Modification of Epidemiological Model for Predicting the Development of a Socially Significant Infection (by the Example of Chronic Viral Hepatitis C)

Purpose of the study: to develop, evaluate the effectiveness and applicability of an epidemiological model for the development of chronic viral hepatitis C, with the ability to predict the number of people who need to be tested for the presence of the virus.Materials and methods. In our study, we used official data for the Republic of Bashkortostan on the spread of chronic viral hepatitis C (annual dynamics of cases) in the period from 2005 to 2020, which were provided at our request by the Republican Clinical Infectious Diseases Hospital. Demographic indicators for births and deaths were taken from the annual statistical report of Bashkortostanstat. The study considered 2 mathematical models: 1) Model SIR considers three groups: susceptible (those who have not yet become infected), infected and dropouts (those who have recovered or died). 2) The STIRD model is the SIR model, improved by the author, which takes into account five population groups: susceptible (those who have not yet become infected), tested (those who have been in contact with the infected people and require a test to clarify the diagnosis), infected, dropouts (those who recovered) and deceased.Results: from 2015 to 2017, the model provided representative data on the forecast of the infected people, the error was about 1.5-4%, but after this period, starting from 2018, the error rate became critical and the model lost its representativeness. To explain this phenomenon, there are 2 reasons: the first is the easy availability of drugs for the treatment of chronic hepatitis C, the second is the need to use Markov models in the model, since the calculation does not take into account the dynamics of changes in the coefficients of the model. As a result of the coronavirus pandemic in 2020, the error was more than 166%, this is due to a decrease in contacts between people and, as a result, a sharp decrease in the incidence of chronic hepatitis C.Conclusion. The complete epidemiological STIRD model proposed by the author (taking into account the demographic change in the structure of the population) has shown itself well in medium-term forecasting up to three years. A significant advantage of this model specification compared to other epidemiological models is the ability to predict the number of diagnostic laboratory tests needed to detect a virus in humans. This is important, since the diagnosis and treatment of chronic hepatitis C is covered from compulsory medical insurance and regional budgets. Epidemiological modeling opens up great opportunities for developing scenarios for combating viral hepatitis C, especially with its chronic form, because, according to WHO, each country has the opportunity to completely get rid of this socially significant infection by 2030.