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METHOD OF EVOLUTIONARY MODELING OF EPIDEMIC DYNAMICS OF HIV INFECTION

机译:HIV感染流行动力学的进化建模方法

摘要

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: Kcc=NIB/NELISA⋅100, where Kcc – is the coefficient of confirmation, %; NIB – is the number of patients screened with a positive result of an ELISA test confirmed by a positive reference study in IB; NELISA – is the number of screened patients with positive result of ELISA test. For a selected population with a high Kcc, 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
机译:技术领域本发明涉及医学,可以在进化模型的基础上预测该地区HIV感染的发生率。 HIV感染流行病学动力学的进化建模方法包括借助酶免疫分析(ELISA)筛选人群,根据筛选结果,确定最有可能感染HIV的人群。此外,在人群中确定参考研究中ELISA阳性结果的确认系数–免疫印迹(IB),并确定可确认系数的值越高,该人群中HIV感染的风险越高:K cc = N IB / N ELISA ⋅100,其中K cc –是确认系数, %; N IB –是通过IB的阳性参考研究确认的ELISA测试呈阳性结果的筛查的患者人数; N ELISA –是ELISA测试呈阳性结果的筛查患者人数。对于具有最高K cc 的特定人群(表征最可能的HIV感染风险),建立HIV感染流行病学动态的数学模型。为此,使用遗传算法原理生成给定HIV感染区域的个体初始种群,并使用交叉算子,突变进行基于模糊形式系统(FNS)的进化建模过程的程序控制。并在随后的几代中形成繁殖体,显示出在病毒基因组突变过程中HIV的进化。根据解释功能的使用选择新的抗病毒药物组合,以鉴定基因组在其进化的这一阶段中哪些突变导致HIV对药物的耐药性出现。效果:该方法可分离模型的突变周期HIV基因组,预测进化的阶段和流行的时间,提出实用的药物使用建议,并根据基因组进化病毒的繁殖能力和变异性,导致突变,指定一种新的抗病毒药物组合,对病毒进行遗传分析,并评估将药物组合用于对病毒具有耐药性的新病毒株的有效性。1cl,8 dwg

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