key: cord-0815408-olbgn3rj
authors: Woodbridge, Y.; Amit, S.; Huppert, A.; Kopelman, N. M.
title: Viral load dynamics of SARS-CoV-2 Delta and Omicron variants following multiple vaccine doses and previous infection
date: 2022-03-23
journal: nan
DOI: 10.1101/2022.03.20.22272549
sha: 6d8c975c4d1d49b96ee1be8abcc5f91beed60f62
doc_id: 815408
cord_uid: olbgn3rj

An important , and often neglected, aspect of vaccine effectiveness is its impact on pathogen transmissibility, harboring major implications for public health policies. As viral load is a prominent factor affecting infectivity, its laboratory surrogate, qRT-PCR cycle threshold (Ct), can be used to investigate the infectivity-related component of vaccine effectiveness. While vaccine waning has previously been observed for viral load, during the Delta wave, it is yet unknown how Omicron viral load is affected by vaccination status, and whether vaccine-derived and natural infection protection are sustainable. By analyzing results of more than 460,000 individuals we show that while recent vaccination reduces Omicron viral load, its effect wanes rapidly. In contrast, a significantly slower waning rate is demonstrated for recovered COVID-19 individuals. Thus, while the vaccine is effective in decreasing morbidity and mortality, their relative minute effect on transmissibility and rapid waning call for reassessment of the scientific justification for "vaccine certificate", as it may promote false reassurance and promiscuous behavior.

In this retrospective study, we combined the meticulated national vaccination data with Ct data of four laboratories performing SARS-CoV-2 PCR tests. Studies on the Delta variant have shown that vaccinated individuals have lower VL, thus considered less infective, and that this effect wanes as time elapses [6, 7] . We augment these studies by examining the influence and temporal dynamics of vaccination and recovery on Omicron VL and how this changes with time since vaccination/infection for the Omicron variant using nationwide PCR data. Notably, the waning effect of infection-induced protection has not been thoroughly analyzed before in terms of VL and infectivity. We further compare presumed infectivity of individuals vaccinated with 2,3, or 4 doses versus COVID-19 recovered individuals.

Ct data of positive tests were obtained from four molecular labs, two of which are major Israeli Health Maintenance Organization labs, representing together approximately 40% of the Isareli population, and the other two are labs commissioned to perform tests for the Israeli Ministry of Health (MoH). All of the PCR tests included in this study were part of MoH surveillance scheme, and charge free for the consumer. We analyzed Ct values dating June 15, 2021 to January 29, 2022, divided into two periods of Delta and Omicron dominance (see Extended Data). Separate analyses were conducted for the viral nucleocapsid gene (N, 441,748 measurements) and envelope gene (E, 328,865 measurements). The patterns observed for E were similar to those of N (see Extended Data). To circumvent platform and other methodological variances between laboratories each lab dataset was analyzed both separately and combined, with similar patterns observed (see Extended Data).

We first performed multivariate linear regression analysis on Ct values of each variant with vaccination status, laboratory, age, sex and calendar time (7-days bins) as covariates (Extended Data Table 2A) . Vaccination status was defined as unvaccinated, 2-dose (divided to 3 bins, 10-39 days, 40-69, >70 days post-vaccination), 3-dose (divided to 3 bins, 10-39, 40-69, >70 days), 4-dose, or recovered; Due to the small number of individuals in the 2-dose (early) groups for the Omicron period, all the 2-dose groups were combined. Like previously reported [7] , during the Delta surge, 2-dose noticeably decreases VL (Fig. 1A) . For the 2nd-dose early cohort (10-39 days), mean Ct is about 1.3 Ct units higher than that of unvaccinated, corresponding to more than two-fold decrease in VL; However, this protection wanes rapidly as time elapses since vaccination, and VL reaches a level similar to that of the unvaccinated by day 70. For the 3-dose (early) cohort, VL is even lower than for the 2-dose (early) cohort, but once again rapid waning follows, and by day 70 VL reaches the baseline level of the unvaccinated. Notably, VL of the recovered cohort is similar to that of the 2-dose (early) and 3-dose (early) cohorts.

During the Omicron period (Fig. 1B) , only a recent 3rd-dose decreases VL among vaccinees, and is similar to infection-derived protection. Otherwise, the differences in VL for the unvaccinated, 2-and late 3-dose groups (Ct values of 25.9, 25.7 and 25.7 respectively) are negligible. In general, the effect of immune status for Omicron is less pronounced than from Delta even upon recent receipt of the 3rd vaccine dose or infection, as manifested by a reduced Ct-values gaps between these groups and the unvaccinated. The relative difference between the recently vaccinated (3-dose, 10-39 days) and the unvaccinated is smaller in Omicron (1.03, 95% CI 0.84-1.22) compared to Delta (1.92, 95% CI 1.71-2.13). Similarly, the relative difference between recovered and unvaccinated is 1.63 (95% CI 1.45-1.81)in Delta, while in Omicron it is reduced to 0.8 (95% CI, 0.72-0.88). These gaps are reduced by a two-fold in Omicron, possibly due to host immune waning and viral evasion [9] (see Extended Data Table 2A for full regression results).

Since the 4-dose jab was administered mainly to the elderly (60+, 90.9% of all 4-dose receivers), we conducted a separate analysis for this age group, pooling the 2-and 3-dose subgroups together. The results, presented in Fig. 2 , reveal that shortly after receiving the 4th dose, VL of the vaccinated individuals (ages >60) reaches levels similar yet slightly higher than those of recovered individuals from the same age group.

Goldberg et al. [10] have shown that natural infection protection wanes over time, with a rate that is slower than that of vaccine-derived protection. Here we demonstrate for the first time that waning of natural infection protection pertains also to VL, for both Delta and Omicron. Fig. 3 shows a clear and consistent waning trend for the recovered, for both Delta (Fig. 3A) and Omicron (Fig. 3B) variants. In contrast to the rapid waning observed for vaccinated individuals (Fig. 1&2) , VL of the previously infected does not reach the baseline level of the unvaccinated even after extended periods of time (>12 months) and for individuals originally infected with the Wuhan or Alpha strains (Fig. 3) .

Some precaution should be taken interpreting Ct data, in light of lab-specific standards [11] and clinical correlations. Regression is a standard approach which partially adjusts for such differences. In addition, Ct values may contain temporal biases due to changing policies and health-seeking behaviors. The inclusion of calendric date as an explanatory variable in the regressions(see Extended Data Tables 1A & 2A) (following [10] ), as well as considering only the first positive test for each patient, mitigate this possible bias. Additionally, we tested the robustness of the results by examining the patterns also for the gene E (Extended Data Fig. 3A ), conducting separate single lab regressions (Extended Data Fig. 4A ), accounting for temporal biases using R0 instead of calendar time (Extended Data Table 4A , Analysis 1), and narrowing the period for Delta as well as restricting age ranges for both variants (Extended Data Table 4A , Analysis 2).

This study indicates that overall the presumed vaccination-related immunity to SARS-CoV-2 has only a negligible long term (>70-days) effect on Ct value, a common surrogate for VL and infectiousness. The combination of vaccine waning and vaccine evasion are most likely the drivers of this finding. In lieu of several prominent publications describing vaccine effectiveness in prevention morbidity and hospitalization for Omicron [12, 13] , this study questions the role of current vaccination campaigns in harnessing the transmissibility of COVID-19 at a time scale greater than two months. Likewise, the scientific justification for "vaccination certificates" should be reassessed, taking into consideration the short term effects in reducing VL, as it may contribute to false reassurance and promiscuous behavior, and prove counterproductive as an epidemiologic restriction measure. Further studies should assess the differential benefits of SARS-CoV-2 vaccines in alleviating disease vs. preventing pathogen spread. Should this gap prove consistent, it may have major ramifications on global pandemic preparedness, vaccination rollout and medical inequity as well as other public health measures. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ; https://doi.org/10.1101/2022.03.20.22272549 doi: medRxiv preprint

Dataset construction. We used a nationwide database of Ct values from positive cases, measured by four different laboratories. Samples were collected between June 15, 2021 to Jan 29, 2022. The dataset contained over four million records of positive PCR tests with Ct-values. Records contained Ct measurements for the genes N, E, Orf1ab or S genes. Results are presented for N and E, two genes whose measurements make up 90% of all available data for the four laboratories. Ct values<10 or >40 units were removed from the dataset, since such values are likely the result of reading errors. A negligible number of records such samples were identified and removed from the four labs, N & E final dataset (9 records).

Multiple Ct measurements for the same individual and gene may belong to the same or different infection event. Sequences of Ct measurements within a single 90 days interval were defined as belonging to the same infection events. For each such sequence, only the first (earliest) Ct value was taken. Multiple infection events for a single individual were included if the time difference between the last measurement of the first sequence and the first measurement of the second sequence was at least 90 days. For the second infection, the patient's status was defined as 'recovered'.

Overall, our analyses, performed on the data of four labs, contained more than 460,000 individuals, 441,748 Ct measurements for the gene N, and 328,865 measurements for the gene E. Using encrypted patients' identity numbers, we merged Ct data with demographic information and vaccination data, to determine the patient's age, sex, and vaccination status. The merged data contained both Ct date and PCR sampling date. For the Ct measurements included in this study, the number of days between these two dates was at most a single day. Since PCR date is the actual sampling date, these dates were used for analyses.

Vaccination statuses were determined for each patient and infection event, based on the PCR date. The following definitions were used to group individuals: ⎼ Unvaccinated: Including up to 6 days after the first dose. Patients who had the infection between first and second dose (i.e, from 7 day after first dose until 10 days after second dose) were not included in the analysis.

We divided the follow-up study into two separate periods, each dominated by a different variant: ⎼ Delta time period: June 15 to Dec 1 2021 (>90% of the cases identified as Delta, see [14] ). ⎼ Omicron time period: Dec 28 2021 to Jan 29 2022 (>90% of the cases identified as Omicron, see [14] ).

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ;

These periods are also in accordance with the first documented case of Omicron infection in Israel (see Extended Data Figure 1A ).

To account for temporal effects in our regression analyses, we partitioned the Delta and Omicron time periods into 7-day time intervals (bins), using PCR dates to classify Ct measurements. Age groups were defined as 0-11, 12-15, 16-39, 40-59, and 60 or older. Due to national policy, individuals of age 0-11 were not present in most cohorts (they were not vaccinated until recently), and this group was thus excluded from the main analysis. Nonetheless, this age group was included in parts of the sensitivity analysis presented in the appendix. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ;

Delta (See Fig. 1A , main text) Omicron (see Fig. 1B , main text) Omicron (60+) (see Fig. 2 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ref. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Table 2A ). Results are provided for each lab in a separate row, note the similar pattern in all labs. Error bars represent 95% CI's around the means.Means were obtained from the weighted sum of age, sex and calendar time (using their frequency for each variant), together with the intercept and the corresponding cohort and lab for each column bar. CI's were obtained using the estimated distribution of each pair of cohort-lab coefficients. As to "Combined", CI's were obtained from the estimated distribution of all labs together with each of the cohorts coefficients.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ; https://doi.org/10.1101/2022.03.20.22272549 doi: medRxiv preprint Fig 3A. E-gene Ct values for different vaccination statuses, measured by four laboratories and combined, for the Delta and Omicron variants (left and right panels, respectively), using the multivariate regression coefficients. Note that both E and N have similar patterns. Results are provided for each lab in a separate row, note the similar pattern in all labs. Error bars represent 95% CI's around the means.Means were obtained from the weighted sum of age, sex and calendar time (using their frequency for each variant), together with the intercept and the corresponding cohort and lab for each column bar. CI's were obtained using the estimated distribution of each pair of cohort-lab coefficients. As to "Combined", CI's were obtained from the estimated distribution of all labs together with each of the cohorts coefficients.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ; Fig. 4A presents the results of regression analyses performed separately on each lab, in order to examine each lab independently, thus accounting for lab variability. The consistency of the results supports our assumption that vaccination status affects Ct values in a similar manner across all labs, regardless of different lab procedures and measurement standards. . Error bars represent 95% CI's around the means. Means were obtained from the weighted sum of age, sex and calendar time (using their frequency for each pair of lab-variant), together with the intercept and the corresponding cohort for each column bar. As to 'Combined', means were obtained from the weighted sum of age, sex, calendar time and lab, together with the intercept and the corresponding cohort for each column bar. CI's were obtained using the estimated distribution of each of the cohort coefficients.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted March 23, 2022. ; Table 4A presents two parts of a sensitivity analysis. In Analysis 1, we performed linear regression with the same covariates as in Fig. 1 & Table 2A , but replaced calendar time with the R0 variable, thus accounting for temporal effects in a different manner. We observe similar patterns in terms of the coefficients, both for Delta and Omicron, as shown in Table 4A . In Analysis 2, we used a restricted follow-up time study for Delta (between Sep 07 and Oct 11, 2021), as well as certain ages for both variants (12-20 for Delta, 5-20 for Omicron. note that in Omicron we included ages 5-11, that were excluded from the main analyses), to mitigate temporal and age effects. Results are provided in the rightmost columns of Table 4A . . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) Table 4A . Additional regression analyses. Analysis 1 (using R0 instead of calendar time, in Delta and Omicron). Analysis 2 (truncation of follow-up study time and age in Delta, truncation of age in Omicron).

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted March 23, 2022. ; https://doi.org/10.1101/2022.03.20.22272549 doi: medRxiv preprint

BNT162b2 mRNA Covid-19 vaccine in a nationwide mass vaccination setting

Protection of BNT162b2 vaccine booster against Covid-19 in Israel

Transmission of COVID-19 in 282 clusters in Catalonia, Spain: a cohort study

Duration of infectiousness and correlation with RT-PCR cycle threshold values in cases of COVID-19

Israel Ministry of Health, coronavirus in Israel -general update

Initial report of decreased SARS-CoV-2 viral load after inoculation with the BNT162b2 vaccine

Viral loads of Delta-variant SARS-CoV-2 breakthrough infections after vaccination and booster with BNT162b2

Duration of viral shedding and culture positivity with post vaccination SARS-CoV-2 delta variant infections

Waning immune humoral response to BNT162b2 Covid-19 vaccine over 6 months

Waning immunity after the BNT162b2 vaccine in Israel

The dangers of using Cq to quantify nucleic acid in biological samples: a lesson from COVID-19

Effectiveness of BNT162b2 vaccine against omicron variant in South Africa

COVID-19 vaccine surveillance report -Week 6

Acknowledgments. This work was supported by the Israel Science Foundation KillCorona-Curbing Coronavirus Research Program (grant no. 3663/19 to N. M. K.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The authors would like to thank Arnona Ziv, Micha Mandel, Yair Goldberg and Ronen Fluss.