Sociodemographic features associated with Hepatitis C Virus (HCV) in pregnant females: A tertiary care centre study from Malwa region of Punjab (North India)

Background

Hepatitis C virus (HCV) infection is high in state of Punjab, however very few studies have been done till date. We all know that pregnant females are a most important section of our community and are usually screened for HCV, HIV, and Hepatitis B at time of presentation. HCV is capable of causing chronic infections and having long-term implications on a person's health. Vertical transmission of HCV can be one of the major route of transmission of this virus to the neonate and there have been various sociodemographic factors like age, literacy, socioeconomic status, occupational status, associated with the disease causation and transmission.

Methods

All pregnant females attending Obstetrics and gynecology department of our institute were included in study. All the sociodemographic characters and socioeconomic records were retrieved and analyzed.

Results

In our study also a lower socioeconomic status, illiteracy have been significantly associated with the HCV-positive group, thus emphasizing the role of education so as to impart education to the masses as regard to mode of transmission and its effects on the disease. Higher age of conceiving is also significant associated with the increased maternal risk.

Conclusions

The more involvement of health care officials and even persons not related to health care set up is required who can educate masses so as to protect the community.

Priority Intervention Targets Identified Using an In-Depth Sampling HIV Molecular Network in a Non-Subtype B Epidemics Area

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.