COVID-19: Top science stories of the week

1. Vaccines: new Phase One trial results and approval in China

It’s been a big week for COVID-19 vaccines, with hopeful early results from yet another Phase One trial, and Beijing approving China’s front-runner vaccine for use in the Chinese military.

The experimental vaccine being developed by Pfizer and BioNTech was shown this week to cause an immune response in 36 healthy volunteers, according to interim results published online.

The study randomly assigned 45 people to receive either the vaccine or a placebo. Individuals who received the vaccine showed levels of antibodies 1.8 to 2.8 times the level of those found in COVID-19 patients who recovered.

Higher antibody levels are a useful proxy for immunity to COVID-19, but it isn’t yet known whether they guarantee immunity. Therefore, although promising, these early results (which have not yet been peer-reviewed) need to be taken with a pinch of salt. Further studies with large groups of people will be required to determine if this vaccine actually provides protection.

Meanwhile in China, the government has approved the use of an experimental COVID-19 vaccine for the country's military. The vaccine, known as Ad5-nCoV, was jointly developed by the Beijing Institute of Biotechnology, which is part of the Chinese government's Academy of Military Medical Sciences, and the vaccine company CanSino Biologics.

Neither the Chinese government nor CanSino has said how broadly the vaccine will be distributed, which parts of the military would be selected or whether it will be mandatory or voluntary for military personnel.

According to a statement from CanSino, Phase One and Two trials of their vaccine have been completed. But experts will want to examine the data to assess how well the vaccine performed in these trials and see whether the side effects were as common as in the early results published in The Lancet.

2. People testing negative for coronavirus antibodies may still have immunity

For every person testing positive for coronavirus antibodies, two were found to have specific T-cells which identify and destroy infected cells, according to new research in Sweden. This was seen even in people who had mild or no symptoms.

While antibodies bind to and neutralise the virus before it enters the body’s cells, T-cells target already-infected cells and completely destroy them, stopping them from spreading to healthy cells.

The T-cell memory responses in this study were akin to those observed in the context of successful vaccines, suggesting that exposure to, or infection by, the virus may prevent re-infection, even in people who don’t have antibodies. However, more analysis is needed to understand whether these T-cells completely block the virus, or whether they might protect an individual from getting sick but not from carrying the virus and transmitting it to others.

The findings could suggest that antibody tests alone might not be sufficient to determine whether a person is immune or not. It is also possible that national statistics of immunity based on antibody test results might not reveal the full extent of population immunity.

3. Test frequency matters more than test sensitivity for stopping outbreaks

New modelling research (not yet published in a journal) suggests that frequency and turnaround of COVID-19 testing is more critical to preventing large viral outbreaks than the sensitivity of the tests, particularly in large communities at risk of mass-spreading.

Tests that rely on a technique called "quantitative polymerase chain reaction" (qPCR) can detect small traces of the genetic material of the new coronavirus but are expensive and slow to return results.

Researchers in Boston modelled the effect of widespread testing on viral spread in a large group of people and found that weekly surveillance testing, paired with case isolation, would limit an outbreak even if the testing method was less sensitive than qPCR. By contrast, surveillance testing done every 14 days would let the total number of infections climb almost as high as if there were no testing at all.