The increasing prevalence of illnesses, particularly Salmonella infections, presents a significant public health challenge. Traditional surveillance and outbreak management methods are resource-intensive and often must catch up to real-time occurrences. This chapter explores the application of artificial intelligence (AI) within a systems thinking framework to revolutionize public health surveillance and outbreak response for Salmonella. By harnessing AI-driven tools for data analysis, early detection, source attribution, and intervention planning, public health agencies can enhance their capacity to prevent and mitigate Salmonella outbreaks. This chapter discusses the potential of AI-driven systems to transform the landscape of public health. The chapter proposes AI as a holistic approach integrating technology, data, and human expertise for more effective Salmonella outbreak control based on actual life outbreaks and the historical contexts of the of a real outbreak event.
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On March 1, 2017, a strain of Salmonella Agbeni infected patient zero (Multistate Outbreak, 2017). From March 1 to December 1, there were 76 cases across 19 states. Luckily, no one died; however, 30 people were hospitalized (Multistate Outbreak, 2017). Epidemiologists were able to link this outbreak to contact with turtles or their environment (Multistate Outbreak, 2017). Approximately 38% of infected individuals had contact with either turtles or their environment; 61% had contact with tiny turtles (shell length of less than four inches). These individuals either had access to these turtles from a street vendor or received them as gifts (Multistate Outbreak, 2017). Through genome sequencing, health officials could relate this outbreak to the turtles from the street vendor (Multistate Outbreak, 2017). This series of events was not without trial and error. Epidemiologists and other professionals must work together to determine what caused this outbreak and what specifically keeps this infectious disease alive.
A solid place to start in epidemiology is with the epidemiologic triangle. This triangle contains three factors: the agent, the host, and the environment (Friis, 2018). In this case, the agent Salmonella Agbeni is essential for the survival of this disease. Without this, there is no outbreak. The host, in this case, humans, is one infected with the disease and provides an area for the agent to thrive unless treated (Friis, 2018). Lastly, the environment is where the agent exists (Friis, 2018). Unfortunately for humans, the agent and the agent's environment proved to be a determining factor in having the illness. Even the water the turtles swam in could be strong enough to give an individual the infection. Combining these three factors gives Salmonella a chance to thrive in an area.
According to the CDC, 32% of the people who were ill were younger than five years old, and 23 of the 60 people interviewed reported contact with turtles or their environment during the week they fell ill. Therefore, epidemiologists have to consider some personal variables when defining a disease. Friis states that age is the most critical factor when characterizing any disease (2018). Looking at age as a variable was an important clue in the infected individuals because a note was made for children under five.