Some have proposed that identifying antibodies to SARS-CoV-2 (coronavirus antibodies) against coronavirus become the basis of “security passports” that allow people to return to work or school, or to travel. Nevertheless, facts show that it is early to take that step.
For example, experts have yet to decide whether the antibodies, or perhaps a start level of antibodies, defend a person from being re-infected. For the another instance, there are many immunoglobulin tests, none with the levels of specificity needed to declare someone immune.
In short, we are far from being at a place where a certain antibody test guarantees that a person cannot perceive COVID-19 nor open it to someone else, the authors say. And the posts are too high to risk getting it wrong.
The Valuable Data
Notwithstanding, these same practices are good enough to monitor the spread of COVID-19 in groups. “There is no obligation to throw out the baby with the bathwater,” says Leung.
“We can use serological testing at the state level to get valuable data about device and the result of interventions, and we don’t need a comprehensive serology test to do it.”
Understanding courses such as where faults are happening and which regions are quiet, and the aspects of who is getting ill and who is saved, can provide data to guide policy.
Is a special county ready to ease constraints? Are seniors safe to go back to school? Do certain populations need extra protection?
One reason many of today’s experiments can work for public-level choices is that they do not just give black and white keys. Alternatively, their parameters can be modified to fit many needs.
A Specific Trial
One of these characteristics is specificity-how well a analysis detects immunoglobulins to SARS-CoV-2 and not to immunoglobulins against other coronaviruses. The other is sensitivity – the minimum level of coronavirus antibodies someone must have in their blood in order to test positive.
In total, there is a tradeoff between the two. Adjusting a test to prioritize sensitivity makes it not as specific, and making a test more specific makes it less sensitive. But it’s ok to sacrifice one for the other in order to answer certain questions, the editorial says.
Take the situation in some rural countryside where relatively few people have had COVID-19 per capita. In that setting, a test with high responsiveness and low specificity would not be optimal.
These things could occur in the same number of people questioning positive who never had COVID-19 as the number of people who really are real. In this section, the results would be essentially absurd.
Yet, the same test can be done if it is tuned for that situation. This can be done by selecting a higher cutoff and assuming that a test does not count as assertive unless it has a stronger signal.
Doing so lowers the wrong positive rate by increasing specificity. In this situation, positive examinations are more likely to be truly assertive and that data can be safely used to monitor that group.
On the other hand, an urban setting where more special dimensions of the population have been affected would do better with a test prioritized for higher sensitivity. That would give a better snapshot of the spread of COVID-19 by capturing a more prominent segment of the community.