New study suggests Covid-19 immunity may be lost within months

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Data analysts at work during the pandemic. (PHOTO: South_Agency/Getty Images)
Data analysts at work during the pandemic. (PHOTO: South_Agency/Getty Images)
South_Agency

A team of scientists at King’s College London conducted the research which suggests immunity may no longer be viable within a couple of months after contracting Covid-19.

Individuals who’ve recovered from coronavirus may lose their immunity to the disease within months after becoming infected.

The research is the first study of its kind in which the immune response of more than 90 patients and healthcare workers at Guy’s and St Thomas’ NHS Foundation Trust were analysed, The Guardian reports.

Researchers found that the level of antibodies that are able to destroy the virus peak three weeks after the onset of symptoms, after which the numbers decline.

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The study results indicate that about 60% of people had a potent antibody response at the height of their battle with Covid-19, but only 17% of them retained the same potency after three months.

“People are producing a reasonable antibody response to the virus, but it’s waning over a short period of time and depending on how high your peak is, that determines how long the antibodies are staying around,” said the study’s lead author, Dr Katie Doores.

The study has major implications for the possible development of a vaccine and in the pursuit of “herd immunity” in a community over time, according to Doores.

Although the immune system has multiple ways to fight coronavirus infection, if antibodies in the bloodstream are the main defences, people could become reinfected in seasonal waves.

This has been strongly suggested by the study, and it has implications for vaccines.

If people become reinfected seasonally then vaccines may not protect them for long.

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It’s also been suggested by Professor Paul Davies, a leading scientist based in the United States, that we may have to live with Covid-19 forever.

Davies is a theoretical physicist not an epidemiologist, who’s currently the director of the Beyond Centre for Fundamental Concepts in Science at Arizona State University. He’s launched new research to stem the spread of Covid-19 by applying network theory – the study of graphs – to the pandemic, The Sun reports. This new project builds on the centre’s work applying network theory to issues such as cancer gene regulation and the origin of life.

“The best compromise, which I think we will end up with, is we take measures but [Covid-19] doesn’t go away totally, and you put out spot fires when they occur,” he said.

“When it gets to the point where the death toll is no worse than from other things we put up with, most obviously flu, then people will start to think it’s just part of the ride.”

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“At the moment the way people deal with this virus is, you spot it somewhere, you try to zap it, you isolate people," he explained.

"It’s putting out spot fires. I wondered if you took a more global or top-down view whether there might be a more clever strategy.

Davies explained what his research team is doing in terms of studying the virus. They’re working with a Californian software company that analyses glitches in computer networks to make them secure. The researchers are using this technology to find vulnerabilities in the pandemic network, such as transport and flight hubs.

“My dream is this top-down idea. You would redesign the [pandemic] network or re-engineer its architecture to make it easier to control and not just be opportunistic (in attacking outbreaks).”

“We should try to outsmart the pandemic and that means coordinated action, really, on a planetary scale, at the very least on a national scale. But I see no evidence of anybody doing that,” he said.

The academic is adamant that Covid-19 is good practice for any future pandemics.

“We have learnt a lot of lessons. It’s such a weird disease. It’s very heterogeneous, it doesn’t look like one disease. It’s like half a dozen diseases,” he said.

Source: The Guardian, The Sun, The Australian

 

 

 

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