28.01.2021 | Modelling method

Herd immunity: How far we really are from it

Demographers from the Austrian Academy of Sciences have used a new, indirect method to reveal what the age distribution and death rate say about the actual spread of the virus and why current testing strategies can only detect some of the infections. The study has now been published in the journal PLOS One.

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Test, test, test. In many countries, tests for SARS-CoV-2 are considered an important requirement for containing the pandemic. But can they detect all infections? Researchers at the Vienna Institute of Demography of the Austrian Academy of Sciences (OeAW) and the Technical University of Vienna have now reevaluated previous testing strategies, the case fatality rate, and the concept of herd immunity using mathematical models. They describe their approach in the journal PLOS One.

One of the results is that, in most countries, no more than 60 percent of all infections are detected. "So far, there are hardly any studies that have examined how efficient the testing strategy is. Different testing methods, asymptomatic individuals, and limited large-scale testing availability reduce the chances of detecting all cases," says Miguel Sánchez-Romero, first author of the publication, from the Academy of Sciences.

Mathematical formula provides the number of people ever infected

The researchers therefore suggest a complementary method. Using a statistical model, they can derive important epidemiological parameters about which no information would otherwise be available: "With our model, we can estimate for any population how many people have ever been infected with COVID-19. We can also quantify how many infections were actually detected," explains OeAW researcher and co-author Vanessa Di Lego.

The indirect estimation technique requires the following demographic data: the age distribution of the population, the age-specific mortality (excluding COVID-19), the number of COVID-19-related deaths, and the case fatality rate, i.e., the COVID-19-related deaths with respect to the number of identified infections.

This method not only provides information about the efficiency of the testing strategy, but also provides data on how close – or rather, how far – a population is from achieving herd immunity. An example: even in those US states severely affected by the pandemic, such as New York and New Jersey, the proportion of people ever infected was still below 20 percent. "Our method shows that herd immunity is not a suitable strategy for this disease," Di Lego says.

Future application: review of vaccination strategies

These results are also confirmed by seroprevalence studies, which are currently the gold standard for retrospectively detecting an infection. These studies measure the levels of specific antibodies in blood serum. Compared to the method presented in PLOS One, however, seroprevalence studies are expensive and time-consuming, so their application is limited in practice.

In the published study, the research team analyzed the spread of the pandemic for the USA, the country with the world's highest death toll to date. But: "Our model is a tool that is suitable for worldwide use – without having to know every country-specific detail," Sánchez-Romero says. For example in Austria based on data from the AGES (19.1.2021) the model calculates that nearly 7 percent of the overall population in Austria have ever been infected with SARS-CoV-2. Of these 7 percent nearly 60 percent of infections have been detected since the beginning of the pandemic in March.

The research team also gives an outlook on future areas of application: "In a few months we can check whether the vaccination strategy is working and to what extent the vaccines actually prevent deaths," Sánchez-Romero says.



"An indirect method to monitor the fraction of people ever infected with COVID-19: an application to the United States", Miguel Sánchez-Romero, Vanessa di Lego, Alexia Prskawetz, Bernardo L Queiroz, PLOS One, 2021.
DOI: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245845