Antimicrobial Resistant (AMR) pathogens have become a significant public health threat. By developing and implementing novel mathematical and computation models, the long-term goals are to optimize AMR control and preventive interventions and to improve the health equity. The central hypothesis is that the outputs of mathematical and computation models will provide optimized and effective guidelines to reduce the threat of AMR pathogen spread and reduce health disparities in healthcare settings. The rationale underlying this project is to fill the critical gap in modeling workforce capacity and develop a new generation of mathematical models for healthcare research. The central hypothesis will be tested by pursuing three specific aims to develop and employ a, (i) One Health modeling approach to understand the source, distribution and spread of AMR Enterobacteriaceae with a focus on Extended-spectrum beta-lactamase (ESBL)-producing E. coli, (ii) a novel Real-Time modeling approach to identify AMR pathogen transmission by asymptomatic spreaders and contaminated medical devices in hospitals, (iii) a novel Agent-Based Nested modeling approach to identify the effects of caregivers as vectors of disease spread, and effects of limited staffing and specialized care on equitable quality of care in nursing homes. We will pursue these aims using an innovative combination of mathematical and computational modeling techniques. These include both recently developed techniques of including human behavior in models and more-established techniques that have been applied very little to the study of health equity and AMR pathogen spread. The workforce development objectives of this proposal are to (i) enhance mathematical and computational modeling research capabilities of the public health workforce and (ii) increase the number of junior modeling professionals that are trained and experienced in modeling transmission of pathogens in healthcare settings partly incorporated with health disparities.
Publications
a. Articles in preparation
[1] Pluta, J., Bani-Yaghoub, M., Spatial and temporal cluster analysis of COVID-19 risk levels associated with the US nursing homes and the general Population.
[2] Arjmand, A., Bani-Yaghoub, M., Corkran, K., Pandit, P., and Aly, S.S. Using Bayesian-stochastic methods to analyze ecology and evolution Enterobacteriaceae with resistance mechanisms at the intersection of environmental boundaries
[3] Bani-Yaghoub, M., Corkran, K. Arjmand, A., Advancing Mathematical Models of Healthcare-Associated Infections to Evaluate the Impact of Antimicrobial Stewardship and Staffing Strategies on Health Equity
[4] Corkran, K., Bani-Yaghoub, M., Sutkin, G., Arjmand, A., and Paschal, S. (2025) Bayesian Inference of Hospital-Acquired MRSA Transmission Among Patients Declaring Drug Use at Admission, to be submitted to Journal of Hospital Infection
[5] Corkran, K., Bani-Yaghoub, M., Sutkin, G., Arjmand, A., and Paschal, S. (2025) The Influence of Prior Antibiotic Use on MRSA Risk in Substance-Using and Non-Using Populations: A Comorbidity-Stratified Logistic Regression Analysis, to be submitted to Infection Control & Hospital Epidemiology
b. Articles submitted or accepted for publication
[6] Thota, R.C., Uddin, M.Y.S., Bani-Yaghoub, M., Abourraja, M.N., Sutkin, G., and Paschal, S. (2025) Enhancing Agent-Based Models with Real-Time Data to Assess Impacts of Movement Patterns and Biosecurity Compliance on Disease Exposure in Healthcare Settings, IEEE Journal of Biomedical and Health Informatics (accepted)
[7] Thota, R.C., Sara, S.M., Uddin, M.Y.S., Bani-Yaghoub, M., Sutkin, G., and Kasula, J. (2024) Estimating Individual Transmission Rates and Reproduction Numbers of Respiratory Diseases in Indoor Gatherings Using UWB-Based Location Data, ACM Transactions on Computing for Healthcare (submitted)
[8] Saha, B., Bani-Yaghoub, M., Podder C.N. (2025) Utility of Compartmental Models to Test the Competing Hypotheses of Pathogen Evolution and Human Intervention, Proceedings of The Royal Society A (Submitted) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5132105
c. Articles published in a refereed journal/conference
[9] Corkran, K., Bani-Yaghoub, M., Sutkin, G., Arjmand, A., and Paschal, S. (2025) Bayesian Inference of Nosocomial Methicillin-resistant Staphylococcus aureus Transmission in an Urban Safety-Net Hospital, Journal of Hospital Infection https://www.sciencedirect.com/science/article/abs/pii/S0195670125002348
[10] Arjmand, A., Bani-Yaghoub, M., Sutkin, G., Corkran, K., and Paschal, S. (2025) Comparative Analysis of Machine Learning Models for Predicting Hospital- and Community-Associated Urinary Tract Infections Using Demographic, Hospital, and Socioeconomic Predictors, Journal of Hospital Infection https://doi.org/10.1016/j.jhin.2025.04.024
[11] Arjmand, A., Bani-Yaghoub, M., Corkran, K., Pandit, P., and Aly, S.S. (2025) Assessing the Impact of Biosecurity Compliance on Farmworker and Livestock Health within a One Health Modeling Framework, One Health https://doi.org/10.1016/j.onehlt.2025.101023
[12] Corkran, K. Gomez, J.P. Arjmand, A., Nuño, M.A., Bani-Yaghoub, M. (2025) An Agent-Based Modeling Framework to Analyze Spread of Infection in A Network of Nursing Homes, BMC Infectious Diseases 25, 635 https://doi.org/10.1186/s12879-025-10786-w
[13] Bani-Yaghoub, M., Rekab, K. Pluta, J., Tabharit, S. (2024) Estimating the Relative Risks of Spatial Clusters Using a Predictor-Corrector Method, Mathematics, Computational and Applied Mathematics 13(2), 180. https://www.mdpi.com/2227-7390/13/2/180
[14] Sara, S.M., Thota, R.C. Uddin, M.Y.S., Bani-Yaghoub, M., Sutkin, G. and Abourraja, M.N. (2024) Patient flow modeling and simulation to study HAI incidence in an Emergency Department, Elsevier Smart Health https://www.doi.org/10.1016/j.smhl.2024.100467
[15] Thota, R. C., Sara, S. M., Uddin, M. Y. S., Bani-Yaghoub, M., and Sutkin, G. (2024, May). Accurate Estimation of Individual Transmission Rates Through Contact Analytics Using UWB-Based Indoor Location Data. In 2024 International Conference on Smart Applications, Communications and Networking (SmartNets) (pp. 1-8). IEEE. https://ieeexplore.ieee.org/document/10577695
Presentations
Pluta, J. July 2025, Machine Learning Models for Predicting UTIs in Long-Term Care Facilities, , CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Corkran, K. July 2025, Estimating HAI MRSA Transmission Rates in Drug-Free and Drug-Using Patient Populations, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Uddin, Y. July 2025, Enhancing Agent-Based Models Using Indoor GPS Data, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Pluta, J. January 2025, Disease Modeling of Medicaid and Medicare Nursing Homes with Health Equity Adjustments December 2024, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Corkran, K. January 2025, Bayesian Inference of HA-MRSA Transmission Rates in a Safety-Net Hospital, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Thota R.C. December 2024, Enhancing Agent-Based Models with Real-Time Movement Data to Understand Antimicrobial Resistance Dynamics in Healthcare Settings, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Arjmand, A. December 2024, Comparative Analysis of Machine Learning Models for Predicting HA- and CA-UTIs, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling Fellowship Presentation
Thota R.C. October 2024, Modeling the Spread of Respiratory Infections in Universities and Colleges Using UWB RTLS Real-Time Movement Data 9th Annual Meeting of SIAM Central States Section, Advances in Mathematical and Computational Models in Biology, Health and Medicine
Corkran, K. October 2024, Utilizing Bayesian Inference to Understand the Evolution of MRSA Infection and Transmission in Urban Archor Hospital Settings, 9th Annual Meeting of SIAM Central States Section, Advances in Mathematical and Computational Models in Biology, Health and Medicine
Arjmand, A. October 2024, Machine Learning Approaches for Predicting Hospital- and Community Acquired Urinary Tract Infections: A Comparative Analysis, 9th Annual Meeting of SIAM Central States Section, Advances in Mathematical and Computational Models in Biology, Health and Medicine
Corkran, K. July 2024, Modeling the Impact of Nurse Units, Shared Staffing, and Pathogen Transmission Dynamics on Quality of Care, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Pluta, J. July 2024, Spatial and temporal analysis of COVID-19 risk levels associated with the US nursing homes and the general Population, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Bani-Yaghoub M. July 2024, One Health Modeling of Optimized Preventive and Control Measures to Reduce Health Disparities, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Sara, S.M. July 2024, Advancing agent-based models of healthcare-associated infections using ultra-wideband location data of healthcare workers and medical devices, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Arjmand, A. June 2024. Poster Presentation: "Modeling E. coli Transmission Dynamics Across Environmental Interfaces: A Bayesian-Stochastic Approach" at the 21st Ecology and Evolution of Infectious Diseases Conference, Stanford University, Stanford, CA.
Corkran, K. June 2024. Poster Presentation: "Modeling Evolution of Healthcare-Associated Infections Caused by Antibiotic- Resident Bacteria Strains" at the 21st Ecology and Evolution of Infectious Diseases Conference, Stanford University, Stanford, CA.
Saha, B. June 2024. Poster Presentation: "A Stochastic-Deterministic Model to Analyze Transmission Dynamics of COVID-19 Variants" at the 21st Ecology and Evolution of Infectious Diseases Conference, Stanford University, Stanford, CA.
Arjmand, A. April 2024, Poster Session: Analyzing Biosecurity Adherence and Antibiotic Resistance Dynamics in Animals and Humans through Mathematical Modeling" UMKC Division of Computing, Analytics, and Mathematics Research-a-Thon, Kansas City, MO
Arjmand, A. April 2024, Poster Session: Analyzing Biosecurity Adherence and Antibiotic Resistance Dynamics in Animals and Humans through Mathematical Modeling" UMKC Division of Computing, Analytics, and Mathematics Research-a-Thon, Kansas City, MO
Bani-Yaghoub M., April 2024, Understanding the Behaviors of Biological Waves Using Mathematical Models with Nonlocality, Department of Mathematical Sciences, New Jersey Institute of Technology (Invited Talk)
Pluta, J. April 2024, Poster Session: “Social and Economic Contributions to COVID-19 Prevalence in Nursing Homes”, UMKC Division of Computing, Analytics, and Mathematics Research-a-Thon, Kansas City, MO
Corkran, K. January 2024, The Mathematics behind Infectious Disease Spread in Nursing Homes, Joint Mathematics Meeting (JMM) San Fransisco, CA
Bani-Yaghoub M., October 2023, Leveraging Machine Learning Models to Identify Possible Outcomes of Discrete and Continuous Dynamical Systems, Advances in Computational Modeling of Infectious Diseases, 8th SIAM Annual Meeting of Central States Section, University of Nebraska-Lincoln
Bani-Yaghoub M., October 2023, Building an agent-based model to simulate the prevalence of epidemics in nursing homes with shared staff, AMS, Fall Central Sectional Meeting Special Session on Mathematical modeling and analysis in ecology and epidemiology III
Arjmand, A. October 2023, "A Mathematical Model of Multidrug-Resistant Salmonella Spread in A Dairy Farm" AMS Fall Sectional Meeting, Creighton University
Arjmand, A. October 2023, "Deterministic and Stochastic Modeling Approaches for Analyzing Dynamics of Antimicrobial Resistant Organisms" SIAM Central States Section 8th Annual Meeting, University of Nebraska
Pluta, J. October 2023, Cluster Analysis of COVID-19 Morbidity and Mortality in Nursing Homes Over 7 Cycles Within the Pandemic, 2020-2023, American Mathematical Society Fall 2023 Central States Sectional Meeting, Omaha, NE
Pluta, J. October 2023, Developing a Predictive Model of Infectious Disease Vulnerability in Long-Term Care Facilities Using Machine Learning, 8th Annual Meeting of Society of Applied and Industrial Mathematics Central States Section, Lincoln, NE
Corkran, K. October 2023, Estimating the individual reproduction numbers for staff and residents of nursing homes linked by a shared staff, 8th Annual Meeting of Society of Applied and Industrial Mathematics Central States Section, Lincoln, NE
Sara, S.M., October 2023, Using Patient Flow Data to Model Infectious Disease Transmission in Emergency Departments, 8th SIAM Annual Meeting of Central States Section, University of Nebraska-Lincoln
Thota, R.C., October 2023, Estimating Infection Transmission Risk During Social Events Using Real-Time Indoor Location Data, SIAM Central States Section 8th Annual Meeting, University of Nebraska
Uddin, M.Y.S. Modeling Healthcare-associated Infections (HAI): A Data-driven Approach, SIAM Central States Section 8th Annual Meeting, University of Nebraska
Corkran, K. November 2023, A Safe Threshold for the use of Shared Staff Between A Network of Nursing Homes, Community of Scholars Research Conference, University of Missouri-Kansas City
Corkran, K. September 2023, Using Model Simulations to Measure the Effects of Asymptotic Superspreaders in a Population, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Pluta, J. September 2023, Modeling Nursing Home Pandemic Preparedness, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Arjmand, A. September 2023, Modeling Farmers' Actions and Perceptions of Preventing Disease Spread and Antibiotic Resistance, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Sara, S.M. September 2023, Indoor Position Data Acquisition to Enhance HAI Modeling and Biosecurity Compliance, CDC MInD and HIRe Global Communications Center (GCC), Roybal Campus
Arjmand, A. July 2023, Incorporating Biosecurity Adherence into a Modeling Framework to Analyze Dynamics of Antimicrobial Resistance in Cattle Farms, Society for Mathematical Biology Annual Meeting, Ohio State University
Corkran, K. July 2023 An Agent-Based modeling approach to Investigate Pandemic Preparedness of Nursing Home, Society for Mathematical Biology Annual Meeting, Ohio State University
Bani-Yaghoub M., May 2023, Basic and individual reproduction numbers influenced by human behavior and uncertainty: Toward digital twin HAI modeling, CDC Healthcare, Infectious Diseases, Research (HIRe) Modeling
GitHub Pages
We have developed our computational tools using Matlab, R, Anylogic, and Python computational environments. These resources are available in the following GitHub repositories:
[1] Modeling Biosecurity and Antibiotic Resistance in a One Health Context Using MATLAB
https://github.com/AArjcode/Biosecurity-Compliance-One-Health-Modeling-Framework
One Health Modeling of Farmworker’s behavior Influencing Antimicrobial Resistance
[2] Agent-Based Modeling of Respiratory Infections in Nursing Homes Using the GAMA Platform
https://github.com/Corkran1/NH_COVID/tree/master/models
Guide to run code is in a separate file called “Instructions to Run Simulations”
[3] Enhancing HAI Modeling with Indoor GPS-Based Contact and Movement Data Using Python
github.com/Ravi-Chandra24/Infection-Modeling-and-Contact-Analytics-for-Infection-Exposure-Assessment
Infection Modeling and Contact Analytics for Infection Exposure Assessment.
[4] Enhancing HAI Modeling with Indoor GPS-Based Contact and Movement Data Using Python
https://github.com/SarawatSara/Emergency-Dept-HAI-Model-using-Anylogic-/tree/main
Emergency Department HAI Model Using Anylogic
[5] Bayesian Estimation of Transmission Rates in HAI Compartmental Models Using MATLAB
https://github.com/Corkran1/UHKC-MRSA-Transmission-Model-FIies
Bayesian Inference of Nosocomial Methicillin-resistant Staphylococcus aureus Transmission
[6] Comparative Modeling of HAI and CAI UTI Transmission Using Machine Learning in Python https://github.com/AArjcode/UTI_MachineLearning_HAI_vs_CAI
AnyLogic Pages
[1] Patient Flow Modeling of Emergency Department
https://cloud.anylogic.com/model/15699432-9dbd-4faa-9c19-675e074380a1?mode=SETTINGS&tab=GENERAL