An Overview Of Neural Network Algorithms In The COVID-19 And Influenza Pandemics With The Integration Of Immunology – Focusing On Predicting Viral Mutations And Enhancing Vaccines Through AI

Viruses such as influenza and coronaviruses change rapidly, and their frequent mutations create variants that differ in transmissibility, pathogenicity, or their ability to evade the immune system. Recently, the emergence of pandemic diseases –such as COVID-19- has underlined major global public-health challenges and underscored that understanding viral evolution and host immunity is pivotal for effective vaccine development and disease control. This allows time to prepare for more infectious or virulent forms of a virus and helps attenuate its impact. The growing use of artificial intelligence has introduced a more data-driven way of dealing with infectious diseases, especially in prediction and prevention. This review looks at many hybrid artificial intelligence (AI) models proposed for COVID-19 prediction. For instance, a study in China created an enhanced susceptibility model (ISI) to assess the change of infection rate so as to study the transmission rules and development trend since traditional epidemic models initially treated all infected individuals with the same infection rate. Second, a natural language processing (NLP) module and a long-short-term memory (LSTM) network were incorporated in the ISI model to produce a hybrid artificial intelligence model for COVID-19 prediction taking into account the impact of preventative and control measures as well as rising public knowledge of prevention. Bringing AI together with immunology can support the identification of risky viral mutations and improve vaccine effectiveness. By examining clinical, genomic, and epidemiological information, neural-network approaches—one group within artificial-intelligence methods—can be used to anticipate mutation trends and possible transmission patterns. These kinds of predictions provide two advantages: they deepen our understanding of immune responses and make quicker and more efficient vaccine design possible. As AI-based techniques continue to advance and strengthen our insight into immune defense while supporting the creation of vaccines against new viral infections, future preparedness appears increasingly achievable.