Virtual presentation, link provided upon registering.
Date: 11/18/2024
Time: 10:00 am CT
Lecture Title: Animal Agriculture and Antimicrobial Resistance
Presented by: Dr. Jared Taylor
Abstract: Antimicrobial resistance is a pressing public health issue that requires a comprehensive One Health approach to address. Much work has been done examining impacts of use of antimicrobials in food producing animals on resistance. While some determinations are well supported and demonstrate the need for action, many holes remain in our understanding. Data regarding usage of antimicrobials in food animals in the US is flawed and hinders our ability to take informed regulatory (or industry-led) actions. Moreover, a failure to understand the complexities and differences in various food animal production systems often leads to over-generalization and improper conclusions both in the scientific and regulatory communities. Our team is taking a One Health approach to examine impacts of routine antimicrobial usage in beef cattle operations using extensive management (as opposed to intensive confinement in CAFO facilities). The presentation will discuss the current state of understanding, highlight some deficiencies in scientific knowledge, and offer some suggestions for future research.
Virtual presentation, link provided upon registering.
Date: 9/26/2025
Time: 1:00 pm CT
Lecture Title: Modernizing Disease Surveillance via Informatics Approaches: Examples from the Regenstrief Institute
Presented by: Dr. Brian Dixon
Abstract: Post COVID-19 pandemic, the CDC is asking state, local, and tribal authorities (STLTs) to modernize their information systems in order to enhance detection and surveillance of disease. This will strengthen U.S. surveillance systems in preparation for the next pandemic. In this presentation, Dr. Dixon will demonstrate how researchers at Indiana University and the Regenstrief Institute applied an informatics lens to advance surveillance of disease over the past two decades. He will give some emphasis to zoonotic diseases, although most approaches can be universally applied to the larger set of notifiable diseases most STLTs seek to surveil. These approaches undergird the recommendations from the CDC and, if implemented broadly across the nation, could enable more rapid detection and surveillance during the next pandemic. Challenges to achieving data modernization goals will also be discussed.<b>Abstract:<b> Post COVID-19 pandemic, the CDC is asking state, local, and tribal authorities (STLTs) to modernize their information systems in order to enhance detection and surveillance of disease. This will strengthen U.S. surveillance systems in preparation for the next pandemic. In this presentation, Dr. Dixon will demonstrate how researchers at Indiana University and the Regenstrief Institute applied an informatics lens to advance surveillance of disease over the past two decades. He will give some emphasis to zoonotic diseases, although most approaches can be universally applied to the larger set of notifiable diseases most STLTs seek to surveil. These approaches undergird the recommendations from the CDC and, if implemented broadly across the nation, could enable more rapid detection and surveillance during the next pandemic. Challenges to achieving data modernization goals will also be discussed.
Virtual presentation, link provided upon registering.
Date: 10/9/2024
Time: 3:00 pm CT
Lecture Title: A Survey of Regenstrief/IU’s Pluripotent Public & Population Surveillance Experience & Capabilities
Presented by: Dr. Shaun Grannis
Abstract: Dr. Shaun Grannis will present an overview of Regenstrief Institute and Indiana University’s extensive experience and capabilities in public and population health surveillance. The presentation will highlight the Institute’s contributions to vaccine effectiveness, long COVID-19 surveillance, and real-world evidence research. Dr. Grannis will detail the vast reach of Indiana’s Health Information Exchange (HIE), which has millions of patients, encounters, and clinical transactions supporting numerous research projects. He will also discuss the utility of large language models (LLMs) for enhancing public health surveillance, disease outbreak detection, and medical documentation. The presentation touches on integration of social determinants of health data and predictive models for improving patient care.
Virtual presentation, link provided upon registering.
Date: 10/22/2024
Time: 3:00 pm CT
Lecture Title: Experimental H5N1 clade 2.3.4.4b virus infections in livestock
Presented by: Dr. Juergen Richt
Abstract: In the past few years, spillover of clade 2.3.4.4b highly pathogenic avian influenza virus (HPAIV) to mammals including humans, and their transmission between mammalian species has been reported. In March 2024, clade 2.3.4.4b H5N1 infections in dairy cows were reported in the US with rapid dissemination to more than 200 farms in 14 states. In this presentation, the results of clade 2.3.4.4b experimental infection studies in pigs and cattle will be discussed: (i) oronasal susceptibility and transmissibility in pigs to a mink-derived clade 2.3.4.4b H5N1 HPAIV isolate from Spain; (ii) oronasal susceptibility and transmission in calves to a US H5N1 bovine isolate genotype B3.13 (H5N1 B3.13); and (iii) susceptibility of lactating cows following direct mammary gland inoculation of either H5N1 B3.13 or a current EU H5N1 wild bird isolate genotype euDG. Experimental infection of pigs caused interstitial pneumonia with necrotizing bronchiolitis with high titers of virus present in the lower respiratory tract and 100% seroconversion. Infected pigs shed limited amount of virus, and there was no transmission to contact pigs. Inoculation of the calves resulted in moderate nasal replication and shedding with no severe clinical signs or transmission to sentinel calves. In dairy cows, infection resulted in no nasal shedding, but severe acute mammary gland infection with necrotizing mastitis and high fever was observed for both H5N1 strains. Milk production was rapidly and drastically reduced and the physical condition of the cows was severely compromised. Virus titers in milk rapidly peaked at 108 TCID50/mL, but did not result in systemic infection. Notably, adaptive mutation PB2 E627K emerged after intramammary replication of H5N1 euDG. Our data suggest that in addition to H5N1 B3.13, other HPAIV H5N1 strains have the potential to replicate in the udder of cows and that milk and milking procedures, rather than respiratory spread, are likely the primary routes of H5N1 transmission between cattle.
Emerging pathogens often spread for months prior to detection, allowing wide dispersal before detection and response. Moreover, the potential for crossover to the human population and subsequent spread is influenced by changing anthropogenic, genetic, ecologic, socioeconomic, and climatic factors. These interrelated driving forces create a Grand Challenge: How can we provide early syndrome and disease detection and effective public health surveillance that can help prevent the spread of new diseases and stop the next pandemic? Traditional epidemiological surveillance methods depend on a sequence of events from people experiencing symptoms, seeking medical attention, and undergoing testing, the tests being analyzed and confirmed, and reporting of cases with a defined infection/disease. Thus, new diseases are often underreported, data availability is delayed, and the information is disconnected from other indicators of emerging disease threats delaying public health responses to the point where action cannot be undertaken in real-time and in proportion to the level of pandemic threat. The lack of coordinated response to COVID-19 underscores the need for new methods of early detection of pathogens or disease/syndrome indicators, novel technologies for more effective data management and integration, efficient monitoring of the human-animal interface to develop One Health surveillance and control systems, and deepening cooperation and information sharing capacities between animal and public health officials across countries, sectors, regions, and localities. This project will prototype solutions and create a national Center roadmap to solve this challenge.
The project consists of five teams working on different aspects.
PI
Gallogly Chair Professor of ECE and CS
Associate Vice President of Research and Partnerships
Director, Data Institute for Societal Challenges (DISC)
University of Oklahoma
Co-PI
Professor, FRS, FNAI, FSNAS, FAPS, FMRS, FWIF, FAAIA, AAPAM
Director, Center for Quantum Research and Technology (CQRT)
Founding Director, Center of Optimal Materials for Emerging Technologies (COMET)
Departments of Physics and ECE
University of Oklahoma
Co-PI
Professor, Civil Engineering and Environmental Science
Director, Oklahoma Water Survey
Associate Director, Water Technologies for Emerging Regions (WaTER) Center
University of Oklahoma
Co-PI
Professor, Epidemiology
Edward E. and Helen T. Bartlett Chair in Public Health
Williams Companies Foundation Presidential Professor
Department of Biostatistics and Epidemiology
The University of Oklahoma Health Sciences Center
Co-PI
Professor
Department of Geography and Environmental Sustainability
University of Oklahoma
Project Management
Program Manager
Data Institute for Societal Challenges
University of Oklahoma
Financials and Administration
Senior Managing Director
Data Institute for Societal Challenges
University of Oklahoma
The dashboard visualizes the integrated data sources in a spatio-temporal manner. The user can select regions such as counties and states, explore the data, and compare them to each other. The time of all charts is linked such that selecting a specific time in a chart will highlight the respective times in the other data sources. The map can be animated to understand better how certain signals spread spatially over time. The data sources include data from the CDC, climate, symptoms searched in Google search, and animal and human pathogens detected in river and wastewater streams.
The transmission cycles of many pathogens interact with environmental factors, including climate, water, and land use. These relationships include direct effects on the pathogen as well as indirect effects on vectors and hosts. For example, influenza and other upper respiratory viruses are sensitive to weather conditions that influence virus persistence in the environment and host behavior and contact rates. Other infectious diseases, such as gastrointestinal pathogens and vector-borne infections, are influenced by extreme weather events such as localized flooding and heat waves. Understanding the ecological niches of hosts, vectors, and pathogens can support the prediction of potential transmission hotspots on the landscape and prioritization of resources for disease surveillance and control. Environmental reservoirs, such as water and soil, can also be directly sampled to detect the presence of pathogens.
The goal of the environmental surveillance team is to collect environmental measurements that can be integrated with data on pathogens, vectors, and hosts and develop predictive models and identify transmission hotspots for specific diseases. We have built a database of environmental variables obtained from multiple sources, including Oklahoma Mesonet ground-based weather stations, GridMET meteorological grids, and satellite Earth observations. We have also prototyped a system for watershed monitoring that involves testing river water samples for human and animal pathogens throughout Oklahoma. These data have been incorporated into the PIPP dashboard and are being used to analyze the relationships between meteorological variables and COVID-19 outbreaks.
Team Lead / Co-PI
Professor
Department of Geography and Environmental Sustainability
University of Oklahoma
Research Scientist
Oklahoma Water Survey
University of Oklahoma
Associate Professor, Microbiology
School of Biological Sciences
University of Oklahoma
Co-PI
Professor, Civil Engineering and Environmental Science
Director, Oklahoma Water Survey
Associate Director, Water Technologies for Emerging Regions (WaTER) Center
University of Oklahoma
Assistant Professor
Department of Geography and Environmental Sustainability
University of Oklahoma
Research Scientist
Oklahoma Water Survey
University of Oklahoma
Coordination
Research Scientist
Data Institute for Societal Challenges
University of Oklahoma
The Animal Surveillance team will work with veterinarians and other entities to utilize animal/zoonotic infectious disease data as a potential indicator for human infectious disease outbreaks. This team is also working in conjunction with other project teams to improve the detection and utilization of animal/zoonotic pathogens in wastewater and environmental samples for determining or predicting potential human infectious disease outbreaks.
Team Co-Lead
Regents Distinguished Professor & KBA Eminent Scholar
College of Veterinary Medicine
Director, Center of Excellence for Emerging and Zoonotic Animal Diseases (CEEZAD)
Director, NIH COBRE Center on Emerging and Zoonotic Infectious Diseases (CEZID)
Kansas State University
Team Co-Lead / Co-PI
Professor, Civil Engineering and Environmental Science
Director, Oklahoma Water Survey
Associate Director, Water Technologies for Emerging Regions (WaTER) Center
University of Oklahoma
Research Assistant & PhD Candidate
Data Institute for Societal Challenges
University of Oklahoma
Gallogly Chair Professor of ECE and CS
Associate Vice President of Research and Partnerships
Director, Data Institute for Societal Challenges (DISC)
University of Oklahoma
Professor, Epidemiology
Department of Veterinary Administration
Purdue University
Postdoctoral Fellow
Oklahoma Water Survey
University of Oklahoma
Research Scientist
Oklahoma Water Survey
University of Oklahoma
Assistant Professor
Department of Geography and Environmental Sustainability
University of Oklahoma
Research Scientist
Oklahoma Water Survey
University of Oklahoma
Research Assistant Professor
College of Veterinary Medicine
Kansas State University
Senior Research Associate
College of Veterinary Medicine
Kansas State University
Research Assistant
College of Veterinary Medicine
Kansas State University
Coordination
Research Scientist
Data Institute for Societal Challenges
University of Oklahoma
Human health accompanies environmental health and animal health as the three pillars of One Health. Our project has a unique combination of data sources: waste-water analysis for animal and human pathogens, breathomics analyzing human breath, and data from animal-human transmission studies. Sentinel and syndromic approaches are two design aspects to improve early detection of emerging pathogens. One of the primary challenges of these surveillance systems' ability to detect early disease emergence is that they are rare events. To address this challenge, we have a multidisciplinary team of experts, representing data science, systems engineering, computer science, as well as health, epidemiology, and bioinformatics. Our approach is to expand the number of data sources used for disease surveillance and combine them to produce information that can be reviewed and analyzed by both machine learning and human experts.
Team Lead / Co-PI
Professor, Epidemiology
Edward E. and Helen T. Bartlett Chair in Public Health
Williams Companies Foundation Presidential Professor
Department of Biostatistics and Epidemiology
The University of Oklahoma Health Sciences Center
Research Assistant & PhD Candidate
Data Institute for Societal Challenges
University of Oklahoma
PI and CEO - MyHealth Access Network
Chair of the Board for the National Committee for Quality Assurance (NCQA)
Board member for Strategic Health Information Exchange Collaborative (SHIEC)
Chair, Department of Medical Informatics, University of Oklahoma
Assistant Professor
Department of Biostatistics and Epidemiology
The University of Oklahoma Health Sciences Center
Associate Professor
Department of Industrial and Systems Engineering
Department of Data Science and Analytics
University of Oklahoma
Managing Director
Center for Quantum Research and Technology (CQRT)
University of Oklahoma
Co-PI
Professor, FRS, FNAI, FSNAS, FAPS, FMRS, FWIF, FAAIA, AAPAM
Director, Center for Quantum Research and Technology (CQRT)
Founding Director, Center of Optimal Materials for Emerging Technologies (COMET)
Departments of Physics and ECE
University of Oklahoma
Coordination
Research Scientist
Data Institute for Societal Challenges
University of Oklahoma
Pioneers innovative approaches for early detection and surveillance of emerging pathogens, crucial for preemptive public health responses. By harnessing breath analysis and wastewater-based epidemiology, this initiative aims to bridge the gap between traditional surveillance methods and real-time, integrated data management, enabling swift and effective action against potential pandemics. Through collaborative efforts across five specialized teams, this project endeavors to establish a national roadmap for proactive disease detection, emphasizing the vital role of technology in safeguarding public health on a global scale.
Team Co-Lead / Co-PI
Professor, FRS, FNAI, FSNAS, FAPS, FMRS, FWIF, FAAIA, AAPAM
Director, Center for Quantum Research and Technology (CQRT)
Founding Director, Center of Optimal Materials for Emerging Technologies (COMET)
Departments of Physics and ECE
University of Oklahoma
Team Co-Lead / Co-PI
Professor, Civil Engineering and Environmental Science
Director, Oklahoma Water Survey
Associate Director, Water Technologies for Emerging Regions (WaTER) Center
University of Oklahoma
PI
Gallogly Chair Professor of ECE and CS
Associate Vice President of Research and Partnerships
Director, Data Institute for Societal Challenges (DISC)
University of Oklahoma
Assistant Professor
Department of Biostatistics and Epidemiology
The University of Oklahoma Health Sciences Center
Associate Professor
Lloyd & Joyce Austin Presidential Professor
CS Interim Director
School of Computer Science
University of Oklahoma
Postdoctoral Fellow
Oklahoma Water Survey
University of Oklahoma
Research Scientist
Oklahoma Water Survey
University of Oklahoma
Associate Professor, Microbiology
School of Biological Sciences
University of Oklahoma
Managing Director
Center for Quantum Research and Technology (CQRT)
University of Oklahoma
Coordination
Research Scientist
Data Institute for Societal Challenges
University of Oklahoma
The team focuses on advancing decision-making processes and analytical frameworks across multiple scales to enhance pandemic response strategies. It integrates all data sources in a single database, checks the data for quality issues, and develops machine learning models for prediction and event detection. Furthermore, the team designs a dashboard where domain experts and model experts can explore all data. This initiative aims to provide decision-makers with timely, comprehensive insights for proactive intervention. Through a multidisciplinary approach, this project seeks to optimize resource allocation, risk assessment, and mitigation efforts, ultimately strengthening the resilience of healthcare systems and communities in the face of complex health challenges.
Team Lead / PI
Gallogly Chair Professor of ECE and CS
Associate Vice President of Research and Partnerships
Director, Data Institute for Societal Challenges (DISC)
University of Oklahoma
Research Assistant & PhD Candidate
Data Institute for Societal Challenges
University of Oklahoma
Associate Professor
Lloyd & Joyce Austin Presidential Professor
CS Interim Director
School of Computer Science
University of Oklahoma
Assistant Professor
Department of Biostatistics and Epidemiology
The University of Oklahoma Health Sciences Center
Assistant Professor
School of Computer Science
University of Oklahoma
Associate Professor
Department of Industrial and Systems Engineering
Department of Data Science and Analytics
University of Oklahoma
Assistant Professor
School of Industrial and Systems Engineering
University of Oklahoma
Co-PI
Professor, Epidemiology
Edward E. and Helen T. Bartlett Chair in Public Health
Williams Companies Foundation Presidential Professor
Department of Biostatistics and Epidemiology
The University of Oklahoma Health Sciences Center
Professor
Department of Geography and Environmental Sustainability
University of Oklahoma
Coordination
Research Scientist
Data Institute for Societal Challenges
University of Oklahoma
Half-day workshop at IEEE VIS, Melbourne, Australia, 22-27 October Workshop date: October 22, 2023
Full-day workshop at the University of Oklahoma, November 8, 2023
Hawaii International Conference on System Sciences (HICSS) Jan 3, 2024 - Jan 6, 2024, Hawaiian Village, Waikiki, Hawaii, USA
