Data-Driven Management of Vaccination and Its Consequences

Vaccination is critical to preventing the spread of diseases. It stimulates the immune system to produce antibodies that fight specific diseases, eradicating and reducing their incidence. However, despite the proven benefits, there is hesitation and skepticism in some areas due to side effects and lack of knowledge. Developing a data collection and processing system to analyze vaccination is critical in today's world. Vaccines are necessary to minimize morbidity and mortality, but success depends on analyzing data on vaccine use and efficacy. This system can identify potential side effects and adverse reactions, ensuring vaccine safety and building public confidence. This research focuses on IT support for analyzing vaccination side effects. The aim of this work is to develop an architecture model of the system to collect and process data on the health status of vaccinated patients. The research methodology consists of analyzing sources on the consequences and side effects of vaccination. On the basis of this knowledge, the key attributes (stakeholders, sources of information, input data, data analysis processes) of the data collection and analysis system were analyzed using an enterprise architecture approach. As a result, a general model of the architecture of the data collection and analysis system was proposed.