The multidisciplinary nature of COVID-19 research

Arencibia-Jorge, Ricardo and García-García, Lourdes and Galban-Rodriguez, Ernesto and Carrillo-Calvet, Humberto The multidisciplinary nature of COVID-19 research. Iberoamerican Journal of Science Measurement and Communication, 2020, vol. 1, n. 1. [Journal article (Unpaginated)]

[img]
Preview
 Text
13-Article Text-219-1-10-20201222.pdf
Download (555kB) | Preview

English abstract

Objective. We analyzed the scientific output after COVID-19 and contrasted it with studies published in the aftermath of seven epidemics/pandemics: Severe Acute Respiratory Syndrome (SARS), Influenza A virus H5N1 and Influenza A virus H1N1 human infections, Middle East Respiratory Syndrome (MERS), Ebola virus disease, Zika virus disease, and Dengue. Design/Methodology/Approach. We examined bibliometric measures for COVID-19 and the rest of the studied epidemics/pandemics. Data were extracted from Web of Science, using its journal classification scheme as a proxy to quantify the multidisciplinary coverage of scientific output. We proposed a novel Thematic Dispersion Index (TDI) for the analysis of pandemic early stages. Results/Discussion. The literature on the seven epidemics/pandemics before COVID-19 has shown explosive growth of the scientific production and continuous impact during the first three years following each emergence or re-emergence of the specific infectious disease. A subsequent decline was observed with the progressive control of each health emergency. We observed an unprecedented growth in COVID-19 scientific production. TDI measured for COVID-19 (29,4) in just six months, was higher than TDI of the rest (7,5 to 21) during the first three years after epidemic initiation. Conclusions. COVID-19 literature showed the broadest subject coverage, which is clearly a consequence of its social, economic, and political impact. The proposed indicator (TDI), allowed the study of multidisciplinarity, differentiating the thematic complexity of COVID-19 from the previous seven epidemics/pandemics. Originality/Value. The multidisciplinary nature and thematic complexity of COVID-19 research were successfully analyzed through a scientometric perspective.

Item type: Journal article (Unpaginated)
Keywords: COVID-19, multidisciplinarity, pandemic diseases, scientometrics, bibliometric indicators, scientific production, citation analysis, thematic dispersion index
Subjects: B. Information use and sociology of information > BB. Bibliometric methods
Depositing user: Unnamed user with email ijsmc@colnes.org
Date deposited: 11 Jan 2021 23:42
Last modified: 11 Jan 2021 23:42
URI: http://hdl.handle.net/10760/40925

References

Arencibia-Jorge, R., Vega-Almeida, R. L., & Carrillo-Calvet, H. (2020). Evolución y alcance multidisciplinar de tres técnicas de análisis bibliométrico. Palabra Clave (La Plata), 10(1), e102. https://doi.org/10.24215/18539912e102

Belli, S., Mugnaini, R., Baltà, J., & Abadal, E. (2020). Coronavirus mapping in scientific publications: When science advances rapidly and collectively, is access to this knowledge open to society? Scientometrics 124 (3), 2661-2685. https://doi.org/10.1007/s11192-020-03590-7

Chahrour, M., Assi, S., Bejjani, M., Nasrallah, A. A., Salhab, H., Fares, M., et al. (2020). A bibliometric analysis of Covid-19 research activity: A call for increased output. Cureus, 12(3), e7357. https://doi.org/10.7759/cureus.7357

Chen, C. (2017) Science mapping: a systematic review of the literature. Journal of Data and Information Science, 2(2), 1-40. https://doi.org/10.1515/jdis-2017-0006

Darsono, D., Rohmana, J. A., & Busro, B. (2020). Against COVID-19 Pandemic: Bibliometric Assessment of World Scholars' International Publications related to COVID-19. Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia, 5(1), 75-89. https://doi.org/10.25008/jkiski.v5i1.356

De Felice, F., & Polimeni, A. (2020). Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis. In vivo, 34(3 suppl), 1613-1617. https://doi.org/10.21873/invivo.11951

Dehghanbanadaki, H., Seif, F., Vahidi, Y., Razi, F., Hashemi, E., Khoshmirsafa, M., et al. (2020). Bibliometric analysis of global scientific research on Coronavirus (COVID-19). Medical Journal of The Islamic Republic of Iran (MJIRI), 34(1), 354-362. https://doi.org/10.34171/mjiri.34.51

El Mohadab, M., Bouikhalene, B., & Safi, S. (2020). Bibliometric method for mapping the state of the art of scientific production in Covid-19. Chaos, Solitons & Fractals, 139, 110052. https://doi.org/10.1016/j.chaos.2020.110052

Fan, V., Jamison, D. T., & Summers, L. H. (2018). Pandemic risk: how large are the expected losses? Bulletin of the World Health Organization, 96(2), 129-134. https://doi.org/10.2471/BLT.17.199588129

Garfield, E., 2006. The history and meaning of the journal impact factor. Jama 295 (1), 90-93. https://doi.org/10.1001/jama.295.1.90

Hamidah, I., Sriyono, S., & Hudha, M. N. (2020). A Bibliometric Analysis of Covid-19 Research using VOSviewer. Indonesian Journal of Science and Technology, 5(2), 34-41. https://doi.org/10.17509/ijost.v5i2.24522

Herrera-Viedma, E., López-Robles, J. R., Guallar, J., & Cobo, M. J. (2020). Global trends in coronavirus research at the time of Covid-19: A general bibliometric approach and content analysis using SciMAT. El Profesional de la Información, 29(3), e290322. https://doi.org/10.3145/epi.2020.may.22

Huber, C., Finelli, L., & Stevens, W. (2018). The economic and social burden of the 2014 Ebola outbreak in West Africa. The Journal of Infectious Diseases, 218(Suppl. 5), S698-S704. https://doi.org/10.1093/infdis/jiy213

Johanson, M. A., Reich, N. G., Meyers, L. A., & Lipsitch, M. (2018). Pre-prints: An underutilized mechanism to accelerate outbreak science. PLoS Medicine, 15(4), e1002549. https://doi.org/10.1371/journal.pmed.1002549

Kambhampati, S. B., Vaishya, R., & Vaish, A. (2020). Unprecedented surge in publications related to COVID-19 in the first three months of pandemic: A bibliometric analytic report. Journal of Clinical Orthopaedics and Trauma, 11(Suppl 3), S304. https://doi.org/10.1016/j.jcot.2020.04.030

Keogh-Brown, M. R., & Smith, R. D. (2008). The economic impact of SARS: how does the reality match the predictions? Health policy, 88(1), 110-120. https://doi.org/10.1016/j.healthpol.2008.03.003

Klavans, R., & Boyack, K. W. (2011). Using global mapping to create more accurate document-level maps of research fields. Journal of the American Society for Information Science and Technology, 62(1), 1-18. https://doi.org/10.1002/asi.21444

Kozlakidis, Z., Abduljawad, J., Al Khathaami, A. M., Schaper, L., & Stelling, J. (2020). Global health and data-driven policies for emergency responses to infectious disease outbreaks. The Lancet Global Health, August 10. https://doi.org/10.1016/S2214-109X(20)30361-2

Kuhar, M., & Fatović-Ferenčić, S. (2020). Victories and defeats: battles with pandemics caused by viruses during the last one hundred years. Liječnički vjesnik, 142(3-4), 107-113. https://doi.org/10.26800/LV-142-3-4-19

Leydesdorff, L., & Bornmann, L. (2016). The operationalization of fields as WoS subject categories (WCs) in evaluative bibliometrics: The cases of library and information science and science & technology studies. Journal of the Association for Information Science and Technology, 67(3), 707-714. https://doi.org/10.1002/asi.23408

Lou, J., Tian, S. J., Niu, S. M., Kang, X. Q., Lian, H. X., Zhang, L. X., et al. (2020). Coronavirus disease 2019: a bibliometric analysis and review. Eur Rev Med Pharmacol Sci, 24(6), 3411-21. https://doi.org/10.26355/eurrev_202003_20712

Moradian, N., Ochs, H. D., Sedikies, C., Hamblin, M. R., Camargo, C. A., Martinez, J. A., et al. (2020). The urgent need for integrated science to fight COVID-19 pandemic and beyond. Journal of Translational Medicine, 18(1), 205. https://doi.org/10.1186/s12967-020-02364-2

Moschini, U., Fenialdi, E., Daraio, C., Ruocco, G., & Molinari, E. (2020). A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of 'authors' documents, their bibliography and their citing papers. Scientometrics, May 15. https://doi.org/10.1007/s11192-020-03481-x

Myers, K. R., Tham, W. Y., Yin, Y., Cohodes, N., Thursby, J. G., Thursby, M.C., et al. (2020). Unequal effects of the COVID-19 pandemic on scientists. Nature human behaviour, 4(9), 880-3.

Peters, M. A., Jandrić, P., & McLaren, P. (2020). Viral modernity? Epidemics, infodemics, and the '' 'bioinformational' paradigm. Educational Philosophy and Theory, 1-23. https://doi.org/10.1080/00131857.2020.1744226

Pike, J., Bogich, T., Elwood, S., Finnoff, D. C., & Daszak, P. (2014). Economic optimization of a global strategy to address the pandemic threat. Proceedings of the National Academy of Sciences, 111(52), 18519-18523. https://doi.org/10.1073/pnas.1412661112

Porta Serra, M. (2014). A Dictionary of epidemiology. Oxford: Oxford University Press.

Porter, A., & Rafols, I. (2009). Is science becoming more interdisciplinary? Measuring and mapping six research fields over time. Scientometrics, 81(3), 719-745. https://doi.org/10.1007/s11192-008-2197-2

Smart, P., 2020. Publishing during pandemic: Innovation, collaboration, and change. Learned Publishing, 33(3), 194-197. https://doi.org/10.1002/leap.1314

Tao, Z., Zhou, S., Yao, R., Wen, K., Da, W., Meng, Y., et al. (2020). COVID-19 will stimulate a new coronavirus research breakthrough: a 20-year bibliometric analysis. Annals of Translational Medicine, 8(8), 528. https://doi.org/10.21037/atm.2020.04.26

Wagner, C. S., Roessner, J. D., Bobb, K., Klein, J. T., Boyack, K. W., Keyton, J., et al. (2011). Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. Journal of informetrics, 5(1), 14-26. https://doi.org/10.1016/j.joi.2010.06.004

Wang, T., Du, Z., Zhu, F., Cao, Z., An, Y., Gao, Y., et al. (2020). Comorbidities and multi-organ injuries in the treatment of COVID-19. The Lancet, 395(10228), e52. https://doi.org/10.1016/S0140-6736(20)30558-4

Wang, X., Wang, Z., Huang, Y., Chen, Y., Zhang, Y., Ren, H., et al. (2017). Measuring interdisciplinarity of a research system: detecting distinction between publication categories and citation categories. Scientometrics, 111, 2023–2039. https://doi.org/10.1007/s11192-017-2348-4

Zhai, F., Zhai, Y., Cong, C., Song, T., Xiang, R., Feng, T., et al. (2020). Research Progress of Coronavirus Based on Bibliometric Analysis. International Journal of Environmental Research and Public Health, 17(11), 3766. https://doi.org/10.3390/ijerph17113766

Zhang, L., Zhao, W., Sun, B., Huang, Y., & Glänzel, W. (2020). How scientific research reacts to international public health emergencies: a global analysis of response patterns. Scientometrics, 124, 747-773. 10.1007/s11192-020-03531-4

Zhou, Y., & Chen, L. (2020). Twenty-Year Span of Global Coronavirus Research Trends: A Bibliometric Analysis. International Journal of Environmental Research and Public Health, 17(9), 3082. https://doi.org/10.3390/ijerph17093082


Downloads

Downloads per month over past year

Actions (login required)

View Item View Item
Altmetric
Contact us
Send email Sponsors
Sponsor: AIMS Sponsor: D&P Sponsor: UniNa CAB Get connected
Facebook Facebook Twitter Twitter Linkedin LinkedIn RSS RSS