Project description:This article is a narrative review of the rapidly moving coronavirus disease 2019 vaccine field with an emphasis on clinical efficacy established in both randomized trials and postmarketing surveillance of clinically available vaccines. We review the major clinical trials that supported authorization for general use of the Janssen (Ad.26.CoV2), Pfizer-BioNTech (BNT162b2), and Moderna (mRNA-1273) vaccines and the publicly available postmarketing information with the goal of providing a broad, clinically relevant comparison of efficacy and safety. This review is primarily focused on the US market.
Project description:COVID-19 is a pandemic of unprecedented proportions in recent human history. Less than 18 months since the onset of the pandemic, there are close to two hundred million confirmed cases and four million deaths worldwide. There have also been massive efforts geared towards finding safe and effective vaccines. By July 2021 there were 184 COVID-19 vaccine candidates in pre-clinical development, 105 in clinical development, and 18 vaccines approved for emergency use by at least one regulatory authority. These vaccines include whole virus live attenuated or inactivated, protein-based, viral vector, and nucleic acid vaccines. By mid-2021 three billion doses of COVID-19 vaccine have been administered around the world, mostly in high-income countries. COVID-19 vaccination provides hope for an end to the pandemic, if and only if there would be equal access and optimal uptake in all countries around the world.
Project description:Given the interest in the COVID mRNA vaccines, we sought to investigate how the RNA modification N1-methylpseudouridine (and its related modification, pseudouridine) is read by ribosomes and reverse transcriptases. By looking at reverse transcriptase data, we can gain information on how the modification affects duplex stability, which may have important consequences for the tRNA-mRNA interactions found in the ribosome.
Project description:The outbreak of coronavirus disease 2019 (COVID-19) has aroused a global alert. To release social panic and guide future schedules, this article proposes a novel mathematical model, the Delay Differential Epidemic Analyzer (D2EA), to analyze the dynamics of epidemic and forecast its future trends. Based on the traditional Susceptible-Exposed-Infectious-Recovered (SEIR) model, the D2EA model innovatively introduces a set of quarantine states and applies both ordinary differential equations and delay differential equations to describe the transition between two states. Potential variations of practical factors are further considered to reveal the true epidemic picture. In the experiment part, we use the D2EA model to simulate the epidemic in Hubei Province. Fitting to the collected real data as non-linear optimization, the D2EA model forecasts that the accumulated confirmed infected cases in Hubei Province will reach the peak at the end of February and then steady down. We also evaluate the effectiveness of the quarantine measures and schedule the date to reopen Hubei Province.
Project description:The COVID-19 pandemic represents a milestone in vaccine research and development in a global context. A worldwide effort, as never seen before, involved scientists from all over the world in favor of the fast, accurate and precise construction and testing of immunogens against the new coronavirus, SARS-CoV-2. Among all the vaccine strategies put into play for study and validation, those based on recombinant viral vectors gained special attention due to their effectiveness, ease of production and the amplitude of the triggered immune responses. Some of these new vaccines have already been approved for emergency/full use, while others are still in pre- and clinical trials. In this article we will highlight what is behind adeno-associated vectors, such as those presented by the immunogens ChaAdOx1, Sputnik, Convidecia (CanSino, Tianjin, China), and Janssen (Johnson & Johnson, New Jersey, EUA), in addition to other promising platforms such as Vaccinia virus MVA, influenza virus, and measles virus, among others.
Project description:COVID-19 (coronavirus disease 2019) vaccines have become available; now, everyone has the opportunity to get vaccinated. We used Google Trends (GT) data to assess the global public interest in COVID-19 vaccines during the pandemic. For the analysis, a period of 17 months was chosen (from Jan 19, 2020, to Jul 04, 2021). Interest in user queries was tracked by keywords (corona vaccine, COVID-19 vaccine development, Sputnik v, Pfizer vaccine, AstraZeneca vaccine, etc.). The geographic analysis of queries was also carried out. The interest of users in the vaccine is significantly increasing. It is focused on the side effects of vaccines, and users pay attention to vaccines' developers from different countries. The correlation between the scientific publications devoted to vaccine development and such requests of users on the internet is absent. This study shows that internet search patterns can be used to gauge public attitudes towards coronavirus vaccination. Safety concerns consistently high follow an interest in vaccine side effects. This data can be used to track and predict attitudes towards vaccination of populations from COVID-19 in different countries before global vaccination becomes available to help mitigate the adverse effects of the pandemic.
Project description:The COVID-19 vaccine is being rolled out globally. High and ongoing public uptake of the vaccine relies on health and social care professionals having the knowledge and confidence to actively and effectively advocate it. An internationally relevant, interactive multimedia training resource called COVID-19 Vaccine Education (CoVE) was developed using ASPIRE methodology. This rigorous six-step process included: (1) establishing the aims, (2) storyboarding and co-design, (3) populating and producing, (4) implementation, (5) release, and (6) mixed-methods evaluation aligned with the New World Kirkpatrick Model. Two synchronous consultations with members of the target audience identified the support need and established the key aim (Step 1: 2 groups: n = 48). Asynchronous storyboarding was used to co-construct the content, ordering, presentation, and interactive elements (Step 2: n = 14). Iterative two-stage peer review was undertaken of content and technical presentation (Step 3: n = 23). The final resource was released in June 2021 (Step 4: >3653 views). Evaluation with health and social care professionals from 26 countries (survey, n = 162; qualitative interviews, n = 15) established that CoVE has high satisfaction, usability, and relevance to the target audience. Engagement with CoVE increased participants' knowledge and confidence relating to vaccine promotion and facilitated vaccine-promoting behaviours and vaccine uptake. The CoVE digital training package is open access and provides a valuable mechanism for supporting health and care professionals in promoting COVID-19 vaccination uptake.