ABSTRACT
BackgroundThe emergence of the Omicron variant (B.1.1.529) which correlated with dramatic losses in cross-neutralization capacity of post-vaccination sera raised concerns about the effectiveness of COVID-19 vaccines against infection and disease. Clinically relevant sub-variants (BA.1, BA.1.1, BA.2, BA.2.12.1, BA.3, and BA.4/5) subsequently emerged rapidly. MethodsWe evaluated published and pre-print studies reporting sub-variant specific reductions in cross-neutralization compared to the prototype strain of SARS-CoV-2 and between sub-variants. Median fold-reduction across studies was calculated by sub-variant and vaccine platform. ResultsAmong 153 studies with post-vaccination data, after primary vaccination the sub-variant specific fold-reduction in neutralization capacity compared to the prototype antigen varied widely, from median 4.2-fold for BA.3 to 21.9-fold for BA.4/5; in boosted participants fold-reduction was similar for all sub-variants (5.9-fold to 7.1-fold) except for BA.4/5 which was 12.7-fold. Relative to BA.1, the other Omicron sub-variants had similar neutralization capacity post-primary vaccination (range median 0.8-fold to 1.1-fold) and post-booster (0.9-fold to 1.2-fold) except for BA.4/5 which was higher (2.0-fold). Omicron sub-variant specific responder rates were low post-primary vaccination (range median 33.5% to 56.7%) compared to the prototype (median 96.0%), but improved post-booster (range median 85.4% to 92.6%). ConclusionFold-reductions in neutralization titers among Omicron sub-variants compared to the prototype strain varied widely post-primary vaccination but were comparable post-booster, except for BA.4/5 which had higher fold-reduction (2-fold relative to BA.1). Considering large fold-decreases in neutralization titers to the parental strain for all Omicron sub-variants, vaccine effectiveness is very likely to be reduced against all Omicron sub-variants, and probably more so against Omicron BA.4/5.
ABSTRACT
ObjectiveWe studied how commonly used vaccine effectiveness (VE) study designs (variations of cohorts, and test-negative designs) perform under epidemiological nuances more prominent in the COVID-19 era, specifically time-varying vaccine coverage, and heterogeneous testing behaviour and baseline attack rates with selection on willingness to vaccinate. MethodologyWe simulated data from a multi-parameter conceptual model of the epidemiological environment using 888125 parameter sets. Four configurations of cohorts, and two test-negative designs, were conducted on the simulated data, from which estimation bias is computed. Finally, stratified and fixed effects linear regressions were estimated to quantify the sensitivity of estimation bias to model parameters. FindingsIrrespective of study designs, dynamic vaccine coverage, and heterogeneous testing behaviour and baseline attack rates are important determinants of bias. Study design choices have non-trivial effects on VE estimation bias even if these factors are absent. The importance of these sources of bias differ across study designs. ConclusionA re-benchmarking of methodology, especially for studying COVID-19 VE, and implementation of vaccine-preventable disease surveillance systems that minimise these sources of bias, are warranted. HighlightsO_LIThis paper simulated a theoretical model with frictions in vaccination, testing, baseline disease risks, and heterogeneous vaccine effectiveness to evaluate estimation bias across four cohort and two test-negative designs. C_LIO_LIIn theory, bias depends on behavioural asymmetries (in testing, and baseline risk) between the vax-willing and vax-unwilling, and the speed of vaccination rollout. C_LIO_LIThere is intrinsic estimation bias across all study designs, with the direction and magnitude contingent on specific conditions. C_LIO_LIIn scenarios that may be reflective of past SARS-CoV-2 waves, the degree of bias can be substantial, attributable to variation in assumed testing and baseline risk frictions. C_LIO_LIA regression-based decomposition indicates that study designs have visibly different primary sources of estimation bias, and degree of robustness in general. C_LIO_LIThis study warrants a re-benchmarking of methodology and reporting checklists for VE research, and informs the design of cost-effective surveillance by quantifying part of the bias-implementation cost trade-off. C_LI
ABSTRACT
BackgroundWe determined circulating anti-S SARS-CoV-2 IgG antibody titres in a vaccinated healthcare workers (HCWs) cohort from Northern Israel in the 11 months following primary vaccination according to age, ethnicity, boosting timing and previous infection status. MethodsAll consenting HCWs were invited to have their circulating IgG levels measured before vaccination and at 6 subsequent timepoints. All HCWs with suspected COVID-19 were PCR tested. We described trends in circulating IgG geometric mean concentration by age, ethnicity, timing of boosting and previous infection status and compared strata using Kruskall-Wallis tests. ResultsAmong 985 vaccinated HCWs. IgG titres gradually decreased in all groups over the study duration. Younger or previously infected individuals had higher initial IgG levels (p<0.001 in both cases); differences substantially decreased or disappeared at 7-9 months, before boosting. Pre-infection IgG levels in infected participants were similar to levels measured at the same timepoint in HCWs who remained uninfected (p>0.3). IgG GMC in those boosted 6-7 months after dose 2 was lower compared with those boosted 8-9 months after (1999-vs 2736, p=0.02). ConclusionsImmunity waned 6 months post-priming in all age groups and in previously infected individuals, reversed by boosting. IgG titres decrease among previously infected individuals and the proportion of reinfected individuals in this group, comparable to the proportion of breakthrough infection in previously uninfected individuals suggests individuals with hybrid immunity (infection+vaccination) may also require further doses. Our study also highlights the difficulty in determining protective IgG levels and the need to clarify the optimal timing in 3 dose regimens
ABSTRACT
While mortality attributable to COVID-19 has devastated global health systems and economies, striking regional differences have been observed. The Bacille Calmette Guerin (BCG) vaccine has previously been shown to have non-specific protective effects on infections, as well as long-term efficacy against tuberculosis. Using publicly available data we built a simple log-linear regression model to assess the association of BCG use and COVID-19-attributable mortality per 1 million population after adjusting for confounders including country economic status (GDP per capita), and proportion of elderly among the population. The timing of country entry into the pandemic epidemiological trajectory was aligned by plotting time since the 100th reported case. Countries with economies classified as lower-middle-income, upper-middle-income and high-income countries (LMIC, UMIC, HIC) had median crude COVID-19 log-mortality of 0.4 (Interquartile Range (IQR) 0.1, 0.4), 0.7 (IQR 0.2, 2.2) and 5.5 (IQR 1.6, 13.9), respectively. COVID-19-attributable mortality among BCG-using countries was 5.8 times lower [95% CI 1.8-19.0] than in non BCG-using countries. Notwithstanding limitations due to testing constraints in LMICs, case ascertainment bias and a plausible rise of cases as countries progress along the epidemiological trajectory, these analyses provide intriguing observations that urgently warrant mobilization of resources for prospective randomized interventional studies and institution of systematic disease surveillance, particularly in LMICs.
