ABSTRACT
Vaccines that elicit mucosal immune responses against SARS-CoV-2 could potent ially be of exceptional importance in providing first line defence at the site of viral entry. In order to understand the mucosal immune response profiles of SARS-CoV-2 vaccines, we examined both the mucosal and systemic responses of subjects vaccinated by two different vaccination platforms: mRNA (Comirnaty) and inactivated virus (CoronaVac). Nasal epithelial lining fluid (NELF) and peripheral blood samples were collected in subjects who had received two doses of CoronaVac or Comirnaty. We quantified IgA and IgG specific to SARS-CoV-2 S1 protein, neutralisation antibody by ELISA in NELF and plasma samples. Only Comirnaty induced nasal S1-specific IgA and IgG responses, which were evident as early as on 14±2 days after the first dose. The NELF samples of 72% of subjects became IgA+IgG+, while in 62.5% of subjects the samples were neutralising by 7±2 days after the second dose. In 45% of the subjects their NELF remained neutralising 50 days after the booster. In plasma, 91% and 100% Comirnaty subjects possessed S1-specific IgA+IgG+ on 14±2 days after the first dose and 7±2 days after booster, respectively. The plasma collected on 7±2 days after booster was 100% neutralising. The induction of S1-specific antibody by CoronaVac was IgG dominant, and 70% of the subjects possessed specific IgG by 7±2 days after booster and were all neutralising. This study reveals that Comirnaty is able to induce S1-specific IgA and IgG r esponse with neutralising activity in the nasal mucosa in addition to a consistent systemic response.
ABSTRACT
As COVID-19 is posing a serious threat to global health, the emerging mutation in SARS-CoV-2 genomes, for example, N501Y substitution, is one of the major challenges against control of the pandemic. Characterizing the relationship between mutation activities and the risk of severe clinical outcomes is of public health importance for informing the healthcare decision-making process. Using a likelihood-based approach, we developed a statistical framework to reconstruct a time-varying and variant-specific case fatality ratio (CFR), and to estimate changes in CFR associated with a single mutation empirically. For illustration, the statistical framework is implemented to the COVID-19 surveillance data in the United Kingdom (UK). The reconstructed instantaneous CFR gradually increased from 1.0% in September to 2.2% in November 2020 and stabilized at this level thereafter, which monitors the mortality risk of COVID-19 on a real-time basis. We identified a link between the SARS-CoV-2 mutation activity at molecular scale and COVID-19 mortality risk at population scale, and found that the 501Y variants may slightly but not significantly increase 18% of fatality risk than the preceding 501N variants. We found no statistically significant evidence of change in COVID-19 mortality risk associated with 501Y variants, and highlighted the real-time estimating potentials of the modelling framework.