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According to the DESI 2022 digital economy and society ranking, Poland still ranks in one of the last position. Although, in digitising healthcare Poland has made significant progress over the last five years, some inequities in the usage of eHealth have been recognised. This has become an especially important topic after the COVID-19 pandemic. Suddenly, eHealth innovations were much needed to maintain the accessibility of healthcare. Thus, the aim of this study was to explore determinants of eHealth usage by Poles and identify existing potential barriers. Data was collected from the databases of Statistic Poland and statistical methods were employed in this research. The results showed that five variables such as Internet access, Internet use, Internet skills and average monthly disposable income per capita in PLN, along with the number of practicing physicians per capita were important determinants explaining eHealth usage by the analysed Poles between the age of 16-74. The findings showed to increase the usage of eHealth, health policy makers should ensure that Poles acquire and improve Internet skills. Based on results of the research an extended model of eHealth development in Poland, consisting of a central governmental institution and local facilities coordinating remote electronic services, collecting statistical data and providing educational campaigns, was proposed as well., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Jankowiak, Rój. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The global effort to sequence millions of SARS-CoV-2 genomes has provided an unprecedented view of viral evolution. Characterizing how selection acts on SARS-CoV-2 is critical to developing effective, long-lasting vaccines and other treatments, but the scale and complexity of genomic surveillance data make rigorous analysis challenging. To meet this challenge, we develop Bayesian Viral Allele Selection (BVAS), a principled and scalable probabilistic method for inferring the genetic determinants of differential viral fitness and the relative growth rates of viral lineages, including newly emergent lineages. After demonstrating the accuracy and efficacy of our method through simulation, we apply BVAS to 6.9 million SARS-CoV-2 genomes. We identify numerous mutations that increase fitness, including previously identified mutations in the SARS-CoV-2 Spike and Nucleocapsid proteins, as well as mutations in non-structural proteins whose contribution to fitness is less well characterized. In addition, we extend our baseline model to identify mutations whose fitness exhibits strong dependence on vaccination status as well as pairwise interaction effects, i.e. epistasis. Strikingly, both these analyses point to the pivotal role played by the N501 residue in the Spike protein. Our method, which couples Bayesian variable selection with a diffusion approximation in allele frequency space, lays a foundation for identifying fitness-associated mutations under the assumption that most alleles are neutral., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Jankowiak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Repeated emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with increased fitness underscores the value of rapid detection and characterization of new lineages. We have developed PyR 0 , a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geographic regions, detects lineages increasing in prevalence, and identifies mutations relevant to fitness. Applying PyR 0 to all publicly available SARS-CoV-2 genomes, we identify numerous substitutions that increase fitness, including previously identified spike mutations and many nonspike mutations within the nucleocapsid and nonstructural proteins. PyR 0 forecasts growth of new lineages from their mutational profile, ranks the fitness of lineages as new sequences become available, and prioritizes mutations of biological and public health concern for functional characterization.