As of December 12, 2022, India had reported the highest number of SARS-CoV-2 Delta variant cases, with around 102.4 thousand cases. In comparison, a total of three cases of the coronavirus (COVID-19) Delta variant had been reported in New Caledonia as of December 12, 2022. The SARS-CoV-2 Delta variant (B.1.617.2) was first detected in India in late 2020.

Background: Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) Delta variant (B.1.617.2) has been responsible for the current increase in Coronavirus disease 2019 (COVID-19) infectivity rate worldwide. We compared the impact of the Delta variant and non-Delta variant on the COVID-19 outcomes in patients from Yogyakarta and Central Java provinces, Indonesia.Methods: In this cross-sectional study, we ascertained 161 patients, 69 with the Delta variant and 92 with the non-Delta variant. The Illumina MiSeq next-generation sequencer was used to perform the whole-genome sequences of SARS-CoV-2.Results: The mean age of patients with the Delta variant and the non-Delta variant was 27.3 ± 20.0 and 43.0 ± 20.9 (p = 3 × 10−6). The patients with Delta variant consisted of 23 males and 46 females, while the patients with the non-Delta variant involved 56 males and 36 females (p = 0.001). The Ct value of the Delta variant (18.4 ± 2.9) was significantly lower than that of the non-Delta variant (19.5 ± 3.8) (p = 0.043). There was no significant difference in the hospitalization and mortality of patients with Delta and non-Delta variants (p = 0.80 and 0.29, respectively). None of the prognostic factors were associated with the hospitalization, except diabetes with an OR of 3.6 (95% CI = 1.02–12.5; p = 0.036). Moreover, the patients with the following factors have been associated with higher mortality rate than the patients without the factors: age ≥65 years, obesity, diabetes, hypertension, and cardiovascular disease with the OR of 11 (95% CI = 3.4–36; p = 8 × 10−5), 27 (95% CI = 6.1–118; p = 1 × 10−5), 15.6 (95% CI = 5.3–46; p = 6 × 10−7), 12 (95% CI = 4–35.3; p = 1.2 × 10−5), and 6.8 (95% CI = 2.1–22.1; p = 0.003), respectively. Multivariate analysis showed that age ≥65 years, obesity, diabetes, and hypertension were the strong prognostic factors for the mortality of COVID-19 patients with the OR of 3.6 (95% CI = 0.58–21.9; p = 0.028), 16.6 (95% CI = 2.5–107.1; p = 0.003), 5.5 (95% CI = 1.3–23.7; p = 0.021), and 5.8 (95% CI = 1.02–32.8; p = 0.047), respectively.Conclusions: We show that the patients infected by the SARS-CoV-2 Delta variant have a lower Ct value than the patients infected by the non-Delta variant, implying that the Delta variant has a higher viral load, which might cause a more transmissible virus among humans. However, the Delta variant does not affect the COVID-19 outcomes in our patients. Our study also confirms that older age and comorbidity increase the mortality rate of patients with COVID-19.

As of February 2022, the latest COVID-19 vaccine by Sanofi/GlaxoSmithKline showed a 77 percent efficacy against the Delta variant of the coronavirus. This statistic illustrates the comparison of select COVID-19 vaccines worldwide, by their efficacy against the Delta variant.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates.Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models.Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible.Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

IntroductionThe Delta variant posed an increased risk to global public health and rapidly replaced the pre-existent variants worldwide. In this study, the genetic diversity and the spatio-temporal dynamics of 662 SARS-CoV2 genomes obtained during the Delta wave across Tunisia were investigated.MethodsViral whole genome and partial S-segment sequencing was performed using Illumina and Sanger platforms, respectively and lineage assignemnt was assessed using Pangolin version 1.2.4 and scorpio version 3.4.X. Phylogenetic and phylogeographic analyses were achieved using IQ-Tree and Beast programs.ResultsThe age distribution of the infected cases showed a large peak between 25 to 50 years. Twelve Delta sub-lineages were detected nation-wide with AY.122 being the predominant variant representing 94.6% of sequences. AY.122 sequences were highly related and shared the amino-acid change ORF1a:A498V, the synonymous mutations 2746T>C, 3037C>T, 8986C>T, 11332A>G in ORF1a and 23683C>T in the S gene with respect to the Wuhan reference genome (NC_045512.2). Spatio-temporal analysis indicates that the larger cities of Nabeul, Tunis and Kairouan constituted epicenters for the AY.122 sub-lineage and subsequent dispersion to the rest of the country.DiscussionThis study adds more knowledge about the Delta variant and sub-variants distribution worldwide by documenting genomic and epidemiological data from Tunisia, a North African region. Such results may be helpful to the understanding of future COVID-19 waves and variants.

The COVID-19 pandemic, driven by SARS-CoV-2, has led to intensive vaccination campaigns worldwide. Despite widespread vaccination, the potential for vaccine escape variants necessitates ongoing research into the virus’s intra-host evolutionary dynamics. In this study we investigated the effects of vaccination on SARS-CoV-2 intra-host evolution during the Delta and Omicron waves in São Paulo, Brazil, analyzing 700 SARS-CoV-2 positive samples collected through the LabMovel initiative, from August 2021 to March 2022. Samples were categorized based on vaccination status (Unvaccinated, Spike protein-based vaccines, and Whole inactivated virus vaccine), enabling comparison of intra-host viral diversity across vaccinated and unvaccinated individuals for both Delta and Omicron VOCs. We evaluated intra-host genetic diversity by measuring intra-host single nucleotide variants (iSNVs), Faith's Phylogenetic Diversity (PD), and haplotype diversity using Normalized Shannon Entropy. For Delta, vaccinated groups exhibited higher haplotype diversity, yet no statistically significant difference was observed in the total number of iSNVs between vaccinated and unvaccinated individuals. Selective pressures in the Delta VOC showed neutral selection in vaccinated individuals, contrasting with purifying selection in unvaccinated individuals, though effect sizes were minimal. For Omicron, a bimodal distribution in Faith's PD across all groups suggests genetic drift events, aligning with Omicron’s rapid spread and high transmissibility. Observed intra-host diversity patterns were variant-specific, with Spike-based vaccines associated with a lower number of haplotypes in Omicron cases. These findings suggest that vaccination modulates SARS-CoV-2’s intra-host evolution, likely contributing to its mutational landscape in a variant-dependent manner. The results highlight variant-specific responses to vaccination, emphasizing the complex role of selective pressures in SARS-CoV-2 intra-host evolution. Our findings support ongoing genomic surveillance to understand vaccination's evolutionary impact on intra-host viral dynamics, particularly as new variants emerge.

Covid-19 Vaccine Market Outlook

The global Covid-19 vaccine market size was valued at approximately $60 billion in 2023 and is projected to reach around $90 billion by 2032, growing at a compound annual growth rate (CAGR) of 4.5%. The increased market size is driven by the ongoing need for booster vaccinations, advancements in vaccine technology, and the rise in government and private sector investment in immunization programs. The rapid development and deployment of Covid-19 vaccines have demonstrated the potential for scientific collaboration and innovation at an unprecedented scale, which continues to fuel market growth.

One of the primary growth factors for the Covid-19 vaccine market is the continuous evolution and mutation of the SARS-CoV-2 virus. Variants such as Delta and Omicron have necessitated the development of new vaccine formulations and booster shots to maintain immunity within populations. This ongoing need for updated vaccines ensures sustained market demand. Additionally, the global effort to achieve herd immunity, particularly in regions with lower vaccination rates, continues to drive market growth as governments and health organizations strive to vaccinate the remaining unvaccinated populations.

Another significant growth factor is the advancement in vaccine technology, particularly with mRNA and vector-based vaccines. These cutting-edge technologies have shown high efficacy rates and have accelerated the vaccine development timeline. The success of Pfizer-BioNTech and Moderna mRNA vaccines has opened new avenues for vaccine research and production, not only for Covid-19 but also for other infectious diseases. This technological progress is expected to reduce production costs, enhance distribution efficiency, and increase the overall market size.

Government and private sector investment in vaccine production and distribution infrastructure has also been a crucial growth driver. Governments worldwide have allocated substantial resources to ensure widespread vaccine availability, including funding for research and development, manufacturing, and logistics. This financial backing has enabled pharmaceutical companies to expand their production capacities and streamline supply chains, ensuring that vaccines reach all corners of the globe. Moreover, public-private partnerships have played a significant role in scaling up vaccine distribution, further propelling market growth.

The introduction of Covid 19 Dna Vaccine technology marks a significant advancement in the field of immunization. Unlike traditional vaccines, DNA vaccines work by introducing a small, circular piece of DNA into the body, which encodes the antigen that triggers an immune response. This method has the potential to be more stable and easier to produce than other vaccine types, making it a promising option for rapid deployment in response to emerging variants. As research continues, DNA vaccines could play a crucial role in broadening the arsenal of tools available to combat Covid-19, offering flexibility in addressing different strains of the virus. The development of DNA vaccines is expected to complement existing vaccine technologies, enhancing the overall effectiveness of global vaccination efforts.

Regionally, the market outlook varies significantly due to differences in vaccine access, healthcare infrastructure, and governmental policies. North America and Europe have seen high vaccination rates, driven by substantial government investment and robust healthcare systems. In contrast, regions like Asia Pacific, Latin America, and Africa face challenges related to vaccine distribution and access. However, these regions also present significant growth opportunities as international organizations and governments work to improve vaccine availability and coverage. The diverse regional dynamics contribute to the overall complexity and potential of the global Covid-19 vaccine market.

Vaccine Type Analysis

The Covid-19 vaccine market is segmented by vaccine type into mRNA, vector, protein subunit, inactivated, and others. The mRNA segment, which includes vaccines such as Pfizer-BioNTech and Moderna, has dominated the market due to its high efficacy rates and rapid development timeline. mRNA vaccines have revolutionized the vaccine industry by utilizing genetic code to stimulate an immune response, leading to quicker and more effective p

The price of crude oil over the past month has been quite volatile, influenced by various global factors. Here is a summary of the crude oil price movements for the last one month: Starting at the beginning of the month, the price of crude oil stood at $65.45 per barrel. The market was optimistic as demand for oil was expected to increase with the easing of COVID-19 restrictions and reopening of economies. However, concerns about the spread of the Delta variant and its potential impact on global oil demand

GISAID ID submissions as selected Alpha, Beta, Gamma, Delta, and Omicron variants.

Explore the factors that have influenced the price of crude oil over the last two months, including economic recovery optimism, inflation worries, geopolitical developments, and concerns over the Delta variant.

IntroductionIn November 2021, the SARS-CoV-2 Omicron variant of concern has emerged and is currently dominating the COVID-19 pandemic over the world. Omicron displays a number of mutations, particularly in the spike protein, leading to specific characteristics including a higher potential for transmission. Although Omicron has caused a significant number of deaths worldwide, it generally induces less severe clinical signs compared to earlier variants. As its impact on blood platelets remains unknown, we investigated platelet behavior in severe patients infected with Omicron in comparison to Delta.MethodsClinical and biological characteristics of severe COVID-19 patients infected with the Omicron (n=9) or Delta (n=11) variants were analyzed. Using complementary methods such as flow cytometry, confocal imaging and electron microscopy, we examined platelet activation, responsiveness and phenotype, presence of virus in platelets and induction of selective autophagy. We also explored the direct effect of spike proteins from the Omicron or Delta variants on healthy platelet signaling.ResultsSevere Omicron variant infection resulted in platelet activation and partial desensitization, presence of the virus in platelets and selective autophagy response. The intraplatelet processing of Omicron viral cargo was different from Delta as evidenced by the distribution of spike protein-positive structures near the plasma membrane and the colocalization of spike and Rab7. Moreover, spike proteins from the Omicron or Delta variants alone activated signaling pathways in healthy platelets including phosphorylation of AKT, p38MAPK, LIMK and SPL76 with different kinetics.DiscussionAlthough SARS-CoV-2 Omicron has different biological characteristics compared to prior variants, it leads to platelet activation and desensitization as previously observed with the Delta variant. Omicron is also found in platelets from severe patients where it induces selective autophagy, but the mechanisms of intraplatelet processing of Omicron cargo, as part of the innate response, differs from Delta, suggesting that mutations on spike protein modify virus to platelet interactions.

The emergence of SARS-CoV-2 variants complicates efforts to control the COVID-19 pandemic. Increasing genomic surveillance of SARS-CoV-2 is imperative for early detection of emerging variants, to trace the movement of variants, and to monitor effectiveness of countermeasures. Additionally, determining the amount of viable virus present in clinical samples is helpful to better understand the impact these variants have on viral shedding. In this study, we analyzed nasal swab samples collected between March 2020 and early November 2021 from a cohort of United States (U.S.) military personnel and healthcare system beneficiaries stationed worldwide as a part of the Defense Health Agency's (DHA) Global Emerging Infections Surveillance (GEIS) program. SARS-CoV-2 quantitative real time reverse-transcription PCR (qRT-PCR) positive samples were characterized by next-generation sequencing and a subset was analyzed for isolation and quantification of viable virus. Not surprisingly, we found that the Delta variant is the predominant strain circulating among U.S. military personnel beginning in July 2021 and primarily represents cases of vaccine breakthrough infections (VBIs). Among VBIs, we found a 50-fold increase in viable virus in nasal swab samples from Delta variant cases when compared to cases involving other variants. Notably, we found a 40-fold increase in viable virus in nasal swab samples from VBIs involving Delta as compared to unvaccinated personnel infected with other variants prior to the availability of approved vaccines. This study provides important insight about the genomic and virological characterization of SARS-CoV-2 isolates from a unique study population with a global presence.

Plasma samples taken at different time points from donors who received either AstraZeneca (Vaxzevria) or Pfizer (Comirnaty) or Moderna (Spikevax) coronavirus disease-19 (COVID-19) vaccine were assessed in virus neutralization assays against Delta and Omicron variants of concern and a reference isolate (VIC31). With the Pfizer vaccine there was 6-8-fold reduction in 50% neutralizing antibody titres (NT50) against Delta and VIC31 at 6 months compared to 2 weeks after the second dose; followed by 25-fold increase at 2 weeks after the third dose. Neutralisation of Omicron was only consistently observed 2 weeks after the third dose, with most samples having titres below the limit of detection at earlier timepoints. Moderna results were similar to Pfizer at 2 weeks after the second dose, while the titres for AstraZeneca samples derived from older donors were 7-fold lower against VIC31 and below the limit of detection against Delta and Omicron. Age and gender were not found to significantly impact our results. These findings indicate that vaccine matching may be needed, and that at least a third dose of these vaccines is necessary to generate sufficient neutralising antibodies against emerging variants of concern, especially Omicron, amidst the challenges of ensuring vaccine equity worldwide.

Background Infections with B.1.1.529 (Omicron) variants of SARS-CoV-2 became predominant worldwide since late 2021, replacing the previously dominant B.1.617.2 variant (Delta). While those variants are highly transmissible and can evade vaccine protection, population studies suggested that outcomes from infection with Omicron variants are better compared with Delta. Data regarding prognosis of maintenance hemodialysis (MHD) patients infected with Omicron vs. Delta variants, however, is scarce. Methods This retrospective cohort study includes all patients with end-stage kidney disease treated with MHD in Meir Medical Center, Kfar-Saba, Israel that were diagnosed with SARS-CoV-2 infection between June 2021 and May 2022. Results Twenty-six subjects were diagnosed with the Delta variant and 71 with Omicron. Despite comparable age between groups and higher mean vaccine doses prior to the infection among Omicron group (p

IntroductionThe emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, notably delta and omicron, has significantly accelerated the global pandemic, worsening conditions worldwide. However, there is a lack of research concerning the molecular mechanisms related to immune responses and metabolism induced by these variants. MethodsHere, metabolomics combined with transcriptomics was performed to elucidate the immunometabolic changes in the lung of hamsters infected with delta and omicron variants.ResultsBoth variants caused acute inflammation and lung pathology in intranasally infected hamsters. Principal component analysis uncovered the delta variant significantly altered lung metabolite levels between the pre- and post-infection states. Additionally, metabolic pathways determined by assessment of metabolites and genes in lung revealed significant alterations in arginine biosynthesis, glutathione metabolism, and tryptophan metabolism upon infection with both variants and closely linked to inflammatory cytokines, indicating immune activation and oxidative stress in response to both variants. These metabolic changes were also evident in the serum, validating the presence of systemic alterations corresponding to those identified in lung. Notably, the delta variant induced a more robust metabolic regulation than the omicron variant. DiscussionThe study suggests that multi-omics is a valuable approach for understanding immunometabolic responses to infectious diseases, and providing insights for effective treatment strategies.

Parameter estimates for model (35) for the Delta and Omicron variants with n = 2.

Additional file 2: Mapping of identified sequence variants in the primer binding sites.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the infectious agent of the COVID-19 pandemic, remains a global medical problem. Angiotensin-converting enzyme 2 (ACE2) was identified as the primary viral entry receptor, and transmembrane serine protease 2 primes the spike protein for membrane fusion. However, ACE2 expression is generally low and variable across tissues, suggesting that auxiliary receptors facilitate viral entry. Identifying these factors is critical for understanding SARS-Cov-2 pathophysiology and developing new countermeasures. However, profiling host–virus interactomes involves extensive genetic screening or complex computational predictions. Here, we leverage the photocatalytic proximity labeling platform μMap to rapidly profile the spike interactome in human cells and identify eight novel candidate receptors. We systemically validate their functionality in SARS-CoV-2 pseudoviral uptake assays with both Wuhan and Delta spike variants and show that dual expression of ACE2 with either neuropilin-2, ephrin receptor A7, solute carrier family 6 member 15, or myelin and lymphocyte protein 2 significantly enhances viral uptake. Collectively, our data show that SARS-CoV-2 synergistically engages several host factors for cell entry and establishes μMap as a powerful tool for rapidly interrogating host–virus interactomes.

The COVID-19 pandemic has had varying impacts across different regions, necessitating localised data-driven responses. SARS-CoV-2 was first identified in a person in Wuhan, China, in December 2019 and spread globally within three months. While there were similarities in the pandemic’s impact across regions, key differences motivated systematic quantitative analysis of diverse geographical data to inform responses. Malawi reported its first COVID-19 case on 2 April 2020 but had significantly less data than Global North countries to inform its response. Here, we present a modelling analysis of SARS-CoV-2 epidemiology and phylogenetics in Malawi between 2 April 2020 and 19 October 2022. We carried out this analysis using open-source tools and open data on confirmed cases, deaths, geography, demographics, and viral genomics. R was used for data visualisation, while Generalised Additive Models (GAMs) estimated incidence trends, growth rates, and doubling times. Phylogenetic analysis was conducted using IQ-TREE, TreeTime, and interactive tree of life. This analysis identifies five major COVID-19 waves in Malawi, driven by different lineages: (1) Early variants, (2) Beta, (3) Delta, (4) Omicron BA.1, and (5) Other Omicron. While the Alpha variant was present, it did not cause a major wave, likely due to competition from the more infectious Delta variant, since Alpha circulated in Malawi when Beta was phasing out and Delta emerging. Case Fatality Ratios were higher for Delta, and lower for Omicron, than for earlier lineages. Phylogeny reveals separation of the tree into major lineages as would be expected, and early emergence of Omicron, as is consistent with proximity to the likely origin of this variant. Both variant prevalence and overall rates of confirmed cases and confirmed deaths were highly geographically heterogeneous. We suggest that real-time analyses should be considered in Malawi and other countries, where similar computational and data resources are available.