Herd immunity is a concept that we all got acquainted with during the COVID-19 pandemic. It means that when a certain percentage of people get an infection in a community, the remaining are protected de facto.
During the initial phase of the pandemic, most countries had been sealing their borders and implementing strict lockdowns to control the spread of the disease, which would, in turn, keep their ICUs from becoming overburdened. However, a few countries like the UK and Sweden had planned to keep only the susceptible people safe while letting the disease spread at a low rate to achieve herd immunity. Experts had suggested that to achieve herd immunity, 70% of the total population in an area should get the disease or get vaccinated against it.
However, soon it was evident that herd immunity might come at a big cost when the cases started to surge in the UK and the government decided to seal the borders. On the other hand, Sweden never sealed their borders and their social distancing guidelines also came later in March. Nevertheless, as other countries sealed their border, Sweden's borders were also, in a way, sealed.
A new study, published in the Journal of Royal Society of Medicine, suggests that Sweden got only 15 percent immunity as opposed to the predicted 40 percent by May 2020. The country had more confirmed COVID-19 cases and fatalities than other Scandinavian countries, which implemented lockdown in March.
Data from Spain
This is not the first time a study or data has shown the impossibility of herd immunity when it comes to COVID-19. An earlier study, conducted in Spain, also had similar results. The study involving over 61,000 people from various areas of the country found that only 5 percent of the people had antibodies against the disease. Immunity was higher in areas that were hit harder by the virus than those where the rate of spread was lower. Presence of antibodies against a pathogen is generally translated to being immune to the said pathogen.
Experts have over and again been pointing out that immunity to coronavirus may not last for long even in those who got the disease. A study conducted in China found that both asymptomatic and symptomatic people lose a big part of neutralising antibodies within 2-3 months of recovering from the infection. Neutralising antibodies are those that fight against and eliminate the virus from the body.
Studies with common cold-causing coronaviruses have also shown that our antibodies against these viruses quickly decline after the infection with an antibody drop of 75 percent within a year.
In fact, scientists have been concerned that if such is the case with SARS-CoV-2, we might have to get a vaccine every six months to sustain immunity against the disease.
Immunological dark matter
Dr Karl Friston, a professor of imaging neuroscience at the University College London, proposed a generative model for studying and predicting the course of COVID-19 pandemic, which is based on American physicist Richard Feynman's theories.
Unlike the SEIR (susceptible, exposed, infected, recovered) model used by epidemiologists, which is based on data collected in real-time, the generative model uses possible causes (based on reasoning and observation) to build a model. When we get proof of the causes or against them, the data is changed accordingly.
Friston suggests that generative models can provide a more accurate picture of what is going to happen. He had predicted that cases would peak in London on April 10 and the actual peak did happen close enough - two days later.
To explain the unknown factors in the model, he used the term "immunological dark matter". Friston believed the reason Germany got fewer cases was either because a lot of its population is not even susceptible to the virus or because they are geographically isolated - as opposed to more testing, which is largely being considered the cause.
The concept has been criticised by a lot of scientists in the world. The generational model does not include public places like clubs or schools in their data but only people at home or hospitals, which is considered a possible flaw in need of fixing.
Whether Friston's model is correct or now, it remains to be seen. However, researchers at Karolinska University have indicated the presence of something called T-cell immunity in people who have recovered from the disease and do not have any antibodies left. The study suggested that we need to look beyond antibody tests to check for the presence of widespread immunity in a population.
According to an article published by the NIH, those who have had encounters with other coronaviruses are less susceptible to COVID-19, indicating some sort of cross-reactivity.
In any case, a lot remains unknown about the disease still, including whether T-cells can provide herd immunity and if some people are naturally immune to the disease.
For more information on herd immunity, read our article on What is herd immunity and can it stop the spread of COVID-19.
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