Mapping the early dispersal patterns of SARS-CoV-2 omicron BA.4 and BA.5 subvariants in the absence of travel restrictions and testing at the borders in Europe

The circulation of SARS-CoV-2 omicron BA.4 and BA.5 subvariants with enhanced transmissibility and capacity for immune evasion resulted in a recent pandemic wave that began in April–May of 2022. We performed a statistical phylogeographic study that aimed to define the cross-border transmission patterns of BA.4 and BA.5 at the earliest stages of virus dispersal. Our sample included all BA.4 and BA.5 sequences that were publicly available in the GISAID database through mid-May 2022. Viral dispersal patterns were inferred using maximum likelihood phylogenetic trees with bootstrap support. We identified South Africa as the major source of both BA.4 and BA.5 that migrated to other continents. By contrast, we detected no significant export of these subvariants from Europe. Belgium was identified as a major hub for BA.4 transmission within Europe, while Portugal and Israel were identified as major sources of BA.5. Western and Northern European countries exhibited the highest rates of cross-border transmission, as did several popular tourist destinations in Southern and Central/Western Europe. Our study provides a detailed map of the early dispersal patterns of two highly transmissible SARS-CoV-2 omicron subvariants at a time when there was an overall relaxation of public health measures in Europe

Phylogenetic Analysis of SARS-CoV-2 Data Is Difficult

Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising a quality-filtered subset of 8,736 out of all 16,453 virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be credible. Finally, an automatic classification of the current sequences into subclasses using the mPTP tool for molecular species delimitation is also, as might be expected, not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution

Bayesian mixture models for phylogenetic source attribution from consensus sequences and time since infection estimates

In stopping the spread of infectious diseases, pathogen genomic data can be used to reconstruct transmission events and characterize population-level sources of infection. Most approaches for identifying transmission pairs do not account for the time that passed since divergence of pathogen variants in individuals, which is problematic in viruses with high within-host evolutionary rates. This is prompting us to consider possible transmission pairs in terms of phylogenetic data and additional estimates of time since infection derived from clinical biomarkers. We develop Bayesian mixture models with an evolutionary clock as signal component and additional mixed effects or covariate random functions describing the mixing weights to classify potential pairs into likely and unlikely transmission pairs. We demonstrate that although sources cannot be identified at the individual level with certainty, even with the additional data on time elapsed, inferences into the population-level sources of transmission are possible, and more accurate than using only phylogenetic data without time since infection estimates. We apply the approach to estimate age-specific sources of HIV infection in Amsterdam MSM transmission networks between 2010-2021. This study demonstrates that infection time estimates provide informative data to characterize transmission sources, and shows how phylogenetic source attribution can then be done with multi-dimensional mixture models

Real-world effectiveness of molnupiravir and nirmatrelvir/ritonavir as treatments for COVID-19 in patients at high risk

Background Using a retrospective cohort study design, we aimed to evaluate the effectiveness of molnupiravir and nirmatrelvir/ritonavir in patients with SARS-CoV-2 who were highly vulnerable. Methods The impact of each drug was determined via comparisons with age-matched control groups of patients positive for SARS-CoV-2 who did not receive oral antiviral therapy. Results Administration of molnupiravir significantly reduced the risk of hospitalization (odds ratio [OR], 0.40; P < .001) and death (OR, 0.31; P < .001) among these patients based on data adjusted for age, previous SARS-CoV-2 infection, vaccination status, and time elapsed since the most recent vaccination. The reductions in risk were most profound among elderly patients (≥75 years old) and among those with high levels of drug adherence. Administration of nirmatrelvir/ritonavir also resulted in significant reductions in the risk of hospitalization (OR, 0.31; P < .001) and death (OR, 0.28; P < .001). Similar to molnupiravir, the impact of nirmatrelvir/ritonavir was more substantial among elderly patients and in those with high levels of drug adherence. Conclusions Collectively, these real-world findings suggest that although the risks of hospitalization and death due to COVID-19 have been reduced, antivirals can provide additional benefits to members of highly vulnerable patient populations

A Nationwide Study about the Dispersal Patterns of the Predominant HIV-1 Subtypes A1 and B in Greece: Inference of the Molecular Transmission Clusters

Our aim was to investigate the dispersal patterns and parameters associated with local molecular transmission clusters (MTCs) of subtypes A1 and B in Greece (predominant HIV-1 subtypes). The analysis focused on 1751 (28.4%) and 2575 (41.8%) sequences of subtype A1 and B, respectively. Identification of MTCs was based on phylogenetic analysis. The analyses identified 38 MTCs including 2&ndash;1518 subtype A1 sequences and 168 MTCs in the range of 2&ndash;218 subtype B sequences. The proportion of sequences within MTCs was 93.8% (1642/1751) and 77.0% (1982/2575) for subtype A1 and B, respectively. Transmissions within MTCs for subtype A1 were associated with risk group (Men having Sex with Men vs. heterosexuals, OR = 5.34, p &lt; 0.001) and Greek origin (Greek vs. non-Greek origin, OR = 6.05, p &lt; 0.001) and for subtype B, they were associated with Greek origin (Greek vs. non-Greek origin, OR = 1.57, p = 0.019), younger age (OR = 0.96, p &lt; 0.001), and more recent sampling (time period: 2011&ndash;2015 vs. 1999&ndash;2005, OR = 3.83, p &lt; 0.001). Our findings about the patterns of across and within country dispersal as well as the parameters associated with transmission within MTCs provide a framework for the application of the study of molecular clusters for HIV prevention

Global and regional dispersal patterns of hepatitis B virus genotype E from and in Africa: A full-genome molecular analysis.

Description of the spatial characteristics of viral dispersal is important in understanding the history of infections. Nine hepatitis B virus (HBV) genotypes (A-I), and a putative 10th genotype (J), with distinct geographical distribution, are recognized. In sub-Saharan Africa (sub)-genotypes A1, D3 and E circulate, with E predominating in western Africa (WA), where HBV is hyperendemic. The low genetic diversity of genotype E (HBV/E) suggests its recent emergence. Our aim was to study the dispersal of HBV/E using full-length, non-redundant and non-recombinant sequences available in public databases. HBV/E was confirmed, and the phylogeny reconstruction performed using maximum likelihood (ML) with bootstrapping. Phylogeographic analysis was conducted by reconstruction of ancestral states using the criterion of parsimony on the estimated ML phylogeny. 46.5% of HBV/E sequences were found within monophyletic clusters. Country-wise analysis revealed the existence of 50 regional clusters. Sequences from WA were located close to the root of the tree, indicating this region as the most probable origin of the HBV/E epidemic and expanded to other geographical regions, within and outside of Africa. A localized dispersal was observed with sequences from Nigeria and Guinea as compared to other WA countries. Based on the sequences available in the databases, the phylogenetic results suggest that European strains originated primarily from WA whereas a majority of American strains originated in Western Central Africa. The differences in regional dispersal patterns of HBV/E suggest limited cross-border transmissions because of restricted population movements

Mapping the Early Dispersal Patterns of SARS-CoV-2 Omicron BA.4 and BA.5 Subvariants in the Absence of Travel Restrictions and Testing at the Borders in Europe

The circulation of SARS-CoV-2 omicron BA.4 and BA.5 subvariants with enhanced transmissibility and capacity for immune evasion resulted in a recent pandemic wave that began in April–May of 2022. We performed a statistical phylogeographic study that aimed to define the cross-border transmission patterns of BA.4 and BA.5 at the earliest stages of virus dispersal. Our sample included all BA.4 and BA.5 sequences that were publicly available in the GISAID database through mid-May 2022. Viral dispersal patterns were inferred using maximum likelihood phylogenetic trees with bootstrap support. We identified South Africa as the major source of both BA.4 and BA.5 that migrated to other continents. By contrast, we detected no significant export of these subvariants from Europe. Belgium was identified as a major hub for BA.4 transmission within Europe, while Portugal and Israel were identified as major sources of BA.5. Western and Northern European countries exhibited the highest rates of cross-border transmission, as did several popular tourist destinations in Southern and Central/Western Europe. Our study provides a detailed map of the early dispersal patterns of two highly transmissible SARS-CoV-2 omicron subvariants at a time when there was an overall relaxation of public health measures in Europe