Open access peer-reviewed chapter

Biological Determinants of Emergence of SARS-CoV-2 Variants

Written By

Ricardo Izurieta, Tatiana Gardellini, Adriana Campos and Jeegan Parikh

Submitted: 08 November 2021 Reviewed: 31 March 2022 Published: 19 May 2022

DOI: 10.5772/intechopen.104758

From the Edited Volume

Contemporary Developments and Perspectives in International Health Security - Volume 3

Edited by Stanislaw P. Stawicki, Ricardo Izurieta, Michael S. Firstenberg and Sagar C. Galwankar

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Abstract

In epidemic and pandemic circumstances, mutant RNA viruses go into a Darwinian selection of species with the predominance of the most transmissible, pathogenic, and virulent variants. Nevertheless, our current knowledge about the determinants of emergence of the new mutants is limited. The perspective chapter presents theoretical concepts related to biological determinants responsible for viral mutations or potential variant emergence. A scoping literature review was done in biomedical databases (PubMed, Medline) and google search engine with papers selected based about the book chapter. Public health and governmental agency websites were utilized for most recent information. Molecular determinants, the heterogenic herd immunity achieved by world populations, partial induced natural immunity by the disease, partial artificial immunity caused by incomplete immunization schedules, animal reservoirs, immunosuppression and chemical and biological antiviral therapies can result in genomic mutations combined with immunological selective pressure resulting in emergence of variants of concern. These variants could be resistant to current vaccines and monoclonal antibodies and can influence the future directions of the COVID-19 pandemic. This can be a threat to international health security and thus it is important to increase the genomic surveillance for mutations and research into modified vaccines and monoclonal antibodies against newer antigens to prevent the prolongation of the pandemic.

Keywords

  • SARS-CoV-2
  • COVID-19
  • variants
  • determinants

1. Introduction

At the time this chapter is being written, the world is still experiencing the Severe Acute Respiratory Syndrome Coronavirus −2 (SARS-CoV-2)/COVID-19 pandemic. The dominant circulating strain of the virus has gone under multiple changes during the pandemic. The initial ancestral strain gave way to the alpha strain which gave way to the delta and omicron strain, which are currently the dominating circulating strains [1]. In addition, there have been emergence of other variants of interests (VOIs) or variants of concern (VOC) such as beta, gamma, P1, P2, lambda, and mu which could be a threat to international health security [1]. The emergence of these variants suggests virus adaptations to various determinants, responsible for the selection of these mutated variants.

This perspective chapter considers different biological determinants capable to contribute to viral mutations and thereby, emergence of new variants and the potential impact of this on the tools (vaccines and antibody therapy) against the SARS-CoV-2. However, it is important to note the determinants mentioned here may not be an exhaustive list of potential mechanisms to induce mutations. This chapter is based on theoretical and fundamental scientific concepts known to be involved from past outbreaks or current case reports from the ongoing pandemic. It is known that biological and environmental, among other determinants may drive viral mutations by different processes or mechanisms. Furthermore, by considering the roles these potential determinants may or already contribute to future SARS-CoV-2 variants we can improve global pandemic responses, saves lives, and contribute to the international health security.

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2. Methods

A scoping literature review in search for current topics associated with SARS-CoV-2 or COVID-19 viral replication, adaptations, and biological determinants known to cause variant emergence (e.g., molecular factors, animal reservoirs, immunological factors, etc.) was conducted in biomedical databases such as PubMed, MEDLINE, and Google search engine. Additionally, World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), and Food and Drug Administration (FDA) websites were relied upon to get the most recent information related to content of the chapter. Papers related to the biological determinants commonly associated with viral replication, recombination, adaptation, and immunological seletion were chosen based on the scope of the chapter. Biological determinants of variant emergence and their possible or current implications on the COVID-19 pandemic are presented below.

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3. Biological determinants of SARS-CoV-2 variants emergence

3.1 Molecular determinants

3.1.1 Viral replication/recombination

SARS-CoV-2, a beta coronavirus, is a RNA virus using an error-prone RNA-dependent RNA polymerase for replication [2]. The virus encodes a proofreading 3′ exonuclease (nsp140) but despite this activity, it accumulates genomic changes having a potential to create heterogenous mixture of antigenic proteins resulting in emergence of new variants [2]. The genomic mutation rate of SARS-CoV-2 in humans is estimated at 0.8–2.38 x 10−3 nucleotide substitutions per site per year with experimental data suggesting the virus capable of mutating and accumulating changes when it encounters new cell types [3, 4]. Thus, high viral load means high viral replication and thus higher potential for genomic errors due to replication. Along with the replication associated changes, dramatic changes in the virus phenotype can be observed due to genomic recombination in a cell infected with more than one coronavirus [2, 5]. Till now eight recombination events have been observed in SARS-CoV-2 but the frequency of such events is not known [6]. Random errors accumulated during replication/recombination along with population level natural and vaccine induced immunity, play an important role in Darwinian selection of these variants [2].

3.2 Zoonotic determinants

Although the exact precursor of SARS-CoV-2 is unknown, it is established it is of wild origin. The initial December 2019 outbreak in Wuhan, China was linked to the seafood and live animal city market [7]. This market was reported to trade poultry, snakes, hedgehogs, and other wild animals [8].

The different SARS-CoV-2 variants detected in animals including dogs, cats, tigers, lions, minks, and gorillas all had genomes related to the human variant yet had additional mutations. The presence and infection of these animal reservoirs with SARS-CoV-2 virus also increases the possibility of viral mutations/recombinations and emergence of variants. Zoonotic reservoirs capable of carrying and providing an environment for viral multiplication are listed below.

3.2.1 Bats and pangolins

At the beginning of the pandemic bats were declared as the possible SARS-CoV-2 reservoir because of the genomic similarities with other coronaviruses infecting bats [9]. During the initial molecular epidemiological investigations, it was found the SARS-CoV-2 genome had similarities with coronaviruses isolated in Rhinolophus bats [10]. In Cambodia, a coronavirus with 93% genomic similarities was detected in horseshoe bats Rhinolophus shameli, but this specific bat species does not reside at the location of original SARS-CoV-2 outbreak [11, 12]. Similarly, 200 novel coronaviruses have been identified among bats worldwide [13]. Furthermore, bats are reservoirs for other emerging pathogens like Ebola, Nipah, rabies, Hendra, and rotaviruses [14]. Nevertheless, there are three events contradicting the hypothesis that bats were the initial reservoir from which SARS-CoV-2 jumped into other species: 1) during the beginning of the pandemic bats were hibernating; 2) bats were not sold at the animal market during the initial outbreak; and 3) although other bat coronaviruses have up to 96% genomic similarities, SARS-CoV-2 has not been detected among bat species [15].

The fist isolated variant of SARS-CoV-2 was identified as pangolin-CoV because of similarities with coronaviruses isolated in the carcasses of Malayan pangolins Manis javanica [16]. SARS-CoV-2 has 89% nucleotide and 98% amino acid similarities with the pangolin coronavirus genome [17]. Moreover, recent investigations done in other pangolin species conclude the pangolin coronavirus can be the precursor of SARS-CoV-2 because of their high genetic variation and given no coronaviruses were found in pre-COVID-19 pangolin samples [18].

3.2.2 SARS-CoV-2 variants in domestic and wild animals

The virus has been detected in domestic cats and dogs [14]. Therefore, the transmission from humans to domestic animals is plausible. Specifically, the B.1.1.7 (Alpha) variant has been identified in domestic cats as well as in domestic dogs [19]. In contrast it appears that cattle, goats, and sheep are not infected by the virus [20].

Among animals kept in zoos the virus has been detected in gorillas, tigers, pumas, cougars, Asian small-clawed otters, and snow leopards. The genetic variability of SARS-CoV-2 is evident from the 9 genomes identified in tigers, lions, and their keepers [21]. The B.1.1.7 (Alpha) variant has been detected in gorillas, lions, leopards, and tigers [20, 22]. In another study the B.1.617.2 (Delta) variant was reported in Asiatic lions from India [23]. Farmed wild animals have been diagnosed with SARS-CoV-2. Specifically, SARS-CoV-2 has been identified in American minks (Neovison vison) and in ferrets (Musteal furo) [20].

Therefore, this possibility of emergence of new variants is ever present due to SARS-CoV-2 spread to different ecological environments and newer animal reservoirs resulting in a subsequent risk for spillover into humans and other species.

3.3 Immunological determinants

3.3.1 Herd immunity

Lately, the phrase “Herd Immunity” is constantly brought up in news outlets, in commentaries, opinion pieces, and peer-reviewed articles. First introduced almost 100 years ago, it only recently gained popularity [24]. Although Herd Immunity is now a widely accepted concept, it may take on multiple meanings, each slightly different than the next. Some researchers consider Herd Immunity a threshold of the proportion of immune individuals that leads to a decline in infections or outbreaks [25, 26]. While others may use it to describe the proportion immune to a specific infection among a population or refer to it as a protective immunity pattern [25]. Herd Immunity is most referred to as the reduction of risk, of an infection, to susceptible individuals by the proximity and presence of immune individuals [25]. Herd Immunity may be used interchangeably as “indirect protection” or “herd effect”. Regardless of the definition variations, Herd Immunity leads to one outcome – the reduction of infection incidence. This concept, in conjunction with vaccines, has contributed to some of the most important public health achievements in the 20th and 21st century such as the smallpox eradication, polio elimination, and other vaccine-preventable diseases. This section explores the concepts behind Herd Immunity and current and future implications during the COVID-19 pandemic.

3.3.1.1 Theories which constructed herd immunity

Topley and Wilson (1923) were the first to coin the term “Herd Immunity” and specifically look at host resistance in comparison with mass infection. After first mention of Herd Immunity, the term and overall concept started appearing and developing soon after [27, 28, 29]. Dudley [27] explored the idea of a “herd” or community and how it could be defined. He defined the idea of “infection pressure” (i.e., fundamental parasite factor) which may be determined by the infectious agent distribution frequency rates which is in the members of the herd [27]. He claimed, infectious pressure reacts with Herd Immunity, the increase of one increases the other and then decreases it to zero. This introduced the idea of needing a minimum amount of Herd Immunity, a threshold, in order to keep the infectious pressure at zero. Furthermore, he mentioned those two factors contributed to the type, quantity, infection speed (i.e., now known as R0) and the frequency and distribution of cases and their severity [27].

Yet Herd Immunity had one large limitation—to provide protection, a high proportion of the population must be immune to the pathogen. Before immunizations individuals had to survive and pass the pathogen to become immune; depending on the pathogen, likelihood of survival and being left with life-altering morbidities varied. However, as concepts behind Herd Immunity were evolving, vaccinations were becoming a staple of public health practice, allowing a large proportion of the population to be safely immunized against specific pathogens. Vaccination allowed for the fulfillment of Herd Immunity at a much faster rate and safer manner. This allowed for the concepts to be turned into mathematical possibilities.

Before vaccination and Herd Immunity there were two main hypotheses as to why outbreaks would end even though not all susceptible were affected: (1) the agent naturally loses virulence (2) the dynamics between susceptible, infected, and immune [26]. The later hypothesis, prevailed with its mathematical idea of “mass action principle” (MAP) [26]. This principle was based on a simple logical argument in favor of indirect protection given by Herd Immunity and became an epidemiological theoretical cornerstone. Eventually three theories converged into one general theory driving Herd Immunity: MAP, case reproduction rates (later called base reproductive rates [BRR]), and the Reed-Frost heterogenous population simulation approach [26]. The current formula used for Herd Immunity is H = 1–1/R0 = (R0–1)/R0, where R0 is the BRR. H is the Herd Immunity threshold, the proportion of immunes needed in order to reduce incidence and R0 is derived from the duration of contagiousness of an infected individual, the likelihood of infection per contact between a susceptible person and an infectious person or vector, and the contact rate [30]. The BRR serves as an indicator of the contagiousness of an infectious agent—the higher the R0, the more transmissible. An R0 > 1 indicates an outbreak will continue, while a R0 < 1 indicates the end of an outbreak, if R0 = 1 then the outbreak is stable [30]. In novel outbreaks, where everyone is susceptible the R0 defines the infectiousness of a pathogen. However, as individuals pass the infection or become immunized, the number of susceptible decreases and immune increases, and although this does not technically reduce the BRR, because the definition of R0 assumes a completely susceptible population, one can use the effective reproduction number (R) in lieu, which is similar to R0 but does not assume complete population susceptibility and, thus, can be estimated with populations with immune members [30]. Efforts aimed at reducing the number of susceptible persons through vaccination would result in a reduction of the R value, rather than R0 value.

3.3.1.2 Herd immunity in the context of COVID-19

Currently there are multiple vaccines approved internationally for human use and immunization campaigns are urging communities to get vaccinated, therefore reducing the number of susceptible in hopes to achieve herd immunity. However, there are multiple factors to consider in achieving herd immunity from the SARS-CoV-2 virus.

Originally, with an estimated BRR of 2–3, researchers estimated the proportion of the population needed to be immunized to induce Herd Immunity around 50–67% [31, 32, 33]. Since then, the emergence of new SARS-CoV-2 variants, most famously the Delta variant, studies suggest a higher BRR (>5) [34, 35] than the alpha variant (2–3) [31, 32, 33, 36, 37, 38, 39] increasing the vaccination/immune threshold needed in order to achieve a protective effect. An increase in the necessary number of individuals vaccinated propose additional hurdles in reaching Herd Immunity, with the ever-increasing anti-vax movement or individuals acting as “freeloaders” (i.e., individuals who are not vaccinated, yet expect to be protected by the rest of the community being vaccinated).

Secondly, future SARS-CoV-2 variants may mutate enough where the protection offered by the currently available vaccines or natural immunity may no longer suffice. The emergence of the Delta variant showed a reduced vaccine effectiveness compared to the previous variants, which the vaccines were developed from [40, 41]. While currently approved vaccines still provide significant protection from the Delta variant for reduced risk of infection and disease severity, the reduction in vaccine effectiveness is alarming. If emerging variants significantly or completely evade the protection offered by current vaccines or natural immunity, individuals may no longer fall under the immune proportion of the population. An example of this possible situation was reported in Manaus, Brazil, where by December 2020 the population was estimated to have naturally achieved the herd immunity threshold (i.e., before vaccinations were approved and available), estimated at 67%, yet experienced a wave of hospitalizations in January 2021 [42]. This case study further highlighted the limitations with calculating Herd Immunity. Possible reasons for the Manaus outbreak were an overestimation of the immune population, a possible waning immune response, mutants capable of evading responses from previous natural infection, and mutants may have higher transmissibility than previously circulating lineages [42]. Future scenarios where Herd Immunity may not be achievable or severely reduced would be staggering in relation to vaccination campaigns and reaching herd immunity—a grave threat to international health security.

3.3.2 Artificial immunization/natural infection

All COVID-19 vaccines authorized or have received emergency use authorization (EUA) by FDA, EU/EEA, or WHO require a two-dose schedule except for the Janssen vaccines. All these vaccines require a period of 21 days to 12 weeks spacing between the primary and secondary dose [43]. In the early phase of the pandemic to reduce widespread community transmission, logistical issues, and shortages, many countries (e.g., UK, Canada) elected to delay the second dose in the population, thereby increasing the number of individuals with at least one dose. Policies such as the aforementioned in conjunction with waning of immunity after SARS-CoV-2 natural infection may result in large groups of people with only partial immunity against SARS-CoV-2 [43].

The Darwinian selection of variants with mutations for immune escape and its transmission in the community will depend on substantial selection pressure [44]. The greatest potential for the emergence of these immune escape mutations will be in those hosts with highest viral loads (increased mutations) while the greatest selection pressure will be in those with strongest immunological response [2, 44]. The level of immunological protection conferred after first dosage is dependent on the type of vaccine product in addition to the individual characteristics and variant [43]. In individuals with poor immunological response after first dose, there is potential for greater infection burden [44]. These individuals will have higher assumed rates of evolutionary adaptation because of higher viral load and replication. In those individuals with strong but partial immunological response, the infection rates would be lower but evolutionary selection pressure would be large, resulting in high rates of viral adaptations. Previous phylogenic research done on influenza viruses suggested the viral evolution and emergence of immune escape variants is maximum in those individuals with partial immunity (i.e., intermediate levels of selection and viral replication) [45]. Thus, having partially immunized individuals could lead to short-term benefits such as reduced peak of disease but in long term can result in higher infection burden and substantially higher risk of viral evolution to immune escape variants [44].

3.3.2.1 Chemical and biological therapy

Several monoclonal antibodies were developed against the spike protein of SARS-CoV-2 to block the transmission of the virus inside the cells [46]. A single (Bamlanivimab) or combination monoclonal antibodies (Bamlanivimab/Etsevimab or Casirivimab/Imdevimab) received EUA for therapeutic management of SARS-CoV-2 and post-exposure prophylaxis [47, 48]. In theory, administration of monoclonal antibody therapy can alter the immunological selective pressure resulting in viral adaptation for the emergence of variants resistant to one or more monoclonal antibodies [49, 50]. This potential for the emergence of monoclonal antibody resistance has been observed in immunocompromised patients [51, 52, 53]. In trials for monoclonal antibodies, mutations resistant to antibodies were detected by next generation sequencing (NGS) assay in 10% of the patients receiving therapy with its transmissibility not determined [54]. Recently, a Wisconsin (WI) study using Bamlanivimab described the emergence of new resistant mutation E484K with further transmission to nearby contacts [55]. The emergence of variants with reduced susceptibility to neutralizing antibodies after polyclonal convalescent plasma therapy provides further proof of the effect of immunological selective pressure on emergence of new variants [49, 56]. It is conceivable, the widespread use of monoclonal or polyclonal antibody therapy may reduce barriers for the emergence of resistant variants to these antibodies which can further transmit to wider communities, potentially becoming a variant of concern. A widespread genomic surveillance is warranted to identify and control the spread of these antibody resistant variants [55].

3.3.3 Immunosuppressed individuals

During evaluation of the efficacy of vaccines, subjects with inhered or acquired immunodeficiencies are excluded from clinical trials. Therefore, there are limited information about the immunogenicity of SARS-CoV-2 vaccines among these patients. Field studies evaluating the effectiveness of COVID-19 vaccines demonstrate that immunocompromised subjects mount a lower antibody response when compared with immunocompetent subjects [57].

Viruses are highly sophisticated molecular machines that can go into an adaptive evolution in the human host establishing a latent reservoir, integrating into the human genome, or causing a chronic infection. Viruses such as hepatitis B virus, hepatitis C virus, and human immunodeficiency virus go into latent stage evading the host immune response while other viruses like Ebola can persist in immune sanctuaries [58]. Considering COVID-19 is an infection of pandemic proportions, it is plausible to think human host immune pressure can contribute to SARS-CoV-2 genetic diversity and selection with phenotypic changes [59]. Consequently, it is necessary to address the relationship between viral persistence in the immunosuppressed host. As a matter of fact, one of the hallmarks of SARS-CoV-2 is its capacity to co-opt various cellular factors and machineries damping the immune response [60]. Although not yet demonstrated, it is plausible to suggest SARS-CoV-2 may establish a latent infection or remain in immune sanctuary. However, SARS-CoV-2 persistence in the immunocompromised patient is well documented [61, 62], with viral persistence reported among cancer patients and transplant recipients [61, 63, 64, 65, 66, 67]. Viral coronavirus RNA has been detected up to ~60 days in cancer patients that developed respiratory symptoms. Moreover, the longest persistence of coronavirus RNA is recorded at 151 days in a patient with anti-phospholipid syndrome, which suggest these pathogens are of the opportunistic characteristic [68, 69, 70]. In the aforementioned patient, there were 31 substitutions and 3 deletions identified in the genome sequencies from the isolated agent. There were 12 mutations in the spike protein including 7 in the receptor-binding domain segment. Due to severe pulmonary complication the patient died [71]. Increased viral changes were also detected in another immunocompromised patient, whose disease prolonged for 101 days, where viral changes were limited during the first 60 days but increased after receiving plasma form a convalescent patient at days 63 and 65. Moreover, rapid shifts were observed in the spike area during the last days of the monitoring [71]. In another case-series, three patients receiving chimeric antigen receptor (CAR) T cells because of B-cell acute lymphocytic leukemia, showed multiple escape SARS-CoV-2 variants [71]. Consequently, like SARS-CoV-2 longer persistence in immunosuppressed patients, immunosusceptible elderly patients may also harbor the virus for prolonged periods compared to immunocompetent patients. Gaspar-Rodriguez et al. enunciated in 2021 that SARS-CoV-2 and other coronaviruses potentially establish a long-term, non-productive persistent infection in epithelial, myeloid, and neural host cells until viral clearance is achieved [62]. Prolonged COVID-19 in the immunosuppressed patient can be a determinant of the development of SARS-CoV-2 variants which can be spread among the general population [71]. This persistence of the virus in different types of immunosuppression are listed below.

3.3.3.1 SARS-CoV-2 in Cancer patients

Cancer patients are in immunodepression conditions because of the malignancy and oncological treatments like chemotherapy, radiotherapy, transplants, and immunotherapy. Patients with lung, blood, and bone marrow carcinomas are at a higher risk of harboring the virus for prolonged periods when compared with other cancer patients [72]. Patients with chronic lymphocytic leukemia (CLL) have shown inadequate levels of antibodies as well as cellular immune response [73]. These inadequate immune responses in CLL patients correlates with severe and prolonged forms of COVID-19 and has been supported by late conversion to negative PCR monitoring tests and longer hospitalizations [74]. The impaired humoral and cellular immune response in the CLL patients make these patients long term shedders of SARS-CoV-2 until infection is passed. One case study showed a COVID-19 positive CLL patient having persistent positive PCR test for 105 days after diagnosis [63]. Moreover, during this period a continuous variability in predominant viral variants was observed [63]. This delay in viral clearance in COVID-19 patients has been observed in patients receiving intravenous immunoglobulins as well as in those with hypertension [75].

3.3.3.2 SARS-CoV-2 in organ transplant patients

Organ transplant recipients are patients with long-lasting immunosuppression; therefore, organ transplant recipients have been declared subjects with high risk for severe COVID-19. When COVID-19 positive liver transplant patients were compared with COVID-19 immunocompetent patients, the transplant recipients showed lower prevalence of antibodies against SARS-CoV-2, as well as a faster antibody decline [57]. Regarding viral shedding, immunocompetent asymptomatic COVID-19 infection subjects experience a faster viral clearance when compared with symptomatic individuals [76]. Kidney transplant patients with immunosuppression showed a longer shedding of the virus, of more than 28 days, which was correlated with a prolongation of symptoms [77].

3.3.3.3 SARS-CoV-2 in elderly patients

It is demonstrated SARS-CoV-2 causes highest mortality among elderly populations. Also, viral shedding is increased, enhancing the spread of the virus as it was observed in the increased transmission in nursing homes. An explanation for these complications may be due to the elderly immune system being less competent than in young populations. In the elderly, it appears the production of cytokine and T-cells production worsen the inflammation process especially among those with comorbidities [78]. The increased shedding of SARS-CoV-2 is associated with a more severe clinical presentation and higher viral load peaks [79, 80, 81]. The delayed viral clearance in elderly patients’ airways can be explained by a decreased respiratory muscle function and diminished mucociliary function [79, 82].

3.3.3.4 SARS-CoV-2 in patients with corticosteroid treatment

Although corticosteroid therapy is being used to ameliorate the inflammation process, the use of corticosteroids at an early stage can suppress the immune cells which can prolong the clearance of the virus as well as its shedding. In a randomized study in the patients without respiratory failure, the methylprednisolone group showed a median viral shedding of 10 days vs. 6 days in the control group [83].

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4. Discussion

The molecular mechanisms of viral replication, multiple animal reservoirs, and immunological selection methods have the possibility for viral evolution to immune escape variants (Figure 1). Such epidemiological and evolutionary mechanisms are already seen in the emergence of different VOC worldwide [44].

Figure 1.

Biological determinants of emergence of SARS-CoV-2 variants. An infection of SARS-CoV-2 in humans results in viral replication. In born errors of viral replication or genomic recombination can result in viral mutations. People with natural/artificial immunity will neutralize the non-mutated virus but has non-neutralizing immune response against mutated variant. Mutated SARS-CoV-2 thus undergoes this immunological selection for emergence of SARS-CoV-2 variant. Infection in animals with different host cell machinery led to mutated SARS-CoV-2 with potential for species jump and spillover into humans and emergence of SARS-CoV-2 variant.

4.1 Impact of emergence of new variants on vaccine

Since the beginning of the pandemic, VOC having selective advantage of more transmissibility and resistance to natural or vaccine induced immunity have been evolving and supplanting previously circulating strains [43, 84]. The emergence of these VOC affects the effectiveness of vaccines in both partially and fully immunized individuals [43]. In vitro studies demonstrated lower neutralization capacity against all VOC compared to ancestral strains [41, 85, 86]. Based on evidence available for all vaccine types, partially immunized individuals have a lower degree of protection against symptomatic infection, moderate disease, and probable transmission with Delta VOC than Alpha VOC. In general, the vaccine effectiveness for all variants against symptomatic disease was much lower than those reported against severe diseases. The fully immunized individuals confer nearly equivalent protection for all outcomes against Alpha to that of Delta variants [43]. Table 1 summarizes the results of vaccine effectiveness by type of vaccine, outcome, and VOC.

VariantOriginalOriginalAlphaBetaGammaDeltaDelta
VaccineSISDSISISISISD
Comirnaty (Pfizer/BioNTech)95%100%89.5%75%61%87.9%96%
SpikeVax (Moderna)94.1%100%↓ Ant Neu↓ Ant Neu↓ Ant Neu↓ Ant Neu
Vaxzeria (AstraZeneca)70.4%81.3%66.1%10.4%↓ Ant Neu59.8%92%
Johnson & Johnson74.2%85.4%64%↓ Ant Neu
Cansino90–95%
Sputnik V91.6%100%No difference↓ Ant Neu
Sinovac78.1%100%↓ Ant Neu↓ Ant Neu↓ Ant Neu
Soberana (Cuba)62%

Table 1.

Vaccine effectiveness of two dose of vaccines against symptomatic infection and severe disease caused by non-VOCs, alpha, and Delta VOCs.

SI, symptomatic disease; SD, Severe disease.

The emergence of new vaccine-resistant variants may necessitate the development of modified vaccines based on new sequences to prevent the prolonged circulation of vaccine-resistant variants [84]. It is important to conduct studies of these modified vaccines to determine its efficacy in developing a neutralizing immunological response against vaccine-resistant variants. This research is important despite the deployment of these newer vaccines not required until there is evidence of failure of current vaccines. Once the modified vaccines are introduced the molecular and immunological determinants of viral adaptation will necessitate to repeat the cycle of monitoring for even newer variants that might require further modifications in the antigenic sequence in vaccines.

4.2 Impact of emergence of new variants antibody therapy

Like vaccines, the viral adaptations seen against the monoclonal antibody therapy can complicate the deployment of these treatments at large scale in the general population [55]. The initial widespread use of Bamlanivimab as a single therapy and later removal due to epidemiologic trend further provides evidence for judicious use of monoclonal antibody therapy [87]. The usage of cocktail of antibodies should in theory reduce the probability of random selection of resistant variants however it does not totally remove this possibility [55]. This combined with monoclonal antibodies not preventing transmission, not providing immediate cure, lacking durable immunity, and potentially leading to antibody strains with some cross-resistance against vaccine or natural-acquired immunity suggests the need for caution before widespread usage of monoclonal antibody therapy [41, 55]. Increasing the scale of surveillance for mutations along with research into monoclonal antibodies against newer antigens should be adopted if the scale of use of monoclonal antibody has to be expanded [55].

Thus, the determinants of emergence of SARS-CoV-2 variants necessitates the inclusion of epidemiological, evolutionary, clinical, animal, and in vitro data related to changing antigenic sequences, vaccine and monoclonal antibody efficacy in the decision making of which antigens to be included in vaccines or targeted for therapy [84]. Lastly, it is important to recognize the limitations of the concepts presented in this chapter. This is a prospective chapter piece using concepts and theoretical ideologies commonly attributed to variant emergence. The inclusion of the determinants presented are a combination of expert knowledge on behalf of the authors and a scoping literature review conducted on SARS-CoV-2 and its current variants, therefore, this chapter is not meant to replace a systematic review.

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5. Conclusion

This chapter presents theoretical and current determinants for variant emergence, specifically for SAR-CoV-2. The emergence of different VOC through the evolutionary cycle of the SARS-CoV-2 virus during the current pandemic (2019- ongoing) makes it important to understand the biological determinants of new emerging variants. The inherent errors in viral replication in humans and animal reservoirs combined with immunological selective pressure result in the Darwinian selection of variants of SARS-CoV-2 with potential for higher transmissibility and resistance to vaccine-based immunity or monoclonal antibodies. The different types of vaccines and associated immune response, partial immunization, waning of immunity, and heterogenicity in worldwide immunity results in wide differences in immunological selective pressure based on regions and virus evolutions. The global inequality in vaccine distribution further complicates this immunological selection pressure. The epidemiological and evolutionary cycle can result in viral adaptations with potential for selection of variants with higher transmissibility and immune escape properties. The emergence of these dangerous new variants can influence vaccine and antibody therapy effectiveness necessitating modifications in antigenic sequences used in production. This emergence of novel variants thus is a concern for international health security with a potential for furthering the COVID-19 pandemic and its associated negative health, economic, and social effects.

References

  1. 1. World Health Organization. Tracking SARS-CoV-2 variants. 2021. Available from: https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/ [Accessed 31-10-2021]
  2. 2. Banerjee A, Mossman K, Grandvaux N. Molecular determinants of SARS-CoV-2 variants. Trends in Microbiology. 2021;29(10):871-873
  3. 3. Massimo A.et al. Mutation rate of SARS-CoV-2 and emergence of mutators during experimental evolution, Evolution, Medicine, and Public Health. 2022;10(1):142-155
  4. 4. De Maio N et al. Mutation rates and selection on synonymous mutations in SARS-CoV-2. Genome Biology and Evolution. 2021;13(5):1-14
  5. 5. Lai MM et al. Recombination between nonsegmented RNA genomes of murine coronaviruses. Journal of Virology. 1985;56(2):449-456
  6. 6. Pollett S et al. A comparative recombination analysis of human coronaviruses and implications for the SARS-CoV-2 pandemic. Scientific Reports. 2021;11(1):17365
  7. 7. Islam A, et al. Transmission dynamics and susceptibility patterns of SARS-CoV-2 in domestic, farmed and wild animals: Sustainable One Health surveillance for conservation and public health to prevent future epidemics and pandemics. Transboundary and Emerging Diseases. 2021 Oct:1-21. https://doi.org/10.1111/tbed.14356
  8. 8. Montagutelli X et al. The B1.351 and P.1 variants extend SARS-CoV-2 host ange to mice. bioRxiv. 2021:1-16. https://doi.org/10.1101/2021.03.18.436013
  9. 9. Ashour HM et al. Insights into the recent 2019 novel coronavirus (SARS-CoV-2) in light of past human coronavirus outbreaks. Pathogens. 2020;9(3):186
  10. 10. Wong G et al. Zoonotic origins of human coronavirus 2019 (HCoV-19 / SARS-CoV-2): Why is this work important? Zoological Research. 2020;41(3):213-219
  11. 11. Delaune D et al. A novel SARS-CoV-2 related coronavirus in bats from Cambodia. Nature Communications. 2021 Nov 9;12(1):6563
  12. 12. Lin XD et al. Extensive diversity of coronaviruses in bats from China. Virology. 2017;507:1-10
  13. 13. Chen L et al. DBatVir: The database of bat-associated viruses. Database. 2014;2014:bau021
  14. 14. Islam A et al. Epidemiology and molecular characterization of rotavirus a in fruit bats in Bangladesh. EcoHealth. 2020;17(3):398-405
  15. 15. Jo WK et al. Potential zoonotic sources of SARS-CoV-2 infections. Transboundary and Emerging Diseases. 2021;68(4):1824-1834
  16. 16. Liu P et al. Are pangolins the intermediate host of the 2019 novel coronavirus (SARS-CoV-2)? PLoS Pathogens. 2020;16(5):e1008421
  17. 17. Zhang C et al. Protein structure and sequence reanalysis of 2019-nCoV genome refutes snakes as its intermediate host and the unique similarity between its spike protein insertions and HIV-1. Journal of Proteome Research. 2020;19(4):1351-1360
  18. 18. Lee J et al. No evidence of coronaviruses or other potentially zoonotic viruses in Sunda pangolins (Manis javanica) entering the wildlife trade via Malaysia. EcoHealth. 2020;17(3):406-418
  19. 19. Hamer SA et al. SARS-CoV-2 B.1.1.7 variant of concern detected in a pet dog and cat after exposure to a person with COVID-19, USA. Transboundary and Emerging Diseases. 2022 May;69(3):1656-1658
  20. 20. World Organization for Animal Health, Special Survival Commission, and W.H.S. Group, Guidelines for Working with Free-Ranging Wild Mammals in the era of the COVID-19 Pandemic. 2020
  21. 21. McAloose D et al. From people to Panthera: Natural SARS-CoV-2 infection in tigers and lions at the Bronx zoo. MBio. 2020;11(5):1-13
  22. 22. Service, A.a.P.H.I. Confirmation of COVID-19 in Otters at an Aquarium in Georgia. U.S. U.S. Department of Agriculture; 2021
  23. 23. Mishra A et al. SARS-CoV-2 Delta Variant among Asiatic Lions, India. Emerging Infectious Diseases. 2021;27(10):2723-2725
  24. 24. Topley WW, Wilson GS. The spread of bacterial infection. The problem of herd-immunity. The Journal of Hygiene. 1923;21(3):243-249
  25. 25. Fine P, Eames K, Heymann DL. "herd immunity": A rough guide. Clinical Infectious Diseases. 2011;52(7):911-916
  26. 26. Fine PE. Herd immunity: History, theory, practice. Epidemiologic Reviews. 1993;15(2):265-302
  27. 27. Dudley SF. Human adaptation to the parasitic environment. Proceedings of the Royal Society of Medicine. 1929;22(5):569-592
  28. 28. Halliday JL. The epidemiology of poliomyelitis. Glasgow Medical Journal. 1931;115(3):121-134
  29. 29. Stocks P. Infectiousness and immunity in regard to chickenpox, whooping-cough, diphtheria, scarlet fever and measles. Proceedings of the Royal Society of Medicine. 1930;23(9):1349-1368
  30. 30. Delamater PL et al. Complexity of the basic reproduction number (R(0)). Emerging Infectious Diseases. 2019;25(1):1-4
  31. 31. Kwok KO et al. Herd immunity - estimating the level required to halt the COVID-19 epidemics in affected countries. Journal of Infection. 2020;80(6):e32-e33
  32. 32. Randolph HE, Barreiro LB. Herd immunity: Understanding COVID-19. Immunity. 2020;52(5):737-741
  33. 33. Syal K. COVID-19: Herd immunity and convalescent plasma transfer therapy. Journal of Medical Virology. 2020;92(9):1380-1382
  34. 34. Dyer O. Covid-19: Delta infections threaten herd immunity vaccine strategy. BMJ. 2021;374:n1933
  35. 35. Liu Y, Rocklöv J. The reproductive number of the Delta variant of SARS- CoV-2 is far higher compared to the ancestral SARS-CoV-2 virus. Journal of Travel Medicine. 2021;28(7):1-3
  36. 36. Billah MA, Miah MM, Khan MN. Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence. PLoS One. 2020;15(11):e0242128
  37. 37. Chen J et al. Herd immunity and COVID-19. European Review for Medical and Pharmacological Sciences. 2020;24(8):4064-4065
  38. 38. Griffin S. Covid-19: Herd immunity is “unethical and unachievable,” say experts after report of 5% seroprevalence in Spain. BMJ. 2020;370:m2728
  39. 39. Jung F et al. Herd immunity or suppression strategy to combatCOVID-19. Clinical Hemorheology and Microcirculation. 2020;75(1):13-17
  40. 40. Lopez Bernal J et al. Effectiveness of Covid-19 vaccines against the B.1.617.2 (Delta) variant. New England Journal of Medicine. 2021;385(7):585-594
  41. 41. Planas D et al. Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization. Nature. 2021;596(7871):276-280
  42. 42. Sabino EC et al. Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence. Lancet. 2021;397(10273):452-455
  43. 43. European Center for Disease Control and Prevention. Partial COVID-19 Vaccination, Vaccination Following SARS-CoV-2 Infection and Heterologous Vaccination Schedule: Summary of Evidence. ECDC: Stockholm; 2021
  44. 44. Saad-Roy CM et al. Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes. Science. 2021;372(6540):363-370
  45. 45. Grenfell BT et al. Unifying the epidemiological and evolutionary dynamics of pathogens. Science. 2004;303(5656):327-332
  46. 46. Lloyd EC, Gandhi TN, Petty LA. Monoclonal antibodies for COVID-19. JAMA. 2021;325(10):1015-1015
  47. 47. U.S. Food and Drug Adminsitration. FDA Authorizes Monoclonal Antibodies for Treatment of COVID-19. 2020
  48. 48. U.S. Food and Drug Adminsitration, FDA authorizes bamlanivimab and etesevimab monoclonal antibody therapy for post-exposure prophylaxis (prevention) for COVID-19. 2021
  49. 49. Colson P et al. A possible role of Remdesivir and plasma therapy in the selective sweep and emergence of new SARS-CoV-2 variants. Journal of Clinical Medicine. 2021;10(15):3276
  50. 50. Kreuzberger N et al. SARS-CoV-2-neutralising monoclonal antibodies for treatment of COVID-19. Cochrane Database of Systematic Reviews. 2021;9(9):Cd013825
  51. 51. Jensen B et al. Emergence of the E484K mutation in SARS-COV-2-infected immunocompromised patients treated with bamlanivimab in Germany. The Lancet Regional Health–Europe. 2021;8:100164
  52. 52. Lohr B et al. Bamlanivimab Treatment Leads to Rapid Selection of Immune Escape Variant Carrying the E484K Mutation in a B.1.1.7-Infected and Immunosuppressed Patient. Clinical Infectious Diseases. 6 Dec 2021;73(11):2144-2145
  53. 53. Peiffer-Smadja N et al. Emergence of E484K mutation following Bamlanivimab monotherapy among High-risk patients infected with the alpha variant of SARS-CoV-2. Viruses.2021;13(8):1642
  54. 54. Chen P et al. SARS-CoV-2 neutralizing antibody LY-CoV555 in outpatients with Covid-19. New England Journal of Medicine. 2020;384(3):229-237
  55. 55. Sabin AP et al. Acquisition and onward transmission of a SARS-CoV-2 E484K variant among household contacts of a bamlanivimab- treated patient. medRxiv. 2021: 1-14. https://doi.org/10.1101/2021.10.02.21264415
  56. 56. Andreano E et al. SARS-CoV-2 escape from a highly neutralizing COVID-19 convalescent plasma. Proceedings of the National Academy of Sciences. 2021;118(36):e2103154118
  57. 57. Deborska-Materkowska D, Kaminska D. The immunology of SARS-CoV-2 infection and vaccines in solid organ transplant recipients. Viruses. 2021;13(9):1879
  58. 58. Zhou Y et al. Viral (hepatitis C virus, hepatitis B virus, HIV) persistence and immune homeostasis. Immunology. 2014;143(3):319-330
  59. 59. Centers for Disease Control and Prevention. Science Brief: Emerging SARS-CoV-2 Variants. 2021. Available from: https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/scientific-brief-emerging-variants.html [Accessed 30-10-2021]
  60. 60. Desimmie BA et al. Insights into SARS-CoV-2 persistence and its relevance. Viruses. 2021;13(6):1025
  61. 61. Fung M, Babik JM. COVID-19 in immunocompromised hosts: What we know so far. Clinical Infectious Diseases. 2021;72(2):340-350
  62. 62. Gaspar-Rodriguez A, Padilla-Gonzalez A, Rivera-Toledo E. Coronavirus persistence in human respiratory tract and cell culture: An overview. The Brazilian Journal of Infectious Diseases. 2021;25(5):101632
  63. 63. Avanzato VA et al. Case study: Prolonged infectious SARS-CoV-2 shedding from an asymptomatic immunocompromised individual with Cancer. Cell. 2020;183(7):1901-1912 e9
  64. 64. Decker A et al. Prolonged SARS-CoV-2 shedding and mild course of COVID-19 in a patient after recent heart transplantation. American Journal of Transplantation. 2020;20(11):3239-3245
  65. 65. Moore JL et al. A 63-year-old woman with a history of non-Hodgkin lymphoma with persistent SARS-CoV-2 infection who was seronegative and treated with convalescent plasma. American Journal of Case Reports. 2020;21:e927812
  66. 66. Nakajima Y et al. Prolonged viral shedding of SARS-CoV-2 in an immunocompromised patient. Journal of Infection and Chemotherapy. 2021;27(2):387-389
  67. 67. Wei L et al. Prolonged shedding of SARS-CoV-2 in an elderly liver transplant patient infected by COVID-19: A case report. Annals of Palliative Medicine. 2021;10(6):7003-7007
  68. 68. Choi B et al. Persistence and evolution of SARS-CoV-2 in an immunocompromised host. New England Journal of Medicine. 2020;383(23):2291-2293
  69. 69. Dominguez SR, Robinson CC, Holmes KV. Detection of four human coronaviruses in respiratory infections in children: A one-year study in Colorado. Journal of Medical Virology. 2009;81(9):1597-1604
  70. 70. Ogimi C et al. Prolonged shedding of human coronavirus in hematopoietic cell transplant recipients: Risk factors and viral genome evolution. The Journal of Infectious Diseases. 2017;216(2):203-209
  71. 71. Corey L et al. SARS-CoV-2 variants in patients with immunosuppression. New England Journal of Medicine. 2021;385(6):562-566
  72. 72. Pratapa SK et al. Caring for Cancer patients during Corona pandemic-(COVID-19)-a narrative review. South Asian Journal of Cancer. 2021;10(1):19-22
  73. 73. Mihaila RG. Management of patients with chronic lymphocytic leukemia during the SARS-CoV-2 pandemic. Oncology Letters. 2021;22(2):636
  74. 74. Paneesha S et al. Covid-19 infection in therapy-naive patients with B-cell chronic lymphocytic leukemia. Leukemia Research. 2020;93:106366
  75. 75. Chen X et al. Risk factors for the delayed viral clearance in COVID-19 patients. Journal of Clinical Hypertension (Greenwich, Conn.). 2021;23(8):1483-1489
  76. 76. Cevik M et al. SARS-CoV-2, SARS-CoV, and MERS-CoV viral load dynamics, duration of viral shedding, and infectiousness: A systematic review and meta-analysis. The Lancet Microbe. 2021;2(1):e13-e22
  77. 77. Laracy JC, Miko BA, Pereira MR. The solid organ transplant recipient with SARS-CoV-2 infection. Current Opinion in Organ Transplantation. 2021;26(4):412-418
  78. 78. Smorenberg A et al. How does SARS-CoV-2 targets the elderly patients? A review on potential mechanisms increasing disease severity. European Journal of Internal Medicine. 2021;83:1-5
  79. 79. Ho JC et al. The effect of aging on nasal Mucociliary clearance, beat frequency, and ultrastructure of respiratory cilia. American Journal of Respiratory and Critical Care Medicine. 2001;163(4):983-988
  80. 80. Liu Y et al. Viral dynamics in mild and severe cases of COVID-19. The Lancet Infectious Diseases. 2020;20(6):656-657
  81. 81. To KK-W et al. Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: An observational cohort study. The Lancet Infectious Diseases. 2020;20(5):565-574
  82. 82. Svartengren M, Falk R, Philipson K. Long-term clearance from small airways decreases with age. The European Respiratory Journal. 2005;26(4):609-615
  83. 83. Tang X et al. Early use of corticosteroid may prolong SARS-CoV-2 shedding in non-intensive care unit patients with COVID-19 pneumonia: A Multicenter, single-blind, randomized control trial. Respiration. 2021;100(2):116-126
  84. 84. Krause PR et al. SARS-CoV-2 variants and vaccines. New England Journal of Medicine. 2021;385(2):179-186
  85. 85. Liu C et al. Reduced neutralization of SARS-CoV-2 B.1.617 by vaccine and convalescent serum. Cell. 2021;184(16):4220-4236.e13
  86. 86. Yadav PD et al. Neutralization of Beta and Delta variant with sera of COVID-19 recovered cases and vaccinees of inactivated COVID-19 vaccine BBV152/Covaxin. Journal of Travel Medicine. 2021;28(7):1-3
  87. 87. U.S. Food and Drug Administration, FDA Revokes Emergency Use Authorization for Monoclonal Antibody Bamlanivimab. U.S. FDA: Silver Spring, MD,U.S.; 2021

Written By

Ricardo Izurieta, Tatiana Gardellini, Adriana Campos and Jeegan Parikh

Submitted: 08 November 2021 Reviewed: 31 March 2022 Published: 19 May 2022