Cited by 1,928Global Security and Public HealthInfluenza Virus Research StudiesInternational Science and Diplomacy

The DOI matches its Crossref record; 10 of the 11 references it cites were found in a registry or an index.

Data, disease and diplomacy: GISAID's innovative contribution to global health

Open access

Elbe, Stefan, Buckland‐Merrett, Gemma·2017·Global Challenges

Open this paper in CoChat — free account Open PDF

Abstract

The international sharing of virus data is critical for protecting populations against lethal infectious disease outbreaks. Scientists must rapidly share information to assess the nature of the threat and develop new medical countermeasures. Governments need the data to trace the extent of the outbreak, initiate public health responses, and coordinate access to medicines and vaccines. Recent outbreaks suggest, however, that the sharing of such data cannot be taken for granted – making the timely international exchange of virus data a vital global challenge. This article undertakes the first analysis of the Global Initiative on Sharing All Influenza Data as an innovative policy effort to promote the international sharing of genetic and associated influenza virus data. Based on more than 20 semi‐structured interviews conducted with key informants in the international community, coupled with analysis of a wide range of primary and secondary sources, the article finds that the Global Initiative on Sharing All Influenza Data contributes to global health in at least five ways: (1) collating the most complete repository of high‐quality influenza data in the world; (2) facilitating the rapid sharing of potentially pandemic virus information during recent outbreaks; (3) supporting the World Health Organization's biannual seasonal flu vaccine strain selection process; (4) developing informal mechanisms for conflict resolution around the sharing of virus data; and (5) building greater trust with several countries key to global pandemic preparedness.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1002/gch2.1018

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Data Sharing
Longo, D. L., & Drazen, J. M. (2016) · New England Journal of Medicine · doi:10.1056/nejme1516564 · Cited by 419
A global initiative on sharing avian flu data
Bogner, P., Capua, I., Lipman, D. J., Cox, N. J., & others (2006) · Nature · doi:10.1038/442981a · Cited by 153
nextflu: real-time tracking of seasonal influenza virus evolution in humans
Neher, R. A., & Bedford, T. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv381 · Cited by 139 · cited 1×
“…in the timely exchange of information integral to the selection of pre-pandemic vaccine viruses.85 Strain selection for the seasonal flu vaccines Beyond the specter of pandemic flu, EpiFlu™ also contains the most up-to-date collection of data on seasonal influenza viruses (Neher and Bedford, 2015).”
Background
Data sharing: Make outbreak research open access
Yozwiak, N. L., Schaffner, S. F., & Sabeti, P. C. (2015) · Nature · doi:10.1038/518477a · Cited by 139 · cited 2×
“…diseases.116 There are certainly signs that this data sharing problem alsomanifested itself during the more recent Ebola outbreak in West Africa, (Yozwiak et al., 2015) as well as the spread of Zika virus.117 Although GISAID was approached to extend its scope to include Ebola viruses, GISAID’s…”
Background
Towards Mutual Trust, Transparency and Equity in Virus Sharing Mechanism: The Avian Influenza Case of Indonesia
Sedyaningsih, E. R., Isfandari, S., Soendoro, T., & Supari, S. F. (2008) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.v37n6p482 · Cited by 123 · cited 6×
“3Interview with Alan Hay, former Director of the WHO Collaborating Centre (World Influenza Centre) in London (1993 to 2009); Co-Chair of Scientific Advisory Council and Scientific Liaison Officer of GISAID.”
BackgroundInfluential
Virus sharing, genetic sequencing, and global health security
Gostin, L. O., Phelan, A., Stoto, . A., Kraemer, J. D., & Reddy, K. S. (2014) · Science · doi:10.1126/science.1257622 · Cited by 31
Flu papers spark row over credit for data
Butler, D., & Cyranoski, D. (2013) · Nature · doi:10.1038/497014a · Cited by 8
Non-WHO global initiative on sharing avian influenza data
Quirk, M. R. (2006) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(06)70589-8 · Cited by 4 · cited 1×
“…of the Karo cluster, resulting in their deposit in Genbank.33 It was an unexpected diplomatic breakthrough, and a decision quickly met with reciprocity by the US CDC, when Cox not long thereafter announced that they too would be making influenza data publically accessible (Quick, 2006: 621).”
Background
Scientist rebels against WHO over bird flu.
Zamiska, N. (2006) · PubMed · Cited by 3
Plan to pool bird-flu data takes off
Pearson, H. E. (2006) · Nature · doi:10.1038/442963a · Cited by 2 · cited 14×
“Global Challenges published by John Wiley & Sons Ltd.36 Practical challenges: funding databases sustainably There is also a much more practical obstacle to the sharing of virus data.”
BackgroundInfluential

Flagged first, then by citations

Show all 11 references

1 of the 11 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

Fukuda K. 2011.Comments at ‘Breaking through the InfluenzaWalls – A Symposium Hosted By The Federal Office For Agriculture And Food’. Bonn Germany. 11 October 2011. Available at:https://www.youtube.com/watch?v=M5ekNjxuArk. [Accessed 11 January 2016].
Supari S., 2008, It's time for the world to change; in the spirit of dignity, equity, and transparency

Sorted by citations

Items 701–800 of 1,005

Phylogenomics reveals viral sources, transmission, and potential superinfection in early-stage COVID-19 patients in Ontario, Canada
Sjaarda, C. P., Rustom, N., Evans, G. A., Huang, D., Pérez-Patrigeón, S., Hudson, M. L., Wong, H., Sun, Z., Guan, T. H., Ayub, M., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-83355-1 · Cited by 17
Different selection dynamics of S and RdRp between SARS-CoV-2 genomes with and without the dominant mutations
Koçhan, N., Eskier, D., Süner, A., Karakülah, G., & Oktay, Y. (2021) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2021.104796 · Cited by 17
Host-dependent editing of SARS-CoV-2 in COVID-19 patients
Gregori, J., Cortese, M. F., Piñana, M., de Campos, C. F., García‐Cehic, D., Andrés, C., Abril, J. F., Codina, M. G., Rando‐Segura, A., Esperalba, J., et al. (2021) · Emerging Microbes & Infections · doi:10.1080/22221751.2021.1969868 · Cited by 17
Using genomic epidemiology of SARS-CoV-2 to support contact tracing and public health surveillance in rural Humboldt County, California
Stoddard, G., Black, A., Ayscue, P., Lu, D. Z., Kamm, J., Bhatt, K. D., Chan, L. Y., Kistler, A. L., Batson, J., Detweiler, A. M., et al. (2022) · BMC Public Health · doi:10.1186/s12889-022-12790-0 · Cited by 17
Design of SARS-CoV-2 Variant-Specific PCR Assays Considering Regional and Temporal Characteristics
Oh, C., Sashittal, P., Zhou, A., Wang, L., El-Kebir, M., & Nguyen, T. H. (2022) · Applied and Environmental Microbiology · doi:10.1128/aem.02289-21 · Cited by 19
Scalable Bayesian phylogenetics
Fisher, A. A., Hassler, G. W., Ji, X., Baele, G., Suchard, M. A., & Lemey, P. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0242 · Cited by 17
Characterization of SARS-CoV-2 viral diversity within and across hostsPreprint
Sashittal, P., Luo, Y., Peng, J., & El-Kebir, M. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.07.083410 · Cited by 18
Prime hAd5 Spike + Nucleocapsid Vaccination Induces Ten-Fold Increases in Mean T-Cell Responses in Phase 1 Subjects that are Sustained Against Spike VariantsPreprint
Sieling, P. A., King, T. B., Wong, R. M. H., Nguyen, A., Wnuk, K., Gabitzsch, E., Rice, A., Adisetiyo, H., Hermreck, M., Verma, M., et al. (2021) · medRxiv · doi:10.1101/2021.04.05.21254940 · Cited by 18
Genomic evidence for divergent co-infections of SARS-CoV-2 lineagesPreprint
Zhou, H., Cheng, Y., Xu, L. S., Li, J.-Y., Tao, C., Ji, C., Han, N., Yang, R., Li, Y., & Wu, A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.03.458951 · Cited by 17
Genomics of Indian SARS-CoV-2: Implications in Genetic Diversity, Possible Origin and Spread of Virus
Mondal, M., Lawarde, A., & Somasundaram, K. (2020) · Current Science · doi:10.18520/cs/v118/i11/1786-1791 · Cited by 16
European context of the diversity and phylogenetic position of SARS-CoV-2 sequences from Polish COVID-19 patients
Hryhorowicz, S., Ustaszewski, A., Kaczmarek-Ryś, M., Lis, E., Witt, M., Pławski, A., & Ziętkiewicz, E. (2021) · Journal of Applied Genetics · doi:10.1007/s13353-020-00603-2 · Cited by 15
Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows
Lagerborg, K. A., Normandin, E., Bauer, M. R., Adams, G. C., Figueroa, K., Loreth, C., Gladden, A. D., Shaw, B. M., Pearlman, L. R., Berenzy, D., et al. (2021) · Nature Microbiology · doi:10.1038/s41564-021-01019-2 · Cited by 23
Evasion of Vaccine-Induced Humoral Immunity by Emerging Sub-Variants of SARS-CoV-2
Koyama, T., Miyakawa, K., Tokumasu, R., Jeremiah, S. S., Kudo, M., & Ryo, A. (2022) · Future Microbiology · doi:10.2217/fmb-2022-0025 · Cited by 15
Broadly Neutralizing Antibodies to SARS-CoV-2 Provide Novel Insights Into the Neutralization of Variants and Other Human Coronaviruses
Bajpai, P., Singh, V., Chandele, A., & Kumar, S. (2022) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2022.928279 · Cited by 16
“The recently emerged, highly mutated, and transmissible Omicron (B.1.1.529) and its variants have now become the dominant circulating SARSCoV-2 variants worldwide with recombinant SARS-CoV-2 variants XD, XE, and XF also causing increased infection in humans (Elbe and Buckland-Merrett, 2017).”
BackgroundInfluential
A 21L/BA.2-21K/BA.1 “MixOmicron” SARS-CoV-2 hybrid undetected by qPCR that screen for variant in routine diagnosis
Colson, P., Delerce, J., Marion‐Paris, E., Lagier, J., Levasseur, A., Fournier, P., Scola, B. L., & Raoult, D. (2022) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2022.105360 · Cited by 15
Amazon Biobank: a collaborative genetic database for bioeconomy development
Kimura, L. T., Andrade, E. R., Nobre, I., Nobre, C. A., de Medeiros, B. A. S., Riaño‐Pachón, D. M., Shiraishi, F. K., Carvalho, T. C. M. D. B., & Junior, M. A. S. (2023) · Functional & Integrative Genomics · doi:10.1007/s10142-023-01015-1 · Cited by 16
The antigenic landscape of human influenza N2 neuraminidases from 2009 until 2017
Catani, J. P. P., Smet, A., Ysenbaert, T., Vuylsteke, M., Bottu, G., Mathys, J., Botzki, A., Cortés-Garcia, G., Strugnell, T., Gomila, R. C., et al. (2023) · eLife · doi:10.7554/elife.90782 · Cited by 16
Evolutionary trajectory of SARS-CoV-2 genome shifts during widespread vaccination and emergence of Omicron variant
Gayvert, K. M., McKay, S., Lim, W. K., Baum, A., Kyratsous, C. A., Copin, R., & Atwal, G. S. (2023) · npj Viruses · doi:10.1038/s44298-023-00007-z · Cited by 17
“Scientists and medical professionals worldwide have sequenced the SARS-CoV-2 genome from patient isolates, and their ﬁ ndings have been rapidly disseminated through curated data repositories such as the global initiative on sharing all in ﬂ uenza data (GISAID, https://www.gisaid.org) 1,2 .”
Diversity of short linear interaction motifs in SARS-CoV-2 nucleocapsid protein
Schuck, P., & Zhao, H. (2023) · mBio · doi:10.1128/mbio.02388-23 · Cited by 15
“Mutation data were based on consensus sequences of SARS-CoV-2 isolates submitted to GISAID and downloaded on 20 January 2023 as database files metadata.tsv and nextclade.tsv preprocessed by Nextstrain (61).”
Influential
Phylodynamics of avian influenza A(H5N1) viruses from outbreaks in Brazil
Júnior, A. V. R., Reischak, D., de Oliveira, C. H. S., Otaka, J. N. P., Domingues, C. S., Freitas, T. D. L., Cardoso, F. G., Montesino, L. O., da Silva, A. L. S., Camillo, S. C. A., et al. (2024) · Virus Research · doi:10.1016/j.virusres.2024.199415 · Cited by 16
Territorywide Study of Early Coronavirus Disease Outbreak, Hong Kong, China
Leung, K. S.-S., Ng, T. T.-L., Wu, A. K. L., Yau, M. C.-Y., Lao, H.-Y., Choi, M.-P., Tam, K. K.-G., Lee, L.-K., Wong, B. K. C., Ho, A. Y. M., et al. (2020) · Emerging infectious diseases · doi:10.3201/eid2701.201543 · Cited by 16
Specific epitopes form extensive hydrogen-bonding networks to ensure efficient antibody binding of SARS-CoV-2: Implications for advanced antibody design
Wang, D., Ge, Y., Zhong, B., & Liu, D. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.03.021 · Cited by 15
Comparative phylogenetic analysis of SARS-CoV-2 spike protein—possibility effect on virus spillover
Ghorbani, A., Samarfard, S., Eskandarzade, N., Afsharifar, A., Eskandari, M. H., Niazi‎, A., Izadpanah, K., & Karbanowicz, T. P. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab144 · Cited by 18
Genomic Epidemiology of SARS-CoV-2 in Pakistan
Song, S., Li, C., Kang, L., Tian, D., Badar, N., Ma, W., Zhao, S., Jiang, X., Wang, C., Sun, Y., et al. (2021) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.08.007 · Cited by 15
SARS-CoV-2 receptor-binding mutations and antibody contact sites
Mejdani, M., Haddadi, K., Pham, C., & Mahadevan, R. (2021) · Antibody Therapeutics · doi:10.1093/abt/tbab015 · Cited by 17
No species-level losses of s2m suggests critical role in replication of SARS-related coronaviruses
Gilbert, C., & Tengs, T. (2021) · Scientific Reports · doi:10.1038/s41598-021-95496-4 · Cited by 16
EpiSurf: metadata-driven search server for analyzing amino acid changes within epitopes of SARS-CoV-2 and other viral species
Bernasconi, A., Cilibrasi, L., Khalaf, R. A., Alfonsi, T., Ceri, S., Pinoli, P., & Canakoglu, A. (2021) · Database · doi:10.1093/database/baab059 · Cited by 16
Immuno-informatics analysis predicts B and T cell consensus epitopes for designing peptide vaccine against SARS-CoV-2 with 99.82% global population coverage
Shukla, P., Pandey, P., Prasad, B., Robinson, T., Purohit, R., D'Cruz, L. G., Tambuwala, M. M., Mutreja, A., Harkin, J., Singh, T., et al. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab496 · Cited by 16
“As of August 2021, a total of 32 mutations have been reported on Spike glycoprotein by Covid-Miner [37] which is enabled by data from the Global Initiative on Sharing Avian Influenza Data [38].”
Whole-genome analysis of SARS-CoV-2 in a 2020 infection cluster in a nursing home of Southern Italy
Marco, C. D., Marascio, N., Veneziano, C., Biamonte, F., Trecarichi, E. M., Santamaria, G., Leviyang, S., Liberto, M. C., Mazzitelli, M., Quirino, A., et al. (2022) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2022.105253 · Cited by 16
“Phylogenetic analysis was carried out using a total of 5095 fulllength SARS-CoV-2 sequences, collected in Italy by March 2021 and downloaded from the GISAID database on June 4th 2021 (Elbe and Buckland-Merrett, 2017).”
Performances of rapid and connected salivary RT-LAMP diagnostic test for SARS-CoV-2 infection in ambulatory screening
Schneider, F. S., Molina, L., Picot, M., l’Helgoualch, N., Espeut, J., Champigneux, P., Alali, M., Baptiste, J., Cardeur, L., Carniel, C., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-04826-7 · Cited by 15
Molecular epidemiological features of SARS-CoV-2 in Japan, 2020–1
Ode, H., Nakata, Y., Nagashima, M., Hayashi, M., Yamazaki, T., Asakura, H., Suzuki, J., Kubota, M., Matsuoka, K., Matsuda, M., et al. (2022) · Virus Evolution · doi:10.1093/ve/veac034 · Cited by 18
“Another concern is that various variants of SARS-CoV-2 have evolved through mutations (Elbe and Buckland-Merrett 2017; Rambaut et al. 2020), albeit at a slow speed because of its proofreading machinery.”
BackgroundInfluential
The Coronavirus Standards Working Group’s roadmap for improved population testing
Mercer, T. R., Almond, N. M., Chain, P., Crone, M. A., Deshpande, A., Eveleigh, D., Freemont, P. S., Fuchs, S., Garlick, R. K., Huggett, J. F., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01538-1 · Cited by 18
Comparison of COVID-19 Pandemic Waves in 10 Countries in Southern Africa, 2020–2021
Smith-Sreen, J., Miller, B. M., Kabaghe, A. N., Kim, A. A., Wadonda-Kabondo, N., Frawley, A. A., Labuda, S. M., Manuel, E., Frietas, H., Mwale, A., et al. (2022) · Emerging infectious diseases · doi:10.3201/eid2813.220228 · Cited by 17
“org) (14); those data were exported on September 19, 2021, and included specimens collected during March 1, 2020– September 6, 2021.”
Background
Coordinated surveillance is essential to monitor and mitigate the evolutionary impacts of SARS-CoV-2 spillover and circulation in animal hosts
Kuchipudi, S. V., Tan, C. C. S., van Dorp, L., Lichtveld, M. Y., Pickering, B., Bowman, J., Mubareka, S., & Balloux, F. (2023) · Nature Ecology & Evolution · doi:10.1038/s41559-023-02082-0 · Cited by 15
Scoring amino acid mutation to predict pandemic risk of avian influenza virus
Qiang, X., & Kou, Z. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2770-0 · Cited by 16
A territory-wide study of early COVID-19 outbreak in Hong Kong community: A clinical, epidemiological and phylogenomic investigationPreprint
Leung, K. S.-S., Ng, T. T.-L., Wu, A. K. L., Yau, M. C.-Y., Lao, H.-Y., Choi, M.-P., Tam, K. K.-G., Lee, L.-K., Wong, B. K.-C., Ho, A. Y.-M., et al. (2020) · medRxiv · doi:10.1101/2020.03.30.20045740 · Cited by 16
No detectable signal for ongoing genetic recombination in SARS-CoV-2Preprint
Richard, D., Owen, C. J., van Dorp, L., & Balloux, F. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.15.422866 · Cited by 15
Ongoing recombination in SARS-CoV-2 revealed through genealogical reconstructionPreprint
Ignatieva, A., Hein, J., & Jenkins, P. A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.21.427579 · Cited by 16
A rapid, cost efficient and simple method to identify current SARS-CoV-2 variants of concern by Sanger sequencing part of the spike protein genePreprint
Jørgensen, T. S., Blin, K., Kuntke, F., Salling, H. K., Michaelsen, T. Y., Albertsen, M., & Larsen, H. (2021) · medRxiv · doi:10.1101/2021.03.27.21252266 · Cited by 16
Chronumental: time tree estimation from very large phylogeniesPreprint
Sanderson, T. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.27.465994 · Cited by 16
Spatial and temporal transmission dynamics of respiratory syncytial virus in New Zealand before and after the COVID-19 pandemic
Jelley, L., Douglas, J., O’Neill, M. P., Berquist, K., Claasen, A., Wang, J., Utekar, S., Johnston, H., Bocacao, J., Allais, M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53998-5 · Cited by 17
Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach
Hossain, M. U., Bhattacharjee, A., Emon, M. T. H., Chowdhury, Z. M., Mosaib, M. G., Mourin, M., Das, K. C., Keya, C. A., & Salimullah, M. (2020) · Gene · doi:10.1016/j.gene.2020.145368 · Cited by 15
Conserved molecular signatures in the spike protein provide evidence indicating the origin of SARS-CoV-2 and a Pangolin-CoV (MP789) by recombination(s) between specific lineages of Sarbecoviruses
Gupta, R. S., & Khadka, B. (2021) · PeerJ · doi:10.7717/peerj.12434 · Cited by 15
The early SARS-CoV-2 epidemic in Senegal was driven by the local emergence of B.1.416 and the introduction of B.1.1.420 from Europe
Perez, L. J., Orf, G. S., Berg, M. G., Rodgers, M. A., Meyer, T. V., Mohaimani, A., Olivo, A., Harris, B., Mowerman, I., Padane, A., et al. (2022) · Virus Evolution · doi:10.1093/ve/veac025 · Cited by 15
“6 million genomes deposited in GISAID (Elbe and Buckland-Merrett 2017) (1.”
Influential
Quasispecies Analysis of SARS-CoV-2 of 15 Different Lineages during the First Year of the Pandemic Prompts Scratching under the Surface of Consensus Genome Sequences
Bader, W., Delerce, J., Aherfi, S., Scola, B. L., & Colson, P. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232415658 · Cited by 17
“org/ (accessed on 30 September 2022)) [62] using the GISAID online search tool”
Method
The Delta variant wave in Tunisia: Genetic diversity, spatio-temporal distribution and evidence of the spread of a divergent AY.122 sub-lineage
Haddad-Boubaker, S., Arbi, M., Souiai, O., Chouikha, A., Fares, W., Edington, K., Sims, S., Cammà, C., Lorusso, A., Diagne, M., et al. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2022.990832 · Cited by 10
Ghosts of the past: Elemental composition, biosynthesis reactions and thermodynamic properties of Zeta P.2, Eta B.1.525, Theta P.3, Kappa B.1.617.1, Iota B.1.526, Lambda C.37 and Mu B.1.621 variants of SARS-CoV-2
Popovic, M. E., Pavlović, M. R. P., & Pavlović, M. M. (2023) · Microbial Risk Analysis · doi:10.1016/j.mran.2023.100263 · Cited by 15
Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection
Milighetti, M., Peng, Y., Tan, C. C. S., Mark, M., Nageswaran, G., Byrne, S., Ronel, T., Peacock, T., Mayer, A., Chandran, A., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106937 · Cited by 18
Why is the Omicron main protease of SARS-CoV-2 less stable than its wild-type counterpart? A crystallographic, biophysical, and theoretical study
Ibrahim, M., Sun, X., de Oliveira, V. M., Liu, R., Clayton, J., Kilani, H. E., Shen, J., & Hilgenfeld, R. (2024) · hLife · doi:10.1016/j.hlife.2024.06.003 · Cited by 15
Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2
Nguyen, A., Zhao, H., Myagmarsuren, D., Srinivasan, S., Wu, D., Chen, J., Piszczek, G., & Schuck, P. (2024) · eLife · doi:10.7554/elife.94836.3 · Cited by 15
Large-scale computational modelling of H5 influenza variants against HA1-neutralising antibodies
Ford, C. T., Yasa, S., Obeid, K., Jaimes, R., Tomezsko, P. J., Guirales-Medrano, S., White, R. A., III, & Janies, D. A. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105632 · Cited by 15
An Immunoinformatics Approach for SARS-CoV-2 in Latam Populations and Multi-Epitope Vaccine Candidate Directed towards the World’s Population
Orduz, A. F. C., Díaz, L. L., Acosta, A. F., Peñaloza, M. K., Méndez, Y. R., Clavijo-Buriticá, D. C., & Yosa, J. (2021) · Vaccines · doi:10.3390/vaccines9060581 · Cited by 16
Whole-Genome Sequencing of SARS-CoV-2 from Quarantine Hotel Outbreak
Leong, L. E. X., Soubrier, J., Turra, M., Denehy, E., Walters, L., Kassahn, K. S., Higgins, G., Dodd, T., Hall, R., D’Onise, K., et al. (2021) · Emerging infectious diseases · doi:10.3201/eid2708.204875 · Cited by 15
Anatomy of the first six months of COVID-19 vaccination campaign in Italy
Gozzi, N., Chinazzi, M., Davis, J. T., Mu, K., y Piontti, A. P., Ajelli, M., Perra, N., & Vespignani, A. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010146 · Cited by 16
A Comparison Between Omicron and Earlier COVID-19 Variants' Disease Severity in the Milan Area, Italy
Consolazio, D., Murtas, R., Tùnesi, S., Lamberti, A., Senatore, S., Faccini, M., & Russo, A. G. (2022) · Frontiers in Epidemiology · doi:10.3389/fepid.2022.891162 · Cited by 14
CoVizu: Rapid analysis and visualization of the global diversity of SARS-CoV-2 genomes
Ferreira, R.-C., Wong, E., Gugan, G., Wade, K. E., Liu, M., Baena, L. M., Chato, C., Lu, B., Olabode, A. S., & Poon, A. F. Y. (2021) · Virus Evolution · doi:10.1093/ve/veab092 · Cited by 15
CRESSP: a comprehensive pipeline for prediction of immunopathogenic SARS-CoV-2 epitopes using structural properties of proteins
An, H., Eun, M., Yi, J., & Park, J. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac056 · Cited by 16
Comparison of the Performance of the PanBio COVID-19 Antigen Test in SARS-CoV-2 B.1.1.7 (Alpha) Variants versus non-B.1.1.7 Variants
van Ogtrop, M. L., van de Laar, T. J. W., Eggink, D., Vanhommerig, J. W., & van der Reijden, W. A. (2021) · Microbiology Spectrum · doi:10.1128/spectrum.00884-21 · Cited by 14
Epidemiology and genetic diversity of SARS-CoV-2 lineages circulating in Africa
Okoh, O. S., Nii-Trebi, N. I., Jakkari, A., Olaniran, T. T., Senbadejo, T. Y., Kafintu-kwashie, A. A., Dairo, E. O., Ganiyu, T. O., Akaninyene, I. E., Ezediuno, L. O., et al. (2022) · iScience · doi:10.1016/j.isci.2022.103880 · Cited by 13
“d The accession numbers of sequences used in the study and respective GISAID acknowledgment table are provided in Data S5. d All original code used in the manuscript has been deposited at: https://github.com/Yinkaokoh/ updatedSARCoV2_project.”
Influential
High-throughput drug screening allowed identification of entry inhibitors specifically targeting different routes of SARS-CoV-2 Delta and Omicron/BA.1
Kuzikov, M., Woens, J., Zaliani, A., Hambach, J., Eden, T., Fehse, B., Ellinger, B., & Riecken, K. (2022) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2022.113104 · Cited by 14
Emerging variants of SARS-CoV-2 NSP10 highlight strong functional conservation of its binding to two non-structural proteins, NSP14 and NSP16
Wang, H., Rizvi, S. R. A., Dong, D., Lou, J., Wang, Q., Sopipong, W., Su, Y., Najar, F. Z., Agarwal, P. K., Kozielski, F., et al. (2023) · eLife · doi:10.7554/elife.87884 · Cited by 19
Evolution of Sequence and Structure of SARS-CoV-2 Spike Protein: A Dynamic Perspective
Sinha, A., Sangeet, S., & Roy, S. (2023) · ACS Omega · doi:10.1021/acsomega.3c00944 · Cited by 14
Upcoming epidemic storm: Empirical formulas, biosynthesis reactions, thermodynamic properties and driving forces of multiplication of the omicron XBB.1.9.1, XBF and XBB.1.16 (Arcturus) variants of SARS-CoV-2
Popovic, M. E., Mihailović, M., & Panić, S. (2023) · Microbial Risk Analysis · doi:10.1016/j.mran.2023.100273 · Cited by 14
Unraveling viral drug targets: a deep learning-based approach for the identification of potential binding sites
Popov, P. A., Kalinin, R. E., Buslaev, P., Kozlovskii, I., Zaretckii, M., Karlov, D. S., Gabibov, A. G., & Stepanov, A. V. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad459 · Cited by 14
“We retrieved amino acid sequences corresponding to the Spike protein from the GISAID [70] database (version March 2023) as well as the reference sequence from the UniProt [71] (UniProt ID: P0DTC2).”
Method
SARS-CoV-2 outbreak: role of viral proteins and genomic diversity in virus infection and COVID-19 progression
Hussein, H. A. M., Thabet, A. A., Wardany, A. A., El-Adly, A. M., Ali, M. E., Hassan, M. E. A., Abdeldayem, M. A. B., Mohamed, A.-R. M. A., Sobhy, A., El‐Mokhtar, M. A., et al. (2024) · Virology Journal · doi:10.1186/s12985-024-02342-w · Cited by 17
Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland
Lipponen, A., Kolehmainen, A., Oikarinen, S., Hokajärvi, A.-M., Lehto, K., Heikinheimo, A., Halkilahti, J., Juutinen, A., Luomala, O., Smura, T., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-58113-8 · Cited by 14
“Specific mutations of the variants were identified from a CoV-Spectrum platform (https:// cov-spect rum. org) based on the Global Initiative on Sharing All Influenza Data (GISAID) 18,19 .”
Method
Differential impact of COVID-19 non-pharmaceutical interventions on the epidemiological dynamics of respiratory syncytial virus subtypes A and B
Holmdahl, I. E., Bents, S. J., Baker, R. E., Casalegno, J., Trovão, N. S., Park, S. W., Metcalf, C. J. E., Viboud, C. G., & Grenfell, B. T. (2024) · Scientific Reports · doi:10.1038/s41598-024-64624-1 · Cited by 14
A broad neutralizing nanobody against SARS-CoV-2 engineered from an approved drug
Liu, Q., Cai, C., 黄燕燕, Zhou, L., Guan, Y., Fu, S., Lin, Y., Yang, T., Yan, H., Zhang, Z., et al. (2024) · Cell Death and Disease · doi:10.1038/s41419-024-06802-7 · Cited by 14
“Compared to its monomeric form, the Tri-VHH60-His construct demonstrated a 9-fold increase in potency in blocking ACE2-RBD interaction, with an IC 50 of 33.57 nM (Fig.”
BackgroundInfluential
Genomic characterization of highly pathogenic H5 avian influenza viruses from Alaska during 2022 provides evidence for genotype-specific trends of spatiotemporal and interspecies dissemination
Ahlstrom, C. A., Torchetti, M. K., Lenoch, J. B., Beckmen, K. B., Boldenow, M. L., Buck, E. J., Daniels, B., Dilione, K. E., Gerlach, R. F., Lantz, K., et al. (2024) · Emerging Microbes & Infections · doi:10.1080/22221751.2024.2406291 · Cited by 14
Concepts and Methods for Predicting Viral Evolution
Meijers, M., Ruchnewitz, D., Eberhardt, J., Karmakar, M., Łuksza, M., & Lässig, M. (2025) · Methods in molecular biology · doi:10.1007/978-1-0716-4326-6_14 · Cited by 15
COVID-19 and post-mortem microbiological studies
Fernández-Rodríguez, A., Casas, I., Culebras, E., Morilla, E., Cohen, M. C., & Alberola, J. (2020) · Revista Española de Medicina Legal · doi:10.1016/j.remle.2020.05.007 · Cited by 13
De novo Genome Assembly of the Raccoon Dog (Nyctereutes procyonoides)
Chueca, L. J., Kochmann, J., Schell, T., Greve, C., Janke, A., Pfenninger, M., & Klimpel, S. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.658256 · Cited by 14
Analysis of SARS-CoV-2 nucleocapsid phosphoprotein N variations in the binding site to human 14-3-3 proteins
Veliz, S. D., Rivera, L., Bustos, D. M., & Uhart, M. (2021) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2021.06.100 · Cited by 14
Recurrent and persistent infection with SARS-CoV-2 – epidemiological data and case reports from Western Sweden, 2020
Ringlander, J., Olausson, J., Nyström, K., Härnqvist, T., Jakobsson, H. E., & Lindh, M. (2021) · Scandinavian Journal of Infectious Diseases · doi:10.1080/23744235.2021.1957143 · Cited by 14
A comprehensive review of the analysis and integration of omics data for SARS-CoV-2 and COVID-19
Zhu, Z., Zhang, S., Wang, P., Chen, X., Bi, J., Cheng, L., & Zhang, X. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab446 · Cited by 14
The seasonal behaviour of COVID-19 and its galectin-like culprit of the viral spike
Caetano-Anollés, K., Hernandez, N., Mughal, F., Tomaszewski, T., & Caetano‐Anollés, G. (2022) · Methods in microbiology · doi:10.1016/bs.mim.2021.10.002 · Cited by 14
Evolutionary dynamics of the severe acute respiratory syndrome coronavirus 2 genomes
Qian, Z., Li, P., Tang, X., & Lü, J. (2022) · Medical Review · doi:10.1515/mr-2021-0035 · Cited by 14
Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants
Hu, Y., Hu, J., Gong, H., Danchin, A., Sun, R., Chu, H., Hung, I. F., Yuen, K., To, K. K., Zhang, B., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.861050 · Cited by 15
“The current virological and epidemiological techniques took several weeks to validate whether the variant is capable of reducing the efficacy of current vaccines (17, 18) or therapeutic antibodies (18, 19), even though their viral sequences have been shared in real time via the Global Initiative for Sharing All Influe…”
MethodInfluential
A Paradigm Shift in the Combination Changes of SARS-CoV-2 Variants and Increased Spread of Delta Variant (B.1.617.2) across the World
Chakraborty, C., Sharma, A. R., Bhattacharya, M., Agoramoorthy, G., & Lee, S. (2022) · Aging and Disease · doi:10.14336/ad.2021.1117 · Cited by 14
“The study used servers, such as Nextstrain (SARS-CoV-2 resources) [41, 42], CoVariants [38,43] and 2019 Novel Coronavirus Resource (2019nCoVR) (developed by CNCB) [44].”
Method
Modelling the interplay of SARS-CoV-2 variants in the United Kingdom
Barreiro, N. L., Govezensky, T., Ventura, C. I., Núñez, M., Bolcatto, P. G., & Barrio, R. A. (2022) · Scientific Reports · doi:10.1038/s41598-022-16147-w · Cited by 12
Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks
Saldivar‐Espinoza, B., Macip, G., Garcia‐Segura, P., Mestres‐Truyol, J., Puigbò, P., Cereto‐Massagué, A., Pujadas, G., & García-Vallvé, S. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232314683 · Cited by 15
Genomics-informed outbreak investigations of SARS-CoV-2 using civet
O’Toole, A. N., Hill, V., Jackson, B., Dewar, R., Sahadeo, N. S. D., Colquhoun, R., Rooke, S., McCrone, J. T., Duggan, K. M., McHugh, M. P., et al. (2022) · PLOS Global Public Health · doi:10.1371/journal.pgph.0000704 · Cited by 14
A Noncoding A-to-U Kozak Site Change Related to the High Transmissibility of Alpha, Delta, and Omicron VOCs
Yang, J., Cui, Y., Yu, D., Zhang, G., Cao, R., Gu, Z., Dai, G., Wu, X., Ling, Y., Yi, C., et al. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad142 · Cited by 15
Independent FDA Analyses of Nirmatrelvir/Ritonavir Resistance in the Phase 2/3 Trials EPIC-HR and EPIC-SR
Rawson, J. M. O., Donaldson, E., O’Rear, J. J., & Harrington, P. R. (2024) · Clinical Infectious Diseases · doi:10.1093/cid/ciae615 · Cited by 13
Principal component analysis of coronaviruses reveals their diversity and seasonal and pandemic potential
Konishi, T. (2020) · PLoS ONE · doi:10.1371/journal.pone.0242954 · Cited by 13
Characterization of SARS-CoV-2 East Java isolate, Indonesia
Rantam, F. A., Prakoeswa, C. R. S., Tinduh, D., Nugraha, J., Susilowati, H., Wijaya, A. Y., Puspaningsih, N. N. T., Puspitasari, D., Husada, D., Kurniati, N. D., et al. (2021) · F1000Research · doi:10.12688/f1000research.53137.1 · Cited by 12
Progressing adaptation of SARS-CoV-2 to humans
Konishi, T. (2022) · Chem-Bio Informatics Journal · doi:10.1273/cbij.22.1 · Cited by 13
“Mutation blacklist” and “mutation whitelist” of SARS-CoV-2
Sun, Y., Wang, M., Lin, W., Dong, W., & Xu, J. (2022) · Journal of Biosafety and Biosecurity · doi:10.1016/j.jobb.2022.06.006 · Cited by 13
Science Education Research within TPACK Framework at a Glance: A Bibliometric Analysis
Putri, A. H., Robandi, B., Samsudin, A., & Suhandi, A. (2022) · International Journal of Technology in Education and Science · doi:10.46328/ijtes.404 · Cited by 13
“In addition, International collaboration is essential in developing countries' efforts to increase scientific capacity (Elbe & Buckland‐Merrett, 2017; Nagendra et al., 2018; Sachs et al., 2019).”
Background
Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection
Arriaga-Canon, C., Contreras‐Espinosa, L., Rebollar‐Vega, R., Montiel-Manríquez, R., Cedro‐Tanda, A., García-Gordillo, J. A., Álvarez-Gómez, R. M., Jiménez-Trejo, F. J., Hernández, C. C., & Herrera, L. A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231911058 · Cited by 14
Enhancing global preparedness during an ongoing pandemic from partial and noisy data
Klamser, P., d’Andrea, V., Lauro, F. D., Zachariae, A., Bontorin, S., Nardo, A. D., Hall, M. D., Maier, B. F., Luca Ferretti, A., Brockmann, D., et al. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad192 · Cited by 13
“For all SARS-CoV-2 sequences belonging to the B.1.1.7 (Alpha), B.1.617.2 (Delta), B.1.1.529, BA.2, BA.5, and BA.2.75 (Omicron) lineages from GISAID (32, 34, 33), we retain only those generated from cases reported during the early stage of the corresponding wave from the country of evolutionary…”
Influential
Comparative analysis of PB2 residue 627E/K/V in H5 subtypes of avian influenza viruses isolated from birds and mammals
Briggs, K., & Kapczynski, D. R. (2023) · Frontiers in Veterinary Science · doi:10.3389/fvets.2023.1250952 · Cited by 13
Comparative Review of the State of the Art in Research on the Porcine Epidemic Diarrhea Virus and SARS-CoV-2, Scope of Knowledge between Coronaviruses
Rosas-Murrieta, N. H., Rodríguez-Enríquez, A., Camacho, I. H., Millán-Pérez-Peña, L., Santos‐López, G., & Rivera-Benítez, J. F. (2024) · Viruses · doi:10.3390/v16020238 · Cited by 13
“On the other hand, on the GISAID platform (https://www.gisaid.org/) (consulted on 16 January 2024) [113,114] until January 2024, almost 16,500,000 genome sequence submissions of virus sequences have been reported.”
Background
Tracking the prevalence and emergence of SARS-CoV-2 variants of concern using a regional genomic surveillance program
Jung, A., Droit, L., Febles, B., Fronick, C., Cook, L., Handley, S. A., Parikh, B. A., & Wang, D. (2024) · Microbiology Spectrum · doi:10.1128/spectrum.04225-23 · Cited by 13
Highly specific SARS-CoV-2 main protease (Mpro) mutations against the clinical antiviral ensitrelvir selected in a safe, VSV-based system
Rauch, S., Costacurta, F., Schöppe, H., Peng, J.-Y., Bante, D., Erisoez, E. E., Sprenger, B., He, X. C., Moghadasi, S. A., Krismer, L., et al. (2024) · Antiviral Research · doi:10.1016/j.antiviral.2024.105969 · Cited by 15
Efficacy of baloxavir marboxil against bovine H5N1 virus in mice
Kiso, M., Uraki, R., Yamayoshi, S., & Kawaoka, Y. (2025) · Nature Communications · doi:10.1038/s41467-025-60791-5 · Cited by 12
“Brie ﬂ y, cDNAs encoding viral RNAs, based on published sequences (EPI_ISL_19014384) 12 , were synthesized by using a commercial vendor (Integrated DNA Technologies) and cloned into RNA polymerase I-based plasmids, followed by in ﬂ uenza virus generation as previously described 5,6 .”
COVID-19 y estudios microbiológicos post mortem
Fernández-Rodríguez, A., Casas, I., Culebras, E., Morilla, E., Cohen, M. C., & Alberola, J. (2020) · Revista Española de Medicina Legal · doi:10.1016/j.reml.2020.05.007 · Cited by 12
Spatio-Temporal Mutational Profile Appearances of Swedish SARS-CoV-2 during the Early Pandemic
Ling, J., Hickman, R. A., Li, J., Lu, X., Lindahl, J. F., Lundkvist, Å., & Järhult, J. D. (2020) · Viruses · doi:10.3390/v12091026 · Cited by 14
Understanding the dynamics of COVID-19; implications for therapeutic intervention, vaccine development and movement control
Salvamani, S., Tan, H., Thang, W., Ter, H., Wan, M., Gunasekaran, B., & Rhodes, A. (2020) · British Journal of Biomedical Science · doi:10.1080/09674845.2020.1826136 · Cited by 14
The Direct and Indirect Impact of SARS-CoV-2 Infections on Neonates
Saha, S., Ahmed, A. N. U., Sarkar, P. K., Ahsan, M. R., Ghosh, K., Rahman, S. W., Rahman, H., Hooda, Y., Ahsan, N., Malaker, R., et al. (2020) · The Pediatric Infectious Disease Journal · doi:10.1097/inf.0000000000002921 · Cited by 13

Authors: Elbe, S., & Buckland‐Merrett, G.
Affiliations: University of Sussex (GB)
Corresponding author: Elbe, Stefan
ORCID: Elbe, Stefan
Venue: Global Challenges
Publisher: Wiley
Published: 2017-01
Volume: 1
Issue: 1
Pages: 33-46
ISSN: 2056-6646 (ISSN-L)
DOI: 10.1002/gch2.1018
PMC: PMC6607375
OpenAlex: W2587970647
Cited by: 1,928
References: 11
Citations by year: 2026: 77 · 2025: 139 · 2024: 184 · 2023: 269 · 2022: 460 · 2021: 530 · 2020: 246 · 2019: 11 · 2018: 6 · 2017: 5
FWCI: 187.75
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor, 9 d)
Locations: Global Challenges (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics: Social Sciences › Sociology and Political Science › Global Security and Public Health
Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
Social Sciences › Political Science and International Relations › International Science and Diplomacy
Keywords: GISAID, international data sharing, pandemic preparedness, global health policy, influenza surveillance, World Health Organization, conflict resolution, trust building, infectious disease outbreaks

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data, disease and diplomacy: GISAID's innovative contribution to global health

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks