HI/ Identifying Parameters to Establish the Criteria for Herd Immunity

Ending Covid

Herd/Population Immunity Definitions

Herd immunity or population immunity is a key concept for epidemic control and the spread of disease or the adaptation of disease within a group of people. When dealing with the prospect of a rise in cases for a particular disease it is imperative to prioritize at which point the threshold referred to as herd/population immunity will be achieved within a given population.

The premise of population immunity states that only a proportion of a population needs to be immune to an infectious agent (such as virus) in order for it to stop generating large outbreaks throughout a geographic location. The method of immunization can be achieved via overcoming natural infection barriers or through the vaccination of small targeted groups or on a large scale.

The general equation to calculate population immunity is the following:

Herd/population immunity is achieved when one infected person in a population generates less than one secondary case on average, which corresponds to the effective reproduction number

R (that is, the average number of persons infected by a case) dropping below 1 in the absence of interventions. In a population in which individuals mix homogeneously and are equally susceptible and contagious

R = (1 − pC)(1 − pI)R0 (equation 1)*

where pC is the relative reduction in transmission rates due to non-pharmaceutical interventions

pI is the proportion of immune individuals within a given population

R0 is the reproduction number in the absence of control measures in a fully susceptible population within a allocated time frame

R0 may vary across populations and over time, depending on the nature and number of contacts among individuals and potentially environmental factors

In the absence of control measures

(pC = 0) the condition for herd immunity

(R < 1, where R = (1 − pI)R0) is therefore achieved when the proportion of immune individuals reaches pI = 1 – 1/R0

For SARS-CoV-2 most estimates of R0 are in the range 2.5–4, with no clear geographical pattern.

It also follows from equation 1* that in the absence of herd immunity or population immunity, the intensity of social distancing measures necessary to control transmission decreases as population immunity grows, therefore mandates to enforce specific distance measurements among a population can become counterproductive at a certain point. 

There are situations when herd immunity might be achieved before the population immunity reaches pI = 1 − 1/R0. For example, if some individuals are more likely to get infected and to transmit, due to more contacts and interactions within the specified group within a specific locale, these, who are referred to as super-spreaders will likely get infected first. This is what was previously defined as a super-spreader, i.e. an individual who has already been exposed to the viral agent, and remains asymptomatic, however precedes to become a vector throughout the population as a whole. As a result, the population of susceptible individuals gets rapidly depleted of these super-spreaders and the pace of transmission slows down, depending on the calculation of what the initial percentage of herd immunity was determined initially. 

However, it remains vague to quantify the impact of this in the context of COVID-19 at the current time due to several factors. These include the constant fluctuations in distance restrictions, the  time length and extent calculated, and the global scale of the viral spread.  For R0 = 3,  it has been previously showed that, if we account for age-specific contact patterns (for example, individuals aged >80 years have substantially less contacts than those aged 20–40 years), the herd immunity threshold drops from 66.7% to 62.5%. 

This immunity was declined due to a lack of interactions at the specific time margin. Contact patterns are to be defined as the number of times a given individual comes across another individual within a group setting within a given geographical location, and the frequency of such interactions. If we further assume that the number of contacts varies substantially between individuals within the same age group, herd immunity could be achieved with only 50% population immunity during a natural course. The natural course of the viral course would have to be predetermined by comparing previous time lengths of similar viral infections within a given population.  However, in this scenario, the departure from the formula pI = 1 − 1/R0 is only expected if it is always the same set of individuals that are potential super-spreaders from the onset, which is feasible considering most are asymptomatic.

If the case of these individuals, identified as population dispersers, moving throughout the region at a given frequency, then super-spreading is driven by events rather than by individuals. If control measures reduce or modify the set of potential super-spreaders, there may be limited impact on herd immunity depending on when it is calculated. Another factor that may feed into a lower herd immunity threshold for Covid is the role of random spread in viral transmission. Preliminary reports find that random events, particularly those at initial set points may be less susceptible and contagious, in which case they may be partially omitted from the computation of herd immunity. This is also a clear implication that the closure of facilities was not necessary in this particular case from the very onset. Initial predictions imply that there was little evidence to suggest that the spread of SARS-CoV-2 might stop naturally before at least 50% of the population has become immune.

COVID-19 herd immunity: where are we? | Nature Reviews Immunology