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O018 Community Viral Load: A new population-based biomarker of HIV disease burden in Scotland
  1. Muhammad Ismail1,
  2. Daniela Brawley2,
  3. Steve Baguley2
  1. 1University of Aberdeen School of’Medicine and Dentistry, Aberdeen, UK
  2. 2NHS Grampian Sexual Health Services, Grampian, UK

Abstract

Background/introduction “Community viral load” (CVL) refers to an aggregate biological measure of viral load (VL) for a particular geographic location. Studies have suggested that CVL may be used as a population-based biomarker for HIV transmission, and that its reduction is associated with a decrease in HIV incidence. Currently, there is no published data on CVL in Scotland.

Aim(s)/objectives This study aims to measure CVL and to estimate the HIV transmission potential of communities in Scotland.

Methods HIV/AIDS surveillance data on patient demographics, first VL in 2014, and region of residence were analysed. Mean CVL was measured as the arithmetic average and total CVL the arithmetic sum of all VL in our data set respectively. Statistical analyses were performed using SPSS 23 at 95% significance level. Shapiro-Wilk test was performed for normality. Chi-square analysis and Kruskal-Wallis test were performed for differences in variables. Spearman’s correlation was performed for correlations between CVL and HIV incidence.

Results 4126 non-duplicate cases were analysed. Mean CVL was highest in Central South-West (CSW) (μ = 20,469, 95% CI = 8146–32,933), followed by Central South-East (CSE) and North respectively. There was a significant difference in mean rank CVL between North-CSW and North-CSE. There was a positive correlation between mean CVL and HIV quarterly incidence for CSW (Spearman’s rho = 0.062, p = 0.01) and CSE (Spearman’s rho = 0.032, p = 0.196), whereas a negative correlation was seen in North (Spearman’s rho = −0.047, p = 0.202).

Discussion/conclusion This study highlights the relationship between CVL and HIV quarterly incidence in Scotland in 2014. Further work using annual incidence data is needed to verify these conclusions and to determine factors influencing these results.

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