METHOD OF EVOLUTIONARY MODELING OF EPIDEMIC DYNAMICS OF HIV INFECTION Russian patent published in 2019 - IPC G09B23/00 G01N33/53 G06N3/00 

FIELD: medicine.

SUBSTANCE: invention relates to medicine, can be used to predict the incidence of HIV infection in the region on the basis of evolutionary modeling. Method of evolutionary modeling of the epidemiological dynamics of HIV infection includes screening the population with the help of an enzyme immunoassay (ELISA), according to the results of the screening, the population with the most likely risk of contracting HIV is identified. Additionally, determine in the population the coefficient of confirmation of the positive ELISA result in the reference studies – the immune blot (IB) and establish that the higher the value of the coefficient of confirmability, the higher the risk of HIV infection in this population group: K_cc=N_IB/N_ELISA⋅100, where K_cc – is the coefficient of confirmation, %; N_IB – is the number of patients screened with a positive result of an ELISA test confirmed by a positive reference study in IB; N_ELISA – is the number of screened patients with positive result of ELISA test. For a selected population with a high K_cc, characterizing the most likely risk of HIV infection, build a mathematical model of the epidemiological dynamics of HIV infection. To do this, the initial population of individuals for a given area of HIV infection is generated using the principles of a genetic algorithm and program control of the evolutionary modeling process based on a fuzzy formal system (FNS) is carried out using crossover operators, mutations and reproductions to form the structure of the population in the following generations with a display of the evolution of HIV in the process of mutations in the genome of the virus. New combination of antiviral drugs is selected based on the use of the interpretation function to identify which mutations in the genome at this stage of its evolution lead to the emergence of HIV resistance to drugs.

EFFECT: method allows to isolate mutation cycles of the model HIV genome, predict the stages of evolution and the time of the epidemic, develop practical recommendations for the use of drugs and, depending on the reproductive capacity and variability of the genome evolution virus, leading to a mutation, appoint a new antiviral combination of drugs, carry out a genetic analysis of the virus and evaluate the effectiveness of using a combination of drugs for new strains of the virus that have resistance to drugs.

1 cl, 8 dwg