Rapidly shifting immunologic landscape and severity of SARS-CoV-2 in the Omicron era in South Africa

Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden

As public health policies shifted in 2023 from emergency response to long-term COVID-19 disease management, immunization programs started to face the challenge of formulating routine booster campaigns in a still highly uncertain seasonal behavior of the COVID-19 epidemic. Mathematical models assessing past booster campaigns and integrating knowledge on waning of immunity can help better inform current and future vaccination programs. Focusing on the first booster campaign in the 2021/2022 winter in France, we used a multi-strain age-stratified transmission model to assess the effectiveness of the observed booster vaccination in controlling the succession of Delta, Omicron BA.1 and BA.2 waves. We explored counterfactual scenarios altering the eligibility criteria and inter-dose delay. Our study showed that the success of the immunization program in curtailing the Omicron BA.1 and BA.2 waves was largely dependent on the inclusion of adults among the eligible groups, and was highly sensitive to the inter-dose delay, which was changed over time. Shortening or prolonging this delay, even by only one month, would have required substantial social distancing interventions to curtail the hospitalization peak. Also, the time window for adjusting the delay was very short. Our findings highlight the importance of readiness and adaptation in the formulation of routine booster campaign in the current level of epidemiological uncertainty.

Integrated analyses of the transmission history of SARS-CoV-2 and its association with molecular evolution of the virus underlining the pandemic outbreaks in Italy, 2019-2023

BACKGROUND

Italy was significantly affected by the COVID-19 pandemic, experiencing multiple waves of infection following the sequential emergence of new variants. Understanding the transmission patterns and evolution of SARS-CoV-2 is vital for future preparedness.

METHODS

We conducted an analysis of viral genome sequences, integrating epidemiological and phylodynamic approaches, to characterize how SARS-CoV-2 variants have spread within the country.

RESULTS

Our findings indicate bidirectional international transmission, with Italy transitioning between importing and exporting the virus. Italy experienced four distinct epidemic waves, each associated with a significant reduction in fatalities from 2021 to 2023. These waves were primarily driven by the emergence of VOCs such as Alpha, Delta, and Omicron, which were reflected in observed transmission dynamics and effectiveness of public health measures.

CONCLUSIONS

The changing patterns of viral spread and variant prevalence throughout Italy's pandemic response underscore the continued importance of flexible public health strategies and genomic surveillance, both of which are crucial for tracking the evolution of variants and adapting control measures effectively to ensure preparedness for future outbreaks.

SARS-CoV-2 infections before, during, and after the Omicron wave: a 2-year Indian community cohort study

Background

We measured the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and re-infections in an adult community-based cohort in southern India.

Methods

We conducted a 2-year follow-up on 1229 participants enrolled between May and October 2021. Participants provided vaccination histories, weekly saliva samples, and blood samples at 0, 6, 12, and 24 months. Salivary reverse transcription polymerase chain reaction (RT-PCR) and Meso-Scale Discovery panels were used for SARS-CoV-2 detection and anti-spike, anti-nucleocapsid immunoglobulin G quantification. Whole genome sequencing was performed on a subset of positive samples. SARS-CoV-2 infection incidence was measured across Pre-Omicron (May-December 2021), Omicron-I (December 2021-June 2022), and Omicron-II (July 2022-October 2023) periods.

Findings

In total, 1166 (95%) participants with 83% seropositivity at baseline completed the follow-up, providing 2205 person-years of observation. Utilizing both RT-PCR and serology we identified 1306 infections and yielded an incidence rate of 591.3 per 1000 person-years (95% confidence interval, 559.6-624.3), which peaked during Omicron-I at 1418.1 per 1000 person-years (95% confidence interval, 1307.4-1535.6). During Omicron-I and II, neither prior infection nor vaccination conferred protection against infection. Overall, 74% of infections were asymptomatic.

Interpretation

Integrated RT-PCR and serology revealed significant SARS-CoV-2 infection frequency, highlighting the prevalence of asymptomatic cases among previously infected or vaccinated individuals. This underscores the effectiveness of combining surveillance strategies when monitoring pandemic trends and confirms the role of non-invasive sampling in ensuring participant compliance, reflecting national transmission patterns.

Funding

The study was funded by the Bill and Melinda Gates Foundation.

SARS-CoV-2 correlates of protection from infection against variants of concern

Serum neutralizing antibodies (nAbs) induced by vaccination have been linked to protection against symptomatic and severe coronavirus disease 2019. However, much less is known about the efficacy of nAbs in preventing the acquisition of infection, especially in the context of natural immunity and against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune-escape variants. Here we conducted mediation analysis to assess serum nAbs induced by prior SARS-CoV-2 infections as potential correlates of protection against Delta and Omicron infections, in rural and urban household cohorts in South Africa. We find that, in the Delta wave, D614G nAbs mediate 37% (95% confidence interval: 34-40%) of the total protection against infection conferred by prior exposure to SARS-CoV-2, and that protection decreases with waning immunity. In contrast, Omicron BA.1 nAbs mediate 11% (95% confidence interval: 9-12%) of the total protection against Omicron BA.1 or BA.2 infections, due to Omicron's neutralization escape. These findings underscore that correlates of protection mediated through nAbs are variant specific, and that boosting of nAbs against circulating variants might restore or confer immune protection lost due to nAb waning and/or immune escape. However, the majority of immune protection against SARS-CoV-2 conferred by natural infection cannot be fully explained by serum nAbs alone. Measuring these and other immune markers including T cell responses, both in the serum and in other compartments such as the nasal mucosa, may be required to comprehensively understand and predict immune protection against SARS-CoV-2.

Impact of Missense Mutations on Spike Protein Stability and Binding Affinity in the Omicron Variant

The global effort to combat the COVID-19 pandemic faces ongoing uncertainty with the emergence of Variants of Concern featuring numerous mutations on the Spike (S) protein. In particular, the Omicron Variant is distinguished by 32 mutations, including 10 within its receptor-binding domain (RBD). These mutations significantly impact viral infectivity and the efficacy of vaccines and antibodies currently in use for therapeutic purposes. In our study, we employed structure-based computational saturation mutagenesis approaches to predict the effects of Omicron missense mutations on RBD stability and binding affinity, comparing them to the original Wuhan-Hu-1 strain. Our results predict that mutations such as G431W and P507W induce the most substantial destabilizations in the Wuhan-Hu-1-S/Omicron-S RBD. Notably, we postulate that mutations in the Omicron-S exhibit a higher percentage of enhancing binding affinity compared to Wuhan-S. We found that the mutations at residue positions G447, Y449, F456, F486, and S496 led to significant changes in binding affinity. In summary, our findings may shed light on the widespread prevalence of Omicron mutations in human populations. The Omicron mutations that potentially enhance their affinity for human receptors may facilitate increased viral binding and internalization in infected cells, thereby enhancing infectivity. This informs the development of new neutralizing antibodies capable of targeting Omicron's immune-evading mutations, potentially aiding in the ongoing battle against the COVID-19 pandemic.

Fine-scale spatial and social patterns of SARS-CoV-2 transmission from identical pathogen sequences

Pathogen genomics can provide insights into disease transmission patterns, but new methods are needed to handle modern large-scale pathogen genome datasets. Genetically proximal viruses indicate epidemiological linkage and are informative about transmission events. Here, we leverage pairs of identical sequences using 114,298 SARS-CoV-2 genomes collected via sentinel surveillance from March 2021 to December 2022 in Washington State, USA, with linked age and residence information to characterize fine-scale transmission. The location of pairs of identical sequences is highly consistent with expectations from mobility and social contact data. Outliers in the relationship between genetic and mobility data can be explained by SARS-CoV-2 transmission between postal codes with male prisons, consistent with transmission between prison facilities. Transmission patterns between age groups vary across spatial scales. Finally, we use the timing of sequence collection to understand the age groups driving transmission. This work improves our ability to characterize transmission from large pathogen genome datasets.

High SARS-CoV-2 incidence and asymptomatic fraction during Delta and Omicron BA.1 waves in The Gambia

Little is known about SARS-CoV-2 infection risk in African countries with high levels of infection-driven immunity and low vaccine coverage. We conducted a prospective cohort study of 349 participants from 52 households in The Gambia between March 2021 and June 2022, with routine weekly SARS-CoV-2 RT-PCR and 6-monthly SARS-CoV-2 serology. Attack rates of 45% and 57% were seen during Delta and Omicron BA.1 waves respectively. Eighty-four percent of RT-PCR-positive infections were asymptomatic. Children under 5-years had a lower incidence of infection than 18-49-year-olds. One prior SARS-CoV-2 infection reduced infection risk during the Delta wave only, with immunity from ≥2 prior infections required to reduce the risk of infection with early Omicron lineage viruses. In an African population with high levels of infection-driven immunity and low vaccine coverage, we find high attack rates during SARS-CoV-2 waves, with a high proportion of asymptomatic infections and young children remaining relatively protected from infection.

Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course

Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology remains unclear. Here, we used a multi-level mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns and to investigate how influenza incidence varies over time, space and age in this population. We estimated median annual influenza infection rates to be approximately 18% from 1968 to 2015, but with substantial variation between years. 88% of individuals were estimated to have been infected at least once during the study period (2009-2015), and 20% were estimated to have three or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long term, epidemiological trends, within-host processes and immunity when analyzed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

SARS-CoV-2 Neutralizing Antibodies in Three African Countries Following Multiple Distinct Immune Challenges

BACKGROUND

The COVID-19 pandemic has affected Madagascar, Cameroon, and the Central African Republic (CAR), with each experiencing multiple waves by mid-2022. This study aimed to evaluate immunity against SARS-CoV-2 strains Wuhan (W) and BA.2 (BA.2) among healthcare workers (HCWs) in these countries, focusing on vaccination and natural infection effects.

METHODS

HCWs' serum samples were analyzed for neutralizing antibodies (nAbs) against W and BA.2 variants, with statistical analyses comparing responses between countries and vaccination statuses.

RESULTS

Madagascar showed significantly higher nAb titers against both strains compared to CAR and Cameroon. Vaccination notably increased nAb levels against W by 2.6-fold in CAR and 1.8-fold in Madagascar, and against BA.2 by 1.6-fold in Madagascar and 1.5-fold in CAR. However, in Cameroon, there was no significant difference in nAb levels between vaccinated and unvaccinated groups.

CONCLUSION

This study highlights the complex relationship between natural and vaccine-induced immunity, emphasizing the importance of assessing immunity in regions with varied epidemic experiences and low vaccination rates.

Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.

Epidemiological features of SARS-CoV-2 Omicron infection under new control strategy: a cross-sectional study of the outbreak since December 2022 in Sichuan, China

BACKGROUND

A major shift in the "dynamic zero-COVID" policy was announced by China's National Health Commission on December 7, 2022, and the subsequent immediate large-scale outbreak of SARS-CoV-2 infections in the entire country has caused worldwide concern. This observational cross-sectional study aimed to describe the epidemiological characteristics of this outbreak in Sichuan, China.

METHODS

All data were self-reported online by volunteers. We described the epidemic by characterizing the infection, symptoms, clinical duration, severity, spatiotemporal clustering, and dynamic features of the disease. Prevalence ratio (PR), Odds ratios (ORs) and adjusted ORs were calculated to analyze the associations between risk factors and infection and the associations of risk factors with clinical severity using log-binomial and multivariable logistic regression models; 95% confidence intervals (CIs) and Wald test results were reported. The prevalence rates and clinical severity among different subgroups were compared using the Chi-square and trend Chi-square tests.

RESULTS

Between January 6 and 12, 2023, 138,073 volunteers were enrolled in this survey, and 102,645 were infected with COVID-19, holding a prevalence rate of 74.34%; the proportion of asymptomatic infections was 1.58%. Log-binomial regression revealed that the risk of infection increased among those living in urban areas. Multivariable logistic regression analysis showed that female sex, chronic diseases, older age and the fewer doses of vaccine received were associated with an increased risk of severe clinical outcomes after infection. We estimated the mean reproduction number during this pandemic was 1.83. The highest time-dependent reproduction number was 4.15; this number decreased below 1 after 11 days from December 7, 2022. Temporal trends revealed a single peak curve with a plateau pattern of incidence during the outbreak, whereas spatiotemporal clustering analysis showed that the onset in 21 cities in the Sichuan province had four-wave peaks.

CONCLUSIONS

The peak of the first wave of Omicron infection in Sichuan Province had passed and could be considered a snapshot of China under the new control strategy. There were significant increases in the risk of severe clinical outcomes after infection among females, with chronic diseases, and the elderly. The vaccines have been effective in reducing poor clinical outcomes.

Characterizing the evolving SARS-CoV-2 seroprevalence in urban and rural Malawi between February 2021 and April 2022: A population-based cohort study

OBJECTIVES

This study aimed to investigate the changing SARS-CoV-2 seroprevalence and associated health and sociodemographic factors in Malawi between February 2021 and April 2022.

METHODS

In total, four 3-monthly serosurveys were conducted within a longitudinal population-based cohort in rural Karonga District and urban Lilongwe, testing for SARS-CoV-2 S1 immunoglobulin (Ig)G antibodies using an enzyme-linked immunosorbent assay. Population seroprevalence was estimated in all and unvaccinated participants. Bayesian mixed-effects logistic models estimated the odds of seropositivity in the first survey, and of seroconversion between surveys, adjusting for age, sex, occupation, location, and assay sensitivity/specificity.

RESULTS

Of the 2005 participants (Karonga, n = 1005; Lilongwe, n = 1000), 55.8% were female and median age was 22.7 years. Between Surveys (SVY) 1 and 4, population-weighted SARS-CoV-2 seroprevalence increased from 26.3% to 89.2% and 46.4% to 93.9% in Karonga and Lilongwe, respectively. At SVY4, seroprevalence did not differ by COVID-19 vaccination status in adults, except for those aged 30+ years in Karonga (unvaccinated: 87.4%, 95% credible interval 79.3-93.0%; two doses: 98.1%, 94.8-99.5%). Location and age were associated with seroconversion risk. Individuals with hybrid immunity had higher SARS-CoV-2 seropositivity and antibody titers, than those infected.

CONCLUSION

High SARS-CoV-2 seroprevalence combined with low morbidity and mortality indicate that universal vaccination is unnecessary at this stage of the pandemic, supporting change in national policy to target at-risk groups.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

Community transmission of SARS-CoV-2 during the Delta wave in New York City

BACKGROUND

Understanding community transmission of SARS-CoV-2 variants of concern (VOCs) is critical for disease control in the post pandemic era. The Delta variant (B.1.617.2) emerged in late 2020 and became the dominant VOC globally in the summer of 2021. While the epidemiological features of the Delta variant have been extensively studied, how those characteristics shaped community transmission in urban settings remains poorly understood.

METHODS

Using high-resolution contact tracing data and testing records, we analyze the transmission of SARS-CoV-2 during the Delta wave within New York City (NYC) from May 2021 to October 2021. We reconstruct transmission networks at the individual level and across 177 ZIP code areas, examine network structure and spatial spread patterns, and use statistical analysis to estimate the effects of factors associated with COVID-19 spread.

RESULTS

We find considerable individual variations in reported contacts and secondary infections, consistent with the pre-Delta period. Compared with earlier waves, Delta-period has more frequent long-range transmission events across ZIP codes. Using socioeconomic, mobility and COVID-19 surveillance data at the ZIP code level, we find that a larger number of cumulative cases in a ZIP code area is associated with reduced within- and cross-ZIP code transmission and the number of visitors to each ZIP code is positively associated with the number of non-household infections identified through contact tracing and testing.

CONCLUSIONS

The Delta variant produced greater long-range spatial transmission across NYC ZIP code areas, likely caused by its increased transmissibility and elevated human mobility during the study period. Our findings highlight the potential role of population immunity in reducing transmission of VOCs. Quantifying variability of immunity is critical for identifying subpopulations susceptible to future VOCs. In addition, non-pharmaceutical interventions limiting human mobility likely reduced SARS-CoV-2 spread over successive pandemic waves and should be encouraged for reducing transmission of future VOCs.

Effectiveness of the booster dose of inactivated COVID-19 vaccine against Omicron BA.5 infection: a matched cohort study of adult close contacts

BACKGROUND

Although COVID-19 vaccines and their booster regimens protect against symptomatic infections and severe outcomes, there is limited evidence about their protection against asymptomatic and symptomatic infections in real-world settings, particularly when considering that the majority of SARS-CoV-2 Omicron infections were asymptomatic. We aimed to assess the effectiveness of the booster dose of inactivated vaccines in mainland China, i.e., Sinopharm (BBIBP-CorV) and Sinovac (CoronaVac), against Omicron infection in an Omicron BA.5 seeded epidemic.

METHODS

Based on an infection-naive but highly vaccinated population in Urumqi, China, the study cohort comprised all 37,628 adults who had a contact history with individuals having SARS-CoV-2 infections, i.e., close contacts, between August 1 and September 7, 2022. To actively detect SARS-CoV-2 infections, RT-PCR tests were performed by local authorities on a daily basis for all close contacts, and a testing-positive status was considered a laboratory-confirmed outcome. The cohort of close contacts was matched at a ratio of 1:5 with the fully vaccinated (i.e., 2 doses) and booster vaccinated groups (i.e., 3 doses) according to sex, age strata, calendar date, and contact settings. Multivariate conditional logistic regression models were adopted to estimate the marginal effectiveness of the booster dose against Omicron BA.5 infection after adjusting for confounding variables. Subgroup analyses were performed to assess vaccine effectiveness (VE) in different strata of sex, age, the time lag from the last vaccine dose to exposure, and the vaccination status of the source case. Kaplan-Meier curves were employed to visualize the follow-up process and testing outcomes among different subgroups of the matched cohort.

FINDINGS

Before matching, 37,099 adult close contacts were eligible for cohort enrolment. After matching, the 2-dose and 3-dose groups included 3317 and 16,051 contacts, and the proportions with Omicron infections were 1.03% and 0.62% among contacts in the 2-dose and 3-dose groups, respectively. We estimated that the adjusted effectiveness of the inactivated booster vaccine versus 2 doses against Omicron infection was 35.5% (95% CI 2.0, 57.5). The booster dose provided a higher level of protection, with an effectiveness of 60.2% (95% CI 22.8, 79.5) for 15-180 days after vaccination, but this VE decreased to 35.0% (95% CI 2.8, 56.5) after 180 days. Evidence for the protection of the booster dose was detected among young adults aged 18-39 years, but was not detected for those aged 40 years or older.

INTERPRETATION

The receipt of the inactivated vaccine booster dose was associated with a significantly lower Omicron infection risk, and our findings confirmed the vaccine effectiveness (VE) of booster doses against Omicron BA.5 variants. Given the rapid evolution of SARS-CoV-2, we highlight the importance of continuously monitoring the protective performance of vaccines against the genetic variants of SARS-CoV-2, regardless of existing vaccine coverage.

Clinical and virological features of asymptomatic and mild symptomatic patients with SARS-CoV-2 Omicron infection at Shanghai Fangcang shelter hospital

OBJECTIVE

The objective of this study is to evaluate and compare clinical and virological characteristics of asymptomatic and mild symptomatic patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2.2 variant infection and identify risk factors associated with the prolonged viral negative conversion duration.

METHODS

We conducted a retrospective observational study in a Shanghai (China) Fangcang shelter hospital from April 9 to May 17, 2022. The patient-related demographic or clinical data were retrospectively recorded. Comparisons of demographic and clinical characteristics between asymptomatic and mild-symptomatic patients were performed. Cox regression was performed to identify the risk factors of prolonged viral negative conversion duration.

RESULTS

A total of 551 patients confirmed with SARS-CoV-2 Omicron variant infection were enrolled in the study. Of these, 297 patients (53.9%) were asymptomatic and 254 patients (46.1%) had mild symptoms. When comparing the clinical and virological characteristics between the asymptomatic and mild symptomatic groups, several clinical parameters, including age, gender, time to viral clearance from the first positive swab, chronic comorbidities, and vaccination dose did not show statistically significant differences. In mild symptomatic patients, the median viral negative conversion duration (NCD) was 7 days (interquartile range [IQR]: 5-9), which was comparable to the median of 7 days (IQR: 5-10) in asymptomatic patients (p = .943). Multivariate Cox analysis revealed that patients age ≥ 60 years had a significantly higher hazard ratio (HR) for prolonged viral NCD (HR: 1.313; 95% confidence interval: 1.014-1.701, p = .039).

CONCLUSION

Asymptomatic and symptomatic patients with non-severe SARS-CoV-2 Omicron BA.2.2 variant infection have similar clinical features and virological courses. Old age was an independent risk factor for prolonged SARS-CoV-2 conversion time.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Real-world COVID-19 vaccine effectiveness against the Omicron BA.2 variant in a SARS-CoV-2 infection-naive population

The SARS-CoV-2 Omicron variant has demonstrated enhanced transmissibility and escape of vaccine-derived immunity. Although first-generation vaccines remain effective against severe disease and death, robust evidence on vaccine effectiveness (VE) against all Omicron infections, irrespective of symptoms, remains sparse. We used a community-wide serosurvey with 5,310 subjects to estimate how vaccination histories modulated risk of infection in infection-naive Hong Kong during a large wave of Omicron BA.2 epidemic in January-July 2022. We estimated that Omicron infected 45% (41-48%) of the local population. Three and four doses of BNT162b2 or CoronaVac were effective against Omicron infection 7 days after vaccination (VE of 48% (95% credible interval 34-64%) and 69% (46-98%) for three and four doses of BNT162b2, respectively; VE of 30% (1-66%) and 56% (6-97%) for three and four doses of CoronaVac, respectively). At 100 days after immunization, VE waned to 26% (7-41%) and 35% (10-71%) for three and four doses of BNT162b2, and to 6% (0-29%) and 11% (0-54%) for three and four doses of CoronaVac. The rapid waning of VE against infection conferred by first-generation vaccines and an increasingly complex viral evolutionary landscape highlight the necessity for rapidly deploying updated vaccines followed by vigilant monitoring of VE.