# Development of an Ontology-Based Solution to Reduce the Spread of Viruses
## 1 Introduction  
Viruses are one of the most well-known types of microorganism and the most common type of infection that affects humans, as they can be transmitted to humans in various ways: through the air, food, or direct contact with an infected person, animal, or surface [1]. Viruses are famous for their ability to mutate and adapt to be able to live and coexist. Throughout history, humanity has undergone several pandemics caused by viral infections, such as swine flu, bird flu, and finally COVID-19 [2]. During the emergence of viruses, countries strove to find solutions to limit their spread among individuals, whether manually or through applications or programs, and the use of digital health applications emerged as a mechanism to confront the repercussions of many viruses. One of the most important examples is the experience of China and the World Health Organization in the field of digital health applications: AI, big data, 3D printing, and digital medicine as mechanisms to mitigate the spread of the virus and limit its spread [3]. The use of digital health applications at the global level enhances the efficiency of healthcareservices in confronting viruses, and artificial intelligence plays a major role in addressing many problems [4]. In the AI family, deep neural networks and recurrent networks are used to predict activities, such as physical and chemical properties, and consistently improve information processing and decision making by developing powerful algorithms. AI is useful not only in treating infected patients but also in monitoring their health [5]. Big data and AI are naturally equipped to play an important role in the containment of viruses. AI contributes to analyzing data and building risk-based models to help analyze infection-transmission scenarios, monitor disease, provide for early detection, diagnose and follow up infected cases, and achieve comprehensive monitoring of all individuals to ensure their compliance. In addition, an analytical descriptive approach was used, with researchers concluding that AI and big data contribute to the prediction of future strategies by providing information about features of viruses such as their physical and chemical properties [4]. Besides this, the use of ontology and the modeling of functional interactions between genes, combined with a growing interest in systems biology, represent an excellent opportunity to create global interaction models for animal viral infection [6]. When applied alone, anti-virus strategies are not sufficient. They are not sufficient to completely eradicate viruses, as software solutions are necessary and complementary to medical treatments. First, one such example is the \"close contact detector\" launched by China, which helped reduce infection rates by informing individuals that an infected person was close to them [7]. Second, the Singapore-developed \"TraceTogether\" is a tracking program that can access information related to those infected with the virus. The app tracks the location and proximity of infected people to other people, notices individuals who come in contact with a confirmed case, and identifies potential locations for the virus to spread [8]. Third, the \"Sickweather\" app relies on social sharing by allowing people to post information about their area and share information about infection with others [9]. On the contrary, if a person is looking for an answer for the appropriate treatment to alleviate the symptoms of infection, the \"MyChart\" application provides the necessary health instructions, in addition to providing information through which you can assess a person's health [10]. In this work we propose a new solution based on ontology and the rules of intelligent reasoning. Based on this smart solution, the sudden emergence and rapid spread of many dangerous viruses that have appeared in recent years can be prevented. This incited researchers to work on developing solutions to limit the spread of a specific virus and not most viruses that share certain symptoms.