Open AccessThe transmission of drug-resistant strains of HIV in heterosexual populations based on genetic sequences
Author(s) -
Xin Jin,
Zhen Wang,
Zhiyuan Zhang,
Hui Wu,
Yuhua Ruan,
Chen Zhang,
Ran Kang,
Hui Xing,
Jie Lou
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0259023
Subject(s) - drug resistance , population , markov chain monte carlo , transmission (telecommunications) , demography , human immunodeficiency virus (hiv) , phylogenetic tree , basic reproduction number , virology , biology , genetics , medicine , statistics , bayesian probability , mathematics , gene , computer science , telecommunications , sociology
Background China’s National Free Antiretroviral Treatment Program (NFATP) has substantially reduced morbidity and HIV/AIDS incidence since 2003. However, HIV resistance to antiretroviral drugs (ARVs) has been a major challenge for the current treatment of HIV/AIDS in China. Methods In the current study, we established a nested dynamic model to predict the multi-drug resistance dynamics of HIV among the heterosexual population and evaluated the impact of intervention measures on the transmission of drug resistance. We obtained an effective reproductive numberR e dfrom each sub-model held at different stages of the dynamic model. Meanwhile, we applied Bayesian phylogenetic methods to infer the weighted average effective reproductive numberR e gfrom four HIV subtypes that sampled from 912 HIV-positive patients in China. It is an original and innovative method by fittingR e dtoR e gby Markov Chain Monte Carlo (MCMC) to generate unknown parameters inR e d. Results By analyzing the HIV gene sequences, we inferred that the most recent common ancestor of CRF01AE, CRF07BC, CRF08BC, and CRFBC dated from 1994, 1990, 1993 and 1990, respectively. The weighted average effective reproductive numberR e gdropped from 1.95 in 1994 to 1.73 in 2018. Considering different interventions, we used a macro dynamic model to predict the trend of HIV resistance. The results show that the number of new infections and total drug resistance under the baseline parameter ( S 1 ) are 253,422 and 213,250 in 2025, respectively. Comparing with the numbers under the target treatment rate ( S 2 ), they were 219,717 and 236,890, respectively. However, under the ideal treatment target ( S 3 , the treatment rate reaches 90% and the treatment success rate reaches 90%), the number of new infections shows a declining trend and will decrease to 46,559 by 2025. Compared with S 1 and S 2 , the total number of resistance also decreased to 160,899 in 2025. Conclusion With the promotion of NFATP in China, HIV resistance to ARVs is inevitable. The strategy of increasing the treatment rate would not only ineffectively curb the epidemic, but also deteriorate drug resistance issue. Whereas, a combination of intervention strategies (the treatment rate reaches 90% and the treatment success rate reaches 90%) can greatly reduce both infection and drug resistance rate than applying one strategy alone.