HIPSTR: highest independent posterior subtree reconstruction in TreeAnnotator X.

In Bayesian phylogenetic and phylodynamic studies it is common to summarise the posterior distribution of trees with a time-calibrated consensus phylogeny. While the maximum clade credibility (MCC) tree is often used for this purpose, we here show that a novel consensus tree method - the highest independent posterior subtree reconstruction, or HIPSTR - contains consistently higher supported clades over MCC. We also provide faster computational routines for estimating both consensus trees in an updated version of TreeAnnotator X, an open-source software program that summarizes the information from a sample of trees and returns many helpful statistics such as individual clade credibilities contained in the consensus tree.

Genomic epidemiology of early SARS-CoV-2 transmission dynamics in Bangladesh.

Background: Genomic epidemiology has helped reconstruct the global and regional movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is still a lack of understanding of SARS-CoV-2 spread in some of the world's least developed countries (LDCs).

Methods: To begin to address this disparity, we studied the transmission dynamics of the virus in Bangladesh during the country's first COVID-19 wave by analysing case reports and whole-genome sequences from all eight divisions of the country.

A phylogenetics and variant calling pipeline to support SARS-CoV-2 genomic epidemiology in the UK.

In response to the escalating SARS-CoV-2 pandemic, in March 2020 the COVID-19 Genomics UK (COG-UK) consortium was established to enable national-scale genomic surveillance in the UK. By the end of 2020, 49% of all SARS-CoV-2 genome sequences globally had been generated as part of the COG-UK programme, and to date, this system has generated >3 million SARS-CoV-2 genomes. Rapidly and reliably analysing this unprecedented number of genomes was an enormous challenge.

Viral SARS-CoV-2 Rebound Rates in Linked Commercial Pharmacy-Based Testing and Health Care Claims.

Background: Viral SARS-CoV-2 rebound (viral RNA rebound) is challenging to characterize in large cohorts due to the logistics of collecting frequent and regular diagnostic test results. Pharmacy-based testing data provide an opportunity to study the phenomenon in a large population, also enabling subgroup analyses. The current real-world evidence approach complements approaches focused on smaller, prospective study designs.