COVID-19

Plant-based ionizers are surprisingly effective at removing aerosols and could play an important role in preventing COVID-19 transmission.

A multifaceted study by the Singapore 2019 Novel Coronavirus Outbreak Research team is filling in some of the gaps left in the urgent quest to understand COVID-19 infection.

Computational models show that there’s much more to COVID-19 transmission than the airborne-or-droplet binary.

A*STAR researchers have developed a point-of-care rapid antibody test kit that can detect antibodies produced in response to SARS-CoV-2 infection in just fifteen minutes.

Multidimensional emotion-sensing algorithms that analyze social media for the public’s concerns during times of crisis could help improve policy and messaging from governments.

By eliminating bottlenecks and automating manual processes, the RESOLUTE test kit and RAVE system co-developed by A*STAR scientists will help give COVID-19 testing a much-needed boost.

A new machine learning technique can predict the dynamics between microbes and therapeutics with unprecedented accuracy.

A*STAR researchers use digital drug simulators to predict the efficacies of repurposed antivirals for treating COVID-19.

Serology testing may be fast and easy to perform, but there are still some limitations that need to be overcome, suggests Laurent Renia.

Antibodies that recognize the SARS-CoV-2 spike protein show potential for diagnosing COVID-19.

The presence of memory T cells in COVID-19-recovered patients hints at their importance in COVID-19 immunity.

Could there be a drug that can both treat and protect against COVID-19? The answer may be found in antibody drugs, a promising therapeutic modality against the coronavirus.