Hybrid immunity against COVID-19 in different countries with a special emphasis on the Indian scenario during the Omicron period

Evaluating Immunologic and Illness Outcomes of SARS-CoV-2 Infection in Vaccinated and Unvaccinated Children Aged ≥ 5 Years, in a Multisite Longitudinal Cohort

Hybrid immunity, as a result of infection and vaccination to SARS-CoV-2, has been well studied in adults but limited evidence is available in children. We evaluated the antibody responses to primary SARS-CoV-2 infection among vaccinated and unvaccinated children aged ≥ 5 years.

METHODS

A longitudinal cohort study of children aged ≥ 5 was conducted during August 2021-August 2022, at sites in Arizona, Texas, Utah, and Florida. Children submitted weekly nasal swabs for PCR testing and provided sera 14-59 days after PCR-confirmed SARS-CoV-2 infection. Antibodies were measured by ELISA against the receptor-binding domain (RBD) and S2 domain of ancestral Spike (WA1), in addition to Omicron (BA.2) RBD, following infection in children, with and without prior monovalent ancestral mRNA COVID-19 vaccination.

RESULTS

Among the 257 participants aged 5 to 18 years, 166 (65%) had received at least two mRNA COVID-19 vaccine doses ≥ 14 days prior to infection. Of these, 53 occurred during Delta predominance, with 37 (70%) unvaccinated at the time of infection. The remaining 204 infections occurred during Omicron predominance, with 53 (26%) participants unvaccinated. After adjusting for weight, age, symptomatic infection, and gender, significantly higher mean RBD AUC values were observed among the vaccinated group compared to the unvaccinated group for both WA1 and Omicron (p < 0.0001). A smaller percentage of vaccinated children reported fever during illness, with 55 (33%) reporting fever compared to 44 (48%) unvaccinated children reporting fever (p = 0.021).

CONCLUSIONS

Children with vaccine-induced immunity at the time of SARS-CoV-2 infection had higher antibody levels during convalescence and experienced less fever compared to unvaccinated children during infection.

Clinical and prognostic implications of hyaluronic acid in patients with COVID-19 reinfection and first infection

Objective

Previous research has shown that human identical sequences of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) promote coronavirus disease 2019 (COVID-19) progression by upregulating hyaluronic acid (HA). However, the association of HA with mortality and long COVID in SARS-CoV-2 reinfection and first infection is unclear.

Methods

Patients with COVID-19 at Beijing Ditan Hospital from September 2023 to November 2023 were consecutively enrolled. SARS-CoV-2 reinfections were matched 1:2 with first infections using a nearest neighbor propensity score matching algorithm. We compared the hospital outcomes between patients with COVID-19 reinfection and first infection. The association between HA levels and mortality and long COVID in the matched cohort was analyzed.

Results

The reinfection rate among COVID-19 hospitalized patients was 25.4% (62 cases). After propensity score matching, we found that reinfection was associated with a better clinical course and prognosis, including lower levels of C-reactive protein and erythrocyte sedimentation rate, fewer cases of bilateral lung infiltration and respiratory failure, and shorter viral clearance time and duration of symptoms (p < 0.05). HA levels were significantly higher in patients with primary infection [128.0 (90.5, 185.0) vs. 94.5 (62.0, 167.3), p = 0.008], those with prolonged viral clearance time [90.5 (61.5, 130.8) vs. 130.0 (95.0, 188.0), p < 0.001], and deceased patients [105.5 (76.8, 164.5) vs. 188.0 (118.0, 208.0), p = 0.002]. Further analysis showed that HA was an independent predictor of death (AUC: 0.789), and the risk of death increased by 4.435 times (OR = 5.435, 95% CI = 1.205-24.510, p = 0.028) in patients with high HA levels. We found that patients with HA levels above 116 ng/mL had an increased risk of death. However, the incidence of long COVID was similar in the different HA level groups (p > 0.05).

Conclusion

Serum HA may serve as a novel biomarker for predicting COVID-19 mortality in patients with SARS-CoV-2 reinfection and first infection. However, HA levels may not be associated with long COVID.

Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021

There has been raging discussion and debate around the quality of COVID death data in South Asia. According to WHO, of the 5.5 million reported COVID-19 deaths from 2020-2021, 0.57 million (10%) were contributed by five low and middle income countries (LMIC) countries in the Global South: India, Pakistan, Bangladesh, Sri Lanka and Nepal. However, a number of excess death estimates show that the actual death toll from COVID-19 is significantly higher than the reported number of deaths. For example, the IHME and WHO both project around 14.9 million total deaths, of which 4.5-5.5 million were attributed to these five countries in 2020-2021. We focus our gaze on the COVID-19 performance of these five countries where 23.5% of the world population lives in 2020 and 2021, via a counterfactual lens and ask, to what extent the mortality of one LMIC would have been affected if it adopted the pandemic policies of another, similar country? We use a Bayesian semi-mechanistic model developed by Mishra et al. (2021) to compare both the reported and estimated total death tolls by permuting the time-varying reproduction number (Rt) across these countries over a similar time period. Our analysis shows that, in the first half of 2021, mortality in India in terms of reported deaths could have been reduced to 96 and 102 deaths per million compared to actual 170 reported deaths per million had it adopted the policies of Nepal and Pakistan respectively. In terms of total deaths, India could have averted 481 and 466 deaths per million had it adopted the policies of Bangladesh and Pakistan. On the other hand, India had a lower number of reported COVID-19 deaths per million (48 deaths per million) and a lower estimated total deaths per million (80 deaths per million) in the second half of 2021, and LMICs other than Pakistan would have lower reported mortality had they followed India's strategy. The gap between the reported and estimated total deaths highlights the varying level and extent of under-reporting of deaths across the subcontinent, and that model estimates are contingent on accuracy of the death data. Our analysis shows the importance of timely public health intervention and vaccines for lowering mortality and the need for better coverage infrastructure for the death registration system in LMICs.

Hybrid immunity and protection against infection during the Omicron wave in Malta

By December 2021, administration of the third dose of COVID-19 vaccinations coincided with the spread of the Omicron variant in Europe. Questions had been raised on protection against infection conferred by previous vaccination and/or infection. Our study population included 252,433 participants from the COVID-19 vaccination registry in Malta. Data were then matched with the national testing database. We collected vaccination status, vaccine brand, vaccination date, infection history, and age. Using logistic regression, we examined different combinations of vaccine dose, prior infection status and time, and the odds of infection during the period when the Omicron variant was the dominant variant in Malta. Participants infected with Sars-Cov-2 prior to the Omicron wave had a significantly lower odds of being infected with the Omicron variant. Additionally, the more recent the infection and the more recent the vaccination, the lower the odds of infection. Receiving a third dose within 20 weeks of the start of the Omicron wave in Malta offered similar odds of infection as receiving a second dose within the same period. Time since vaccination was a strong determinant against infection, as was previous infection status and the number of doses taken. This finding reinforces the importance of future booster dose provision especially to vulnerable populations.

Population-Level Immunity for Transient Suppression of COVID-19 Waves in Japan from April 2021 to September 2022

Multiple COVID-19 waves have been observed worldwide, with varying numbers of positive cases. Population-level immunity can partly explain a transient suppression of epidemic waves, including immunity acquired after vaccination strategies. In this study, we aimed to estimate population-level immunity in 47 Japanese prefectures during the three waves from April 2021 to September 2022. For each wave, characterized by the predominant variants, namely, Delta, Omicron, and BA.5, the estimated rates of population-level immunity in the 10-64-years age group, wherein the most positive cases were observed, were 20%, 35%, and 45%, respectively. The number of infected cases in the BA.5 wave was inversely associated with the vaccination rates for the second and third injections. We employed machine learning to replicate positive cases in three Japanese prefectures to validate the reliability of our model for population-level immunity. Using interpolation based on machine learning, we estimated the impact of behavioral factors and vaccination on the fifth wave of new positive cases that occurred during the Tokyo 2020 Olympic Games. Our computational results highlighted the critical role of population-level immunity, such as vaccination, in infection suppression. These findings underscore the importance of estimating and monitoring population-level immunity to predict the number of infected cases in future waves. Such estimations that combine numerical derivation and machine learning are of utmost significance for effective management of medical resources, including the vaccination strategy.

The Omicron Variant Reinfection Risk among Individuals with a Previous SARS-CoV-2 Infection within One Year in Shanghai, China: A Cross-Sectional Study

Reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants due to immune escape is challenging for the global response to the pandemic. We estimated the Omicron reinfection prevalence among people who had a previous SARS-CoV-2 infection in Shanghai, China. We conducted a telephone survey in December 2022 with those who had previously been infected with Omicron between March and May 2022. Information on their demographics, coronavirus disease 2019 (COVID-19) testing, and vaccination history was collected. The overall and subgroup reinfection rates were estimated and compared. Among the 1981 respondents who were infected between March and May 2022, 260 had positive nucleic acid or rapid antigen tests in December 2022, with an estimated reinfection rate of 13.1% (95% confidence interval [95% CI]: 11.6-14.6). The reinfection rate for those who had a booster vaccination was 11.4% (95% CI: 9.2-13.7), which was significantly lower than that for those with an incomplete vaccination series (15.2%, 95% CI: 12.3-18.1) (adjusted odds ratio [aOR]: 0.579; 95% CI: 0.412-0.813). Reinfection with the Omicron variant was lower among individuals with a previous SARS-CoV-2 infection and those who had a booster vaccination, suggesting that hybrid immunity may offer protection against reinfection with Omicron sublineages.

Projection of COVID-19 Positive Cases Considering Hybrid Immunity: Case Study in Tokyo

Since the emergence of COVID-19, the forecasting of new daily positive cases and deaths has been one of the essential elements in policy setting and medical resource management worldwide. An essential factor in forecasting is the modeling of susceptible populations and vaccination effectiveness (VE) at the population level. Owing to the widespread viral transmission and wide vaccination campaign coverage, it becomes challenging to model the VE in an efficient and realistic manner, while also including hybrid immunity which is acquired through full vaccination combined with infection. Here, the VE model of hybrid immunity was developed based on an in vitro study and publicly available data. Computational replication of daily positive cases demonstrates a high consistency between the replicated and observed values when considering the effect of hybrid immunity. The estimated positive cases were relatively larger than the observed value without considering hybrid immunity. Replication of the daily positive cases and its comparison would provide useful information of immunity at the population level and thus serve as useful guidance for nationwide policy setting and vaccination strategies.

Effects of the second dose of COVID-19 vaccines in patients with autoimmune rheumatic diseases with hybrid immunity

Patients with autoimmune rheumatic diseases with a previous infection by the SARS-CoV-2 virus have exaggerated responses to a single dose of COVID-19 vaccination as compared to fully vaccinated infection naive patients. The second dose is currently recommended at an extended gap after the infection, but the information available regarding response to the second dose in this subgroup is limited. Patients with AIRDs previously infected with COVID-19, who have received at least one dose of AZD1222/ChAdOx1 (n = 200) were included and stratified based on vaccine doses (V), and infection (I) into I + V, I + V + V, V + I, V + V + I. Anti-RBD (receptor binding domain) antibodies were compared across the four groups. In 49 patients of the I + V + V group (AZD12222), paired sera were compared for antibody levels and neutralization after each vaccine dose. Thirty patients with hybrid immunity after BBV152 and 25 with complete vaccination without infection were included as controls. The highest anti-RBD antibody levels were observed in the V + V + I group (18,219 ± 7702 IU/ml) with statistically similar titers in the I + V + V (10,392 ± 8514 IU/ml) and the I + V (8801 ± 8122 IU/ml). This was confirmed in the 49 paired samples that paradoxically showed a lowering of antibody titers after the second dose [9626 (IQR: 4575-18,785)-5781 (2484-11,906); p < 0.001]. Neutralization of the Delta variant was unaffected but Omicron neutralization was significantly reduced after the second dose [45.7 (5.3-86.53)-35% (7.3-70.9); p = 0.028]. Ancillary analyses showed that only the hybrid immune sera could neutralize the Omicron variant and AZD1222 hybrids performed better than BBV152 hybrids. The second dose of AZD1222 did not boost antibody titers in patients with RD who had COVID-19 previously. In the analysis of paired sera, the second dose led to a statistically significant reduction in antibody titers and also reduced neutralization of the Omicron variant.

A Detailed Overview of SARS-CoV-2 Omicron: Its Sub-Variants, Mutations and Pathophysiology, Clinical Characteristics, Immunological Landscape, Immune Escape, and Therapies

The COVID-19 pandemic has created significant concern for everyone. Recent data from many worldwide reports suggest that most infections are caused by the Omicron variant and its sub-lineages, dominating all the previously emerged variants. The numerous mutations in Omicron's viral genome and its sub-lineages attribute it a larger amount of viral fitness, owing to the alteration of the transmission and pathophysiology of the virus. With a rapid change to the viral structure, Omicron and its sub-variants, namely BA.1, BA.2, BA.3, BA.4, and BA.5, dominate the community with an ability to escape the neutralization efficiency induced by prior vaccination or infections. Similarly, several recombinant sub-variants of Omicron, namely XBB, XBD, and XBF, etc., have emerged, which a better understanding. This review mainly entails the changes to Omicron and its sub-lineages due to it having a higher number of mutations. The binding affinity, cellular entry, disease severity, infection rates, and most importantly, the immune evading potential of them are discussed in this review. A comparative analysis of the Delta variant and the other dominating variants that evolved before Omicron gives the readers an in-depth understanding of the landscape of Omicron's transmission and infection. Furthermore, this review discusses the range of neutralization abilities possessed by several approved antiviral therapeutic molecules and neutralizing antibodies which are functional against Omicron and its sub-variants. The rapid evolution of the sub-variants is causing infections, but the broader aspect of their transmission and neutralization has not been explored. Thus, the scientific community should adopt an elucidative approach to obtain a clear idea about the recently emerged sub-variants, including the recombinant variants, so that effective neutralization with vaccines and drugs can be achieved. This, in turn, will lead to a drop in the number of cases and, finally, an end to the pandemic.

Current surge of COVID-19 infection in China and its impact on India

Background

COVID-19, the pandemic caused by the SARS-CoV-2, is a global health calamity and one of the greatest challenges faced by the humankind across the globe. The virus originated in Wuhan, China and spread rapidly to more than 200 countries/nations, affected more than 600 billion individuals and caused around 65 lakh deaths worldwide. Since the start of the pandemic, SARS-CoV-2 mutates and accumulates genetic variations which constantly resulted in the emergence of new variants.

Objective

The current article discusses about the new omicron sub variant BF.7, and how this BF.7 variant may pose risk in India, if it overrides the current COVID-19 circulating variants.

Content

The emergence and potential consequences of the circulating SARS-CoV-2 variants usually augment virus transmissibility and host immune evasion. The current spurt in COVID-19 infections in China which has alarmed people around the world, is believed to be driven by an omicron sub variant BF.7. Although India has been reporting a "steady decline" in COVID-19 cases, we need constant surveillance to keep a track of the new emerging variants in circulation. Keeping in mind, the new surge in COVID-19 cases across many nations, we discuss about the new variant and its possible impact on India.

A Scoping Review of Three Dimensions for Long-Term COVID-19 Vaccination Models: Hybrid Immunity, Individual Drivers of Vaccinal Choice, and Human Errors

The virus that causes COVID-19 changes over time, occasionally leading to Variants of Interest (VOIs) and Variants of Concern (VOCs) that can behave differently with respect to detection kits, treatments, or vaccines. For instance, two vaccination doses were 61% effective against the BA.1 predominant variant, but only 24% effective when BA.2 became predominant. While doses still confer protection against severe disease outcomes, the BA.5 variant demonstrates the possibility that individuals who have received a few doses built for previous variants can still be infected with newer variants. As previous vaccines become less effective, new ones will be released to target specific variants and the whole process of vaccinating the population will restart. While previous models have detailed logistical aspects and disease progression, there are three additional key elements to model COVID-19 vaccination coverage in the long term. First, the willingness of the population to participate in regular vaccination campaigns is essential for long-term effective COVID-19 vaccination coverage. Previous research has shown that several categories of variables drive vaccination status: sociodemographic, health-related, psychological, and information-related constructs. However, the inclusion of these categories in future models raises questions about the identification of specific factors (e.g., which sociodemographic aspects?) and their operationalization (e.g., how to initialize agents with a plausible combination of factors?). While previous models separately accounted for natural- and vaccine-induced immunity, the reality is that a significant fraction of individuals will be both vaccinated and infected over the coming years. Modeling the decay in immunity with respect to new VOCs will thus need to account for hybrid immunity. Finally, models rarely assume that individuals make mistakes, even though this over-reliance on perfectly rational individuals can miss essential dynamics. Using the U.S. as a guiding example, our scoping review summarizes these aspects (vaccinal choice, immunity, and errors) through ten recommendations to support the modeling community in developing long-term COVID-19 vaccination models.