Epidemiological Considerations for SARS-CoV-2 Herd Immunity
Immunity Threshold in the Absence of a Vaccine One important measure to evaluate the impact of SARS-CoV-2 spread is the overall case fatality rate (CFR). The CFR is the proportion of deaths attributed to a certain disease among all individuals diagnosed with that disease (i.e., cases) over a specified period of time. It is worth noting that there is still significant uncertainty in the CFR for COVID-19 due to variation in the testing capacity per country, selection bias for which individuals receive testing, and differences in how deaths are officially attributed to
COVID-19. Further, CFR is also sensitive to variation in the underlying age structure and distribution of comorbidities among populations.
Consequently, CFRs may differ considerably over time and between countries. In the case of COVID-19, the initial estimate of the CFR in a small cohort of 41 individuals with laboratory-confirmed SARS-CoV-2 infection was high (15%) (Huang et al., 2020). However, this number has markedly decreased as more data have become available. Using data from all laboratory-confirmed and clinically diagnosed cases from mainland China, Verity et al. obtained an estimated overall CFR of 1.38%, adjusted for censoring, under-ascertainment, and the underlying demography in China, and similar estimates have been obtained from other groups (Verity et al., 2020; Wu et al., 2020a). Like many other infectious diseases, a non-uniform COVID-19 CFR has been reported across age groups, with the vast majority of deaths occurring among individuals 60 years old or greater.
Because SARS-CoV-2 is a novel pathogen, many features of its transmission and infection dynamics are not well characterized. Thus, our above analysis provides only a sense of the potential ramifications given a scenario in which we attain herd immunity via natural infection. We do not consider numerous complexities of viral spread and infectivity, including variation in R0 across time and populations, heterogeneity in the attack and contact
rates across demographic groups, and inter-individual variation in communicability and disease severity, although these aspects are essential to understand the full picture of SARS-CoV-2 community spread.
While these epidemiological factors have important implications in the context of herd immunity, currently, they are difficult to estimate given the limited data available. Differences in population density, cultural behaviors, population age structure, underlying comorbidity rates, and contact rates across groups influence transmission dynamics within communities, so the assumption of a uniform R0 across populations is not realistic. Further, variation in transmissibility between individuals may play a major role in SARS-CoV-2 spread. Superspreading events occur when circumstances favorable for high rates of transmission arise.
These events involve a single index case infecting a large number of secondary contacts and are known to be important in driving outbreaks of infectious diseases, including SARS, Middle East respiratory syndrome (MERS), and measles (Lloyd-Smith et al., 2005). Reports of SARS-CoV-2 superspreading events have been documented, suggesting that heterogeneity in infectivity may significantly impact the dynamics of its transmission (Liu et al., 2020). Finally, the factors that influence inter-individual heterogeneity in COVID-19 susceptibility, clinical pathology, and disease outcome are not well understood. Reported differences in sex- and ethnicity-specific CFRs suggest that genetic, environmental, and social determinants likely underlie variation in susceptibility to COVID-19 and the severity of COVID-19 complications, although future studies are needed to explore this further (Nasiri et al., 2020).
Immunological Considerations for SARS-CoV-2 Herd Immunity
The ability to establish herd immunity against SARS-CoV-2 hinges on the assumption that infection with the virus generates sufficient, protective immunity. At present, the extent to which humans are able to generate sterilizing immunity to SARSCoV-2 is unclear. A recent study assessing the possibility of SARS-CoV-2 reinfection in a small cohort of rhesus macaques found that reinfection was not able to occur 1 month after the first viral challenge, suggesting at least short-term sterilizing immunity in these animals (Bao et al., 2020). In a cohort of 175 recovered COVID-19 patients, SARS-CoV-2-specific serum neutralizing antibodies (NAbs) were detected at considerable, albeit variable, titers in most (n = 165) individuals (Wu et al., 2020b),
Acquired immunity is established at the level of the individual, either through natural infection with a pathogen or through immunization with a vaccine. Herd immunity (Box 1) stems from the effects of individual immunity scaled to the level of the population. It refers to the indirect protection from infection conferred to susceptible individuals when a sufficiently large proportion of immune individuals exist in a population. This population-level effect is often considered in the context of vaccination programs, which aim to establish herd immunity so that those who cannot be vaccinated, including the very young and immunocompromised, are still protected against disease. Depending on the prevalence of existing immunity to a pathogen in a population, the introduction of an infected individual will lead to different outcomes (Figure).
In a completely naive population, a pathogen will propagate through susceptible hosts in an unchecked manner following effective exposure of susceptible hosts to infected individuals. However, if a fraction of the population has immunity to that same pathogen, the likelihood of an effective contact between infected and susceptible hosts is reduced, since many hosts are immune and, therefore, cannot transmit the pathogen. If the fraction of susceptible individuals in a population is too few, then the pathogen cannot successfully spread, and its prevalence will decline. The point at which the proportion of susceptible individuals falls below the threshold needed for transmission is known as the herd immunity threshold (Anderson and May, 1985). Above this level of immunity, herd immunity begins to take effect, and susceptible individuals benefit from indirect protection from infection (Figure 1B).
Consequences of Reaching the SARS-CoV-2 Herd
Under the simplest model, the herd immunity threshold depends on a single parameter known as R0, or the basic reproduction number (Figure 2A). R0 refers to the average number of secondary infections caused by a single infectious individual introduced into a completely susceptible population (Anderson and May, 1985). If we consider a hypothetical pathogen with an R0 of, this means that, on average, one infected host will infect four others during the infectious period, assuming no immunity exists in the population. Mathematically, the herd immunity threshold is defined by 1 – 1/R0 (e.g., if R0 = 4, the corresponding herd immunity threshold is 0.75) (Anderson and May, 1985).
Therefore, the more communicable a pathogen, the greater its associated R0 and the greater the proportion of the population that must be immune to block sustained transmission (Figure 2B). A similar parameter important for understanding population-level immunity is the effective reproduction number (Re or Rt). Re is defined as the average number of secondary cases generated by a single index case over an infectious period in a partially immune population (Delamater et al., 2019). Unlike R0, Re does not assume a completely susceptible population and, consequently, will vary depending on a population’s current immune state, which will change dynamically as an outbreak event or vaccination campaign unfolds. Ultimately, the goal of vaccination programs is to bring the value of Re below. This occurs when the proportion of the population with immunity exceeds the herd immunity threshold. At this point, pathogen spread cannot be maintained, so there is a decline in the number of infected individuals within the population.
The above interpretation of R0 and its relation to the herd immunity threshold is the simplest understanding of these terms. It relies on several key assumptions, including homogeneous mixing of individuals within a population and that all individuals develop sterilizing immunity—immunity that confers lifelong protection against reinfection—upon vaccination or natural infection. In real-world situations, these epidemiological and immunological assumptions are often not met, and the magnitude of indirect protection attributed to herd immunity will depend on variations in these assumptions. R0 is defined by both the pathogen and the particular population in which it circulates.
Thus, a single pathogen will have multiple R0 values depending on the characteristics and transmission dynamics of the population experiencing the outbreak (Delamater et al., 2019). This inherently implies that the herd immunity threshold will vary between populations, which is a well-documented occurrence (Delamater et al., 2019). For any infectious disease, communicability depends on many factors that impact transmission dynamics, including population density, population structure, and differences in contact rates across demographic groups, among others (Anderson and May, 1985). All of these factors will directly or indirectly impact R0 and, consequently, the herd immunity threshold. To establish herd immunity, the immunity generated by vaccination or natural infection must prevent onward transmission, not just clinical disease.
For certain pathogens, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), clinical manifestations are a poor indicator of transmissibility, as asymptomatic hosts can be highly infectious and contribute to the spread of an epidemic. Once the herd immunity threshold is reached, the efficacy of herd immunity largely depends on the strength and duration of the immunity acquired. For pathogens in which lifelong immunity is induced, as is the case for measles vaccination or infection, herd immunity is highly effective and can prevent pathogen spread within a population. However, this situation is relatively rare, as immunity for many other infectious diseases, such as pertussis and rotavirus, wanes over time. As a consequence, herd immunity is less effective, and periodic outbreaks can still occur. Finally, if immunity is unevenly distributed within a population, clusters of susceptible hosts that frequently contact one another may remain. Even if the proportion of immunized individuals in the population as a whole surpasses the herd immunity threshold, these pockets of susceptible individuals are still at risk for local outbreaks
ng accurate R0 estimates in an ongoing pandemic, and the current estimated SARS-CoV-2 R0 values likely do not indicate a complete picture of the transmission dynamics across all countries. Assuming an R0 estimate of 3 for SARS-CoV-2, the herd immunity threshold is approximately 67%. This means that the incidence of infection will start to decline once the proportion of individuals with acquired immunity to SARS-CoV-2 in the population exceeds 0.67. As discussed above, this model relies on simplifying assumptions, such as homogeneous population mixing and uniform sterilizing immunity in recovered individuals across demographic groups, which are unlikely to hold true. Nevertheless, this basic model can give us a rough idea of the number of individuals that would need to be infected to achieve herd immunity in the absence of a vaccine given an approximate herd immunity threshold and a country’s population.
Author:E.Randolph B. Barreiro
