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The uncertainty of herd immunity

With a lack of scientific consensus on the subject, experts warn that protection measures against COVID-19 must be maintained

Alexandre Affonso

One question has been repeatedly asked among the scientific community since the COVID-19 pandemic spread around the world: what percentage of a population needs to be immune to the SARS-CoV-2 virus before the transmission rate begins to fall and eventually stops altogether? The question remains unanswered, as with so many others relating to the novel coronavirus. “There is still much that scientists need to discuss, but what we can say with certainty is right now, as a planet, as a global population, we are nowhere close to the levels of immunity required to stop this disease transmitting,” said Irish epidemiologist Mike Ryan, executive director of the World Health Organization’s Health Emergencies Program, at a press conference on August 18. “We need to focus on what we can actually do now to suppress transmission and not live in the hope of herd immunity being our salvation,” he continued.

The term herd immunity was first coined in the early twentieth century and became more widely used in the 1970s with the rising number of vaccines and vaccination campaigns. The concept, which has been the subject of heated debates in academia and beyond, encompasses two key ideas. The first is that the likelihood of infection in a given population decreases as the ratio of immune to susceptible individuals increases. The second, which is less obvious and was discovered using mathematical models, is that even if there are still susceptible people, there is a certain level of immunity—which varies depending on the infectivity of the pathogen and how people interact with each other—that is sufficient for a negligible rate of contagion, leading to eradication of the pathogen. It is therefore not necessary to vaccinate an entire population to eliminate the pathogen. The discovery of this second idea was very important to defining the concept.

The notion is fundamental to planning immunization against diseases such as measles or polio, which have been virtually eradicated after successful campaigns but have seen recent resurgences due to failures in vaccination coverage and growing anti-vaccine movements.

Epidemiologist Paulo Lotufo, a professor of clinical medicine at the School of Medicine (FM) of the University of São Paulo (USP), argues that herd immunity should only be used as a public health target in the context of vaccination, and not as a way to “manage” an epidemic. “From the way it is being discussed, it seems like it has become a [public policy] objective and that is the problem. It becomes a major target, but it is an unethical issue. By saying that the possibility of natural herd immunity exists, we are encouraging the idea of doing nothing and letting people die,” he adds.

At the beginning of the epidemic, UK authorities did a U-turn after experts estimated how many people would die from COVID-19 if no action was taken, in an effort to achieve herd immunity. The suggested figure was 250,000 deaths in the country, which has roughly 68 million inhabitants. Lotufo did the math for Brazil in the early days of the pandemic: taking no action could cost up to 1.5 million lives.

Five months after the WHO declared the pandemic, with SARS-CoV-2 having spread worldwide, there is still no consensus on the threshold needed to achieve herd immunity, and nobody knows if anywhere has already reached that level.

“Every article on this subject is preliminary,” says biochemist Hernan Chaimovich, a retired professor at USP’s Institute of Chemistry and former president of the Brazilian National Council for Scientific and Technological Development (CNPQ). “COVID-19 is a very new disease that requires us to use the very best models, but they can be wrong. Not because they are inaccurate, but because we just don’t know enough about the virus. Depending on what assumptions you make, you can reach pretty much any number.”

The classic formula for calculating the herd immunity threshold uses the basic reproduction number of the infection, known as the R, an indicator of a pathogen’s infectivity in an environment where no one has yet acquired immunity. Every disease has a different R. Measles, for example, is usually given a basic reproduction number of between 12 and 18, meaning that on average, every infected person transmits the disease to 12–18 other people. For COVID-19, it was calculated as between 2.5 and 3. This means that every infected person passes the virus onto an average of two or three individuals. The higher the R, the greater the percentage of immune people needed to establish herd immunity.

Using this standard calculation, the threshold for SARS-CoV-2 herd immunity is 0.60, signifying that at least 60% of the population need to be immune to the pathogen. The numbers suggested by epidemiological studies testing for the presence of antibodies against the novel coronavirus in populations around the world are a long way below this level.

In Spain, one of the countries most seriously affected by the pandemic, for example, a study published in The Lancet in July indicated that only about 5% of the population tested positive. In New York City, the figure was 21%. A paper published in August by a group from Imperial College London stated that tests across England found antibodies in less than 6% in the population. London had the highest rate, at 13%.

In Brazil, which has the second highest number of cases and deaths in the world with more than 120,000 deaths by the end of August, the most comprehensive population study on the novel coronavirus is Epicovid19-BR, led by the Center for Epidemiological Research at the Federal University of Pelotas (UFPEL) in the state of Rio Grande do Sul. In the third and most recent testing phase (at the time of writing), carried out between June 21 and 24, 3.8% of the Brazilian population had SARS-Cov-2 antibodies.

The numbers differ greatly depending on the region of the country and the municipality surveyed. The city with the highest prevalence of antibodies detected so far among the Brazilian population was Sobral, in the state of Ceará, with 26.4%. In the first phase, only 2% had antibodies, in the second, 22.1%. The results surprised the researchers, especially for the North, where local healthcare systems collapsed in several cities. In Breves, Pará, although the prevalence was 25% in the first phase of the Epicovid study, it dropped to 12.2% and 9.4% in the second and third phases respectively. In Manaus, the percentage rose between the first and second phases of the study (from 12.7% to 14.6%), but in the third phase, the number of people who had SARS-CoV-2 antibodies fell to 8%. In the city of São Paulo, the figures were 3.3%, 2.3%, and 1.4% in phases 1, 2, and 3 respectively.

“At the beginning of our study, we expected the number of people with antibodies to increase between each phase, since we assumed that the antibodies would last at least a few months,” says epidemiologist Aluísio Barros, a professor at UFPEL and a member of the Epicovid19-BR team. “But this epidemic has been a great learning experience for everyone and an enormous challenge. Our existing knowledge of immunity in general and our ideas of herd immunity are being put to the test,” he says.

One of their hypotheses for the unexpected findings, with populations actually showing a drop in prevalence, is that the number of antibodies drops relatively quickly after the person has recovered from the disease, to levels not detectable by the test used in the study, which has a sensitivity of 85%. “Whether people who have been infected with the virus are immune or not despite this drop in antibodies, nobody knows,” says Barros. Scientists are also investigating the possibility that some people do not even produce the antibodies, relying only on the protection offered by T lymphocytes, another type of immune cell (see Pesquisa FAPESP issue no. 294).

This would help to explain why in some places, such as Manaus, the epidemic has abated even though the percentage of people with antibodies is well below the 60% or 70% estimated to confer herd immunity. “It seems like several things are happening in parallel, and nothing is proven. Everything is a little speculative,” says the UFPEL scientist.

He believes that herd immunity is playing a part in how these cities are responding. “There was probably a reduction in the number of susceptible people in the total population,” he says. “But things are more complicated than first thought. There is evidence that although the virus is new, not everyone is equally susceptible, for a number of reasons. It could be that cellular immunity is developed from other previous infections, or individual genetics, or something else entirely.”

Two recently published scientific articles emphasized the importance of populations being heterogeneous when modeling and estimating the herd immunity threshold. One of them, published in Science in mid-August by two researchers from the Department of Mathematics at Stockholm University, Sweden, and a third from the School of Mathematical Sciences at the University of Nottingham, UK, claims that herd immunity can be achieved with an infection rate of about 40% of the population. In this scenario, transmission and immunity would be concentrated among the most active members of the population, who are generally younger and less vulnerable.

The second article, which has not yet been peer-reviewed, was posted on the medRxiv preprints repository at the end of July by a group led by Portuguese mathematician Gabriela Gomes, a professor at the University of Strathclyde, Scotland. The model suggested by the group, calculated based on data from four countries (Belgium, Spain, England, and Portugal), indicates an even lower herd immunity threshold of between 10% and 20%.

Brazilian physician Marcelo Urbano Ferreira, a professor at USP’s Institute of Biomedical Sciences and coauthor of the study, explains that varying infection risks in different populations may be due to different levels of exposure and distinctions in susceptibility. “Natural infections act as a selective process, with individuals at higher risk the first to contract the virus. Thus, the average infection risk among the remaining susceptible population is reduced,” he says. The model also takes into account the social distancing and prevention measures taken by different governments and to what extent the population has adhered to them.

“This dynamic phenomenon could explain why infection rates remain below early predictions in several European countries, even with a return to normal activities,” points out Ferreira. The USP doctor is leading a FAPESP-funded project investigating the scale and duration of herd immunity and the number of infections that go unrecorded in communities in the Amazon. The data collected in the field will be used to test the assumptions of mathematical models and refine their forecasts.

Because they appear counterintuitive, these estimated herd immunity thresholds, which are not supported by all experts, often surprise the general public. “These figures should be viewed with reservation,” says physician Claudio Struchiner, a professor at the School of Applied Mathematics of the Getulio Vargas Foundation (FGV) in Rio de Janeiro and a retired researcher from the Oswaldo Cruz Foundation (FIOCRUZ). “The work is important and offers new perspectives, but it still needs to be confirmed.”

According to Struchiner, one potential flaw in the article is that it arrives at the range of 10% to 20% based largely on a presumed reduction in the movement of people and adoption of certain hygiene practices by at least some of the population. “The problem is, if you say ‘we’ve reached the threshold,’ people stop following these safety measures. They relax and stop wearing masks and washing their hands. They start going to shopping malls and restaurants again. By changing our behavior, we may be adding fuel to the fire.” Struchiner does not believe that the herd immunity threshold has been reached in cities like Manaus and Rio de Janeiro. “In my opinion, I don’t think we should abandon safety measures and practices.”

Epidemiologist José Eluf Neto, a professor at USP’s School of Medicine and president of the São Paulo Oncocentro Foundation, also recommends caution. “We are just starting to understand COVID-19. The situation is constantly changing and the assumptions used by mathematical models are being altered as we learn more about the disease,” he explains. “One very serious issue, for example, is that little is known about reinfection. The limitations of mathematical models are well known. But in the midst of this pandemic, with numerous uncertainties surrounding the virus and its natural infection history, many predictions have been published without warning of their limitations. So you have to be cautious.”

Mapping the spread of SARS-CoV-2: Scale of the outbreak, transmission dynamics, clinical outcomes of infection, and duration of antibody response in a small Amazonian town (no. 20/04505-3); Grant Mechanism Regular Research Grant; Principal Investigator Marcelo Urbano Ferreira; Investment R$361,767.81.

Scientific articles
BRITTON, T. et al. A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2. Science. Aug. 14, 2020.
AGUAS, R. et al. Herd immunity thresholds for SARS-CoV-2 estimated from unfolding epidemics (preprint). medRxiv. July 24, 2020.