Abstract:

The work is devoted to the theoretical analysis of existing models of population development in order to determine the model of the dynamics of disease development. The analysis of influenza and SARS diseases in two villages of the Kherson region was carried out. Conditions for reducing diseases and r educing economic costs have been obtained. To reduce the number of diseases, it is necessary to reduce the factor that causes the disease, then it is necessary that β, while the economic costs may increase, so to minimize the economic costs, it is necessary to achieve the minimum of the function that describes them. Statistical analysis and theoretical modeling of the development of noncommunicable diseases. Conduct of anti-epidemic measures requires economic and social approaches in their optimization and assessment of the consequences of their conduct. Indeed, it is possible to stop the educational process (to dissolve students ´and students´ homes), even production, and to introduce a general quarantine, for example, but then there is a question of the economic justification of such measures. Victory over epidemics has always been one of the first tasks of medical science. In the modern world, a number of medicines used to treat many diseases are constantly being created and used. Methods of prevention are also important, but this is not enough to successfully fight epidemics. In order for physicians to better cope with epidemics, mathematical models were created to predict the development of the disease. Mathematical models play a huge role in medical science, proclaiming epidemics, and are very important now. In our time, many models of biological systems and processes have been developed, due to which models of the concept of "norm" and "pathology", as well as state intervals were established. This allowed not only to find ways to treat many diseases, but also to identify methods for their prevention. Medicine is increasingly becoming an exact science, which is characterized by the use of physical representations and methods with a mathematical description of events.

Keywords: disease, statistics, model