How countries are using genomics to help avoid a second coronavirus wave C Watson, Nature News, May 27, 2020

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 Coronavirus

How countries are using genomics to help avoid a second coronavirus wave
C Watson, Nature News, May 27, 2020

Countries that have successfully suppressed infections are entering the next phase of the pandemic — where there's a risk of new cases appearing. Researchers say that genomics will be crucial to quickly track and control these outbreaks. Studies already show that outbreaks tend to be shorter and smaller when genomics is used to help contact tracing.

COVID-19 and Your Smartphone: BLE-based Smart Contact Tracing
PC Ng et al ARXIV, May 28, 2020

From Prediction to Prescription: AI-Based Optimization of Non-Pharmaceutical Interventions for the COVID-19 Pandemic
R Miikulainen et al, ARXIV, May 28, 2020

Early Screening of SARS-CoV-2 by Intelligent Analysis of X-Ray Images
D Gil et al, ARXIV, May 28, 2020

Mobility data can reveal the entire COVID− 19 outbreak course in Japan
J Kurita et al, MEDRXIV, May 28, 2020

Hospitalization and Mortality among Black Patients and White Patients with Covid-19.
Price-Haywood Eboni G et al. The New England journal of medicine 2020 May

In a large cohort in Louisiana, 76.9% of the patients who were hospitalized with Covid-19 and 70.6% of those who died were black, whereas blacks comprise only 31% of the Ochsner Health population. Black race was not associated with higher in-hospital mortality than white race, after adjustment for differences in sociodemographic and characteristics on admission.

A Droplet Digital PCR Assay to Detect SARS-CoV-2 RNA
MJ Romeo et al, MEDRXIV, May 28, 2020

Blood-borne biomarkers may help predict COVID-19 mortality
I de Vlaminck, Sci Trans Med, May 28, 2020

An interpretable mortality prediction model for COVID-19 patients
L Yan et al, Nature Machine Intelligence, May 28, 2020

This study leverages a database of blood samples from 485 infected patients in the region of Wuhan, China, to identify crucial predictive biomarkers of disease mortality. Machine learning tools selected three biomarkers that predict the mortality of individual patients more than 10 days in advance with more than 90% accuracy.