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Having adopted a dynamic zero-COVID strategy to respond to SARS-CoV-2 variants with higher transmissibility since August 2021, China is now considering whether, and for how long, this policy can remain in place. The debate has thus shifted towards the identification of mitigation strategies for minimizing disruption to the healthcare system in the case of a nationwide epidemic. To this aim, we developed an age-structured stochastic compartmental susceptible-latent-infectious-removed-susceptible model of SARS-CoV-2 transmission calibrated on the initial growth phase for the 2022 Omicron outbreak in Shanghai, to project COVID-19 burden (that is, number of cases, patients requiring hospitalization and intensive care, and deaths) under hypothetical mitigation scenarios. The model also considers age-specific vaccine coverage data, vaccine efficacy against different clinical endpoints, waning of immunity, different antiviral therapies and nonpharmaceutical interventions. We find that the level of immunity induced by the March 2022 vaccination campaign would be insufficient to prevent an Omicron wave that would result in exceeding critical care capacity with a projected intensive care unit peak demand of 15.6 times the existing capacity and causing approximately 1.55 million deaths. However, we also estimate that protecting vulnerable individuals by ensuring accessibility to vaccines and antiviral therapies, and maintaining implementation of nonpharmaceutical interventions could be sufficient to prevent overwhelming the healthcare system, suggesting that these factors should be points of emphasis in future mitigation policies. Estimates from a new modeling study suggest that current levels of vaccine coverage in China are insufficient to prevent overwhelming the healthcare system, and that, if left untreated, a nationwide Omicron wave could result in up to 1.55 million deaths.

AbstractObjectiveTo provide global, regional, and national estimates of target population sizes for coronavirus disease 2019 (covid-19) vaccination to inform country specific immunisation strategies on a global scale.DesignDescriptive study.Setting194 member states of the World Health Organization.PopulationTarget populations for covid-19 vaccination based on country specific characteristics and vaccine objectives (maintaining essential core societal services; reducing severe covid-19; reducing symptomatic infections and stopping virus transmission).Main outcome measureSize of target populations for covid-19 vaccination. Estimates use country specific data on population sizes stratified by occupation, age, risk factors for covid-19 severity, vaccine acceptance, and global vaccine production. These data were derived from a multipronged search of official websites, media sources, and academic journal articles.ResultsTarget population sizes for covid-19 vaccination vary markedly by vaccination goal and geographical region. Differences in demographic structure, presence of underlying conditions, and number of essential workers lead to highly variable estimates of target populations at regional and country levels. In particular, Europe has the highest share of essential workers (63.0 million, 8.9%) and people with underlying conditions (265.9 million, 37.4%); these two categories are essential in maintaining societal functions and reducing severe covid-19, respectively. In contrast, South East Asia has the highest share of healthy adults (777.5 million, 58.9%), a key target for reducing community transmission. Vaccine hesitancy will probably impact future covid-19 vaccination programmes; based on a literature review, 68.4% (95% confidence interval 64.2% to 72.6%) of the global population is willing to receive covid-19 vaccination. Therefore, the adult population willing to be vaccinated is estimated at 3.7 billion (95% confidence interval 3.2 to 4.1 billion).ConclusionsThe distribution of target groups at country and regional levels highlights the importance of designing an equitable and efficient plan for vaccine prioritisation and allocation. Each country should evaluate different strategies and allocation schemes based on local epidemiology, underlying population health, projections of available vaccine doses, and preference for vaccination strategies that favour direct or indirect benefits.

Genomic surveillance has shaped our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. We performed a global landscape analysis on SARS-CoV-2 genomic surveillance and genomic data using a collection of country-specific data. Here, we characterize increasing circulation of the Alpha variant in early 2021, subsequently replaced by the Delta variant around May 2021. SARS-CoV-2 genomic surveillance and sequencing availability varied markedly across countries, with 45 countries performing a high level of routine genomic surveillance and 96 countries with a high availability of SARS-CoV-2 sequencing. We also observed a marked heterogeneity of sequencing percentage, sequencing technologies, turnaround time and completeness of released metadata across regions and income groups. A total of 37% of countries with explicit reporting on variants shared less than half of their sequences of variants of concern (VOCs) in public repositories. Our findings indicate an urgent need to increase timely and full sharing of sequences, the standardization of metadata files and support for countries with limited sequencing and bioinformatics capacity. Analyses on the global diversity of SARS-CoV-2 genomic surveillance across 118 countries and the extent of public availability of genomic data provide evidence to better inform SARS-CoV-2 surveillance policy.

ObjectiveTo characterise gut microbiome in patients with hepatocellular carcinoma (HCC) and evaluate the potential of microbiome as non-invasive biomarkers for HCC.DesignWe collected 486 faecal samples from East China, Central China and Northwest China prospectively and finally 419 samples completed Miseq sequencing. We characterised gut microbiome, identified microbial markers and constructed HCC classifier in 75 early HCC, 40 cirrhosis and 75 healthy controls. We validated the results in 56 controls, 30 early HCC and 45 advanced HCC. We further verified diagnosis potential in 18 HCC from Xinjiang and 80 HCC from Zhengzhou.ResultsFaecal microbial diversity was increased from cirrhosis to early HCC with cirrhosis. Phylum Actinobacteria was increased in early HCC versus cirrhosis. Correspondingly, 13 genera including Gemmiger and Parabacteroides were enriched in early HCC versus cirrhosis. Butyrate-producing genera were decreased, while genera producing-lipopolysaccharide were increased in early HCC versus controls. The optimal 30 microbial markers were identified through a fivefold cross-validation on a random forest model and achieved an area under the curve of 80.64% between 75 early HCC and 105 non-HCC samples. Notably, gut microbial markers validated strong diagnosis potential for early HCC and even advanced HCC. Importantly, microbial markers successfully achieved a cross-region validation of HCC from Northwest China and Central China.ConclusionsThis study is the first to characterise gut microbiome in patients with HCC and to report the successful diagnosis model establishment and cross-region validation of microbial markers for HCC. Gut microbiota-targeted biomarkers represent potential non-invasive tools for early diagnosis of HCC.

ObjectiveTo characterise the oral microbiome, gut microbiome and serum lipid profiles in patients with active COVID-19 and recovered patients; evaluate the potential of the microbiome as a non-invasive biomarker for COVID-19; and explore correlations between the microbiome and lipid profile.DesignWe collected and sequenced 392 tongue-coating samples, 172 faecal samples and 155 serum samples from Central China and East China. We characterised microbiome and lipid molecules, constructed microbial classifiers in discovery cohort and verified their diagnostic potential in 74 confirmed patients (CPs) from East China and 37 suspected patients (SPs) with IgG positivity.ResultsOral and faecal microbial diversity was significantly decreased in CPs versus healthy controls (HCs). Compared with HCs, butyric acid-producing bacteria were decreased and lipopolysaccharide-producing bacteria were increased in CPs in oral cavity. The classifiers based on 8 optimal oral microbial markers (7 faecal microbial markers) achieved good diagnostic efficiency in different cohorts. Importantly, diagnostic efficacy reached 87.24% in the cross-regional cohort. Moreover, the classifiers successfully diagnosed SPs with IgG antibody positivity as CPs, and diagnostic efficacy reached 92.11% (98.01% of faecal microbiome). Compared with CPs, 47 lipid molecules, including sphingomyelin (SM)(d40:4), SM(d38:5) and monoglyceride(33:5), were depleted, and 122 lipid molecules, including phosphatidylcholine(36:4p), phosphatidylethanolamine (PE)(16:0p/20:5) and diglyceride(20:1/18:2), were enriched in confirmed patients recovery.ConclusionThis study is the first to characterise the oral microbiome in COVID-19, and oral microbiomes and lipid alterations in recovered patients, to explore their correlations and to report the successful establishment and validation of a diagnostic model for COVID-19.

Several mechanisms driving SARS-CoV-2 transmission remain unclear. Based on individual records of 1178 potential SARS-CoV-2 infectors and their 15,648 contacts in Hunan, China, we estimated key transmission parameters. The mean generation time was estimated to be 5.7 (median: 5.5, IQR: 4.5, 6.8) days, with infectiousness peaking 1.8 days before symptom onset, with 95% of transmission events occurring between 8.8 days before and 9.5 days after symptom onset. Most transmission events occurred during the pre-symptomatic phase (59.2%). SARS-CoV-2 susceptibility to infection increases with age, while transmissibility is not significantly different between age groups and between symptomatic and asymptomatic individuals. Contacts in households and exposure to first-generation cases are associated with higher odds of transmission. Our findings support the hypothesis that children can effectively transmit SARS-CoV-2 and highlight how pre-symptomatic and asymptomatic transmission can hinder control efforts. Detailed knowledge of COVID-19 epidemiology is needed to inform public health responses. Here, the authors use large-scale contact tracing data to provide empirical estimates of key parameters, and show that susceptibility increases with age but transmissibility does not vary significantly.

In mammals, the transcription factor Pax5 is a key regulator of B cell development and maturation and specifically expressed in naive/mature B cells but repressed upon B cell activation. Despite the long-standing proposal that Pax5 repression is essential for proper B cell activation, the underlying mechanisms remain largely elusive. In this study, we used a teleost model to elucidate the mechanisms governing Pax5 repression during B cell activation. Treatment with lipopolysaccharide (LPS) and chitosan oligosaccharide (COS) significantly enhanced the antibody secreting ability and phagocytic capacity of IgM + B cells in large yellow croaker ( Larimichthys crocea ), coinciding with upregulated expression of activation-related genes, such as Bcl6, Blimp1, and sIgM, and downregulated expression of Pax5. Intriguingly, two CpG islands were identified within the promoter region of Pax5. Both CpG islands exhibited hypomethylation in naive/mature B cells, while CpG island1 was specifically transited into hypermethylation upon B cell activation. Furthermore, treatment with DNA methylation inhibitor 5-aza-2’-deoxycytidine (AZA) prevented the hypermethylation of CpG island1, and concomitantly impaired the downregulation of Pax5 and activation of B cells. Finally, through in vitro methylation experiments, we demonstrated that DNA methylation exerts an inhibitory effect on promoter activities of Pax5. Taken together, our findings unveil a novel mechanism underlying Pax5 repression during B cell activation, thus promoting the understanding of B cell activation process.

Background Peritoneal metastasis (PM) is not uncommon in patients with gastric cancer(GC), which affects clinical treatment decisions, but the relevant examination measures are not efficiently detected. Our goal was to develop a clinical radiomics nomogram to better predict peritoneal metastases. Methods A total of 3480 patients from 2 centers were divided into 1 training, 1 internal validation, and 1 external validation cohort(1949 in the internal training set, 704 in the validation set, and 827 in the external validation cohort) with clinicopathologically confirmed GC. We recruited 11 clinical factors, including age, sex, smoking status, tumor size, differentiation, Borrmann type, location, clinical T stage, and serum tumor markers (STMs) comprising carbohydrate antigen 19–9 (CA19-9), carbohydrate antigen 72–4 (CA72-4), and carcinoembryonic antigen (CEA), to develop the radiomics nomogram. For clinical predictive feature selection and the establishment of clinical models, statistical methods of analysis of variance (ANOVA), relief and recursive feature elimination (RFE) and logistic regression analysis were used. To develop combined predictive models, tumor diameter, type, and location, clinical T stage and STMs were finally selected. The discriminatory ability of the nomogram to predict PM was evaluated by the area under the receiver operating characteristic curve(AUC), and decision curve analysis (DCA) was conducted to evaluate the clinical usefulness of the nomogram. Results The AUC of the clinical models was 0.762 in the training cohorts, 0.772 in the internal validation cohort, and 0.758 in the external validation cohort. However, when combined with STMs, the AUC was improved to 0.806, 0.839 and 0.801, respectively. DCA showed that the combined nomogram was of good clinical evaluation value to predict PM in GC. Conclusions The present study proposed a clinical nomogram with a combination of clinical risk factors and radiomics features that can potentially be applied in the individualized preoperative prediction of PM in GC patients.

The novel coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China, where the initial wave of intense community transmissions was cut short by interventions. Using multiple data sources, here we estimate the disease burden and clinical severity by age of COVID-19 in Wuhan from December 1, 2019 to March 31, 2020. Our estimates account for the sensitivity of the laboratory assays, prospective community screenings, and healthcare seeking behaviors. Rates of symptomatic cases, medical consultations, hospitalizations and deaths were estimated at 796 (95% CI: 703–977), 489 (472–509), 370 (358–384), and 36.2 (35.0–37.3) per 100,000 persons, respectively. The COVID-19 outbreak in Wuhan had a higher burden than the 2009 influenza pandemic or seasonal influenza in terms of hospitalization and mortality rates, and clinical severity was similar to that of the 1918 influenza pandemic. Our comparison puts the COVID-19 pandemic into context and could be helpful to guide intervention strategies and preparedness for the potential resurgence of COVID-19. Here the authors analyze disease burden and clinical severity of COVID-19 during the first wave in Wuhan, China in comparison to past influenza virus pandemics and COVID-19 in the US and Canada. These estimates of symptomatic cases, medical consultations, hospitalizations and deaths should guide preparedness for this disease.

Like mammals, fish possess an interferon regulatory factor (IRF) 3/IRF7-dependent type I IFN responses, but the exact mechanism by which IRF3/IRF7 regulate the type I IFNs remains largely unknown. In this study, we identified two type I IFNs in the Perciforme fish large yellow croaker Larimichthys crocea, one of which belongs to the fish IFNd subgroup and the other is assigned to a novel subgroup of group I IFNs in fish, tentatively termed IFNh. The two IFN genes are constitutively expressed in all examined tissues, but with varied expression levels. Both IFN genes can be rapidly induced in head kidney and spleen tissues by polyinosinic-polycytidylic acid. The recombinant IFNh was shown to be more potent to trigger a rapid induction of the antiviral genes MxA and protein kinase R than the IFNd, suggesting that they may play distinct roles in regulating early antiviral immunity. Strikingly, IFNd, but not IFNh, could induce the gene expression of itself and IFNh through a positive feedback loop mediated by the IFNd-dependent activation of IRF3 and IRF7. Furthermore, our data demonstrate that the induction of IFNd can be enhanced by the dimeric formation of IRF3 and IRF7, while the IFNh expression mainly involves IRF3. Taken together, our findings demonstrate that the IFN responses are diverse in fish and are likely to be regulated by distinct mechanisms.