of S. Dublin, we (i) developed a mathematical model of S. Dublin transmission on a HRO, (ii) evaluated the vaccine effectiveness and cleaning improvements for controlling the infection, and (iii) evaluated the influence of infection and control strategies on the HRO's operating income. We developed a modified Susceptible-Infected-Recovered-Susceptible model of S. Dublin spread in a batch-stocking HRO post-introduction of an index case, with stochasticity introduced through Monte Carlo simulations. Epidemiological outcomes (S. Dublin-induced deaths and abortions during raising and S. Dublin carriers and asymptomatic infections among raised replacement heifers) and operating income per 100-head raised on a HRO over a 2-year simulation were compared between control scenarios. We validated our model against S. Dublin infection data in cattle. Partial rank correlation coefficient analysis and classification trees were used to determine parameter influence on model outcomes. Our model predicts a median of 37 carriers and 92 asymptomatic infections among raised replacement heifers out of 2,330 heifers that departed the operation by the end of the 2-year simulation period, suggesting a relevant role of HROs in spreading S. Dublin. Increasing barn floor cleaning frequency (to a maximum of 12x per day) meaningfully reduced the S. Dublin epidemiological outcomes and improved the HRO's operating income. Depending on the cost of cleaning, the median operating income increased between 1.2% to 10.6% in the first year when cleaning 12x per day compared to baseline (cleaning 1x per week). In most cost scenarios, predictions do not support using a vaccine that solely reduces mortality, even when paired with stringent cleaning measures. The developed model is expected to aid efforts to control S. Dublin in HROs.

  PublisherDOI

Frequent coauthors

• Martin Wiedmann

  Cornell University

  73 shared

• Yrjo T. Gröhn

  56 shared

• Amelia Greiner Safi

  43 shared

• Ece Bulut

  Cornell University

  43 shared

• P. Moroni

  University of Milan

  40 shared

• Michelle Wemette

  Cornell University

  28 shared

• Wendy Beauvais

  22 shared

• Sebastián Llanos‐Soto

  Cornell University

  21 shared

Labs

• IvanekLabPI

  Our computer lab solves societal problems related to infectious and foodborne diseases, and food production using cutting-edge modeling and epidemiologic methods.

Awards & honors

• Mark Gearhart Graduate Student Award ($1,000)
• Sigma Xi, Honor Scientific Research Society
• Texas A&M’s College of Veterinary Medicine & Biomedical Scie…
• Zoetis Award for Veterinary Research Excellence ($1,000)
• SUNY Chancellor's Award for Excellence in Teaching