Scientists using computer modelling to study SARS-CoV-2, the virus that caused the COVID-19 pandemic, have discovered the virus is most ideally adapted to infect human cells - rather than bat or pangolin cells, again raising questions of its origin.

In a paper published in the Nature journal Scientific Reports, Australian scientists describe how they used high-performance computer modelling of the form of the SARS-CoV-2 virus at the beginning of the pandemic to predict its ability to infect humans and a range of 12 domestic and exotic animals.

A smartphone-based eye screening and referral system used in the community has been shown to almost triple the number of people with eye problems attending primary care, as well as increasing appropriate uptake of hospital services, compared to the standard approach. The new findings come from research carried out in Kenya, published in The Lancet Digital Health.

Pioneering technology developed by UCL (University College London) and Africa Health Research Institute (AHRI) researchers could transform the ability to accurately interpret HIV test results, particularly in low- and middle-income countries.

In 1943, two scientists named Max Delbrück and Salvador Luria conducted an experiment to show that bacteria can mutate randomly, independent of external stimulus, such as an antibiotic that threatens a bacterial cells' survival. Today the Luria-Delbrück experiment is widely used in laboratories for a different purpose - scientists use this classic experiment to determine microbial mutation rates.

Artificial intelligence (AI) technology developed by researchers at the University of Waterloo is capable of assessing the severity of COVID-19 cases with a promising degree of accuracy.

A study, which is part of the COVID-Net open-source initiative launched more than a year ago, involved researchers from Waterloo and spin-off start-up company DarwinAI, as well as radiologists at the Stony Brook School of Medicine and the Montefiore Medical Center in New York.

A pilot project using an online survey to gather data on COVID-19 symptoms received more than 87,000 responses from around the world, providing important insight into the spread of disease. Project leaders from Regenstrief Institute, Indiana University and Microsoft believe these questionnaires could be a valuable tool for population health.

UC San Francisco researchers have found a way to double doctors' accuracy in detecting the vast majority of complex fetal heart defects in utero - when interventions could either correct them or greatly improve a child's chance of survival - by combining routine ultrasound imaging with machine-learning computer tools.