Estimating Asymptomatic and Symptomatic Transmission of the COVID-19 First Few Cases in Selenge Province, Mongolia.

Background: Following the first locally transmitted case in Sukhbaatar soum, Selenge Province, we aimed to investigate the ultimate scale of the epidemic in the scenario of uninterrupted transmission.

Methods: This was a prospective case study following the locally modified WHO FFX cases generic protocol. A rapid response team collected data from November 14 to 29, 2020.

Analyses of publicly available genomes revealed genetic distances indicating they belong to more than one species.

has been observed to be a member of the gut microbiome. Unfortunately, little is known about this organism in spite of being associated with human fatalities; it is important to understand virulence mechanisms and epidemiological prospective to cause disease. In this study, a patient with chronic neurologic symptoms presented to the clinic with subsequent isolation of a strain with phenotypic characteristics suggestive of .

Biological Machine Learning Combined with Population Genomics Reveals Virulence Gene Allelic Variants Cause Disease.

Highly dimensional data generated from bacterial whole-genome sequencing is providing an unprecedented scale of information that requires an appropriate statistical analysis framework to infer biological function from populations of genomes. The application of genome-wide association study (GWAS) methods is an appropriate framework for bacterial population genome analysis that yields a list of candidate genes associated with a phenotype, but it provides an unranked measure of importance. Here, we validated a novel framework to define infection mechanism using the combination of GWAS, machine learning, and bacterial population genomics that ranked allelic variants that accurately identified disease.