Comparative analysis of epidemiological trends of COVID-19 in Shanghai and New York City

ObjectiveTo assess the effects of countermeasures against coronavirus disease 2019 (COVID-19) in Shanghai from March to May 2022 in comparison with epidemiological trend of COVID-19 in New York City. MethodsDaily confirmed cases, asymptomatic SARS-CoV-2 carriers, and daily deaths were obtained in the Shanghai Municipal Health Commission and the Center for Disease Control and Prevention (CDC) of the United States. Descriptive study was conducted by using these data. ResultsFrom March 1 to May 17, the number of daily asymptomatic SARS-CoV-2 infections in Shanghai was up to 58 times as large as that of daily confirmed cases;however, the number of daily confirmed cases in Shanghai was generally less than that in New York in the same time period. At the peak of the COVID-19 epidemic, the growth of daily attack rate in Shanghai was significantly lower than that in New York (P < 0.05). Moreover, the number of daily death was evidently less than that in New York. In addition, the vaccination rate in the elderly (aged 60 years) in Shanghai was evidently lower than that in New York (aged 65 years). ConclusionThe COVID-19 epidemics in Shanghai from March to May 2022 and in New York after December 2021 were both caused by the Omicron variant. Compared with the Delta variant, the Omicron variant has stronger replication ability and infectivity, resulting in challenges to the containment of the epidemic in metropolis such as Shanghai and New York City. The epidemic in New York City remained crucial due to absence of effective countermeasures, while that in Shanghai has been effectively contained with strict countermeasures. The prevention and control strategies may be adjusted along with the continual evolution of SARS-CoV-2 and increasing trend of imported COVID-19 cases.

Immune response and homeostasis mechanism following administration of BBIBP-CorV SARS-CoV-2 inactivated vaccine.

The BBIBP-CorV severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccine has been authorized for emergency use and widely distributed. We used single-cell transcriptome sequencing to characterize the dynamics of immune responses to the BBIBP-CorV inactivated vaccine. In addition to the expected induction of humoral immunity, we found that the inactivated vaccine induced multiple, comprehensive immune responses, including significantly increased proportions of CD16+ monocytes and activation of monocyte antigen presentation pathways; T cell activation pathway upregulation in CD8+ T cells, along with increased activation of CD4+ T cells; significant enhancement of cell-cell communications between innate and adaptive immunity; and the induction of regulatory CD4+ T cells and co-inhibitory interactions to maintain immune homeostasis after vaccination. Additionally, comparative analysis revealed higher neutralizing antibody levels, distinct expansion of naive T cells, a shared increased proportion of regulatory CD4+ T cells, and upregulated expression of functional genes in booster dose recipients with a longer interval after the second vaccination. Our research will support a comprehensive understanding of the systemic immune responses elicited by the BBIBP-CorV inactivated vaccine, which will facilitate the formulation of better vaccination strategies and the design of new vaccines.

Characterization of SARS-CoV-2 worldwide transmission based on evolutionary dynamics and specific viral mutations in the spike protein.

BACKGROUND: The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) is pandemic. However, the origins and global transmission pattern of SARS-CoV-2 remain largely unknown. We aimed to characterize the origination and transmission of SARS-CoV-2 based on evolutionary dynamics. METHODS: Using the full-length sequences of SARS-CoV-2 with intact geographic, demographic, and temporal information worldwide from the GISAID database during 26 December 2019 and 30 November 2020, we constructed the transmission tree to depict the evolutionary process by the R package "outbreaker". The affinity of the mutated receptor-binding region of the spike protein to angiotensin-converting enzyme 2 (ACE2) was predicted using mCSM-PPI2 software. Viral infectivity and antigenicity were tested in ACE2-transfected HEK293T cells by pseudovirus transfection and neutralizing antibody test. RESULTS: From 26 December 2019 to 8 March 2020, early stage of the COVID-19 pandemic, SARS-CoV-2 strains identified worldwide were mainly composed of three clusters: the Europe-based cluster including two USA-based sub-clusters; the Asia-based cluster including isolates in China, Japan, the USA, Singapore, Australia, Malaysia, and Italy; and the USA-based cluster. The SARS-CoV-2 strains identified in the USA formed four independent clades while those identified in China formed one clade. After 8 March 2020, the clusters of SARS-CoV-2 strains tended to be independent and became "pure" in each of the major countries. Twenty-two of 60 mutations in the receptor-binding domain of the spike protein were predicted to increase the binding affinity of SARS-CoV-2 to ACE2. Of all predicted mutants, the number of E484K was the largest one with 86 585 sequences, followed by S477N with 55 442 sequences worldwide. In more than ten countries, the frequencies of the isolates with E484K and S477N increased significantly. V367F and N354D mutations increased the infectivity of SARS-CoV-2 pseudoviruses (P < 0.001). SARS-CoV-2 with V367F was more sensitive to the S1-targeting neutralizing antibody than the wild-type counterpart (P < 0.001). CONCLUSIONS: SARS-CoV-2 strains might have originated in several countries simultaneously under certain evolutionary pressure. Travel restrictions might cause location-specific SARS-CoV-2 clustering. The SARS-CoV-2 evolution appears to facilitate its transmission via altering the affinity to ACE2 or immune evasion.

Transcriptional Start Site Coverage Analysis in Plasma Cell-Free DNA Reveals Disease Severity and Tissue Specificity of COVID-19 Patients.

Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. A deep understanding of the variation of biological characteristics in severe COVID-19 patients is crucial for the detection of individuals at high risk of critical condition for the clinical management of the disease. Herein, by profiling the gene expression spectrum deduced from DNA coverage in regions surrounding transcriptional start site in plasma cell-free DNA (cfDNA) of COVID-19 patients, we deciphered the altered biological processes in the severe cases and demonstrated the feasibility of cfDNA in measuring the COVID-19 progression. The up- and downregulated genes in the plasma of severe patient were found to be closely related to the biological processes and functions affected by COVID-19 progression. More importantly, with the analysis of transcriptome data of blood cells and lung cells from control group and cases with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, we revealed that the upregulated genes were predominantly involved in the viral and antiviral activity in blood cells, reflecting the intense viral replication and the active reaction of immune system in the severe patients. Pathway analysis of downregulated genes in plasma DNA and lung cells also demonstrated the diminished adenosine triphosphate synthesis function in lung cells, which was evidenced to correlate with the severe COVID-19 symptoms, such as a cytokine storm and acute respiratory distress. Overall, this study revealed tissue involvement, provided insights into the mechanism of COVID-19 progression, and highlighted the utility of cfDNA as a noninvasive biomarker for disease severity inspections.

Analyses of epidemiological characteristics and anti-epidemic measures of coronavirus disease 2019

Objective To analyze the epidemiological characteristics and development trend of coronavirus disease 2019 (COVID-19), and to evaluate the impact of prevention and control measures on the epidemic in China and other countries, so as to provide a basis for further prediction of the epidemic development and formulation of targeted prevention and control measures. Methods The statistics of domestic epidemic situation released by the provincial and municipal health committees and National Health Commission of the People's Republic of China from Jan. 10 to Mar. 30, 2020 were collected, as well as the daily data and papers of COVID-19 published by the epidemic countries and the World Health Organization until Apr. 16, 2020. The epidemiological characteristics (including the number of confirmed cases, fatality rate, critical rate and cure rate, etc.) were used to analyze the epidemic development and the effects of prevention and control measures in different regions of China, and they were compared with the epidemic prevention and control effects of the United States and Italy. Results The epidemic showed the characteristics of outbreak, and the cases increased rapidly. COVID-19 infection was found in 31 provincial-level regions in Chinese mainland, Hong Kong and Macao special administrative regions and Taiwan Province.

Pressure and challenge of pathogen carriers in the prevention and control of Coronavirus disease 2019

The Coronavirus disease 2019 (COVID-19) epidemic has become a pandemic. Although the current epidemic has been effectively contained in China, the prevention and control are still facing great pressure. As a potential source of infection, healthy carriers and latent carriers play important roles in the spread of the epidemic. Some issues are of great significance for the prevention and control of the current epidemic situation, including high-quality epidemiological investigations, detection of viral nucleic acids in specific populations, and small-scale screening in locations where COVID-19 cases occur more frequently, as well as strengthening the horizontal communication among the different clustered epidemic investigations. Clear understanding of the spectrum of infection, infection period, carriers in recovery period, nosocomial infection and the length of incubation period of COVID-19 can help to take targeted measures in the future prevention and control work of this epidemic.