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      SARS-CoV-2 antibody dynamics and transmission from community-wide serological testing in the Italian municipality of Vo’

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      Nature Communications
      Nature Publishing Group UK
      Computational models, Viral infection, SARS-CoV-2, Epidemiology

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          Abstract

          In February and March 2020, two mass swab testing campaigns were conducted in Vo’, Italy. In May 2020, we tested 86% of the Vo’ population with three immuno-assays detecting antibodies against the spike and nucleocapsid antigens, a neutralisation assay and Polymerase Chain Reaction (PCR). Subjects testing positive to PCR in February/March or a serological assay in May were tested again in November. Here we report on the results of the analysis of the May and November surveys. We estimate a seroprevalence of 3.5% (95% Credible Interval (CrI): 2.8–4.3%) in May. In November, 98.8% (95% Confidence Interval (CI): 93.7–100.0%) of sera which tested positive in May still reacted against at least one antigen; 18.6% (95% CI: 11.0–28.5%) showed an increase of antibody or neutralisation reactivity from May. Analysis of the serostatus of the members of 1,118 households indicates a 26.0% (95% CrI: 17.2–36.9%) Susceptible-Infectious Transmission Probability. Contact tracing had limited impact on epidemic suppression.

          Abstract

          Vo’, Italy, is a unique setting for studying SARS-CoV-2 antibody dynamics because mass testing was conducted there early in the pandemic. Here, the authors perform two follow-up serological surveys and estimate seroprevalence, the extent of within-household transmission, and the impact of contact tracing.

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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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            Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR

            Background The ongoing outbreak of the recently emerged novel coronavirus (2019-nCoV) poses a challenge for public health laboratories as virus isolates are unavailable while there is growing evidence that the outbreak is more widespread than initially thought, and international spread through travellers does already occur. Aim We aimed to develop and deploy robust diagnostic methodology for use in public health laboratory settings without having virus material available. Methods Here we present a validated diagnostic workflow for 2019-nCoV, its design relying on close genetic relatedness of 2019-nCoV with SARS coronavirus, making use of synthetic nucleic acid technology. Results The workflow reliably detects 2019-nCoV, and further discriminates 2019-nCoV from SARS-CoV. Through coordination between academic and public laboratories, we confirmed assay exclusivity based on 297 original clinical specimens containing a full spectrum of human respiratory viruses. Control material is made available through European Virus Archive – Global (EVAg), a European Union infrastructure project. Conclusion The present study demonstrates the enormous response capacity achieved through coordination of academic and public laboratories in national and European research networks.
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              Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

              Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; p interaction =0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. Funding UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D’Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca.
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                Author and article information

                Contributors
                i.dorigatti@imperial.ac.uk
                enrico.lavezzo@unipd.it
                a.drcrisanti@imperial.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 July 2021
                19 July 2021
                2021
                : 12
                : 4383
                Affiliations
                [1 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, , Imperial College London, ; London, UK
                [2 ]GRID grid.5608.b, ISNI 0000 0004 1757 3470, Department of Molecular Medicine, , University of Padova, ; Padova, Italy
                [3 ]GRID grid.411474.3, ISNI 0000 0004 1760 2630, Azienda Ospedale Padova, ; Padova, Italy
                [4 ]GRID grid.5608.b, ISNI 0000 0004 1757 3470, Department of Surgery, Oncology and Gastroenterology, , University of Padova, ; Padova, Italy
                [5 ]GRID grid.5608.b, ISNI 0000 0004 1757 3470, Department of Medicine, , University of Padova, ; Padova, Italy
                [6 ]GRID grid.5608.b, ISNI 0000 0004 1757 3470, Department of Statistical Sciences, , University of Padova, ; Padova, Italy
                [7 ]GRID grid.5608.b, ISNI 0000 0004 1757 3470, CRIBI Biotech Centre, , University of Padova, ; Padova, Italy
                [8 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Statistics, , University of Oxford, ; Oxford, UK
                [9 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Department of Life Science Imperial College London, Exhibition Road, ; London, UK
                Author information
                http://orcid.org/0000-0001-9959-0706
                http://orcid.org/0000-0002-3902-8356
                http://orcid.org/0000-0002-3053-4391
                http://orcid.org/0000-0001-6705-1716
                http://orcid.org/0000-0002-2798-552X
                http://orcid.org/0000-0002-5925-4035
                http://orcid.org/0000-0002-0233-9134
                http://orcid.org/0000-0001-8482-1436
                http://orcid.org/0000-0003-4073-4861
                http://orcid.org/0000-0002-9120-4003
                http://orcid.org/0000-0002-1154-8093
                http://orcid.org/0000-0002-0195-2463
                Article
                24622
                10.1038/s41467-021-24622-7
                8289856
                34282139
                c6ad749b-90fb-4df1-b449-702a36ba9183
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 March 2021
                : 21 June 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100009187, RCUK | MRC | Medical Research Foundation;
                Award ID: MR/R015600/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100004440, Wellcome Trust (Wellcome);
                Award ID: 213494/Z/18/Z
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010661, EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020);
                Award ID: 874735
                Award ID: 874735
                Award Recipient :
                Categories
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                Custom metadata
                © The Author(s) 2021

                Uncategorized
                computational models,viral infection,sars-cov-2,epidemiology
                Uncategorized
                computational models, viral infection, sars-cov-2, epidemiology

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