Dynamic variations in COVID-19 with the SARS-CoV-2 Omicron variant in Kazakhstan and Pakistan.

BACKGROUND: The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) and the Omicron variant presents a formidable challenge for control and prevention worldwide, especially for low- and middle-income countries (LMICs). Hence, taking Kazakhstan and Pakistan as examples, this study aims to explore COVID-19 transmission with the Omicron variant at different contact, quarantine and test rates. METHODS: A disease dynamic model was applied, the population was segmented, and three time stages for Omicron transmission were established: the initial outbreak, a period of stabilization, and a second outbreak. The impact of population contact, quarantine and testing on the disease are analyzed in five scenarios to analysis their impacts on the disease. Four statistical metrics are employed to quantify the model's performance, including the correlation coefficient (CC), normalized absolute error, normalized root mean square error and distance between indices of simulation and observation (DISO). RESULTS: Our model has high performance in simulating COVID-19 transmission in Kazakhstan and Pakistan with high CC values greater than 0.9 and DISO values less than 0.5. Compared with the present measures (baseline), decreasing (increasing) the contact rates or increasing (decreasing) the quarantined rates can reduce (increase) the peak values of daily new cases and forward (delay) the peak value times (decreasing 842 and forward 2 days for Kazakhstan). The impact of the test rates on the disease are weak. When the start time of stage II is 6 days, the daily new cases are more than 8 and 5 times the rate for Kazakhstan and Pakistan, respectively (29,573 vs. 3259; 7398 vs. 1108). The impact of the start times of stage III on the disease are contradictory to those of stage II. CONCLUSIONS: For the two LMICs, Kazakhstan and Pakistan, stronger control and prevention measures can be more effective in combating COVID-19. Therefore, to reduce Omicron transmission, strict management of population movement should be employed. Moreover, the timely application of these strategies also plays a key role in disease control.

Long-term variations and potency of neutralizing antibodies against Omicron subvariants after CoronaVac-inactivated booster: A 7-month follow-up study.

The long-term protective efficacy of neutralizing antibodies (Nabs) against Omicron subvariants after inactivated booster vaccines remains elusive. During the follow-up study, 54 healthy volunteers aged 20-31 years received inactivated CoronaVac booster vaccinations and were monitored for 221 days. The dynamic efficacy and durability of Nab against Omicron subvariants BA.1, BA.2, BA.2.12.2, and BA4/5 were assessed using a pseudotyped virus neutralization assay at up to nine time points post immunization. The antibody response against Omicron subvariants was substantially weaker than D614G, with BA.4/5 being the least responsive. The geometric mean titer (GMT) of Nab against Omicron subvariants BA.1, BA.2, BA.2.12.1, and BA.4/5 was 2.2-, 1.7-, 1.8-, and 2.2-fold lower than that against D614G (ps < 0.0001). The gap in Nab response between Omicron subvariants was pronounced during the 2 weeks-2 months following booster vaccination (ps < 0.05). Seven months post booster, the antibody potency against D614G was maintained at 100% (50% for Nab titers ≥ 100 50% inhibitory dilution [EC50 ]), whereas at 77.3% for BA.1, 90.9% for BA.2, 86.4% for BA.2.12.1, and 86.4% for BA.4/5 (almost 20% for Nab titers ≥ 100 EC50 ). Despite the inevitable immune escape, Omicron subvariants maintained sustained and measurable antibody potency post-booster vaccination during long-term monitoring, which could help optimize immunization strategies.

Cross-reactivity of eight SARS-CoV-2 variants rationally predicts immunogenicity clustering in sarbecoviruses.

A steep rise in Omicron reinfection cases suggests that this variant has increased immune evasion ability. To evaluate its antigenicity relationship with other variants, antisera from guinea pigs immunized with spike protein of SARS-CoV-2 variants of concern (VOCs) and variants of interest (VOIs) were cross-tested against pseudotyped variants. The neutralization activity against Omicron was markedly reduced when other VOCs or VOIs were used as immunogens, and Omicron (BA.1)-elicited sera did not efficiently neutralize the other variants. However, a Beta or Omicron booster, when administered as the 4th dose 3-months after the 3rd dose of any of the variants, could elicit broad neutralizing antibodies against all of the current variants including Omicron BA.1. Further analysis with 280 available antigen-antibody structures and quantification of immune escape from 715 reported neutralizing antibodies provide explanations for the observed differential immunogenicity. Three distinct clades predicted using an in silico algorithm for clustering of sarbecoviruses based on immune escape provide key information for rational design of vaccines.

Structural basis of nanobodies neutralizing SARS-CoV-2 variants.

Because of the evolutionary variants of SARS-CoV-2, development of broad-spectrum neutralizing antibodies resilient to virus escape is urgently needed. We identified a group of high-affinity nanobodies from camels immunized with receptor-binding domain (RBD) of SARS-CoV-2 spike protein and resolved the structures of two non-competing nanobodies (NB1A7 and NB1B11) in complex with RBD using X-ray crystallography. The structures show that NB1A7 targets the highly conserved cryptic epitope shared by SARS-CoV-2 variants and some other coronaviruses and blocks ACE2 receptor attachment of the spike protein, and NB1B11 epitope overlaps with the contacting surface of ACE2 and is different from the binding site of NB1A7. These two nanobodies were covalently linked into multivalent and bi-paratopic formats, which significantly improved the avidity and neutralization potency and may further inhibit viral escape. The results contribute to the structure-guided design of antibodies against future variants of SARS-CoV-2 virus to combat coronavirus epidemics and pandemics.

Antigenicity comparison of SARS-CoV-2 Omicron sublineages with other variants contained multiple mutations in RBD.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, particularly those with multiple mutations in receptor-binding domain (RBD), pose a critical challenge to the efficacy of coronavirus disease 2019 (COVID-19) vaccines and therapeutic neutralizing monoclonal antibodies (mAbs). Omicron sublineages BA.1, BA.2, BA.3, as well as the recent emergence of C.1.2, B.1.630, B.1.640.1, and B.1.640.2, have multiple mutations in RBD and may lead to severe neutralizing antibody evasion. It is urgent to evaluate the antigenic change of the above seven variants against mAbs and sera from guinea pigs immunized with variants of concern (VOCs) (Alpha, Beta, Gamma, Delta, Omicron) and variants of interest (VOIs) (Lambda, Mu) immunogens. Only seven out of the 24 mAbs showed no reduction in neutralizing activity against BA.1, BA.2, and BA.3. However, among these seven mAbs, the neutralization activity of XGv337 and XGv338 against C.1.2, B.1.630, B.1.640.1, and B.1.640.2 were decreased. Therefore, only five neutralizing mAbs showed no significant change against these seven variants. Using VOCs and VOIs as immunogens, we found that the antigenicity of variants could be divided into three clusters, and each cluster showed similar antigenicity to different immunogens. Among them, D614G, B.1.640.1, and B.1.630 formed a cluster, C.1.2 and B.1.640.2 formed a cluster, and BA.1, BA.2, and BA.3 formed a cluster.

Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies.

The SARS-CoV-2 B.1.1.529 (Omicron) variant contains 15 mutations of the receptor-binding domain (RBD). How Omicron evades RBD-targeted neutralizing antibodies requires immediate investigation. Here we use high-throughput yeast display screening1,2 to determine the profiles of RBD escaping mutations for 247 human anti-RBD neutralizing antibodies and show that the neutralizing antibodies can be classified by unsupervised clustering into six epitope groups (A-F)-a grouping that is highly concordant with knowledge-based structural classifications3-5. Various single mutations of Omicron can impair neutralizing antibodies of different epitope groups. Specifically, neutralizing antibodies in groups A-D, the epitopes of which overlap with the ACE2-binding motif, are largely escaped by K417N, G446S, E484A and Q493R. Antibodies in group E (for example, S309)6 and group F (for example, CR3022)7, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but a subset of neutralizing antibodies are still escaped by G339D, N440K and S371L. Furthermore, Omicron pseudovirus neutralization showed that neutralizing antibodies that sustained single mutations could also be escaped, owing to multiple synergetic mutations on their epitopes. In total, over 85% of the tested neutralizing antibodies were escaped by Omicron. With regard to neutralizing-antibody-based drugs, the neutralization potency of LY-CoV016, LY-CoV555, REGN10933, REGN10987, AZD1061, AZD8895 and BRII-196 was greatly undermined by Omicron, whereas VIR-7831 and DXP-604 still functioned at a reduced efficacy. Together, our data suggest that infection with Omicron would result in considerable humoral immune evasion, and that neutralizing antibodies targeting the sarbecovirus conserved region will remain most effective. Our results inform the development of antibody-based drugs and vaccines against Omicron and future variants.

The significant immune escape of pseudotyped SARS-CoV-2 variant Omicron.

The emergence of Omicron/BA.1 has brought new challenges to fight against SARS-CoV-2. A large number of mutations in the Spike protein suggest that its susceptibility to immune protection elicited by the existing COVID-19 infection and vaccines may be altered. In this study, we constructed the pseudotyped SARS-CoV-2 variant Omicron. The sensitivity of 28 serum samples from COVID-19 convalescent patients infected with SARS-CoV-2 original strain was tested against pseudotyped Omicron as well as the other variants of concern (VOCs, Alpha, Beta, Gamma, Delta) and variants of interest (VOIs, Lambda, Mu). Our results indicated that the mean neutralization ED50 of these sera against Omicron decreased to 66, which is about 8.4-folds compared to the D614G reference strain (ED50 = 556), whereas the neutralization activity of other VOC and VOI pseudotyped viruses decreased only about 1.2-4.5-folds. The finding from our in vitro assay suggest that Omicron variant may lead to more significant escape from immune protection elicited by previous SARS-CoV-2 infection and perhaps even by existing COVID-19 vaccines.

Evaluation and prediction of the COVID-19 variations at different input population and quarantine strategies, a case study in Guangdong Province, China

In this study, an epidemic model was developed to simulate and predict the disease variations of Guangdong province which was focused on the period from Jan 27 to Feb 20, 2020. To explore the impacts of the input population and quarantine strategies on the disease variations at different scenarios, four time points were assumed as Feb 6, Feb 16, Feb 24 and Mar 5 2020. The major results suggest that our model can well capture the disease variations with high accuracy. The simulated peak value of the confirmed cases is 1002 at Feb 10, 2020 which is mostly close to the reported number of 1007 at Feb 9, 2020. The disease will become extinction with peak value of 1397 at May 11, 2020. Moreover, the increased numbers of the input population can mainly shorten the disease extinction days and the increased percentages of the exposed individuals of the input population increase the number of cumulative confirmed cases at a small percentage. Increasing the input population and decreasing the quarantine strategy together around the time point of the peak value of the confirmed cases, may lead to the second outbreak.

Dynamical Variations of the Global COVID-19 Pandemic Based on a SEICR Disease Model: A New Approach of Yi Hua Jie Mu.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has caused more than 150 million cases of infection to date and poses a serious threat to global public health. In this study, global COVID-19 data were used to examine the dynamical variations from the perspectives of immunity and contact of 84 countries across the five climate regions: tropical, arid, temperate, and cold. A new approach named Yi Hua Jie Mu is proposed to obtain the transmission rates based on the COVID-19 data between the countries with the same climate region over the Northern Hemisphere and Southern Hemisphere. Our results suggest that the COVID-19 pandemic will persist over a long period of time or enter into regular circulation in multiple periods of 1-2 years. Moreover, based on the simulated results by the COVID-19 data, it is found that the temperate and cold climate regions have higher infection rates than the tropical and arid climate regions, which indicates that climate may modulate the transmission of COVID-19. The role of the climate on the COVID-19 variations should be concluded with more data and more cautions. The non-pharmaceutical interventions still play the key role in controlling and prevention this global pandemic.

Dynamic variations of the COVID-19 disease at different quarantine strategies in Wuhan and mainland China.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) firstly announced in Wuhan of Hubei province, China is rapidly spreading to all the other 31 provinces of China and to more than 140 countries. Quarantine strategies play the key role on the disease controlling and public health in the world with this pandemic of the COVID-19 defined by the World Health Organization. METHODS: In this study, a SEIRQ epidemic model was developed to explore the dynamic changes of COVID-19 in Wuhan and mainland China, from January 27, 2020 to March 5, 2020. Moreover, to investigate the effects of the quarantine strategies, two perspectives are employed from the different quarantine magnitudes and quarantine time points. RESULTS: The major results suggest that the COVID-19 variations are well captured by the epidemic model with very high accuracy in the cumulative confirmed cases, confirmed cases, cumulative recovered cases and cumulative death cases. The quarantine magnitudes in the susceptible individuals play larger roles on the disease control than the impacts of the quarantines of the exposed individuals and infectious individuals. For the quarantine time points, it shows that the early quarantine strategy is significantly important for the disease controlling. The time delayed quarantining will seriously increase the COVID-19 disease patients and prolongs the days of the disease extinction. CONCLUSIONS: Our model can simulate and predict the COVID-19 variations and the quarantine strategies are important for the disease controlling, especially at the early period of the disease outbreak. These conclusions provide important scientific information for the government policymaker in the disease control strategies.