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Background: As sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker., Results: We explore the effect of different bootstrap and genetic distance thresholds on clusters identified in a data set of publicly available HIV sequences, and compare these results to those of a previously published tool for cluster identification. To demonstrate their utility, we then use the Cluster Picker and Cluster Matcher together to investigate how clusters in the data set changed over time. We find that clusters containing sequences from more than one UK location at the first time point (multiple origin) were significantly more likely to grow than those representing only a single location., Conclusions: The Cluster Picker and Cluster Matcher can rapidly process phylogenetic trees containing tens of thousands of sequences. Together these tools will facilitate comparisons of pathogen transmission dynamics between studies and countries.

While HIV-1 subtype B has caused a large epidemic in the Western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV-1 subtype B viruses circulating in Ukraine, characterized the transmission group structure, and estimated key evolutionary and epidemiological parameters. We analyzed 120 HIV-1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002 and 2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and date the most recent common ancestors of identified clades. A phylodynamic birth-death model was used to estimate the effective reproductive number (Re) of these clades. We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV-1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV-1 subtype A into Ukraine. Re was estimated to be 1.42 [95% highest posterior density (HPD) 1.26-1.56] for Clade 1 and 1.69 (95% HPD 1.49-1.84) for Clade 2. Evidently, the subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV-1 subtype B.

While HIV-1 subtype B has caused a large epidemic in the Western world, its transmission in Ukraine remains poorly understood. We assessed the genetic diversity of HIV-1 subtype B viruses circulating in Ukraine, characterized the transmission group structure, and estimated key evolutionary and epidemiological parameters. We analyzed 120 HIV-1 subtype B pol sequences (including 46 newly generated) sampled from patients residing in 11 regions of Ukraine between 2002 and 2017. Phylogenies were estimated using maximum likelihood and Bayesian phylogenetic methods. A Bayesian molecular clock coalescent analysis was used to estimate effective population size dynamics and date the most recent common ancestors of identified clades. A phylodynamic birth–death model was used to estimate the effective reproductive number (Re) of these clades. We identified two phylogenetically distinct predominantly Ukrainian (≥75%) clades of HIV-1 subtype B. We found no significant transmission group structure for either clade, suggesting frequent mixing among transmission groups. The estimated dates of origin of both subtype B clades were around early 1970s, similar to the introduction of HIV-1 subtype A into Ukraine. Re was estimated to be 1.42 [95% highest posterior density (HPD) 1.26–1.56] for Clade 1 and 1.69 (95% HPD 1.49–1.84) for Clade 2. Evidently, the subtype B epidemic in the country is no longer concentrated in specific geographical regions or transmission groups. The study results highlight the necessity for strengthening preventive and monitoring efforts to reduce the further spread of HIV-1 subtype B. [ABSTRACT FROM AUTHOR]

Background: The United Kingdom human immunodeficiency virus (HIV) epidemic was historically dominated by HIV subtype B transmission among men who have sex with men (MSM). Now 50% of diagnoses and prevalent infections are among heterosexual individuals and mainly involve non-B subtypes. Between 2002 and 2010, the prevalence of non-B diagnoses among MSM increased from 5.4% to 17%, and this study focused on the drivers of this change.Methods: Growth between 2007 and 2009 in transmission clusters among 14 000 subtype A1, C, D, and G sequences from the United Kingdom HIV Drug Resistance Database was analysed by risk group.Results: Of 1148 clusters containing at least 2 sequences in 2007, >75% were pairs and >90% were heterosexual. Most clusters (71.4%) did not grow during the study period. Growth was significantly lower for small clusters and higher for clusters of ≥7 sequences, with the highest growth observed for clusters comprising sequences from MSM and people who inject drugs (PWID). Risk group (P< .0001), cluster size (P< .0001), and subtype (P< .01) were predictive of growth in a generalized linear model.Discussion: Despite the increase in non-B subtypes associated with heterosexual transmission, MSM and PWID are at risk for non-B infections. Crossover of subtype C from heterosexuals to MSM has led to the expansion of this subtype within the United Kingdom. [ABSTRACT FROM AUTHOR]