A study published on July 24 on the medRxiv platform, still without peer review, estimates that the collective immunity threshold to the new coronavirus (SARS-CoV-2), also known as herd immunity, can be achieved in a given region if somewhere between 10% and 20% of the population is infected.
If the projection is confirmed in practice, the developments tend to be positive in two aspects. First, because it means that there is little risk of a second overwhelming wave of the pandemic in countries that have adopted measures to contain the spread of COVID-19 and today they are already registering a drop in the number of new cases.
Secondly, because it indicates that it is possible for a city, state or country to reach the threshold of collective immunity even though it has adopted measures of social distance that help to prevent the collapse of the health system and to minimize the number of deaths.
“Our model shows that there is no need to sacrifice the population by letting it circulate freely for collective immunity to develop. On the other hand, it suggests that there is also no need to keep people at home for many, many months, until a vaccine is approved ”, says Portuguese biomathematician Gabriela Gomes to Agência FAPESP, currently at the University of Strathclyde, in the United Kingdom.
The mathematical model to which the researcher refers was developed in collaboration with scientists from Brazil, Portugal and the United Kingdom. Among the co-authors of the article are Marcelo Urbano Ferreira, professor at the Institute of Biomedical Sciences at the University of São Paulo (ICB-USP) and his doctoral student Rodrigo Corder.
“We have been working together with Gabriela Gomes for some years using this approach to describe the dynamics of malaria transmission in the Brazilian Amazon, with support from FAPESP (São Paulo State Research Support Foundation).
She had also done some studies on tuberculosis. The model we use is different from the others, as it takes into account the fact that the risk of contracting a certain disease varies from person to person, ”says Ferreira.
As Gomes explains, the factors that influence an individual’s risk of contracting COVID-19, for example, can be divided into two categories. In one of them are the biological ones, such as genetics, nutrition and immunity. The other includes behavioral factors, which determine the level of contact with other people that each of us has in our daily lives.
“This has to do with the type of occupation, the place of residence, the means of transportation and even the personality profile. A person who prefers to stay at home reading a book has a lower risk of being exposed to the virus than someone who goes out very often and has relationships with many people ”, says the researcher.
According to Gomes, the models that estimated the threshold of immunity to SARS-CoV-2 varying between 50% and 70% consider that the risk of infection is the same for all individuals.
“We have seen that, in the case of COVID-19, the greater the degree of heterogeneity in the population, the lower the threshold for group immunity becomes,” says Gomes.
Measuring in each individual of a population each of the factors that influence the susceptibility to contract the new coronavirus and then calculating what would be the so-called “coefficient of variation” – a key parameter of the model described in the article – would be unviable. For this reason, the researchers chose to take the path backwards.
“We know that if we change the variation coefficient, there is an impact on the epidemic curve projected by the model. We then decided to do the reverse: we used the epidemic curve of countries where the epidemic was already at an advanced stage to calculate the coefficient of variation ”, explains Gomes.
The most recent version of the work is based on incidence data (number of new daily cases) from Belgium, England, Spain and Portugal. “We intend to study data from Brazil and the United States soon, where the epidemic is still evolving,” says the researcher.
According to the authors, although the coefficient of variation is different in each country, in general, the collective immunity threshold tends to remain between 10% and 20% and this is extremely relevant for the formulation of public policies.
“In places where the collective immunity threshold has already been reached, the trend is that the number of new cases will continue to fall even if the economy is reopened. But if the distance measures are relaxed before collective immunity is achieved, cases are likely to rise again and managers should be aware, ”says Corder. “Conceptually, after reaching collective immunity, transmission tends to be prolonged if control measures are removed quickly”, he warns
According to Gomes’ report, in Portugal it is possible to observe two different situations. The northern region, where the virus entered the country, was much more impacted at the beginning of the pandemic and now, even with the economy reopened, the number of new cases remains falling. In the south, where the capital Lisbon is located, the cases follow an upward trend.
“For the time being there are localized outbreaks, in Lisbon neighborhoods, which are being contained locally through testing and isolating infected people. People were only released to return to work in Portugal after taking tests ”, says the researcher.
A partially similar situation occurs in Brazil. The region of Manaus (AM), in the North, apparently reached the peak of the epidemic curve in May, when the health system collapsed. After that, the number of new cases has fallen even with the open economy and schools resuming face-to-face activities Serological studies have indicated that in cities like Manaus and Belém, in Pará, more than 10% of the population already has antibodies against the new coronavirus.
The South region, which registered a small number of infections at the beginning of the epidemic and where the seroprevalence rate in the population was around 1% in May, has registered an increase in the number of new cases as activities are resumed. . Unlike Portugal, investment in testing and tracking infected people in Brazil still falls short of what is considered ideal
As the authors of the article point out, the fact that the collective immunity threshold is lower than initially planned does not diminish the importance of public health measures to contain the spread of the virus and reduce the number of deaths.
“If any manager defends collective immunity as a public policy, he is wrong. Control measures are important to avoid overloading the health system. But the new understanding of the transmission dynamics of COVID-19 that our model brings points to a more optimistic scenario ”, says Corder.
In Gomes’ assessment, adherence to isolation measures tends to be greater if people know that sacrifice will be necessary for a shorter period. “When we say that the epidemic will only be overcome when the vaccine arrives, people start to think about breaking the rules, as they can no longer handle a life that is not so sociable, with so many restrictions”, he says.
Next steps. Feeding the model with real-world data is the best way to make your simulations and estimates more realistic. With this objective, Ferreira intends to test in a field study in Acre two assumptions used in the group’s calculations: the disease detection index (the difference between the actual number of infected and the number of diagnosed cases) and the duration of the disease. immunity against SARS-CoV-2.
“At work, we consider that around 10% of real cases are detected by health services and that immunity against the virus lasts for at least one year. We will see if this is confirmed in a population that we have been following for some years in the city of Mâncio Lima ”, says the researcher.
The ICB-USP group has been carrying out household surveys every six months with a sample of the population of the Acriana city located on the border with Peru. In addition to applying questionnaires, the researchers collect blood samples. The idea is to monitor how SARS-CoV-2 seroprevalence evolves in this population over the next year and to observe how long antibodies can be detected in the blood. The work is supported by Fapesp.