Importations of SARS-CoV-2 lineages decline after nonpharmaceutical interventions in phylogeographic analyses.

During the early stages of the SARS-CoV-2 pandemic, before vaccines were available, nonpharmaceutical interventions (NPIs) such as reducing contacts or antigenic testing were used to control viral spread. Quantifying their success is therefore key for future pandemic preparedness. Using 1.8 million SARS-CoV-2 genomes from systematic surveillance, we study viral lineage importations into Germany for the third pandemic wave from late 2020 to early 2021, using large-scale Bayesian phylogenetic and phylogeographic analysis with a longitudinal assessment of lineage importation dynamics over multiple sampling strategies. All major nationwide NPIs were followed by fewer importations, with the strongest decreases seen for free rapid tests, the strengthening of regulations on mask-wearing in public transport and stores, as well as on internal movements and gatherings. Most SARS-CoV-2 lineages first appeared in the three most populous states with most cases, and spread from there within the country. Importations rose before and peaked shortly after the Christmas holidays. The substantial effects of free rapid tests and obligatory medical/surgical mask-wearing suggests these as key for pandemic preparedness, given their relatively few negative socioeconomic effects. The approach relates environmental factors at the host population level to viral lineage dissemination, facilitating similar analyses of rapidly evolving pathogens in the future.

Recombination-aware phylogenetic analysis sheds light on the evolutionary origin of SARS-CoV-2.

SARS-CoV-2 can infect human cells through the recognition of the human angiotensin-converting enzyme 2 receptor. This affinity is given by six amino acid residues located in the variable loop of the receptor binding domain (RBD) within the Spike protein. Genetic recombination involving bat and pangolin Sarbecoviruses, and natural selection have been proposed as possible explanations for the acquisition of the variable loop and these amino acid residues. In this study we employed Bayesian phylogenetics to jointly reconstruct the phylogeny of the RBD among human, bat and pangolin Sarbecoviruses and detect recombination events affecting this region of the genome. A recombination event involving RaTG13, the closest relative of SARS-CoV-2 that lacks five of the six residues, and an unsampled Sarbecovirus lineage was detected. This result suggests that the variable loop of the RBD didn't have a recombinant origin and the key amino acid residues were likely present in the common ancestor of SARS-CoV-2 and RaTG13, with the latter losing five of them probably as the result of recombination.

Reconstructing relative transmission rates in Bayesian phylodynamics: Two-fold transmission advantage of Omicron in Berlin, Germany during December 2021.

Phylodynamic methods have lately played a key role in understanding the spread of infectious diseases. During the coronavirus disease (COVID-19) pandemic, large scale genomic surveillance has further increased the potential of dynamic inference from viral genomes. With the continual emergence of novel severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, explicitly allowing transmission rate differences between simultaneously circulating variants in phylodynamic inference is crucial. In this study, we present and empirically validate an extension to the BEAST2 package birth-death skyline model (BDSKY), BDSKY[Formula: see text], which introduces a scaling factor for the transmission rate between independent, jointly inferred trees. In an extensive simulation study, we show that BDSKY[Formula: see text] robustly infers the relative transmission rates under different epidemic scenarios. Using publicly available genome data of SARS-CoV-2, we apply BDSKY[Formula: see text] to quantify the transmission advantage of the Omicron over the Delta variant in Berlin, Germany. We find the overall transmission rate of Omicron to be scaled by a factor of two with pronounced variation between the individual clusters of each variant. These results quantify the transmission advantage of Omicron over the previously circulating Delta variant, in a crucial period of pre-established non-pharmaceutical interventions. By inferring variant- as well as cluster-specific transmission rate scaling factors, we show the differences in transmission dynamics for each variant. This highlights the importance of incorporating lineage-specific transmission differences in phylodynamic inference.

Rapid incidence estimation from SARS-CoV-2 genomes reveals decreased case detection in Europe during summer 2020.

By October 2021, 230 million SARS-CoV-2 diagnoses have been reported. Yet, a considerable proportion of cases remains undetected. Here, we propose GInPipe, a method that rapidly reconstructs SARS-CoV-2 incidence profiles solely from publicly available, time-stamped viral genomes. We validate GInPipe against simulated outbreaks and elaborate phylodynamic analyses. Using available sequence data, we reconstruct incidence histories for Denmark, Scotland, Switzerland, and Victoria (Australia) and demonstrate, how to use the method to investigate the effects of changing testing policies on case ascertainment. Specifically, we find that under-reporting was highest during summer 2020 in Europe, coinciding with more liberal testing policies at times of low testing capacities. Due to the increased use of real-time sequencing, it is envisaged that GInPipe can complement established surveillance tools to monitor the SARS-CoV-2 pandemic. In post-pandemic times, when diagnostic efforts are decreasing, GInPipe may facilitate the detection of hidden infection dynamics.

The quantitative impact of fluid vs. solid interfaces on the catalytic performance of pickering emulsions.

Pickering emulsions (PEs), i.e. particle stabilized emulsions, are used as reaction environments in biphasic catalysis for the hydroformylation of 1-dodecene into tridecanal using the catalyst rhodium (Rh)-sulfoxantphos (SX). The present study connects the knowledge about particle-catalyst interactions and PE structure with the reaction results. It quantifies the efficiency of the catalytic performance of the catalyst localized in the voids between the particles (liquid-liquid interface) and the catalyst adsorbed on the particle surface (liquid-solid interface) using a new numerical approach. First, it is ensured that the overall packing density and geometry at the droplet interface and the size of the water droplets of the resulting w/o PEs are predictable. Second, it is shown that approximately all particles assemble at the droplet surface after emulsion preparation and neither the packing parameter nor the droplet size change with the particle surface charge or size when the total particle cross section is kept constant. Third, studies on the influence of the catalyst on the emulsion structure reveal that irrespective of the particle charge the surface active and negatively charged catalyst Rh-SX reduces the PE droplet size significantly and decreases the particle packing parameter from s = 0.91 (hexagonal packing in 2D) to s = 0.69 (shattered structure). In this latter case, large voids of the free w/o interface form and become covered with the catalyst. With a deep knowledge about the PE structure the reaction efficiencies of the liquid-liquid vs. the solid-liquid interface are quantified. By excluding any other influence factors, it is shown that the activity of the catalyst is the same at the fluid and solid interface and the performance of the reaction is explained by the geometry of the system. After the reaction, the catalyst retention via membrane filtration is shown to be successfully achieved without damaging the emulsions. This enables the continuous recovery of the catalyst, i.e. the most expensive compound in PE-based catalytic reactions, being a crucial criterion for industrial applications.