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      Rapid, robust, and sustainable antibody responses to mRNA COVID-19 vaccine in convalescent COVID-19 individuals

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          Abstract

          Longitudinal studies are needed to evaluate the SARS-CoV-2 mRNA vaccine antibody response under real-world conditions. This longitudinal study investigated the quantity and quality of SARS-CoV-2 antibody response in 846 specimens from 350 patients, comparing BNT162b2-vaccinated individuals (19 previously diagnosed with COVID-19, termed RecoVax; and 49 never diagnosed, termed NaiveVax) with 122 hospitalized unvaccinated (HospNoVax) and 160 outpatient unvaccinated (OutPtNoVax) COVID-19 patients. NaiveVax experienced delay in generating SARS-CoV-2 total antibodies (TAb) and surrogate neutralizing antibodies (SNAb) after the first vaccine dose (D1) but rapid increase in antibody levels after the second dose (D2). However, these never reached RecoVax’s robust levels. In fact, NaiveVax TAb and SNAb levels decreased 4 weeks after D2. For the most part, RecoVax TAb persisted, after reaching maximal levels 2 weeks after D2, but SNAb decreased significantly about 6 months after D1. Although NaiveVax avidity lagged behind that of RecoVax for most of the follow-up periods, NaiveVax did reach similar avidity by about 6 months after D1. These data suggest that 1 vaccine dose elicits maximal antibody response in RecoVax and may be sufficient. Also, despite decreasing levels in TAb and SNAb over time, long-term avidity may be a measure worth evaluating and possibly correlating to vaccine efficacy.

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          Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine

          Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (Covid-19) have afflicted tens of millions of people in a worldwide pandemic. Safe and effective vaccines are needed urgently. Methods In an ongoing multinational, placebo-controlled, observer-blinded, pivotal efficacy trial, we randomly assigned persons 16 years of age or older in a 1:1 ratio to receive two doses, 21 days apart, of either placebo or the BNT162b2 vaccine candidate (30 μg per dose). BNT162b2 is a lipid nanoparticle–formulated, nucleoside-modified RNA vaccine that encodes a prefusion stabilized, membrane-anchored SARS-CoV-2 full-length spike protein. The primary end points were efficacy of the vaccine against laboratory-confirmed Covid-19 and safety. Results A total of 43,548 participants underwent randomization, of whom 43,448 received injections: 21,720 with BNT162b2 and 21,728 with placebo. There were 8 cases of Covid-19 with onset at least 7 days after the second dose among participants assigned to receive BNT162b2 and 162 cases among those assigned to placebo; BNT162b2 was 95% effective in preventing Covid-19 (95% credible interval, 90.3 to 97.6). Similar vaccine efficacy (generally 90 to 100%) was observed across subgroups defined by age, sex, race, ethnicity, baseline body-mass index, and the presence of coexisting conditions. Among 10 cases of severe Covid-19 with onset after the first dose, 9 occurred in placebo recipients and 1 in a BNT162b2 recipient. The safety profile of BNT162b2 was characterized by short-term, mild-to-moderate pain at the injection site, fatigue, and headache. The incidence of serious adverse events was low and was similar in the vaccine and placebo groups. Conclusions A two-dose regimen of BNT162b2 conferred 95% protection against Covid-19 in persons 16 years of age or older. Safety over a median of 2 months was similar to that of other viral vaccines. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728.)
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            Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine

            Abstract Background Vaccines are needed to prevent coronavirus disease 2019 (Covid-19) and to protect persons who are at high risk for complications. The mRNA-1273 vaccine is a lipid nanoparticle–encapsulated mRNA-based vaccine that encodes the prefusion stabilized full-length spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes Covid-19. Methods This phase 3 randomized, observer-blinded, placebo-controlled trial was conducted at 99 centers across the United States. Persons at high risk for SARS-CoV-2 infection or its complications were randomly assigned in a 1:1 ratio to receive two intramuscular injections of mRNA-1273 (100 μg) or placebo 28 days apart. The primary end point was prevention of Covid-19 illness with onset at least 14 days after the second injection in participants who had not previously been infected with SARS-CoV-2. Results The trial enrolled 30,420 volunteers who were randomly assigned in a 1:1 ratio to receive either vaccine or placebo (15,210 participants in each group). More than 96% of participants received both injections, and 2.2% had evidence (serologic, virologic, or both) of SARS-CoV-2 infection at baseline. Symptomatic Covid-19 illness was confirmed in 185 participants in the placebo group (56.5 per 1000 person-years; 95% confidence interval [CI], 48.7 to 65.3) and in 11 participants in the mRNA-1273 group (3.3 per 1000 person-years; 95% CI, 1.7 to 6.0); vaccine efficacy was 94.1% (95% CI, 89.3 to 96.8%; P<0.001). Efficacy was similar across key secondary analyses, including assessment 14 days after the first dose, analyses that included participants who had evidence of SARS-CoV-2 infection at baseline, and analyses in participants 65 years of age or older. Severe Covid-19 occurred in 30 participants, with one fatality; all 30 were in the placebo group. Moderate, transient reactogenicity after vaccination occurred more frequently in the mRNA-1273 group. Serious adverse events were rare, and the incidence was similar in the two groups. Conclusions The mRNA-1273 vaccine showed 94.1% efficacy at preventing Covid-19 illness, including severe disease. Aside from transient local and systemic reactions, no safety concerns were identified. (Funded by the Biomedical Advanced Research and Development Authority and the National Institute of Allergy and Infectious Diseases; COVE ClinicalTrials.gov number, NCT04470427.)
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              An interactive web-based dashboard to track COVID-19 in real time

              In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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                Author and article information

                Contributors
                Journal
                JCI Insight
                JCI Insight
                JCI Insight
                JCI Insight
                American Society for Clinical Investigation
                2379-3708
                22 October 2021
                22 October 2021
                22 October 2021
                : 6
                : 20
                : e151477
                Affiliations
                [1 ]Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York, USA.
                [2 ]NewYork-Presbyterian Hospital, Weill Cornell Medical Campus, New York, New York, USA.
                [3 ]Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA.
                [4 ]School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
                [5 ]Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
                [6 ]Departments of Laboratory Medicine and Pathology at Hennepin Healthcare/Hennepin County Medical Center and University of Minnesota, Minneapolis, Minnesota, USA.
                [7 ]Department of Biomedical Engineering, Shenzhen Research Institute, Beijing University of Chinese Medicine, Shenzhen, China.
                [8 ]Department of Radiation Oncology and
                [9 ]Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
                Author notes
                Address correspondence to: Sabrina E. Racine-Brzostek, 525 East 68th Street, F-705, New York, New York 10065, USA. Phone: 212.746.0514; Email: srb9029@ 123456med.cornell.edu . Or to Zhen Zhao, 525 East 68th Street, F-701, New York, New York 10065, USA. Phone: 212.746.2682; Email: zhz9010@ 123456med.cornell.edu .

                Authorship note: SERB and JKY contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-6296-6682
                http://orcid.org/0000-0003-1595-6585
                http://orcid.org/0000-0002-5126-8782
                http://orcid.org/0000-0001-5827-992X
                http://orcid.org/0000-0003-2997-4573
                http://orcid.org/0000-0002-8227-8924
                http://orcid.org/0000-0001-8042-1494
                Article
                151477
                10.1172/jci.insight.151477
                8564891
                34499052
                958a6f9a-ff74-407b-b112-5926739d7001
                © 2021 Racine-Brzostek et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 May 2021
                : 8 September 2021
                Funding
                Funded by: Weill Cornell Medicine
                Award ID: not provided
                Funded by: Weill Cornell
                Award ID: NYP-WELCOME study
                Funded by: ET Healthcare
                Award ID: ET HeathCare seed funding
                Funded by: Roche Diagnostics
                Award ID: Investigator initiated research funding
                This research was partially funded by a COVID-19 research grant from Weill Cornell Medicine.
                Weill Cornell MEdicine Competitive Research Funding
                Seed instruments and reagents were provided
                Roche Diagnostics provided support via Investigator initiated research funding
                Categories
                Research Article

                covid-19,immunology,adaptive immunity
                covid-19, immunology, adaptive immunity

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