| Literature DB >> 32836335 |
Abstract
This study sought to understand the nature of scientific globalism during a global crisis, particularly COVID-19. Findings show that scientific globalism occurs differently when comparing COVID-19 publications with non-COVID-19 publications during as well as before the pandemic. Despite the tense geopolitical climate, countries increased their proportion of international collaboration and open-access publications during the pandemic. However, not all countries engaged more globally. Countries that have been more impacted by the crisis and those with relatively lower GDPs tended to participate more in scientific globalism than their counterparts. © Springer Nature B.V. 2020.Entities:
Keywords: COVID-19; China; Geopolitics; International collaboration; USA
Year: 2020 PMID: 32836335 PMCID: PMC7378298 DOI: 10.1007/s10734-020-00589-0
Source DB: PubMed Journal: High Educ (Dordr) ISSN: 0018-1560
Fig. 1Map of the 111 countries that published articles on COVID-19 from January 12, 2020, to May 9, 2020
Frequencies of single country publications and international publications for articles published between 2015 and 2019, for non-COVID-192020 articles and for COVID-192020 articles
| Time period | Total publications | Total single country -publications | % Single country publications | Total international collaborations | % International collaborations |
|---|---|---|---|---|---|
| 2015–2019 | 10,043,064 | 7,691,933 | 76.59% | 2,351,131 | 23.41% |
| Non-COVID-192020 | 679,600 | 490,187 | 72.13% | 189,413 | 27.87% |
| COVID-192020 | 3401 | 2259 | 66.42% | 1142 | 33.58% |
Frequencies of single country publications and international publications for articles published between 2015 and 2019, for non-COVID-192020 articles, and for COVID-192020 articles by top 25 country/region
| Country/region | Total COVID-19 publications | % International collaborations on COVID-19 | % International collaborations 2015–2019 | % International collaborations non-COVID-192020 | ||
|---|---|---|---|---|---|---|
| China | 1079 | 20.02% | 22.48% | .05 | 25.00% | 0.00 |
| United States | 624 | 42.95% | 39.94% | .12 | 42.68% | 0.89 |
| Italy | 310 | 39.68% | 49.88% | .00 | 53.11% | 0.00 |
| United Kingdom | 209 | 67.46% | 60.02% | .05 | 65.07% | 0.47 |
| India | 141 | 26.95% | 18.60% | .01 | 21.97% | 0.15 |
| France | 122 | 42.62% | 59.02% | .00 | 63.96% | 0.00 |
| Canada | 118 | 74.58% | 55.63% | .00 | 59.69% | 0.00 |
| Germany | 106 | 62.26% | 55.34% | .15 | 59.77% | 0.60 |
| Australia | 93 | 69.89% | 57.55% | .02 | 62.92% | 0.17 |
| Spain | 89 | 50.56% | 49.75% | .88 | 54.16% | 0.50 |
| Iran | 74 | 31.08% | 21.91% | .06 | 31.82% | 0.89 |
| Singapore | 74 | 40.54% | 68.64% | .00 | 73.33% | 0.00 |
| Switzerland | 62 | 66.13% | 72.37% | .27 | 75.14% | 0.10 |
| South Korea | 57 | 29.82% | 28.50% | .82 | 32.75% | 0.64 |
| Netherlands | 54 | 81.48% | 63.91% | .01 | 67.42% | 0.03 |
| Hong Kong | 53 | 75.47% | 74.60% | .89 | 77.73% | 0.70 |
| Brazil | 52 | 46.15% | 32.14% | .03 | 40.12% | 0.38 |
| Japan | 48 | 50.00% | 30.87% | .00 | 36.41% | 0.05 |
| Taiwan | 46 | 39.13% | 35.20% | .56 | 42.80% | 0.62 |
| Belgium | 44 | 88.64% | 69.38% | .01 | 74.62% | 0.03 |
| Sweden | 37 | 70.27% | 65.53% | .54 | 69.07% | 0.87 |
| Saudi Arabia | 36 | 75.00% | 77.41% | .73 | 78.61% | 0.60 |
| Mexico | 33 | 42.42% | 42.86% | .96 | 50.03% | 0.38 |
| Turkey | 33 | 27.27% | 22.86% | .55 | 30.31% | 0.71 |
| Austria | 28 | 89.29% | 68.88% | .02 | 72.91% | 0.05 |
Frequencies of open access and non-open–access publications for articles published between 2015 and 2019, for non-COVID-192020 articles and for COVID-192020 articles
| Time period | Non-open access | Open access | % Open access |
|---|---|---|---|
| 2015–2019 | 7,140,116 | 2,902,948 | 28.90% |
| Non-COVID-192020 | 461,811 | 217,789 | 32.04% |
| COVID-192020 | 825 | 2576 | 75.74% |
Frequencies of non-open access and open-access publications for articles published between 2015 and 2019, for non-COVID-192020 articles, and for COVID-192020 articles by top 25 country/region
| Country/region | Open access on COVID-19 | % Open access on COVID-19 | % Open access 2015–2019 | % Open-access non-COVID-192020 | ||
|---|---|---|---|---|---|---|
| China | 732 | 67.84% | 22.68% | .00 | 26.23% | .00 |
| United States | 541 | 86.70% | 32.20% | .00 | 31.21% | .00 |
| Italy | 234 | 75.48% | 30.70% | .00 | 40.88% | .00 |
| United Kingdom | 174 | 83.25% | 39.05% | .00 | 43.44% | .00 |
| India | 87 | 61.70% | 22.12% | .00 | 19.02% | .00 |
| France | 95 | 77.87% | 29.47% | .00 | 34.36% | .00 |
| Canada | 106 | 89.83% | 30.94% | .00 | 31.98% | .00 |
| Germany | 82 | 77.36% | 33.07% | .00 | 45.25% | .00 |
| Australia | 78 | 83.87% | 28.96% | .00 | 31.76% | .00 |
| Spain | 74 | 83.15% | 32.44% | .00 | 42.32% | .00 |
| Iran | 54 | 72.97% | 18.08% | .00 | 22.59% | .00 |
| Singapore | 65 | 87.84% | 27.53% | .00 | 29.36% | .00 |
| Switzerland | 54 | 87.10% | 40.52% | .00 | 44.19% | .00 |
| South Korea | 53 | 92.98% | 32.85% | .00 | 39.07% | .00 |
| Netherlands | 36 | 66.67% | 46.19% | .00 | 58.95% | .25 |
| Hong Kong | 47 | 88.68% | 23.62% | .00 | 26.93% | .00 |
| Brazil | 41 | 78.85% | 45.55% | .00 | 34.04% | .00 |
| Japan | 43 | 89.58% | 37.33% | .00 | 35.94% | .00 |
| Taiwan | 43 | 93.48% | 33.80% | .00 | 41.18% | .00 |
| Belgium | 34 | 77.27% | 34.05% | .00 | 41.75% | .00 |
| Sweden | 32 | 86.49% | 43.13% | .00 | 55.98% | .00 |
| Saudi Arabia | 28 | 77.78% | 33.04% | .00 | 41.01% | .00 |
| Mexico | 24 | 72.73% | 35.08% | .00 | 36.55% | .00 |
| Turkey | 24 | 72.73% | 30.49% | .00 | 24.87% | .00 |
| Austria | 22 | 78.57% | 42.72% | .00 | 55.63% | .01 |
Final generalized linear model on the influences of past international collaboration, COVID-19 cases, and GDP on COVID-19 international collaboration (N = 111 countries)
| Parameter | B | Std Error | Exp(B) | 95% CI for Exp(B) | |
|---|---|---|---|---|---|
| % Int Authors 2015–19 | .03 | .00 | 1.04 | 1.03–1.04 | < .001 |
| COVID-19 cases* | .05 | .02 | 1.06 | 1.02–1.09 | .001 |
| GDP** | −.05 | .02 | .95 | .93–.98 | .002 |
Goodness of fit: Deviance value/df = 2.41
*In 100-thousands
**In trillions
Final generalized linear model on the influences of past open-access articles, COVID-19 cases, and GDP on COVID-19 open-access articles (N = 110* countries)
| Parameter | B | Std Error | Exp(B) | 95% CI for Exp(B) | |
|---|---|---|---|---|---|
| % Open access 2015–2019 | .02 | .01 | 1.02 | .99–1.05 | .277 |
| COVID-19 cases** | .08 | .02 | 1.09 | 1.05–1.12 | < .001 |
| GDP*** | −.03 | .01 | .97 | .94–1.00 | .023 |
Goodness of fit: Deviance value/df = 1.96
*1 case (Slovakia) was dropped as the number for COVID-19 (2) was higher than for 2015–2019 (1)
**In 100-thousands
***In trillions