Abstract
Molecular network analysis based on the genetic similarity of HIV-1 is increasingly used to guide targeted interventions. Nevertheless, there is a lack of experience regarding molecular network inferences and targeted interventions in combination with epidemiological information in areas with diverse epidemic strains of HIV-1.We collected 2,173 pol sequences covering 84% of the total newly diagnosed HIV-1 infections in Shenyang city, Northeast China, between 2016 and 2018. Molecular networks were constructed using the optimized genetic distance threshold for main subtypes obtained using sensitivity analysis of plausible threshold ranges. The transmission rates (TR) of each large cluster were assessed using Bayesian analyses. Molecular clusters with the characteristics of ≥5 newly diagnosed cases in 2018, high TR, injection drug users (IDUs), and transmitted drug resistance (TDR) were defined as priority clusters. Several HIV-1 subtypes were identified, with a predominance of CRF01_AE (71.0%, 1,542/2,173), followed by CRF07_BC (18.1%, 393/2,173), subtype B (4.5%, 97/2,173), other subtypes (2.6%, 56/2,173), and unique recombinant forms (3.9%, 85/2,173). The overall optimal genetic distance thresholds for CRF01_AE and CRF07_BC were both 0.007 subs/site. For subtype B, it was 0.013 subs/site. 861 (42.4%) sequences of the top three subtypes formed 239 clusters (size: 2-77 sequences), including eight large clusters (size ≥10 sequences). All the eight large clusters had higher TR (median TR = 52.4/100 person-years) than that of the general HIV infections in Shenyang (10.9/100 person-years). A total of ten clusters including 231 individuals were determined as priority clusters for targeted intervention, including eight large clusters (five clusters with≥5 newly diagnosed cases in 2018, one cluster with IDUs, and two clusters with TDR (K103N, Q58E/V179D), one cluster with≥5 newly diagnosed cases in 2018, and one IDUs cluster. In conclusion, a comprehensive analysis combining in-depth sampling HIV-1 molecular networks construction using subtype-specific optimal genetic distance thresholds, and baseline epidemiological information can help to identify the targets of priority intervention in an area epidemic for non-subtype B.
Highlights
A total of 70.8% (1,539/2,173) had senior high school education or above; 66.2% of them were registered in five major districts of Shenyang; 34.6% (751/2,173) were diagnosed during Recent HIV infections (RHI) stages (Table 1)
It has been noted that the sampling depth is a key factor for the high resolution of transmission network inference; low sampling coverage might lead to missing the potential linkages among infections (Little et al, 2014), and even missing some important small molecular clusters with transmission potential
From the view of both the medical care of patients and public health, HIV drug resistance testing should be recommended for all newly diagnosed HIV infections prior to initiation of antiviral therapy (ART). This is because it helps to understand the drug resistance among HIV-infected persons to guide the rational use of antiviral drugs, but it is of great significance for the construction of local HIV molecular networks to understand local HIV transmission dynamics and to guide prevention and interventions of HIV infection
Summary
Molecular epidemiology analysis with viral sequences among HIV-1-infected patients has long been used to explore the origin of HIV and to track the course of HIV spread (Aldous et al, 2012; Wertheim et al, 2014; Wertheim et al, 2017).In recent years, many studies inferred HIV-1 transmission clusters among populations using phylogenetic (Ragonnet-Cronin et al, 2013) or genetic distance-based methods (Kosakovsky Pond et al, 2018). Several studies in China have inferred the HIV molecular networks of CRF01_AE using publicly available sequences around China (Wang et al, 2019), local MSM population (Chen et al, 2018; Yan et al, 2020), and patients suffering from virologic failure (Yuan et al, 2019). These studies usually use a phylogenetic approach or follow the genetic distance threshold of subtype B and the sampling depth remains low. There is a lack of molecular networks combined with epidemiological information to guide the accurate targeting of the intervention population
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
