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Franz C, Holzscheiter A, Kickbusch I. Germany's role in global health at a critical juncture. Lancet 2024; 404:82-94. [PMID: 38971595 DOI: 10.1016/s0140-6736(24)00936-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 03/31/2024] [Accepted: 05/03/2024] [Indexed: 07/08/2024]
Abstract
In 2017, we set out-along with a larger group of authors-to assess Germany's contribution and potential leadership role in global health. We considered the ambitions and manifold efforts of Chancellor Angela Merkel's administration to become a trusted leader in global health governance and a reliable supporter of multilateral institutions, especially WHO. Based on the recommendations of our 2017 paper, in this Review we determine whether the country has indeed lived up to its vision and ambitions expressed in the Global Health Strategy adopted by the cabinet in 2020. Also, we outline what challenges Germany is now facing in a more complex global health environment and geopolitical situation, where leadership in the field is being redefined following the impact of the COVID-19 pandemic and amid broader shifts in the international order.
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Affiliation(s)
- Christian Franz
- CPC Analytics, Berlin, Germany; School of Public Health, Bielefeld University, Bielefeld, Germany
| | | | - Ilona Kickbusch
- Graduate Institute of International and Development Studies, Geneva, Switzerland
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2
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Katz R, Toole K, Robertson H, Case A, Kerr J, Robinson-Marshall S, Schermerhorn J, Orsborn S, Van Maele M, Zimmerman R, Stevens T, Phelan A, Carlson C, Graeden E. Open data for COVID-19 policy analysis and mapping. Sci Data 2023; 10:491. [PMID: 37500627 PMCID: PMC10374886 DOI: 10.1038/s41597-023-02398-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 07/18/2023] [Indexed: 07/29/2023] Open
Abstract
As the COVID-19 pandemic unfolded in the spring of 2020, governments around the world began to implement policies to mitigate and manage the outbreak. Significant research efforts were deployed to track and analyse these policies in real-time to better inform the response. While much of the policy analysis focused narrowly on social distancing measures designed to slow the spread of disease, here, we present a dataset focused on capturing the breadth of policy types implemented by jurisdictions globally across the whole-of-government. COVID Analysis and Mapping of Policies (COVID AMP) includes nearly 50,000 policy measures from 150 countries, 124 intermediate areas, and 235 local areas between January 2020 and June 2022. With up to 40 structured and unstructured characteristics encoded per policy, as well as the original source and policy text, this dataset provides a uniquely broad capture of the governance strategies for pandemic response, serving as a critical data source for future work in legal epidemiology and political science.
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Affiliation(s)
- Rebecca Katz
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | - Kate Toole
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | - Hailey Robertson
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | | | | | | | - Jordan Schermerhorn
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | | | | | - Ryan Zimmerman
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | - Tess Stevens
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | - Alexandra Phelan
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | - Colin Carlson
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA
| | - Ellie Graeden
- Center for Global Health Science and Security, Georgetown University, Washington, DC, USA.
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3
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Tegally H, Wilkinson E, Tsui JLH, Moir M, Martin D, Brito AF, Giovanetti M, Khan K, Huber C, Bogoch II, San JE, Poongavanan J, Xavier JS, Candido DDS, Romero F, Baxter C, Pybus OG, Lessells RJ, Faria NR, Kraemer MUG, de Oliveira T. Dispersal patterns and influence of air travel during the global expansion of SARS-CoV-2 variants of concern. Cell 2023; 186:3277-3290.e16. [PMID: 37413988 PMCID: PMC10247138 DOI: 10.1016/j.cell.2023.06.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 07/08/2023]
Abstract
The Alpha, Beta, and Gamma SARS-CoV-2 variants of concern (VOCs) co-circulated globally during 2020 and 2021, fueling waves of infections. They were displaced by Delta during a third wave worldwide in 2021, which, in turn, was displaced by Omicron in late 2021. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of VOCs worldwide. We find that source-sink dynamics varied substantially by VOC and identify countries that acted as global and regional hubs of dissemination. We demonstrate the declining role of presumed origin countries of VOCs in their global dispersal, estimating that India contributed <15% of Delta exports and South Africa <1%-2% of Omicron dispersal. We estimate that >80 countries had received introductions of Omicron within 100 days of its emergence, associated with accelerated passenger air travel and higher transmissibility. Our study highlights the rapid dispersal of highly transmissible variants, with implications for genomic surveillance along the hierarchical airline network.
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Affiliation(s)
- Houriiyah Tegally
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa; KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa.
| | - Eduan Wilkinson
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | | | - Monika Moir
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Darren Martin
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa; Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Marta Giovanetti
- Laboratorio de Flavivirus, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil; Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Department of Science and Technology for Humans and the Environment, University of Campus Bio-Medico di Roma, Rome, Italy
| | - Kamran Khan
- BlueDot, Toronto, ON, Canada; Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, ON, Canada
| | | | - Isaac I Bogoch
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, ON, Canada
| | - James Emmanuel San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Jenicca Poongavanan
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Joicymara S Xavier
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa; Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Unaí, Brazil
| | - Darlan da S Candido
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Filipe Romero
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Cheryl Baxter
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK; Pandemic Sciences Institute, University of Oxford, Oxford, UK; Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
| | - Richard J Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Nuno R Faria
- Department of Biology, University of Oxford, Oxford, UK; MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK; Departamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Moritz U G Kraemer
- Department of Biology, University of Oxford, Oxford, UK; Pandemic Sciences Institute, University of Oxford, Oxford, UK.
| | - Tulio de Oliveira
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa; KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa; Department of Global Health, University of Washington, Seattle, WA, USA.
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Hill V, Githinji G, Vogels CBF, Bento AI, Chaguza C, Carrington CVF, Grubaugh ND. Toward a global virus genomic surveillance network. Cell Host Microbe 2023; 31:861-873. [PMID: 36921604 PMCID: PMC9986120 DOI: 10.1016/j.chom.2023.03.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
The COVID-19 pandemic galvanized the field of virus genomic surveillance, demonstrating its utility for public health. Now, we must harness the momentum that led to increased infrastructure, training, and political will to build a sustainable global genomic surveillance network for other epidemic and endemic viruses. We suggest a generalizable modular sequencing framework wherein users can easily switch between virus targets to maximize cost-effectiveness and maintain readiness for new threats. We also highlight challenges associated with genomic surveillance and when global inequalities persist. We propose solutions to mitigate some of these issues, including training and multilateral partnerships. Exploring alternatives to clinical sequencing can also reduce the cost of surveillance programs. Finally, we discuss how establishing genomic surveillance would aid control programs and potentially provide a warning system for outbreaks, using a global respiratory virus (RSV), an arbovirus (dengue virus), and a regional zoonotic virus (Lassa virus) as examples.
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Affiliation(s)
- Verity Hill
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
| | - George Githinji
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Department of Biochemistry and Biotechnology, Pwani University, Kilifi, Kenya
| | - Chantal B F Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Yale Institute for Global Health, Yale University, New Haven, CT, USA
| | - Ana I Bento
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA; The Rockefeller Foundation, New York, NY, USA
| | - Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Yale Institute for Global Health, Yale University, New Haven, CT, USA
| | - Christine V F Carrington
- Department of Preclinical Sciences, The University of the West Indies, St. Augustine Campus, St. Augustine, Trinidad and Tobago
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Yale Institute for Global Health, Yale University, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA; Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
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Li Z, Yang B, Wang J, Wen Y, Xu J, Ling L, Wang T. Global border restrictions in 2020-2021: Adherence and the effectiveness in long-term COVID-19 epidemic control. Travel Med Infect Dis 2023; 52:102556. [PMID: 36805032 PMCID: PMC9946459 DOI: 10.1016/j.tmaid.2023.102556] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 12/05/2022] [Accepted: 02/15/2023] [Indexed: 02/23/2023]
Abstract
BACKGROUND Restrictions on international travel were widely applied to contain cross-border COVID-19 diffusion, while such applications varied globally, and little was known about their impacts on the long-term epidemic progression. METHODS We explored the global diversity in maintaining border policies classified to four levels (screening, quarantine, ban on regions and total border closure) using data of 185 countries and regions between 01 January 2020 to 31 December 2021. By using Ordinary least squares (OLS) regression and quantile regression (QR) models, we examined the relationship between total COVID-19 incidence and the cumulative duration of each policy level in 2020-2021, and the heterogeneity of such association across different transmission severity countries. RESULTS Firstly, "ban on regions" was the most durable policy applied in high-income countries, while in low-income countries, less stringent measures of screening and quarantine arrivals were applied the longest. Secondly, the cumulatively longer maintenance of the border quarantine was significantly associated with lower infections (log) in COVID-19 high-prevalent countries (75th QR, coefficient estimates [β] = -0.0038, 95% confidence interval: -0.0066 to -0.0010). By contrast, in medium and high transmission severity countries, those with longer duration of imposing bans on regions showed no suppressing effects but significantly higher COVID-19 incidence (OLS regression, β = 0.0028, 95% CI: 0.0009-0.0047; 75th QR, β = 0.0039, 95% CI: 0.0014-0.0063). No other significant results were found. CONCLUSION From the long-term perspective, inbound quarantine was effective in mitigating severe epidemics. However, in countries with medium or high COVID-19 prevalence, our findings of ban on regions highlighted its ineffectiveness in the long-term epidemic progression.
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Affiliation(s)
- Zhiyao Li
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, PR China; Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical University, Taiyuan, 030001, PR China
| | - Boran Yang
- Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical University, Taiyuan, 030001, PR China
| | - Jiale Wang
- Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical University, Taiyuan, 030001, PR China
| | - Yanchao Wen
- Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical University, Taiyuan, 030001, PR China
| | - Jianguo Xu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, PR China; Institute of Public Health, Nankai University, Tianjing, 300350, PR China
| | - Li Ling
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, PR China; Clinical research design division, Clinical research center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510080, PR China.
| | - Tong Wang
- Department of Health Statistics and Epidemiology, School of Public Health, Collaborative Innovation Center of Reverse Microbial Etiology, Shanxi Medical University, Taiyuan, 030001, PR China; Shanxi Provincial Key Laboratory of Major Infectious Disease Pandemic Response, Taiyuan, 030001, PR China.
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Worsnop CZ, Grépin KA, Lee K, Marion S. The Unintended Consequences of Information Provision: The World Health Organization and Border Restrictions during COVID-19. INTERNATIONAL STUDIES PERSPECTIVES 2023; 24:39-66. [PMID: 36778757 PMCID: PMC9903402 DOI: 10.1093/isp/ekac010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Why do some international agreements fail to achieve their goals? Rather than states' engaging in cheap talk, evasion, or shallow commitments, the World Health Organization's (WHO) International Health Regulations (IHR)-the agreement governing states' and WHO's response to global health emergencies-point to the unintended consequences of information provision. The IHR have a dual goal of providing public health protection from health threats while minimizing unnecessary interference in international traffic. As such, during major outbreaks WHO provides information about spread and severity, as well as guidance about how states should respond, primarily regarding border policies. During COVID-19, border restrictions such as entry restrictions, flight suspensions, and border closures have been commonplace even though WHO recommended against such policies when it declared the outbreak a public health emergency in January 2020. Building on findings from the 2014 Ebola outbreak, we argue that without raising the cost of disregarding (or the benefits of following) recommendations against border restrictions, information from WHO about outbreak spread and severity leads states to impose border restrictions inconsistent with WHO's guidance. Using new data from COVID-19, we show that WHO's public health emergency declaration and pandemic announcement are associated with increases in the number of states imposing border restrictions.
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Ohlsen EC, Hawksworth AW, Wong K, Guagliardo SAJ, Fuller JA, Sloan ML, O'Laughlin K. Determining Gaps in Publicly Shared SARS-CoV-2 Genomic Surveillance Data by Analysis of Global Submissions. Emerg Infect Dis 2022; 28:S85-S92. [PMID: 36502409 DOI: 10.3201/eid2813.220780] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Viral genomic surveillance has been a critical source of information during the COVID-19 pandemic, but publicly available data can be sparse, concentrated in wealthy countries, and often made public weeks or months after collection. We used publicly available viral genomic surveillance data submitted to GISAID and GenBank to examine sequencing coverage and lag time to submission during 2020-2021. We compared publicly submitted sequences by country with reported infection rates and population and also examined data based on country-level World Bank income status and World Health Organization region. We found that as global capacity for viral genomic surveillance increased, international disparities in sequencing capacity and timeliness persisted along economic lines. Our analysis suggests that increasing viral genomic surveillance coverage worldwide and decreasing turnaround times could improve timely availability of sequencing data to inform public health action.
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Tegally H, Wilkinson E, Martin D, Moir M, Brito A, Giovanetti M, Khan K, Huber C, Bogoch II, San JE, Tsui JLH, Poongavanan J, Xavier JS, Candido DDS, Romero F, Baxter C, Pybus OG, Lessells R, Faria NR, Kraemer MUG, de Oliveira T. Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.11.22.22282629. [PMID: 36451885 PMCID: PMC9709793 DOI: 10.1101/2022.11.22.22282629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
In many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed <15% of all global exports of Delta to other countries and South Africa <1-2% of all global Omicron exports globally. We further estimate that >80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance. Highlights Global phylogenetic analysis reveals relationship between air travel and speed of dispersal of SARS-CoV-2 variants of concern (VOCs)Omicron VOC spread to 5x more countries within 100 days of its emergence compared to all other VOCsOnward transmission and dissemination of VOCs Delta and Omicron was primarily from secondary hubs rather than initial country of detection during a time of increased global air travelAnalysis highlights highly connected countries identified as major global and regional exporters of VOCs.
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Affiliation(s)
- Houriiyah Tegally
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Eduan Wilkinson
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Darren Martin
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Monika Moir
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Anderson Brito
- Instituto Todos pela Saúde, São Paulo, São Paulo, Brazil
| | - Marta Giovanetti
- Laboratorio de Flavivirus, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil
- Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Department of Science and Technology for Humans and the Environment, University of Campus Bio-Medico di Roma, Rome, Italy
| | - Kamran Khan
- BlueDot, Toronto, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada
| | | | - Isaac I Bogoch
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada
| | - James Emmanuel San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | | | - Jenicca Poongavanan
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Joicymara S Xavier
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Unaí, Brazil
| | - Darlan da S Candido
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Filipe Romero
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Cheryl Baxter
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
| | - Richard Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
- Departamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
- Department of Biology, University of Oxford, Oxford, UK
| | - Moritz U G Kraemer
- Department of Biology, University of Oxford, Oxford, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Tulio de Oliveira
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Department of Global Health, University of Washington, Seattle, WA, USA
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Rahmani S, Rezaei N. SARS-CoV-2 Omicron (B.1.1.529) Variant: No Time to Wait! ACTA BIO-MEDICA : ATENEI PARMENSIS 2022; 93:e2022097. [PMID: 35546004 PMCID: PMC9171856 DOI: 10.23750/abm.v93i2.12712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 04/10/2022] [Indexed: 11/10/2022]
Abstract
On November 26th, a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), B.1.1.529, was designated by the World Health Organization (WHO), named Omicron, and classified as a variant of concern (VOC). The news raised an international alarm about a new wave of coronavirus disease 2019 (Covid-19) outbreak, since Omicron has a large group of mutations which may affect the way it spread, cause disease, and escape from the immunity. Therefore, it is essential to take a closer look at how it has emerged, how it may sustain the pandemic, and how we can act correspondingly, both nationally and internationally, to help control the spreading of the disease.
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Affiliation(s)
- Shayan Rahmani
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Nima Rezaei
- University of Medical Sciences, Tehran, Iran.
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