Herd Immunity
history, concepts, and ethical rationale
Davide Vecchi* and Giorgio Airoldi†
* Centro de Filosofia das Ciências, Departamento de História e Filosofia das Ciências, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal .
†Departamento de Lógica, Historia y Filosofía de la Ciencia, Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain.
Correspondence: Davide Vecchi, Centro de Filosofia das Ciências, Universidade de Lisboa, Campo Grande, Lisboa 1649-004 Portugal.
Email: davide.s.vecchi@gmail.com.
Vecchi, D., & Airoldi, G. (2023). Herd Immunity: History, Concepts, and Ethical Rationale. Perspectives in Biology and Medicine 66(1), 38-57.
https://www.muse.jhu.edu/article/884003
ABSTRACT Public health emergencies are fraught by epistemic uncertainty, which raises policy issues of how to handle that uncertainty and devise sustainable public health responses. Among such responses, a herd immunity policy might be an option. Particularly before the development of vaccines, the current COVID-19 pandemic has highlighted the polarized nature of the political debate concerning the ethical feasibility of herd immunity strategies. This article provides a conceptual framework tailored to uncover the ethical rationale behind such strategies. Clarity on this issue is important in order to facilitate the terms of the political debate when tackling future health emergencies.
The chief question we tackle in this article is What is, if any, the ethical rationale of herd immunity strategies of infection control? In order to answer this question, we need to distinguish between “herd immunity” as an ideal immunological state of a population of interest and “herd immunity” as a strategy to reach such a state. Although in the scientific literature the expression “herd immunity” is used mostly in the former sense, in policy briefings and in the mass media, reference is often to the latter sense, creating confusion. These two senses should be clearly conceptually distinguished (Bhopal 2020). In this article, we shall always use the terminological expression “herd immunity strategy/policy” when we refer to a public health strategy (or policy implementing it) that has the purpose of achieving the population state of herd immunity.
Herd immunity as an ideal immunological population state is reached when a sufficient percentage of a population becomes immune to an infectious disease, creating a shield that indirectly protects susceptible individuals against the disease and thus both prevents sustained transmission and reduces its probability of spreading further. This state can be reached in several ways by balancing pharmaceutical (when available) and nonpharmaceutical interventions, while at the same time tolerating some degree of population infection. As we shall explain, allowing a disease to spread freely without barriers in order to reach herd immunity as quickly as possible—regardless of the loss of lives—or allowing only low-risk individuals to get sick while protecting high-risk individuals through restrictions are distinct public health strategies. While the former strategy has been associated with herd immunity during the COVID-19 pandemic, the original herd immunity strategy is the latter.
In order to clear up any such misunderstanding and characterize herd immunity as a public health strategy of infection control, we start by delineating the historical context and we then situate herd immunity strategies epidemiologically within the panoply of strategies of infection control. We next elucidate the nature of the contemporary debate concerning the legitimacy of herd immunity strategies before discussing the ethical rationale of herd immunity strategies.
Concepts of Herd Immunity
According to Jones and Helmreich (2020), the concept of herd immunity was first articulated in 1916 by US veterinarian George Potter (with Adolph Eichhorn), in relation to a practice aimed to create groups of farmed animals resistant to disease. Significantly, for the disease in question—abortion disease in cattle—
there were neither effective drugs nor vaccines available at the time. Potter proposed that a herd immunity policy was, in such circumstances, the strategy of controlling disease by fostering the population
immunity of the farmed animals. This practice involved “retaining the immune cows, raising the calves, and avoiding the introduction of foreign cattle,” as foreign cattle susceptible to infection, or already infected, would decrease population immunity (Potter 1918, 10).
According to Jones and Helmreich (2020), the negative connotation of herd immunity emerged when veterinary practices for disease control were eventually applied to humans. To draw a parallel between the dynamics of disease transmission in animal and human populations is of course useful. But in the 1920s, this practice was still unconventional. During this period, the bacteriologist William W. C.
Topley suggested that epidemiology would profit from taking the parallel seriously. In a series of contributions, Topley and collaborators proposed that the experimental protocols developed to study the spread of enteric bacterial infections in mice could also be applied to humans. In a trivial sense, the adoption of the analogy implied the application of herd terminology to humans: “Ballonius, like
Hippocrates and Sydenham, was primarily a physician not an epidemiologist; the unit of the physician, as we have suggested, is a sick man, the unit of an epidemiologist is a herd, a group of men” (Greenwood and Topley 1925, 48).
The analogy between herds of mice and herds of humans potentially provided other valuable epidemiological insights. One of these concerned the experimental study of the effects on population immunity of the practice of introducing different numbers of “immigrants” (Potter’s “foreigners”) at different time intervals. Greenwood and Topley (1925) suggested that the epidemiological patterns they observed in mice populations resembled in significant respects those concerning humans: mortality manifested wave-like behavior, and both innate and acquired immunity influence epidemiological
dynamics. Most importantly, Greenwood and Topley showed that deadly infection will continue for a period longer than a generation in the mice population as long as immigrants not infected prior to introduction were added, eventually replenishing the original population completely. This meant that the members of the original population newly infected the immigrants, compromising the achievement of herd immunity—or, we would add, that the immigrants hid undetectable infection. The most important conclusion was that the assumption that “the admission to a herd of individuals free from the disease it is hoped to control is not a danger to the herd accepting them” must be flawed, with obvious implications for the control of infections (108). The important implication for public health was thus that a healthy
“herd” must be protected from the introduction of immigrants through isolation and segregation strategies.
With Topley, the terminology of herd immunity clearly entered human medicine. Another important contributor in the same direction was British pathologist Sheldon Francis Dudley. Following Topley’s analogy, Dudley not only used expressions such as “the urban herd,” “the rural herd,” and “the English herd,” but he also performed a series of experiments with human “herds” in “laboratory-like”
conditions (such as those provided by boarding schools and navy ships). Dudley’s studies on the spread of diphtheria at the Greenwich Hospital School are a chief example. This boarding school provided the ideal circumstances for performing epidemiological studies in controlled conditions, with “immigrants” being the students entering every year into the “human herd” constituted by the entire population of students.
Dudley observed that, after inoculation of toxoid or toxoid-antitoxin floccules, the younger generation of students were developing immunity at a lower rate than the older generation, indicating that the latter group contained “more boys in a sensitized or ‘pre-immune’ condition than the new entries did” (Dudley 1928, 295). Dudley extrapolated many inferences from such studies, including that reaching herd
immunity through inoculation is quicker than through mere natural exposure,and that “the higher the proportion of immunes in a community the easier it will be to immunize the susceptibles in that community” (294). Dudley concluded that: “this investigation closely parallels Glenny's (1925)
experiments with diphtheria toxin and guinea-pigs, except that a dense diphtherial environment was the primary stimulus, and a herd of human boys were used in lieu of the guinea-pigs” (295). The analogy
between schoolboys and guinea pigs captures the discomfort—even at a time that saw the apogee of eugenics—generated by Dudley’s studies. Indeed, with unapologetic nonchalance, Dudley described the schoolboys as an ideal “experimental herd,” a gaffe that even triggered a question in the House of Commons (Hedley-Whyte and Milamed 2018).
By the 1930s, the terminology of herd immunity was extensively used in the Anglophone epidemiological literature. Jones and Helmreich (2020) argue that the transposition of herd animal terminology to humans initiated by Topley resonates “with visions of people being treated as animals to be domesticated and culled” (811)—that is, sacrificed for a higher public health goal. However, our reconstruction of the early history of the idea of herd immunity does not look as damning as Jones and Helmreich suggest. However tasteless the use of herd terminology is judged to be in relation to human medicine, the transposition hardly justifies a particular ethical stance towards a herd immunity strategy.
While comparing groups of schoolboys to groups of mice within controlled conditions is as objectionable today as it was in the 1920s, the analogy between the dynamics of infectious disease transmission in animal and human populations is clearly defensible. The research carried out by Potter, Topley, and Dudley lacks the chief negative element of herd immunity policies striking the contemporary social imagery—in other words, the culling dimension Jones and Helmreich refer to.
As a matter of fact, we suggest that there is a mismatch between the original conception of herd immunity articulated by Potter, Topley and Dudley and the way in which the concept is generally interpreted today. First of all, Potter and Topley originally proposed that the immune “herd” should be isolated from the introduction of “foreign” or “immigrant” organisms. Isolation, they argued, is essential for two reasons: first, the achieved state of herd immunity would be compromised by the introduction of external susceptible individuals (healthy ones who could become infected and then transmit the disease);
and second, immigrants could be infected in the first place. As we discuss later, we suggest that this isolationist ethos is today a chief element of local suppression strategies of infection control, rather than one of herd immunity. Second, according to Jones and Helmreich (2020), a herd immunity policy seems to require something approaching the unrestrained and indiscriminate culling of the population of interest,
with no significant attempt to protect the vulnerable. As we emphasized, Potter’s concept of herd immunity does not contain this element. Indeed, Potter suggests, in rather compassionate terms, that we should aim to treat the animals with the disease. Even in Topley’s and Dudley’s research, this element is absent, and Dudley practiced a form of vaccination-dependent herd immunity policy. We suggest that the morally repugnant aspect of the contemporary concept of herd immunity could be described as
Malthusian, in that it proposes that natural selection should be allowed to run its course in the absence of any kind of public health intervention.
Ultimately, we suspect that the negative Malthusian connotation of the herd immunity strategy emerged after the 1920s. Since the 1950s, the herd immunity strategy has been chiefly discussed in the context of vaccination programs aimed to eradicate diseases (Gonçalves 2008; Jones and Helmreich 2020). As we related above, Dudley considered the prophylactic inoculation of schoolboys instrumental to reaching herd immunity; in contrast, Potter’s herd immunity was a strategy of infection control achieved through the natural exposure of the population to the infection in the absence of effective drugs or vaccines. The existence or absence of pharmaceutical interventions is an important element in the evaluation of the sustainability of public health responses.
Situating Herd Immunity Strategies
We shall now situate herd immunity strategies within the panoply of public health strategies of infection control. In order to do so, we first distinguish between the governments’ public health target and the strategy employed to pursue it.
Public Health Targets
Suppose we are at the initial stages of a health emergency: a new pathogen has been identified as the cause of a new infectious disease, and a diagnostic test has been devised. The evidential basis is otherwise scarce. The kind of information governments could rely on in order to choose the appropriate policy target might consist of the policy indicators shown in the first section of Table 1. Among these indicators, the transmission rate (how many infections an infected person might cause on average) is
epidemiologically crucial. In this context, it is important to distinguish between R0 (the original infection reproductive number) and the effective reproduction number R. When R is equal to 1, the infection is stable in the population, while higher and lower values indicate that the infection will either spread or disappear. We hereby characterize long-term governments’ public health targets in terms of R reduction.
<Table 1 about here>
In order to choose the appropriate public health target, however, initial estimates concerning fatality rate and “pandemicity” are also crucial. By pandemicity, we mean the degree of global
distribution of an epidemic infection, but considered independently of its severity and transmission rate.
In this sense, seasonal influenza has a high degree of pandemicity even though, when infection severity is taken into account, it is not considered a “pandemic” in the nonclassical, vernacular sense (Kelly 2011).
The reason is simply that “only some pandemics cause severe disease in some individuals or at a population level” (Porta 2014, 209). Particularly at the initial stages of a health emergency, these
indicators are both hard to estimate (for instance, due to the lack of reliable data) and heavily theory-laden (for instance, due to the lack of a commonly agreed estimation methodology, Airoldi and Vecchi 2021).
The ultimate public health goal is eradication (see Table 2)—that is, a prevalence of zero in the population, which requires reaching and maintaining R = 0. (Note that the prevalence could be higher than 0 even if R = 0, but maintaining R = 0 for a long enough time results in a zero prevalence.) The eradication of a new infection ideally requires early action in order to stifle infection locally. But the identification of the pathogen might require sophisticated biomedical infrastructure (such as genomic surveillance) that is not universally available. Additionally, knowledge about the temporal and spatial origin of the infection is crucial in order to evaluate the pandemicity of an infectious disease and
accurately estimate R0, but such knowledge is often unavailable. The more an infection is localized, or the lower its degree of pandemicity, the higher the prospects of global eradication. Historically, global eradication has been achieved for some infections (such as SARS) by means of local suppression strategies. Global eradication can also be achieved if the infection has a high degree of pandemicity by means of pharmaceutical interventions such as mass vaccination programs (as in the case of smallpox).
<Table 2 about here>
Alternatively, some countries might pursue the target of local elimination, or stopping transmission in a specific geographical area. The chances of successfully reaching this target depend heavily on the characteristics of the country—its geographical and social structure, such as being an island or having low population density—and of the disease, including factors such as its rate of transmission. Local elimination has been reached for diseases such as poliomyelitis or malaria, but it is probably not viable for countries with high population density and no natural borders, or even for infections with high transmission rates and asymptomaticity such as COVID-19.
If the indication is that the infection has a high degree of pandemicity, governments generally aim at a much humbler target: effective management. Epidemiologically, this target is keeping R @ 1, with the aim of reaching R < 1. There are two main kinds of effective management without eradication. The first is dependent on the existence of effective pharmaceutical interventions, and the second focuses on
transmission control in order to achieve herd immunity.
An instance of the first kind is illustrated by the current management of the HIV health emergency, which has been achieved through the development of a breakthrough therapy based on a combination of antiretroviral drugs. This breakthrough came only in the mid-1990s, more than a decade after the HIV virus was first identified. Concerning R reduction, two points should be highlighted. First, population immunity has surely increased. For instance, people homozygous for the mutant allele CCR5Δ32 seem to be resistant to HIV infection. If CCR5Δ32 increases in frequency in the human population (and there are some indications that this is actually happening, at least in Northern European countries), population immunity grows. Nevertheless, herd immunity has not been reached yet. The human population is still highly susceptible to HIV, and a vaccine is still unavailable. But despite this, the HIV epidemic can be effectively managed whenever the antiretroviral therapy is available. Thus, the second factor in R reduction has been the effects of antiretroviral therapy, together with the
implementation of a variety of nonpharmaceutical interventions, such as the decriminalization of drug consumption in Portugal (Vasylyeva et al. 2019).
Whenever effective pharmaceutical interventions are absent, and local elimination is not viable due to the features of the country and of the infection, the only way to reach the target of sustainable effective management is through the achievement of herd immunity. In epidemiological terms, herd immunity can be conceptualized as that desirable state whereby the current reproduction rate R
permanently becomes < 1 in the absence of nonpharmaceutical interventions (Fontanet and Cauchemez 2020). The following equation might be used to make sense of this conceptualization:
R = (1—pc) (1—pi) R0
In the equation, pc refers to the reduction in transmission risk due to nonpharmaceutical interventions—in other words, the broad range of restrictions to social interaction that governments adopt in order to limit contagion; pi refers to the proportion of immune organisms in the population of interest; and R0 refers to the original infection reproduction number—that is, its transmissibility at the time when the infection first emerged in a population of uniformly susceptible organisms randomly interacting, a situation therefore characterized by pc = 0 and pi = 0. Estimates of R0 might vary extensively. The assumption of uniform susceptibility is a simplification, because (1) native immunity makes pi ≠ 0; (2) native immunity distribution is biased, so that the population is not uniformly susceptible; and (3), the organisms of a population do not randomly interact.
Herd immunity is reached when pi = 1—1/R0. So, for example, if R0 = 4, the transmission chain would be broken once pi = 0.8, or when at least 80% of the population overcomes infection with lasting immunity. The crucial aspect of the debate on how to achieve herd immunity concerns what kinds of strategies of infection control to endorse in order to reach this target.
Strategies of Infection Control
Given the discrimination between various public health targets, we can now characterize different strategies of infection control (see Table 2). Let us suppose that this choice takes into consideration a growing evidential basis that can be channeled to build epidemiological models (see the policy indicators in the second section of Table 1). What governments aim to do is to estimate the effects of infection on
health-care infrastructure (given B indicators in Table 1), as well as the societal effects of nonpharmaceutical interventions. This evaluation also depends on the prospects of developing
pharmaceutical interventions (see C indicators in Table 1), on which the duration of nonpharmaceutical interventions depends. Among the epidemiological indicators, the estimated fatality rate plays a major role in policy making.
Local suppression is the strategy of pushing R towards 0 at the local level (Figure 1). Local suppression is one strategy to achieve the target of eradication or, more modestly, of local elimination.
The higher the fatality rate, the higher the need for local suppression (as in the case of Ebola). The first obstacle to local suppression is the high level of pandemicity of the infection: the more the infection is detected in multiple geographically scattered locations, the harder it is to achieve global eradication through synchronized local suppression efforts. The second obstacle is that local suppression is impaired by disparity in local biomedical infrastructure: the more governments are unable to stifle infection locally, the lower the chances of eradication. The third limitation concerns the availability of pharmaceutical interventions. In the absence of pharmaceutical interventions, the only way to maintain R ≅ 0 via local suppression strategies is, paraphrasing Potter’s and Topley’s words, by avoiding the introduction of foreign and immigrant humans indefinitely.
<Figure 1 about here>
The emphasis on limiting the introduction of foreigners in the local population and on the latter’s segregation from the global population makes local suppression akin to the original herd immunity strategy. Note, however, that there is a conceptual difference behind this common aspect: in Potter’s case, foreigners were not allowed because, if uninfected, they (1) might be in danger of getting sick and (2) reduce the proportion of immune individuals in the population; in local suppression strategies, foreigners are not allowed because they might carry the infection.
For infections with a high degree of pandemicity, the target of eradication is unfeasible without pharmaceutical interventions, because as soon as borders are opened, the infection will find a susceptible local population (given its low pi). In such cases, however, local suppression can be a temporary solution
that helps some countries reach local elimination or reduce the immediate impact of a disease until pharmaceutical interventions become available—although it arguably cannot be pursued indefinitely without heavy economic and social costs. If there is a general lesson from the history of human
pandemics, it is that the isolationist idyll of local suppression strategies is dangerous in the long term if not complemented by pharmaceutical interventions (Crosby 1986; Eyler 2003). For the above reasons, local suppression should be considered only as a short- or medium-term policy.
Consider now a case in which the policy focus is switched to the target of effective
management—that is, keeping R not too far from 1. In the absence of pharmaceutical interventions, this target can only be realized by the achievement of herd immunity through either a containment or a mitigation strategy. Note that these strategies form a continuum, depending on what value of R is admitted and to what end: strict containment (R almost equal to 1) and light mitigation strategies (R slightly higher than 1) might have many aspects in common (see Figure 2).
<Figure 2 about here>
Containment aims to control R so that it does not increase to greater than 1 or, at least, so that it does not fluctuate substantially from 1; when circumstances require, it is brought below 1 through pc
increase (new or more restrictive nonpharmaceutical interventions). Containment so characterized
requires that nonpharmaceutical interventions must be maintained in place until the percentage of infected people becomes negligible, or until pharmaceutical interventions allowing effective management emerge.
Mitigation consists of letting the disease spread among the population at a controlled rate of R > 1.
With an R > 1, population immunity might increase towards the relevant herd immunity threshold (which is dependent on R0). Thus, mitigation strategies target the effective management of the health emergency through policies tailored to achieve herd immunity by means of the natural exposure of the population to infection. The exposure might be targeted to protect high-risk categories (see Figure 3i). As in
containment, nonpharmaceutical interventions are used in order to control infection transmission by distributing across time the pathological effects of the infection in terms of morbidity and mortality.
These strategies are not mutually exclusive and can be blended (Trauer et al. 2021).
<Figure 3 about here>
Herd Immunity as Mitigation Strategy
Both containment and mitigation strategies are implemented via nonpharmaceutical interventions.
Given that there exists an indefinite variety of types of interventions and given that every type can be realized in multifarious ways, containment and mitigation form continua. Herd immunity strategies can be situated along the mitigation continuum between those aiming to keep R just slightly over 1 and what might be called the Malthusian strategy, whereby R is left to naturally fluctuate in order to reduce the duration of the health emergency and more rapidly achieve herd immunity (Figure 3ii). In the Malthusian strategy, nonpharmaceutical interventions are completely absent (pc= 0). In certain circumstances, such as when the infection fatality rate is substantial, this strategy approximates the indiscriminate and
unrestrained “culling” of the human population that, according to Jones and Helmreich (2020), characterises a herd immunity policy in the social imagery (stet).
Herd immunity strategies so characterised cover the entire mitigation continuum between R ≥ 1 and R0 (Figure 2). Herd immunity strategies also cover the entire set of nonpharmaceutical interventions (pcs) that keep R > 1, with 0 < 𝑝! < 𝑝!", where 𝑝!" is the value of nonpharmaceutical interventions appropriate to keep R =1. The value of 𝑝!" is calculated by taking into account the current pi (the proportion of immune organisms in the population of interest) estimate, according to the following formula, deduced from eq. 1 (stet):
𝑝!" = 1 − 1
(1 − 𝑝#) 1 𝑅$
The more the value of pc (nonpharmaceutical interventions) approximates 0, the more herd immunity strategies possess the Malthusian element. The more pc approximates 𝑝!", the more similar the strategies are to containment.
Framing the Herd Immunity Debate
Containment and mitigation strategies do not diverge axiologically: reaching herd immunity is the aim of
both strategies. Containment and mitigation strategies also do not diverge radically as strategies of infection control, because both adopt nonpharmaceutical interventions. In this general sense, there is no principled reason to consider them as alternative choices. As a matter of fact, containment and mitigation are often difficult to discriminate and can obviously be blended. Thus, the difference between
containment and mitigation only concerns how to reach the population state of herd immunity. Within this context, the debate concerning herd immunity is two-fold: first, can herd immunity be achieved only with pharmaceutical interventions? and second, what is the role, if any, of nonpharmaceutical
interventions in achieving herd immunity? The first question can be considered the immunological core of the debate, while the second question points to the social policy core of the debate.
The Immunological Dispute
In a situation characterized by absence of effective drug therapies or vaccines, containment and mitigation advocates might diverge on a host of issues concerning the prospect of their emergence. The C indicators (Table 3) refer to a variety of policy issues that might drive governments towards endorsing either containment or mitigation (Anderson et al. 2020; Poland et al. 2020; Thorp 2020). Evaluating the prospects of pharmaceutical interventions reinforces the basic point that political input—informed by scientific and industry insider knowledge—is key in opting for containment or mitigation. For instance, C3 depends on the biomedical promise of the research already undergone on vaccine development for phylogenetically related infections (the game changer in the context of the COVID-19 pandemic).
Another important consideration concerns history: the contention that mitigation merely through natural infection and without vaccination has never achieved herd immunity for any infectious disease is probably overstated. For instance, Fine and colleagues (2011) relate that, in the case of measles, herd immunity was naturally reached in Boston, Massachusetts, after several outbreaks lasting approximately 30 years between the 1900s and the 1930s. This is clearly a significant amount of time, even though measles is one of the most contagious diseases, with an R0 estimated at 12 or higher. Moreover, Kilbourne (2006) seems to suggest that a substantial degree of population immunity to the H3N2 influenza virus
causing the pandemic in 1968 was at least partially naturally acquired during the 1957 pandemic, which was caused by H2N2 (given the similar molecular properties of the two viruses).
A crucial immunological issue concerns the estimate of pi at a given moment. In order to be able to estimate pi accurately, it is essential to understand the idiosyncrasies of organismal immunity. A general model of organismal immunity would need to provide a taxonomy of the molecular and cellular resources that organisms might be able to mobilize in case of infection. Native and cellular adaptive immunity might, for instance, need to be encompassed. Native immunity might comprise some form of pre-immunity acquired through exposure to similar infections, while cellular immunity not mediated by B-cells but, for instance, by helper and cytotoxic T cells, might also be important. This would be
particularly the case whenever the presence of such cells is detected in people exposed to infection despite lacking antibodies, suggesting that T-cell memory responses might be induced by the infection in the absence of humoral immune responses. The taxonomy would provide the basis for estimating pi by focusing on the detection of a range of biological markers in population studies. If immunity encompasses these additional dimensions, estimating pi by merely detecting antibody presence (immunoglobulins such as IgAs, IgMs and IgCs) is clearly insufficient.
Even if immunity is understood more broadly, it is also essential to investigate the longevity of natural immunity. Such estimates are based both on knowledge concerning immunity for phylogenetically related infections and the growing pathophysiological knowledge concerning the new infection, for instance concerning the immunology of reinfection and its frequency. Low levels of lasting immunity and high levels of reinfection would continuously erode pi and shift backwards the herd immunity target pi = 1—1/R0. Mitigation would be thus impaired if population immunity is not increased through natural immunity.
Finally, when pharmaceutical interventions become available (potentially allowing the focused protection of the vulnerable subpopulation), the debate between containment and mitigation advocates is substantially transformed. However, the immunological dispute remains hugely important. For example, when planning vaccination programs, it is crucial to know whether vaccination reduces transmission, how
long vaccination-induced immunity lasts, and how it compares to natural immunity.
The Social Policy Dispute
Nonpharmaceutical interventions play a fundamental role in fostering the achievement of herd immunity through mitigation. Conversely, herd immunity through containment works on the principle that nonpharmaceutical interventions are merely aimed to curb R, effectively delaying transmission until pharmaceutical interventions emerge. How this delaying is achieved is irrelevant. The important point is that nonpharmaceutical interventions are devised with the aim of reaching R < 1. Thus, containment and mitigation strategies seem to clash. But this clash is, in our opinion, partially spurious in at least two senses.
First of all, the way to reduce R should be devised by continuously monitoring pi and by manipulating pcs accordingly. In this sense, pi should be continuously estimated in order to gradually reduce the invasiveness of pcs. What is at dispute, as we argued above, is the estimation rationale for calculating pi. However, independently of how pi is estimated in practice, monitoring systems of actual levels of population immunity should be implemented in the context of both containment and mitigation strategies in order to manipulate pcs accordingly.
This means that the heart of the social policy dispute between containment and mitigation concerns the targeting of nonpharmaceutical interventions. Mitigation proposes that nonpharmaceutical interventions should be tailored to allow infection to seep through the population, targeting its less vulnerable members instead of curbing and delaying transmission in an unplanned way. If the distinction between vulnerable and non-vulnerable subpopulations is problematic, or if shielding policies are unfeasible, mitigation is impaired. Nonetheless, containment and mitigation strategies are not fundamentally different when vulnerability is characterizable. Increasing the value of pc should be targeted to protect the vulnerable subpopulation, spreading the residual risk among the members of the non-vulnerable one. Decreasing the value of pc should be conversely targeted to increase the risk of infection among the members of the non-vulnerable subpopulation instead of spreading the risk
indiscriminately among the population as a whole. Governments might officially justify the tightening or relaxation of nonpharmaceutical interventions in multifarious ways: either in terms of necessary
protection of the vulnerable in case of rising R, or in terms of calculated increase of the risk of infection among the members of the non-vulnerable subpopulation in case of decreasing R. Another interpretation is that governments’ policy equates to an epidemiological experiment in herd immunity building. This is because guaranteeing the functioning of society will inevitably—if lasting immunity through natural exposure is achievable—increase the population immunity of the non-vulnerable subpopulation. All targeted policies will thus, to different degrees, increase pi. In such cases, discriminating between containment and mitigation becomes difficult.
The Ethical Rationale
All the public health strategies of infection control illustrated earlier have virtues and limitations. Their adoption depends on complex political decisions informed by a growing but fallible evidential basis concerning the various policy indicators so far taken into consideration and summarized (with additions) in the third section of Table 1. Of course, this growing evidential basis might lead governments to change public health targets and strategies. Consequently, there is no privileged strategy of infection control:
even a Malthusian strategy might be ethically defensible if the infection fatality rate is sufficiently low or if very effective drugs are available. In the end, policy choice depends on the idiosyncrasies of specific infections and the context in which their effects materialize. Given this state of affairs, when are herd immunity strategies ethically defensible? And what kind of ethical principles might support them? We argue that herd immunity strategies are defensible most clearly within a utilitarian ethical framework and are supported by utilitarian ethical principles. But other ethical frameworks could also support these strategies.
Life Expectancy Matters
A public health rule of thumb is that the more the estimated fatality rate of the new infection approaches that of seasonal influenza (a disease not amenable to eradication), the more a strategy of
mitigation—rather than containment—is justified. Governments are not generally held accountable in case substantial excessive death tolls due to seasonal influenza occur, with the caveat that this situation does not seriously disrupt the health system. The chief reason is that vaccination plans are in place. Thus, substantial excess death tolls might be due to vaccines being ineffective or to the influenza virus mutating unpredictably rather than to governments’ responsibility.
The influenza benchmark has been important during the COVID-19 pandemic (Baker and Wilson 2020; Lee et al. 2020). The COVID-19 infection fatality rate was initially estimated at nearly seven times that of seasonal influenza (Verity et al. 2020); coupled with an estimated R0 between 2.0 and 2.6, some models predicted the impending collapse of health systems (Ferguson et al. 2020). The comparison with influenza is instrumental to emphasizing that a focus on fatality rate might be considered ethically insufficient. The 1957 and 1968 pandemics had significant death tolls (Viboud et al. 2016; WHO 2011).
Noticeably, these tolls were not confined to the elderly population: for instance, in 1968 half the deaths in the UK and the US were among people younger than 65 years (Honigsbaum 2020). In contrast, COVID- 19 exhibits a more markedly skewed mortality distribution. Within a deontological approach, this skewing might be considered irrelevant. However, within a utilitarian framework, it should facilitate the estimate of the societal effects of nonpharmaceutical interventions.
It is surely difficult to compare different policy effects, most obviously on lives and livelihoods.
However, within a utilitarian framework, differences in life expectancy matter because maximization of good encompasses both considerations of length and quality of life. Bluntly put, the number of lives saved is not necessarily relevant; what is most relevant is how long these lives would be prolonged by the policy, as this is the parameter for estimating long-term good maximization (Savulescu, Persson, and Wilkinson 2020). A way to formalize this approach is by substituting the target of minimizing the number of lives lost with the target of minimizing the number of potential years of life lost: if average life
expectancy is 90 years, the death of a 50-year-old would contribute 40 years to the pool of lost years, while the death of an 85-year-old would only contribute 5 years. Unpalatable as it might seem, under this utilitarian approach not all lives count the same.
The same consideration would still hold under other ethical frameworks as well. Egalitarianism, for instance, maintains that all citizens should be granted equal rights (Dworkin 2002). This position can be interpreted to imply that all people have the right to live the same number of years, therefore
suggesting that, all other things being equal, public health policies should be targeted for the relative benefit of younger people. Prioritarianism, a version of utilitarism, contends that ethical decisions should prioritize the well-being of worse-off individuals (Parfit 1997). Given that young people are worse off in terms of years lived with respect to old people, prioritarianism would suggest that public health policies should be targeted for the relative benefit of youths. Considering that egalitarianism and prioritarianism are sometimes considered as opposed proposals with respect to considering individual differences as relevant to ethical decisions (see Hirose 2011), our point seems to hold across a wide range of ethical frameworks.
Precautionary Rationale
In a situation of treading uncertainty—in particular, in a state of epistemic ignorance concerning the nature of natural immunity and its lasting protection—totally curbing transmission in an untargeted fashion through such strategies as an indefinite lockdown or with local suppression would, in the absence of effective pharmaceutical interventions, create a population immunity scenario with a low pi similar to that of the initial stages of the health emergency, whereby the vulnerable subpopulation will be eventually
“culled” as soon as restrictions are, inevitably, relaxed. Within this context, the rationale of health system mitigation (HS mitigation, see figure 2) as a particular herd immunity strategy might be understandable.
This strategy seeks to simultaneously prevent health system collapse by keeping R under control; delay transmission through targeted nonpharmaceutical interventions until vaccines or effective drug therapies become available; and, crucially, slowly foster populationimmunity of the lower-risk members of the human population through the same targeted nonpharmaceutical interventions. This strategy might be particularly justified in the case of infections with high pandemicity and transmissibility. In this sense, health system mitigation is a policy with a surprisingly clear precautionary rationale—in fact, it takes into
consideration both the prospective failure of developing effective pharmaceutical interventions and, concomitantly, the prospective failure of building lasting population immunity through natural exposure.
Long-Termism
One problematic aspect of health system mitigation is that it allows death in the short term in order to save life in the long term. The policy clashes with our “presentist” cognitive bias—our tendency to focus prevention on the present or near future—but the ultimate justification of herd immunity
strategies is the actual maximization of good in the long term. Health system mitigation is in this sense a utilitarian policy focusing on long-term effects. In fact, it is important to remember that aiming to
minimize the short or medium-term death toll (either in terms of number of deaths, or even in terms of the estimated number of years of life lost) might engender a higher death toll in the long run (Figure 3iii), particularly when the long-term effects of nonpharmaceutical interventions turn out to be higher than expected.
The Ethical Framing of Public Health Policies
We have argued that the ethical feasibility of herd immunity strategies of infection control is dependent on a variety of policy indicators, chief among them the pandemicity of the infection, its estimated fatality rate and transmissibility, the availability or prospect of developing pharmaceutical interventions, as well as the nature of natural immunity. We have also unearthed some aspects of the utilitarian roots of herd immunity strategies of infection control. In so doing, our aim has been to facilitate the terms of a pivotal public debate that—as the current COVID-19 pandemic has clearly shown—has often been couched by politicians, media, and even “experts” in a distressingly simplistic way—namely, as a clash between moral degeneracy and decency. By taking into consideration different historical and epidemiological evidential sources, we believe that our conceptual analysis clarifies, at least, that herd immunity strategies of infection control are not necessarily the expression of a degenerate Malthusian ideology. Rather, what we have argued is that herd immunity strategies are morally objectionable only in so far as an ethical theory (most obviously utilitarianism) can be considered as such.
Although it is beyond the scope of this article to defend any specific ethical theory, it is
nonetheless hard to deny the relevance of a utilitarian perspective in public health contexts. Utilitarianism highlights the striking clash between local and global public health approaches, it is founded on the principle of impartiality, and it prescribes that the right policy is the one that maximizes the good for all moral agents, as the moral community of relevance is global. Utilitarianism is thus both long-termist and cosmopolitan, the opposite of approaches based on a hic et nunc or “here and now” motto, and in this sense, strategies of infection control that maintain or increase the unequal distribution of biomedical infrastructure and the unequal allocation of pharmaceutical interventions might be criticized from a utilitarian perspective. Thus, despite its often counter-intuitive and (for some at least) shocking moral implications, utilitarianism provides an important standpoint from which to evaluate public health responses in the context of future global health emergencies.
Acknowledgements
Davide Vecchi acknowledges the financial support of the FCT—Fundação para a Ciência e a Tecnologia (DL57/2016/CP1479/ CT0072; Grants N. UIDB/00678/2020 and UIDP/00678/2020). Giorgio Airoldi acknowledges the financial support of the Ministerio de ciencia e innovación, Gobi- erno de España (Grant N. PID2021-128835NB-I00 NORMABioMed: Normativity and Mechanistic Approach in the Philosophy of Biological and Biomedical Sciences, from Medicine to Animal Cog- nition).
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<Figure labels and legends>
Figure 1
Decision tree for the identification of an adequate strategy of infection control
Figure 2
Public health strategies interpreted in terms of effect on R
Figure 3
Comparisons between containment and mitigation strategies
Figure 3i - The option ‘Case isolation, home quarantine, social distancing of > 70s’ (blue line) corresponds to a mitigation strategy (Source: Adapted from Ferguson et al. 2020).
Figure 3ii – Evolution of R with respect to the adoption of different public health strategies. In the Malthusian case (red line), R is allowed to naturally fluctuate, starting from R
0and causing the “culling” of the vulnerable but also shortening the duration of the pandemic. In containment (blue line), p
cs are strengthened as soon as R increases above 1 and relaxed when R is under control, creating waves of infection and protracting the duration of the pandemic indefinitely until a vaccine or effective drugs are available. The mitigation strategy hereby represented (green line) uses p
cs in order to stably keep R slightly above 1. The curves are represented after the initial phases of the outbreak, particularly after the initial bout of p
cs have been implemented.
Number of deaths is proportional to the area below the curves.
Figure 3iii – Short-term and long-term deaths caused by adopting different public health strategies. Deaths are proportional to the area below the curves. A mitigation strategy might cause a higher death toll (area A) in the short-term, but the long-term death toll due to containment (area B) might exceed it, as containment tends to extend the duration of the epidemic in case p
iincreases through natural infection.
Table 1
Evidential basis during the different phases of the health emergency
Table 2
Possible public health targets and strategies to implement them during a pandemic
