Lim, seunghyun2024-01-052024-01-052023-08https://hdl.handle.net/11299/259761University of Minnesota Ph.D. dissertation. August 2023. Major: Biomedical Informatics and Computational Biology. Advisor: Andres Perez. 1 computer file (PDF); xii, 166 pages.Bioinformatic and big data analysis tools have emerged as valuable resources for pathogen surveillance and outbreak detection, offering versatile applications across various organisms and providing critical insights into outbreaks and response strategies. This study aims to explore the potential of bioinformatic tools and big data analysis in the context of the One Health approach, which encompasses human, animal, and environmental health. The research focuses on developing and applying bioinformatic tools to support decision-making in the prevention and control of animal diseases, with a particular emphasis on viral and bacterial diseases.Three case studies were conducted to assess the economic importance and impact on One Health in the state of Minnesota (MN). Case study 1 investigates the evaluation of antimicrobial resistance (AMR) in Salmonella across multiple hosts. The study explores the dissemination of plasmids carrying acquired antimicrobial resistance genes (AARGs) in different Nontyphoidal Salmonella (NTS) serotypes from U.S. swine clinical cases. Case study 2 examines the development of a windborne transmission model for porcine reproductive and respiratory syndrome virus (PRRSv), enabling the assessment of the risk of transmission between swine farms. Case study 3 focuses on predicting the risk of highly pathogenic avian influenza (HPAI) outbreaks in MN, taking into account the role of migratory water birds in disease spread. The results of these case studies demonstrate the applicability of big data and bioinformatic tools in preventing and mitigating disease risks. Case study 1 highlights the presence of AARGs in multiple NTS serotypes circulating in swine, suggesting the potential for resistance expansion through horizontal transmission. Case study 2 reveals the seasonal variability of PRRSv transmission risk, allowing for targeted control measures. Case study 3 introduces a groundbreaking early warning detection system, DashFLUboard, for HPAI, enabling early detection in free zones connected by wild bird movements. Overall, this research showcases the potential of bioinformatic and big data analysis tools in disease prevention and control, emphasizing their significance in the One Health framework. By leveraging these tools, stakeholders can make informed decisions, mitigate risks, and implement timely control measures to safeguard public and animal health.enThesis or Dissertation