Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes a spectrum of clinical manifestations, ranging from asymptomatic to mild, moderate, or severe illness with multi-organ failure and death. Using a new machine learning algorithm developed by us, we have reported a significantly higher number of predicted COVID-19 cases than the documented counts across the world. The sole reliance on confirmed symptomatic cases overlooking the symptomless COVID-19 infections and the dynamics of waning immunity may not provide ‘true’ spectrum of infection proportion, a key element for an effective planning and implementation of protection and prevention strategies. We and others have previously shown that strategic orthogonal testing and leveraging systematic data-driven modeling approach to account for asymptomatics and waning cases may situationally have a compelling role in informing efficient vaccination strategies beyond prevalence reporting. However, currently Centers for Disease Control and Prevention (CDC) does not recommend serological testing either before or after vaccination to assess immune status. Given the 27% occurrence of breakthrough infections in fully vaccinated (FV) group with many being asymptomatics and still a larger fraction of the general mass remaining unvaccinated, the relaxed mask mandate and distancing by CDC can drive resurgence. Thus, we believe it is a key time to focus on asymptomatics (no symptoms) and oligosymptomatics (so mild that the symptoms remain unrecognized) as they can be silent reservoirs to propagate the infection. This perspective thus highlights the need for proactive efforts to reevaluate the current variables/strategies in accounting for symptomless and waning fractions.
Introduction
This is a perspective chiefly based on the reports that have suggested antibody quantitation could be a prevaccination screening strategy and specifically, a single dose of COVID-19 vaccine may likely suffice for the already SARS-CoV-2 infected cohort (–). These studies along with other findings similar to ours, have shown that the serological assessment of nucleocapsid (N)- and spike (S)-specific IgG antibody levels could differentiate vaccine-induced responses from those acquired following SARS-CoV-2 infection (, , ). In addition, these interesting and elegant studies demonstrated that the first dose (1D) of mRNA vaccine generated similar protective antibody responses in previously SARS-CoV-2 infected healthcare workers to that of a second dose (2D) seen in immunologically naïve patients (, , , ). Further, the modest ACE2 binding inhibition responses of 2D versus 1D vaccine doses among COVID-19 recovered individuals reassures that a single dose could govern a protective antibody response in this population (). This emphasis concerning the potential for single dose vaccination in prior COVID-19 individuals is relevant and timely, given the drastic decrease in new cases reported with that approach in many countries alongside a prolonged antigenic stimulation that has the likelihood of dampening the immune response via effector T-cells exhaustion, as has been observed with several other viruses (). Among the vaccinated, there appears to be some difference in the extent and duration of immune response depending on the number of doses taken, time gap given between the first and second dose, prior infection/disease burden besides the physical, environmental, and general health status’ influences (). Based on some select studies, Table 1 enlists some key responses and differences seen after administration of 1D and 2D of COVID-19 vaccines.
Table 1
| S.No. | Particulars | 1D | 2D | Comments | Reference |
|---|---|---|---|---|---|
| 1. | IgM | Low | High | Low and high was relative to the unvaccinated controls. IgM levels were found to be increased by 1.7-fold in the 2D-received naïve group (seronegative) with no appreciable change in the prior infected group. This was, however, only transient and during the initial period following vaccination. | () |
| 2. | IgG | Low | High | Low and high was assigned based on the relative levels with the pre-vaccine status. Median IgG levels was increased by 7.0-fold in sero+ 2D group; 8.6-fold in sero- 2D group; no change in the prior COVID-19+ group; with ~1.8-fold in the overall 2D population that includes sero+, sero-, and prior COVID-19+ subgroups. | () |
| 3. | Virus neutralizing potency | Low | High | Low and high was based on the neutralization antibody titers relative to pre-vaccine (1D). The median potency of 2D when adjusted and compared to 1D was increased in the range between 2.6 and 26-fold in sero- group; between 1.3 and 1.7-fold in 2D sero+ group. | (, ) |
| 4. | Vaccine Efficacy- (VE) | ❖ VE* was assessed in terms of onset of COVID infection and a low VE indicates a high infection. VE was found to be 52.4% in the period between 1D and 2D and was increased to 92.7% at 2 or more days after 2D. ❖ In a multicenter SIREN study including 23,324 participants from 104 sites (all in England), the VE# assessed in terms of new infections observed at ≥21 days after 1D was reduced by 50% at 7 days after 2D. ❖ In a nationwide historical cohort study from Israel with 6286 subjects, between ≥14 days after 1D until the receipt of 2D, VE@ was found to be 61%, which was increased to 82% from 1 to 6 days after the 2D. | () () () |
Some key responses and differences seen after 1D and 2D of COVID-19 vaccines.
*VE was derived according to the Clopper–Pearson method using the formula 100× (1−IRR), where IRR is the calculated ratio of confirmed COVID-19 cases per 1000 person-years of follow-up in the active vaccine group to the corresponding illness rate in the placebo group.
#VE was deduced from the incidence density of new infections/10,000 person-days (8 following 1D vs 4 after 2D).
@VE was deduced from the effectiveness of vaccine against PCR positive SARS-CoV-2 (with or without symptoms).
Along these lines, the potential biases around presumed high proportion of ‘silent’ asymptomatic patients must be duly acknowledged. Also concerning is the nebulously defined asymptomatic testing by Centers for Disease Control and Prevention (CDC) guidelines on one hand (–), and its relaxed guidelines on masking and distancing for FV population that can still contract breakthrough infections. Together, these clearly portend the need for careful surveillance/assessment mechanism(s) for the symptomless and distinguishing them from presymptomatic cases. Notably, as of May 25, 2021 CDC’s report, about 27% (2725/10262) vaccine breakthrough infections were asymptomatic, and in those, 29% (289/995) of hospitalizations were related to asymptomatic or unrelated to COVID-19 (). While some anecdotal evidence raises optimism that asymptomatic-driven transmission of the infection can subtly result in comprehensive immunization of the population towards herd immunity. There are other studies that report only one in five asymptomatic carriers possesses the capacity to seroconvert compared with severe and mild COVID-19 cases during or after hospitalization (). Thus, it is tenuous whether asymptomatic infections can allow protective immunity. Hence, we believe it is the right time to proactively characterize asymptomatics and oligosymptomatics from such studies that assess and deduce prevalence-based protection and prevention measures. Only then, the challenges surrounding vaccine redirection to hotspots/appropriate groups, mitigation of vaccination inequities, and efforts to enhance the speed, coverage, and impact of vaccination across the globe will be tackled adeptly.
Asymptomatic Infections and Waning Immunity Remain as an Uncharted Territory in the Understanding of SARS-CoV-2 Infection
A vast majority of the studies alluding to emphasize the potential of a single dose vaccination strategy in prior infected cohorts has included only the confirmed cases (symptomatic) and assessed the effectiveness of vaccination in terms of quantifying the antibody levels (–). However, it is to be noted that a significant percentage of COVID-19 infections were silent/asymptomatic causing many infections to go unreported (–). Using a new machine learning algorithm developed by our team (accounting for undocumented infections), we have reported that the total numbers of predicted COVID-19 cases to be significantly higher than reported across the nation and worldwide (). Represented in the Figures 1A, B is an estimated cumulative incidence (~27%) and estimated total current infections (90 million) across the U.S, respectively as of April 16, 2021. This is very critical given the relevant published study’s () central theme is that a single dose vaccination could be sufficient for prior infected, for which an accurate estimation of the true size of infected population is pivotal. Note that stringent reliance on confirmed cases only can lead to under-ascertainment of COVID-19 infections (). Not accounting for the asymptomatic and oligosymptomatic population in the context can mislead the experts in gauging the vulnerability of a community to the virus and confound the subsequent decisions on mitigation strategies. Could strategic surveillance testing using adequate follow-up (serial PCR) and orthogonal immunological assessments (antigen- and antibody- based tests) of people that are likely exposed to confirmed cases (e.g., contact tracing) or are high-risk spreaders (e.g., front-line and congregate facility workforce) be leveraged along with systematic data-driven modeling approach (integrating age, sex, chronic conditions and COVID-19 risk factors, etc.) allow better characterization of infection dynamics (proliferation, clearance, and persistence) in asymptomatic pool and ably guide the planning and optimization of specific actions?
Figure 1
Compounding the asymptomatics, waning immunity, per se, may challenge the testing and interpretation with false negative immunoassay results because of decreasing levels of antibodies and higher positive cut-off thresholds set by vendors that were mainly derived from active infection cases. Importantly more the ‘interacting asymptomatics and oligosymptomatics (e.g.: working age)’ socially mix with the non-immunized or immunized (under waning immunity), greater and sustained will be the spread of infection. Thus, a disruption in the timing and intensity of interventional strategies and/or efforts is imminent when the asymptomatic and waning immunity considerations are discounted. While the effectiveness of authorized COVID-19 vaccines is apparent from real-world scenarios and a spate of clinical studies, the emergence of new variants and reports of a worldwide surge of recent vaccine breakthrough infections with the Delta variant (B.1.617.2) of coronavirus in the FV have raised alarms about the waning vaccine immunity (
From the laboratory-based analysis, to monitor such circumstances, binding immunoassay format such as anti-nucleocapsid-pan-Immunoglobulin (anti-N-pan-Ig) electro-chemiluminescence assay (ECLIA) that detects late, mature, high affinity antibodies regardless of the subclass with high sensitivity and specificity from <5 days (proportion of infection detected only by PCR) until >15–22 days samples post-symptom when used in serial measurements could come in handy (
Is There a Case to Consider an ‘Editable Threshold’ of Serology Assays to Reveal Previously Undiagnosed Infections?
The bigger purpose of studies focused on understanding if a single dose vaccination is sufficient for prior-infected subjects (
Many reports, including Ebinger’s study, identified a fraction of the naïve individuals following 1D reached the neutralizing threshold titer or beyond (for instance, nearly 8% in the 1D category; Figure 1 from Ref #1). This raises important questions whether these naïve individuals that exhibited a hyper-IgG response following 1D (compared to the prior-infected individuals) were truly naïve, or perhaps asymptomatically infected, or their samples collected at a later period within the 7-21 days (≥14 days, where typical IgG response is highly likely). This can be addressed (i) if those naïve group subjects who had all 3 data points (baseline, 1D and 2D) are plotted longitudinally per individual basis and (ii) by providing distribution of antibody response over time for the 1D and 2D separately. These data are critical in obtaining a clearer picture when defining a cohort for a single dose vaccination. Moreover, vaccine-triggered protective immunity is also known to decay progressively and wane over time, requiring revaccinations. In such situations, studies reflecting the accurate prevalence and persistence of infection (e.g.: accounting for asymptomatics) and immune status/sustainability (e.g.: waning) could be valuable to illuminate the impending patterns of oscillating infection(s)/outbreaks. This, in turn, can help guide and drive an effective periodic immunization program (e.g.: extending immunity duration via administering another booster).
Is It Worth Establishing a Pan Ig: Neutralization Titer?
In the course of COVID-19 disease, the kinetics of generation and persistence of IgM and IgG antibodies are typically asynchronous and vary with time. In particular, IgM emerges early during primary and secondary immune responses, while IgG typically appears later, but remains in circulation for a longer duration. Akin to IgG, IgM also functions in toxic neutralization, agglutination, complement activation, and acts as a mediator of inflammation. But, since IgM class of antibodies has a shorter persistence in relation to IgG, its detection may be used to indicate a recent event (infection or immunization). In the context of SARS-CoV-2 infection or COVID-19 immunization, determining IgM antibodies early in the event (within 2 weeks that may persist up to nearly 3 weeks following disease onset or immunization) and IgG antibodies (beyond 2 weeks until several months after infection or immunization), have been evidently recognized to be more informative for evaluating antibody-based immunological responses with sufficient sensitivity and specificity (
What Is the Impact of Time Interval Between Prior Infection and Vaccination on Vaccine-Elicited Antibody Responses?
While a slew of studies claim that a single dose of vaccine is sufficient to protect the prior infected individuals as they mounted robust immune response following 1D (
Conclusions
While clearly endorsing the compelling findings on the adequacy of single-dose vaccination to prior infected cohorts (
Funding
The data for Figure 1 was generated from the Lyda Hill Philanthropies-supported, a freely available GitHub repository.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Statements
Data availability statement
The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author. The code, latest updated estimates, and their visualizations presented in Figure 1 are freely available at a GitHub repository (https://github.com/JungsikNoh/COVID19_Estimated-Size-of-Infectious-Population).
Author contributions
NM, LM, and AM conceived the idea, wrote, and proofread the manuscript. JN provided the data. All authors contributed to the article and approved the submitted version.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
asymptomatic, waning, serology testing, COVID-19, vaccination
Citation
Narasimhan M, Mahimainathan L, Noh J and Muthukumar A (2021) Silent SARS-CoV-2 Infections, Waning Immunity, Serology Testing, and COVID-19 Vaccination: A Perspective. Front. Immunol. 12:730404. doi: 10.3389/fimmu.2021.730404
Received
24 June 2021
Accepted
31 August 2021
Published
21 September 2021
Volume
12 - 2021
Edited by
Mariana Gisela Bego, McGill University, Canada
Reviewed by
Shetty Ravi Dyavar, University of Nebraska Medical Center, United States; W. Todd Farmer, Research Institute of the McGill University Health Center (RI-MUHC), Canada
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Copyright
© 2021 Narasimhan, Mahimainathan, Noh and Muthukumar.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alagarraju Muthukumar, alagarraju.muthukumar@utsouthwestern.edu
This article was submitted to Viral Immunology, a section of the journal Frontiers in Immunology
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.