TY - JOUR
T1 - A Direct Comparison of Two Densely Sampled HIV Epidemics
T2 - The UK and Switzerland
AU - Ragonnet-Cronin, Manon L.
AU - Shilaih, Mohaned
AU - Günthard, Huldrych F.
AU - Hodcroft, Emma B.
AU - Böni, Jürg
AU - Fearnhill, Esther
AU - Dunn, David
AU - Yerly, Sabine
AU - Klimkait, Thomas
AU - Aubert, Vincent
AU - Yang, Wan Lin
AU - Brown, Alison E.
AU - Lycett, Samantha J.
AU - Kouyos, Roger
AU - Brown, Andrew J.Leigh
PY - 2016/9/19
Y1 - 2016/9/19
N2 - Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes.
AB - Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes.
UR - http://www.scopus.com/inward/record.url?scp=84988495414&partnerID=8YFLogxK
U2 - 10.1038/srep32251
DO - 10.1038/srep32251
M3 - Article
C2 - 27642070
AN - SCOPUS:84988495414
SN - 2045-2322
VL - 6
JO - Scientific Reports
JF - Scientific Reports
M1 - 32251
ER -
