COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion.

Background: The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods: We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (C r ). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (R t ). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results: (1) The overall level of R t in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, R t decreased rapidly, and the overall R t level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion: Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion

Background The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown. Methods We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (Cr). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (Rt). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses. Results (1) The overall level of Rt in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, Rt decreased rapidly, and the overall Rt level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage. Conclusion Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

Success of nano-vaccines against COVID-19: a transformation in nanomedicine.

INTRODUCTION: The vaccines being used against COVID-19 are composed of either non-viral or viral nanoparticles (NPs). Nanotechnology-based vaccine technology was studied for its potentially transformative advancement of medicine. AREAS COVERED: NPs protect the encapsulated mRNA in vaccines, thereby enhancing the stability of the ribonucleic acids and facilitating their intact delivery to their specific targets. Compared to liposomes, lipid nanoparticles (LNPs) are unique and, through their rigid morphology and better cellular penetrability, render enhanced cargo stability. To explore nanotechnology-mediated vaccine delivery and its potential in future pandemics, we assessed articles from various databases, such as PubMed, Embase, and Scopus, including editorial/research notes, expert opinions, and collections of data from several clinical research trials. In the current review, we focus on the nanoparticulate approach of the different SARS-CoV-2 vaccines and explore their success against the pandemic. EXPERT OPINION: The mRNA-based vaccines, with their tremendous efficacy of ~95% (under phase III-IV clinical trials) and distinct nanocarriers (LNPs), represent a new medical front alongside DNA and siRNA-based vaccines.

Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission.

With the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission. Hence, we collect Internet multisource big data (including retrieval, migration, and media data) and propose comprehensive and relative application strategies to eliminate the impact of national and media data. We use statistical classification and regression to construct an early warning model for occurrence and development. Under the guidance of the improved coronavirus herd immunity optimizer (ICHIO), we construct a "sampling-feature-hyperparameter-weight" synchronous optimization strategy. In occurrence warning, we propose an undersampling synchronous evolutionary ensemble (USEE); in development warning, we propose a bootstrap-sampling synchronous evolutionary ensemble (BSEE). Regarding the internal training data (Heilongjiang Province), the ROC-AUC of USEE3 incorporating multisource data is 0.9553, the PR-AUC is 0.8327, and the R2 of BSEE2 fused by the "nonlinear + linear" method is 0.8698. Regarding the external validation data (Shaanxi Province), the ROC-AUC and PR-AUC values of USEE3 were 0.9680 and 0.9548, respectively, and the R2 of BSEE2 was 0.8255. Our method has good accuracy and generalization and can be flexibly used in the prediction of cryptic transmission in various regions. We propose strategy research that integrates multiple early warning tasks based on multisource Internet big data and combines multiple ensemble models. It is an extension of the research in the field of traditional infectious disease monitoring and has important practical significance and innovative theoretical value.

Theranostic efficiency of biosurfactants against COVID-19 and similar viruses - A review.

The world has witnessed an extreme vulnerability of a pandemic during 2020; originated from China. The coronavirus disease 2019 (COVID-19) is infecting and beginning deaths in thousands to millions, creating of the global economic crisis. Biosurfactants (BSs) can carry the prevention, control and management of pandemic out through diverse approaches, such as pharmaceutical, therapeutic, hygienic and environmental. The microbiotas having virulent intrinsic properties towards starting as easily as spreading of diseases (huge morbidity and mortality) could be inhibited via BSs. Such elements could be recognised for their antimicrobial activity, capability to interact with the immune system via micelles formation and in nanoparticulate synthesis. However, they can be used for developing novel and more effective therapeutics, pharmaceuticals, non-toxic formulations, vaccines, and effective cleaning agents. Such approaches can be utilized for product development and implemented for managing and combating the pandemic conditions. This review emphasized on the potentiality of BSs as key components with several ways for protecting against unknown and known pathogens, including COVID-19.

The Spatiotemporal Characteristics and Climatic Factors of COVID-19 in Wuhan, China

COVID-19 is threatening the whole world. This paper aims to explore the correlation between climatic factors and the morbidity of COVID-19 in Wuhan, China, mainly by using a geographic detector and GWR model. It was found that the response of the morbidity of COVID-19 to meteorological factors in Wuhan is different at different stages. On the whole, the morbidity of COVID-19 has a strong spatial aggregation, mainly concentrated in the central area of Wuhan City. There is a positive correlation between wind speed and the spread of COVID-19, while temperature has a negative correlation. There is a positive correlation between air pressure and the number of COVID-19 cases. Rainfall is not significantly correlated with the spread of COVID-19. It is concluded that wind speed, relative humidity, temperature, and air pressure are important meteorological factors affecting the spread of COVID-19 in Wuhan. Any two variables have greater interaction with the spatial distribution of the incidence rate of COVID-19 than any one factor alone. Those findings not only provide a new insight for the key intervention measures and the optimal allocation of health care resources accordingly but also lay a theoretical foundation for disease prevention, disease intervention and health services.

Diagnosis, prevention, and treatment of coronavirus disease: a review.

INTRODUCTION: Coronavirus disease (COVID-19) was first reported in Wuhan, China, in late December 2019 and subsequently, declared a pandemic. As of 3 June 2021, 172,493,290 individuals have acquired COVID-19 and 3,708,334 patients have died worldwide, according to the World Health Organization. AREAS COVERED: This review explores epidemiology; virology; pathogenesis; genomic variations; mode of transmission; clinical occurrence; diagnosis; and treatment with antiviral agents, antibiotics, and supportive therapies. It covers a nanotechnology-based treatment approach and emphasizes the importance of herbal and marine antiviral drugs. The review attempts to explain current advances in research, prevention, and control of COVID-19 spread through artificial intelligence and vaccine development status under cosmopolitan consideration. EXPERT OPINION: While COVID-19 research is advancing at full capacity, the discovery of drugs or vaccines that can fight the pandemic is necessary. Human survival in such a critical situation will be possible only with the development of strong immunity by opting for exercise, yoga, and consumption of hygienic food and beverages. Therefore, education about COVID-19 lethality and its impact on livelihood is important. The pandemic has also shown positive effects on the environment, such as a significant reduction in environmental pollution and global warming and improvement in river water quality.

Neutralizing IFNL3 Autoantibodies in Severe COVID-19 Identified Using Molecular Indexing of Proteins by Self-Assembly (preprint)

Unbiased antibody profiling can identify the targets of an immune reaction. A number of likely pathogenic autoreactive antibodies have been associated with life-threatening SARS-CoV-2 infection; yet, many additional autoantibodies likely remain unknown. Here we present Molecular Indexing of Proteins by Self Assembly (MIPSA), a technique that produces ORFeome-scale libraries of proteins covalently coupled to uniquely identifying DNA barcodes for analysis by sequencing. We used MIPSA to profile circulating autoantibodies from 55 patients with severe COVID-19 against 11,076 DNA-barcoded proteins of the human ORFeome library. MIPSA identified previously known autoreactivities, and also detected undescribed neutralizing interferon lambda 3 (IFNL3) autoantibodies. At-risk individuals with anti-IFNL3 antibodies may benefit from interferon supplementation therapies, such as those currently undergoing clinical evaluation.

Repositioning microbial biotechnology against COVID-19: the case of microbial production of flavonoids.

Coronavirus-related disease 2019 (COVID-19) became a pandemic in February 2020, and worldwide researchers try to tackle the disease with approved drugs of all kinds, or to develop novel compounds inhibiting viral spreading. Flavonoids, already investigated as antivirals in general, also might bear activities specific for the viral agent causing COVID-19, SARS-CoV-2. Microbial biotechnology and especially synthetic biology may help to produce flavonoids, which are exclusive plant secondary metabolites, at a larger scale or indeed to find novel pharmaceutically active flavonoids. Here, we review the state of the art in (i) antiviral activity of flavonoids specific for coronaviruses and (ii) results derived from computational studies, mostly docking studies mainly inhibiting specific coronaviral proteins such as the 3CL (main) protease, the spike protein or the RNA-dependent RNA polymerase. In the end, we strive towards a synthetic biology pipeline making the fast and tailored production of valuable antiviral flavonoids possible by applying the last concepts of division of labour through co-cultivation/microbial community approaches to the DBTL (Design, Build, Test, Learn) principle.