Heterologous prime-boost immunisation with mRNA- and AdC68-based 2019-nCoV variant vaccines induces broad-spectrum immune responses in mice.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or 2019-nCoV) variants has been associated with the transmission and pathogenicity of COVID-19. Therefore, exploring the optimal immunisation strategy to improve the broad-spectrum cross-protection ability of COVID-19 vaccines is of great significance. Herein, we assessed different heterologous prime-boost strategies with chimpanzee adenovirus vector-based COVID-19 vaccines plus Wuhan-Hu-1 (WH-1) strain (AdW) and Beta variant (AdB) and mRNA-based COVID-19 vaccines plus WH-1 strain (ARW) and Omicron (B.1.1.529) variant (ARO) in 6-week-old female BALB/c mice. AdW and AdB were administered intramuscularly or intranasally, while ARW and ARO were administered intramuscularly. Intranasal or intramuscular vaccination with AdB followed by ARO booster exhibited the highest levels of cross-reactive IgG, pseudovirus-neutralising antibody (PNAb) responses, and angiotensin-converting enzyme-2 (ACE2)-binding inhibition rates against different 2019-nCoV variants among all vaccination groups. Moreover, intranasal AdB vaccination followed by ARO induced higher levels of IgA and neutralising antibody responses against live 2019-nCoV than intramuscular AdB vaccination followed by ARO. A single dose of AdB administered intranasally or intramuscularly induced broader cross-NAb responses than AdW. Th1-biased cellular immune response was induced in all vaccination groups. Intramuscular vaccination-only groups exhibited higher levels of Th1 cytokines than intranasal vaccination-only and intranasal vaccination-containing groups. However, no obvious differences were found in the levels of Th2 cytokines between the control and all vaccination groups. Our findings provide a basis for exploring vaccination strategies against different 2019-nCoV variants to achieve high broad-spectrum immune efficacy.

Transmission Characteristics and Predictive Model for Recent Epidemic Waves of COVID-19 Associated With OMICRON Variant in Major Cities in China.

Objectives: Waves of epidemics associated with Omicron variant of Coronavirus Disease 2019 (COVID-19) in major cities in China this year have been controlled. It is of great importance to study the transmission characteristics of these cases to support further interventions. Methods: We simulate the transmission trajectory and analyze the intervention influences of waves associated with Omicron variant in major cities in China using the Suspected-Exposed-Infectious-Removed (SEIR) model. In addition, we propose a model using a function between the maximum daily infections and the duration of the epidemic, calibrated with data from Chinese cities. Results: An infection period of 5 days and basic reproduction number R0 between 2 and 8.72 are most appropriate for most cases in China. Control measures show a significant impact on reducing R0, and the earlier control measures are implemented, the shorter the epidemic will last. Our proposed model performs well in predicting the duration of the epidemic with an average error of 2.49 days. Conclusion: Our results show great potential in epidemic model simulation and predicting the end date of the Omicron epidemic effectively and efficiently.

Progress of research on COVID-19 animal models

OBJECTIVE: COVID-19 continues to spread globally, which poses a significant threat to global public health security. Recently, the emergence of new variant strains of SARS-CoV-2 complicates the containment of COVID-19 due to its rapid transmission, high infectivity, high viral load, atypical symptoms and high number of severe cases. In order to further understand the transmission route, pathogenesis and pathological changes of COVID-19, and accelerate the research and development of antiviral drugs and vaccines, animal models of COVID-19 have played an important role in this process. The status of research on different animal models of COVID-19 was reviewed, the characteristics were compared among the models so as to provide theoretical basis for selecting appropriate animal models of COVID-19.

How Seasonality and Control Measures Jointly Determine the Multistage Waves of the COVID-19 Epidemic: A Modelling Study and Implications.

The current novel Coronavirus Disease 2019 (COVID-19) is a multistage epidemic consisting of multiple rounds of alternating outbreak and containment periods that cannot be modeled with a conventional single-stage Suspected-Exposed-Infectious-Removed (SEIR) model. Seasonality and control measures could be the two most important driving factors of the multistage epidemic. Our goal is to formulate and incorporate the influences of seasonality and control measures into an epidemic model and interpret how these two factors interact to shape the multistage epidemic curves. New confirmed cases will be collected daily from seven Northern Hemisphere countries and five Southern Hemisphere countries from March 2020 to March 2021 to fit and validate the modified model. Results show that COVID-19 is a seasonal epidemic and that epidemic curves can be clearly distinguished in the two hemispheres. Different levels of control measures between different countries during different seasonal periods have different influences on epidemic transmission. Seasonality alone cannot cause the baseline reproduction number R0 to fall below one and control measures must be taken. A superposition of a high level of seasonality and a low level of control measures can lead to a dramatically rapid increase in reported cases.

Combining intramuscular and intranasal homologous prime-boost with a chimpanzee adenovirus-based COVID-19 vaccine elicits potent humoral and cellular immune responses in mice.

The efficacy of many coronavirus disease 2019 (COVID-19) vaccines has been shown to decrease to varying extents against new severe acute respiratory syndrome coronavirus 2 variants, which are responsible for the continuing COVID-19 pandemic. Combining intramuscular and intranasal vaccination routes is a promising approach for achieving more potent immune responses. We evaluated the immunogenicity of prime-boost protocols with a chimpanzee adenovirus serotype 68 vector-based vaccine, ChAdTS-S, administered via both intranasal and intramuscular routes in BALB/c mice. Intramuscular priming followed by an intranasal booster elicited the highest levels of IgG, IgA, and pseudovirus neutralizing antibody titres among all the protocols tested at day 42 after prime immunization compared with the intranasal priming/intramuscular booster and prime-boost protocols using only one route. In addition, intramuscular priming followed by an intranasal booster induced high T-cell responses, measured using the IFN-γ ELISpot assay, that were similar to those observed upon intramuscular vaccination. All ChAdTS-S vaccination groups induced Th1-skewing of the T-cell response according to intracellular cytokine staining and Meso Scale Discovery cytokine profiling assays on day 56 after priming. This study provides reference data for assessing vaccination schemes of adenovirus-based COVID-19 vaccines with high immune efficacy.

How Seasonality and Control Measures Jointly Determine the Multistage Waves of the COVID-19 Epidemic: A Modelling Study and Implications

The current novel Coronavirus Disease 2019 (COVID-19) is a multistage epidemic consisting of multiple rounds of alternating outbreak and containment periods that cannot be modeled with a conventional single-stage Suspected-Exposed-Infectious-Removed (SEIR) model. Seasonality and control measures could be the two most important driving factors of the multistage epidemic. Our goal is to formulate and incorporate the influences of seasonality and control measures into an epidemic model and interpret how these two factors interact to shape the multistage epidemic curves. New confirmed cases will be collected daily from seven Northern Hemisphere countries and five Southern Hemisphere countries from March 2020 to March 2021 to fit and validate the modified model. Results show that COVID-19 is a seasonal epidemic and that epidemic curves can be clearly distinguished in the two hemispheres. Different levels of control measures between different countries during different seasonal periods have different influences on epidemic transmission. Seasonality alone cannot cause the baseline reproduction number R0 to fall below one and control measures must be taken. A superposition of a high level of seasonality and a low level of control measures can lead to a dramatically rapid increase in reported cases.

Rapid detection of viruses: Based on silver nanoparticles modified with bromine ions and acetonitrile.

Nearly 200 million people have been diagnosed with COVID-19 since the outbreak in 2019, and this disease has claimed more than 5 million lives worldwide. Currently, researchers are focusing on vaccine development and the search for an effective strategy to control the infection source. This work designed a detection platform based on Surface-Enhanced Raman Spectroscopy (SERS) by introducing acetonitrile and calcium ions into the silver nanoparticle reinforced substrate system to realize the rapid detection of novel coronavirus. Acetonitrile may amplify the calcium-induced hot spots of silver nanoparticles and significantly enhanced the stability of silver nanoparticles. It also elicited highly sensitive SERS signals of the virus. This approach allowed us to capture the characteristic SERS signals of SARS-CoV-2, Human Adenovirus 3, and H1N1 influenza virus molecules at a concentration of 100 copies/test (PFU/test) with upstanding reproduction and signal-to-noise ratio. Machine learning recognition technology was employed to qualitatively distinguish the three virus molecules with 1000 groups of spectra of each virus. Acetonitrile is a potent internal marker in regulating the signal intensity of virus molecules in saliva and serum. Thus, we used the SERS peak intensity to quantify the virus content in saliva and serum. The results demonstrated a satisfactory linear relationship between peak intensity and protein concentration. Collectively, this rapid detection method has a broad application prospect in clinical diagnosis of viruses, management of emergent viral infectious diseases, and exploration of the interaction between viruses and host cells.

A novel enhanced substrate for label-free detection of SARS-CoV-2 based on surface-enhanced Raman scattering.

Accurate and sensitive detection of SARS-CoV-2 is an effective strategy for preventing the COVID-19 pandemic in the current absence of specific drug therapy. This study presents a novel enhanced substrate for label-free detection of respiratory viruses using surface-enhanced Raman Scattering. Sodium borohydride reduces silver ions to clustered silver nanoparticles to eliminate the disorganized peak signal of the traditional citrate reducing agent. Meanwhile, the study obtained the fingerprints and concentration-dependent curves of many respiratory viruses, including SARS-CoV-2, human adenovirus type 7, and H1N1 virus, with good linear relationships. The three viruses were also identified in serum and saliva within two minutes, combined with linear discriminant diagnostic analysis. Therefore, establishing this enhanced substrate is greatly valuable for the global response to the COVID-19 pandemic.

Spatial statistics and influencing factors of the COVID-19 epidemic at both prefecture and county levels in Hubei Province, China

The coronavirus disease 2019 (COVID-19) epidemic has had a crucial influence on people's lives and socio-economic development. An understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic on multiple scales could benefit the control of the outbreak. Therefore, we used spatial autocorrelation and Spearman's rank correlation methods to investigate these two topics, respectively. The COVID-19 epidemic data reported publicly and relevant open data in Hubei province were analyzed. The results showed that (1) at both prefecture and county levels, the global spatial autocorrelation was extremely significant for the cumulative confirmed COVID-19 cases (CCC) in Hubei province from 30 January to 18 February 2020. Further, (2) at both levels, the significant hotspots and cluster/outlier areas were observed solely in Wuhan city and most of its districts/sub-cities from 30 January to 18 February 2020. (3) At the prefecture level in Hubei province, the number of CCC had a positive and extremely significant correlation (p < 0.01) with the registered population (RGP), resident population (RSP), Baidu migration index (BMI), regional gross domestic production (GDP), and total retail sales of consumer goods (TRS), respectively, from 29 January to 18 February 2020 and had a negative and significant correlation (p < 0.05) with minimum elevation (MINE) from 2 February to 18 February 2020, but no association with the land area (LA), population density (PD), maximum elevation (MAXE), mean elevation (MNE), and range of elevation (RAE) from 23 January to 18 February 2020. (4) At the county level, the number of CCC in Hubei province had a positive and extremely significant correlation (p < 0.01) with PD, RGP, RSP, GDP, and TRS, respectively, from 27 January to 18 February 2020, and was negatively associated with MINE, MAXE, MNE, and RAE, respectively, from 26 January to 18 February 2020, and negatively associated with LA from 30 January to 18 February 2020. It suggested that (1) the COVID-19 epidemics at both levels in Hubei province had evident characteristics of significant global spatial autocorrelations and significant centralized high-risk outbreaks. (2) The COVID-19 epidemics were significantly associated with the natural factors, such as LA, MAXE, MNE, and RAE, -only at the county level, not at the prefecture level, from 2 February to 18 February 2020. (3) The COVID-19 epidemics were significantly related to the socioeconomic factors, such as RGP, RSP, TRS, and GDP, at both levels from 26 January to 18 February 2020. It is desired that this study enrich our understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic and benefit classified prevention and control of the COVID-19 epidemic for policymakers.