One Health Research

Reducing Antimicrobial Resistance: a One Health Perspective

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. Tabharit, S., Pluta, J., Rekab, K., Bani-Yaghoub, M. Forecasting the relative risk of spatial clusters using a predictor-corrector method.

3.  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

4. Corkran, K. Arjmand, A., Bani-Yaghoub, M. A mathematical model representing dynamics and evolution of antibiotic- resident bacteria in staff and patient populations

5.  Sara, S.M., Thota, R.C. Uddin, M.Y.S., Bani-Yaghoub, M., Sutkin, G. Advancing agent-based models of healthcare-associated infections using ultra-wideband location data of healthcare workers and medical devices

6. Thota, R.C., April 2024, Exploring Transmission Dynamics of Infections in Social Settings Using Ultra-Wideband Indoor Tracking and Digital Contact Analysis, ACM Transactions on Computing for Healthcare

b.      Articles submitted or accepted for publication

1. Thota, R.C., Sara, S.M., Uddin, Y.S., Bani-Yaghoub, M., Sutkin, G. (2024) Accurate Estimation of Individual Transmission Rates Through Contact Analytics Using UWB Based Indoor Location Data, International Conference on Smart Applications, Communications and Networking, IEEE SmartNets (Accepted)

2. Corkran, K. Gomez, J.P. Arjmand, A., Nuño, M.A., Bani-Yaghoub, M. (2024) An Agent-Based Modeling Framework to Analyze Spread of Infection in A Network of Nursing Homes, Global Epidemiology (submitted)

3.  Arjmand, A., Bani-Yaghoub, M., Corkran, K., Pandit, P., and Aly, S.S. (2024) Assessing the Impact of Biosecurity Compliance on Farmworker and Livestock Health within a One Health Modeling Framework, One Health (submitted)

c.       Articles published in a refereed journal

1. 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

 

 Presentations

 

1. 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

2. 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)

3. 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

4. Corkran, K. January 2024, The Mathematics behind Infectious Disease Spread in Nursing Homes, Joint Mathematics Meeting (JMM) San Fransisco, CA

5. 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

6.  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

7.  Arjmand, A. October 2023, "A Mathematical Model of Multidrug-Resistant Salmonella Spread in A Dairy Farm" AMS Fall Sectional Meeting, Creighton University

8. 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

9. 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

10. 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

11. 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 

12. 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

13. 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 

14. Uddin, M.Y.S. Modeling Healthcare-associated Infections (HAI): A Data-driven Approach, SIAM Central States Section 8th Annual Meeting, University of Nebraska

15. Corkran, K. November 2023, A Safe Threshold for the use of Shared Staff Between A Network of Nursing Homes UMKC’s Community of Scholars Research Conference

16. 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

17. 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

 

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:

 

·         https://github.com/AArjcode/Biosecurity-Compliance-One-Health-Modeling-Framework

One Health Modeling of Farmworker’s behavior Influencing Antimicrobial Resistance

 

·         https://github.com/Corkran1/NH_COVID/tree/master/models 

Guide to run code is in a separate file called “Instructions to Run Simulations”

 

·         github.com/Ravi-Chandra24/Infection-Modeling-and-Contact-Analytics-for-Infection-Exposure-Assessment 

Infection Modeling and Contact Analytics for Infection Exposure Assessment. 


·         https://github.com/SarawatSara/Emergency-Dept-HAI-Model-using-Anylogic-/tree/main 

Emergency Department HAI Model Using Anylogic