Quantitative chest computed tomography combined with plasma cytokines predict outcomes in COVID-19 patients
American scientists have used machine learning algorithms together with k-fold cross-validation to better predict the occurrence of severe COVID-19.
Another study published in the prestigious Science magazine confirms that the epicenter of the COVID-19 outbreaks was the Huanan Seafood Market in Wuhan, China. Among the tested over 40,000 blood samples collected from patients at Wuhan hospitals between October and December 2019, no positive test result for SARS-CoV-2 was reported.
Multiomics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity
The clinical manifestation of COVID-19 is extremely diverse. Therefore, Swedish scientists using system-wide network-based system biology analysis characterized the main factors aggravating the severity of the disease on an individual and group level.
Using multiagent modeling to forecast the spatiotemporal development of the COVID‑19 pandemic in Poland
An interdisciplinary team of Polish scientists has presented a multi-antigen model simulating the development of the COVID-19 pandemic at the regional level. The developed model uses a number of parameters including the spatial and demographic differentiation of Poland
It is estimated that about 30% of all convalescents suffer from the so-called long-COVID which is chronic and recurring health problems including fatigue, shortness of breath, pulmonary fibrosis, neuropathic symptoms
In November 2021, a new SARS-CoV-2 variant, Omicron, was described for the first time and has become the globally dominant variant. Recent sequencing has revealed two new sub-variants of Omicron BA.4 and BA.5