Literature DB >> 34720251

Evolution and structure of research fields driven by crises and environmental threats: the COVID-19 research.

Mario Coccia1.   

Abstract

Evolution of science and behavior of new research fields emerging under conditions of crisis are new topics hardly known in social studies of science and scientometrics. In particular, the ecosystem and dynamics of research fields during crisis are vital aspects for explaining and planning the scientific development, and allocating resources efficaciously toward positive societal impact. This study here endeavors to analyze the evolution and structure of COVID-19 (Coronavirus Disease 2019) research, a new research field emerged and driven by a global pandemic crisis. The dynamics and structure of this research field are compared to related fields concerning respiratory disorders that are not guided by pandemic crisis, such as chronic obstructive pulmonary disease and lung cancer, to explain similarities and differences. Results suggest that a crisis-driven research field is characterized by an unparalleled velocity of scientific production equal to about 1.2% daily, based on notes and short papers mainly open access that support scientific advances and discoveries in research arena over a short period of time, such as the development of innovative drugs given by novel vaccines and new antiviral COVID-19 treatments. Findings are generalized in properties that clarify the evolution and structure of new research fields and their research behavior in a period of crisis for guiding decisions of policymakers to support scientific and technological progress in human society in the presence of environmental threats. © Akadémiai Kiadó, Budapest, Hungary 2021.

Entities:  

Keywords:  COVID-19; Crisis management; Dynamics of science; Evolution of science; Pandemic crisis; Research fields; Scientific development; Scientific discovery; Scientific ecosystem ; Structure of science; Technological change; mRNA vaccine

Year:  2021        PMID: 34720251      PMCID: PMC8541882          DOI: 10.1007/s11192-021-04172-x

Source DB:  PubMed          Journal:  Scientometrics        ISSN: 0138-9130            Impact factor:   3.238


Introduction

The evolution and structure of research fields driven by crisis are critical aspects to science and society for allocating resources and planning scientific development efficaciously to support scientific discoveries and new technology having a positive societal impact in the presence of environmental threats (Coccia & Bellitto, 2018; Coccia, 2020a, 2020b, 2020c, 2020d, 2021e; Sun et al., 2013). In this context, the evolution of and ecosystem of scientific research concerning the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the Coronavirus Disease 2019 (COVID-19) global pandemic can clarify dynamics and characteristics of research fields and their research behavior in conditions of crisis (Bontempi et al., 2021; Bontempi & Coccia, 2021; Boyack et al., 2009; Coccia, 2018a, 2018b, 2020a, 2021a, 2021b, 2021c, 2021d, 2021e, 2021f, 2021g, 2021a, 2021b, 2021c, 2021d, 2021e, 2021f, 2021g; Dos Santos, 2020; Fanelli & Glänzel, 2013; Fortunato et al., 2018; Sun et al., 2013). The research questions of this study are: How does a new scientific field driven by crisis grow over time compared to established research fields not driven by environmental threats? What are the characteristics of research fields under conditions of crises and environmental threats? Which areas are major knowledge producers? This paper confronts these questions here by developing an inductive study focused on scientific documents in COVID-19 research to analyze the evolution and structure of a new research field originated in a period of crisis to explain basic characteristics of scientific development with environmental threats. This study is part of a large body of research that endeavors to explain how scientific fields and new technology emerge and evolve for designing appropriate research policies directed to progress of science in human society (Ardito et al., 2021; Coccia & Bozeman, 2016; Coccia & Wang, 2016; Coccia, 2018a, 2018b, 2020a, 2020b, 2020c, 2020d; Gibbons et al., 1994; Roshani et al., 2021).

Theoretical framework

The investigation of the research field of COVID-19, driven by a global crisis, can clarify how the dynamics of science sustains new knowledge and develops innovations to solve health and social issues that threat nations and global economy (del Rio-Chanona et al., 2020; Di Girolamo & Meursinge Reynders, 2020; Ebadi et al., 2020; Guerrieri et al., 2020). Scholars are investigating different aspects of COVID-19, such as Haghani and Bliemer (2020) that perform a comparative analysis across different epidemics (SARS, MERS and 2019‑nCoV) showing that studies focus on epidemic control, chemical constitution of the virus, innovative treatments, vaccines and clinical care. Zhang et al. (2020) also investigate different infectious diseases and show that scholars responded quickly to this public health emergency with an accelerated production of publications in disciplines of virology and immunology. Ebadi et al. (2020) analyze temporal evolution of COVID‑19 research through machine learning and show that research communities focus their studies on people with comorbidities. Instead, Di Girolamo and Meursinge Reynders (2020) investigate characteristics of scientific articles during the initial phase of COVID-19 pandemic crisis and suggest that the majority of early publications on COVID-19 are explorative studies with tentative results. In this research field, Belli et al. (2020) show that international collaboration is growing in all countries to support science advances to cope with COVID-19 pandemic crisis (Coccia & Wang, 2016). Atlasi et al. (2021) confirm that the literature on COVID-19 is increasing with a fast rate of scientific production and higher performance of research labs (cf., Coccia, 2008; Coccia & Rolfo, 2008). New results can be used for an effective management of research and allocation of budgets to novel studies to avoid duplication of information and support the prevention, control, and treatment of COVID-19 (cf., Coccia, 2021f, 2022). Pal (2021) demonstrates that the acceleration of publication growth (given by 1600%) reveals a synergic response of researchers to combat pandemic threat of COVID-19 and its variants. Moreover, many scholarly publishers have disclosed their preprint servers to make publications in this research field available immediately in Open Access platforms to increase the diffusion of science, of new knowledge and of new solutions for COVID-19 pandemic crisis. Moreover, the majority of contributions is in medical sciences, focusing on disciplines of virology, immunology, epidemiology, pharmacology, nursing, etc. The most active academic institutions for scientific production concerning COVID-19 are located in the USA, Canada, France, China, Italy, and the UK (cf., Coccia, 2015a). The advanced countries produced more than 50% of the global research about COVID-19 with a lot of scientific collaborations. Sachini et al. (2021) investigate the evolution of publications in COVID-19 having researchers of Greek institutions, showing a steady increase in publications and research collaborations over time. In addition, results suggest that scientific outputs are mainly driven by higher education and government sectors. At international scale, a significant amount of publications (roughly 20%) is due to countries having “traditionally” major scientific production in the field of medicine. This study here develops an inductive analysis, which explains as far as possible dynamics of science and underlying relationships of the research field of COVID-19, driven by a pandemic crisis, to understand characteristics of the research behavior in the presence of environmental threats (del Rio-Chanona et al., 2020; Di Girolamo & Meursinge Reynders, 2020; Ebadi et al., 2020; Guerrieri et al., 2020; Xu et al., 2021). The study shows a preliminary comparison of the scientific growth of different pandemics in the initial phase of diffusion to assess the evolutionary path of COVID-19 research. In particular, the study considers the initial growth of publications in COVID-19 compared to: Middle East Respiratory Syndrome (MERS) that is a viral respiratory disease caused by a novel coronavirus (CoV) called MERS‐CoV, which was first identified in Saudi Arabia in 2012 (WHO, 2021a, b) Human Immunodeficiency Virus (HIV) infection and acquired immunodeficiency syndrome (AIDS) that is a spectrum of conditions caused by infection with the retrovirus of HIV. The first case of this infectious disease seems to appear in May 1981 (Sepkowitz, 2001). Zika virus disease that is caused by a virus transmitted primarily by Aedes mosquitoes, which bite during the day (WHO, 2021a) H1N1 (H1N1pdm09) virus that was detected in the United States in 2009 and spread quickly across the United States and the world. This H1N1 virus contained a unique combination of influenza genes not previously identified in animals or people. This virus was designated as influenza A (H1N1)pdm09 virus (CDC, 2021) In addition, the paper makes a comparative analysis between the evolution of studies concerning the COVID-19 driven by a pandemic crisis and research fields associated with serious respiratory disorders—such as Chronic Obstructive Pulmonary Disease (COPD) and lung cancer—that are not driven by environmental threats. COPD is defined as a disease state characterized by the presence of airflow obstruction given by chronic bronchitis and emphysema. COPD is a highly prevalent disease affecting more than 10% of the population worldwide. The first manifestations occur at the cellular level with biochemical processes that lead to inflammation (Decramer & Cooper, 2010). COPD generates an accelerated decline in forced expiratory volume in one second (FEV1) over time (Lange et al., 2015). COPD generates a great morbidity and mortality (Halbert et al., 2006; Siafakas et al., 2018). The COVID-19 is also compared to studies in lung cancer: “that forms in tissues of the lung, usually in the cells lining air passages” [as defined by the National Cancer Institute (2021)]. Lung cancer is one of the main diseases in several countries and a leading cause of death worldwide. The comparative analysis between the evolution of COVID-19 research, which is crisis-driven, and other research fields that are not driven by crises and environmental threats (e.g., COPD and Lung Cancer) can reveal main differences to clarify characteristics and properties of the dynamics of science under conditions of crises to design research policy for efficient allocation of resources directed to discoveries and innovations for a positive impact in science and society (Fig. 1).
Fig. 1

Structure of the investigation of research fields in a period of crisis

Structure of the investigation of research fields in a period of crisis

Methods and materials

Source and research setting

The study uses data of Scopus (2021) to analyze scientific documents having in title, abstract or keyword the terms connected with respiratory diseases, such as: “COVID”, “COPD”, and “LUNG CANCER” under study here. Scientific products are appropriate units of analysis that can explain the structure and evolution of science. Period under study is from 1st April 2020 onwards, using daily data of document results from Scopus (2021). The year 2021 is not considered in some statistical analyses here because the scientific production is ongoing. Moreover, the statistical analyses of trends of research fields under study consider the first published documents and different periods of the scientific evolution, given by: 1929–2020 for lung cancer 1969–2020 for COPD and finally, 2019–2020 for COVID-19

Measures

Accumulation and development of knowledge in research fields under study here (COVID-19, COPD and Lung Cancer) are measured with total document results given by: article, letter, review, note, editorial, conference paper, short survey, book chapter and conference review. In particular, daily data are gathered from April 2020 onwards (Scopus, 2021). Documents of research fields under study per subject areas (e.g., medicine, biochemistry, genetics and molecular biology, etc.). Document type of research fields under study (i.e., article, letter, conference paper, book chapter, etc.). Documents of research fields under study per source title, such as journals. Documents of research fields under study per affiliation, such as universities, public and private research labs, hospitals, etc. Documents of research fields under study per funding sponsors, such as National Science Foundation, etc. Documents of research fields under study per countries.

Data analysis and procedure

In order to answer the first research question of how a scientific field evolves in a period of crisis compared to established research fields not driven by crisis, the comparative method of inquiry is as follows (cf., Coccia, 2018c). Question 1 (evolution of a crisis-driven research field compared to other related fields)

Methods to explain question 1

Data of documents (in short, Docs) per research fields i (i = COVID-19, COPD and Lung Cancer) are gathered daily from 1st April 2020 to 6th June 2021. It is calculated the daily growth (%) of documents (Docs) per research field (i) given by:The percent increment is calculated from April 2020 to June 2021 for three research fields (COVID-19, COPD and Lung cancer). Results of COVID-19 are also divided in three periods: from April to July 2020, from August to December 2020 and from January to June 2021 to better assess the different magnitude of the growth of this new research field over time. The data of documents and derived variables are transformed in logarithmic scale to have a normal distribution for appropriate parametric analyses and/or to design graphs and trends with comparable values. In addition, the study also compares the scientific growth (with publications) of different pandemics in the initial phase of diffusion to assess the evolutionary path of COVID-19 from 2019 to 2021, compared to:The rate of growth is similar to Eq. (1) but it considers documents in the initial year t and year t’ as indicated above. MERS from t = 2012 to t’ = 2015 HIV from 1981 to 1984 Zika virus disease from 2010 to 2016 H1N1 (H1N1pdm09) virus from 2009 to 2012 Firstly, preliminary analyses of variables are descriptive statistics based on arithmetic mean and std. error of the mean; coefficients of skewness and kurtosis are applied to assess the normality of distributions and, if necessary, to fix the distribution of variables with a log-transformation. Trends and bar graphs of research fields under study can show the type of scientific development and annual increment over 2020–2021 period in a context of comparative analysis. Secondly, the study analyses the evolution of documents as a function of time. The specification of relationship is based on a linear model: y = scientific documents in the research field i (i = COVID-19, COPD, Lung Cancer) t = time = progressive series indicating the time from 1 (1st day), 2 (2nd day), …, to 420 (420 day) b0 = constant b1 = coefficient of regression ε = error term Ordinary Least Squares (OLS) method is applied for estimating the unknown parameters of models [2] in regression analysis. Thirdly, the study analyses whether the difference of arithmetic mean (formula [1]) between data of research fields considered as independent groups is significant (e.g., COVID-19 = group 1 that is driven by crisis vs. COPD = group 2, which is not driven by crisis, etc.). In particular, the Independent Samples t-Test is applied to compare the means of two independent groups to determine whether there is statistical evidence that the associated population means are significantly different. The Independent Samples t-Test requires the assumption of homogeneity of variance—i.e., both groups have the same variance and as a consequence Levene's Test is performed. After that, null hypothesis (H0) and alternative hypothesis (H1) of the Independent Samples t-Test are: H0: µ1 = µ2, the two population means are equal in groups. H1: µ1 ≠ µ2, the two population means are not equal in groups. The arithmetic mean of groups is compared considering pair of research fields under study as follows: COVID-19 (group 1)—COPD (group 2) COVID-19 (group 1)—Lung Cancer (group 3) and COPD (group 2)—Lung Cancer (group 3) Remark. Group 1 indicates a crisis-driven research field; Groups 2 and 3 are research fields not driven by crises but by endogenous factors of the science dynamics (e.g., collaboration, etc.). This analysis is performed considering data from April to December 2020 for 260 days to assess the differences between means in the initial evolution of COVID-19 research to obtain stable results. Data of 2021 are not considered in this analysis because they are ongoing. Question 2 and 3 (characteristics of crisis-driven research fields and research behavior in a period of crisis) In order to clarify the second and third question concerning main drivers and characteristics of the research field of COVID-19, the method is as follows.

Methods to clarify question 2 and 3

Data analysis procedure here uses total number of documents published in the research field of COVID-19 from April to December 2020 and from January to June 2021 to assess variations of research behavior in a period of crisis considering: Main research areas supporting the evolution of the research field of COVID-19 Leading journals supporting the evolution of the COVID-19 research The most prolific institutions in the production of COVID-19 research The most important institutions that have funded studies in the research field of COVID-19 Finally, a ranking of the most prolific countries in COVID-19 research that have supported scientific and technological advances. Statistical analyses are performed with the Statistics Software SPSS® version 26.

Results

Dynamics of the research field driven by crisis compared to other research fields (question 1)

Pandemic is a very special condition of crisis in society that it affects the behavior and characteristics of scientific activity. First of all, the study here shows a comparison of the scientific production growth of different pandemics in the initial phase of diffusion to assess the evolutionary path of COVID-19 research and of other infectious diseases. In particular, the study considers the initial growth of publications in COVID-19 research compared to Middle East Respiratory Syndrome (MERS) from 2012 to 2015, HIV from 1981 to 1984, Zika virus disease from 2010 to 2016 and H1N1pdm09 virus from 2009 to 2012. Figure 2 suggests the unparalleled growth of publications in COVID-19 research, likely associated with the high number of deaths that has supported a lot of scientific research to solve this global pandemic crisis (cf., Pal, 2021).
Fig. 2

Rate of growth of publications concerning some pandemics in the initial phase of diffusion

Rate of growth of publications concerning some pandemics in the initial phase of diffusion Figure 3 shows the evolution of research fields, in which COVID-19 research with a crisis-driven origin in 2019 is compared to research field of lung cancer started in 1929 (though some occasional previous papers) and COPD originated in 1969 or thereabouts. Results suggest two different types of evolution of research fields:
Fig. 3

Evolution of crisis- and problem- driven research fields over time (at 6 June 2021). Note: Log scale is to have comparable trends

crisis-driven evolution is associated with exogenous factors that generate shocks and environmental threats in socioeconomic systems and need to be solved as soon as possible. These research fields (e.g., COVID-19) have an accelerated growth. problem-driven evolution is associated with factors of normal science based on consequential problems concerning people and environment that need to be solved. These research fields have a steady-state and linear growth over time (e.g., studies in COPD and lung cancer). Evolution of crisis- and problem- driven research fields over time (at 6 June 2021). Note: Log scale is to have comparable trends Results show that the evolution of research fields in COPD and lung cancer, originated because of main diseases in society (problem-driven origin), has a linear development (arithmetic growth) of publications (y) given by equation y(t) = α + βt with an acceleration for lung cancer from 1975 (about 45 years after its origin in 1929) and for COPD from 1995 (25 years after the origin); instead, crisis-driven research field of COVID-19 originated with a global pandemic threat has an evolutionary paths similar to an exponential development of publications: y(t) = α·eβ (cf. also Fig. 4).
Fig. 4

Evolution of COVID-19 research compared to COPD and Lung Cancer (t = 420 days from April to December 2020 and from January to June 6th, 2021). COVID-19 = Coronavirus Disease 2019; COPD = Chronic Obstructive Pulmonary Disease; Log scale is to have comparable trends

Evolution of COVID-19 research compared to COPD and Lung Cancer (t = 420 days from April to December 2020 and from January to June 6th, 2021). COVID-19 = Coronavirus Disease 2019; COPD = Chronic Obstructive Pulmonary Disease; Log scale is to have comparable trends Figure 4 shows the initial evolution of the research field of COVID-19 with some chronological events given by the first cases in China (year 2019), the alarming levels of spread and severity in Europe from March 2020 and the announcement of first vaccines in November 2020. Table 1 considers the initial number of publications in COVID-19, COPD and lung cancer research (first three years since origin). It is important to observe that the annual scientific production of COVID-19 studies in December 2020 (i.e., 83,621 documents) has surpassed annual production of main research fields, such as COPD having 4397 documents and in particular lung cancer having 29,362 documents.
Table 1

Number of publications of research fields in the first three years after their origin

YearCOVID-19YearCOPDYearLung cancer
2019571969119291
202085,5391970519300
2021on going1971319314
20204,397202029,362

Data refer to 6th June 2021 (Scopus, 2021)

Number of publications of research fields in the first three years after their origin Data refer to 6th June 2021 (Scopus, 2021) Table 2 confirms the unparalleled evolution of the research field of COVID-19 compared to lung cancer and COPD. In particular, in April 2020 the research field of COVID-19 was at the initial stage of evolution and had the lowest number of publications, whereas in June 2021 it has outclassed over other research fields (COPD and Lung Cancer) that have had a stable evolution over time. In fact, the average growth of the research field of COVID-19 is + 1.2% daily from April 2020 to June2021, whereas other research fields have had a normal evolution given by a steady growth equal to about + 0.42% of daily publications (cf., Fig. 5). In addition, Table 2 shows that the evolution of the research field of COVID-19 from April to July 2020 had an average growth of + 3.16% daily, whereas from August to December 2020 has reduced the acceleration of scientific production, converging towards a more stable growth of about + 0.65% daily; in the 2021 (January-June 2021 period) the growth is + about 0.38%, showing a cycle of life that is directed towards a phase of maturity.
Table 2

Descriptive statistics of scientific documents in the research fields of COVID-19, COPD and Lung Cancer based on 420 days from April 2020 to June 6th, 2021

VariablesArithmetic MeanStd. Error
COVID-19, documents (Docs)68,067.612,135.79
COPD, documents3,743.2374.32
Lung Cancer, documents25,119,04504.17
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right) of$$\end{document}ΔDocs%of COVID-19, daily increment April 2020 to June20211.190.16
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\mathrm{\%}\right) of$$\end{document}ΔDocs%of COPD, daily increment April 2020 to June20210.4170.024
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right) of$$\end{document}ΔDocs%of Lung Cancer, daily increment April 2020 to June20210.4190.023
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right) of$$\end{document}ΔDocs%of COVID-19, daily increment April-July 20203.160.56
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right) of$$\end{document}ΔDocs%of COVID-19, daily increment August-December 20200.650.06
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right) of$$\end{document}ΔDocs%of COVID-19, daily increment January-June 20210.380.04

COVID-19 = Coronavirus Disease 2019; COPD = Chronic Obstructive Pulmonary Disease

Fig. 5

Daily growth (%) of scientific production of research fields based on 420 days from April 2020 to June 6th 2021. COVID-19 = Coronavirus Disease 2019; COPD = Chronic Obstructive Pulmonary Disease

Descriptive statistics of scientific documents in the research fields of COVID-19, COPD and Lung Cancer based on 420 days from April 2020 to June 6th, 2021 COVID-19 = Coronavirus Disease 2019; COPD = Chronic Obstructive Pulmonary Disease Daily growth (%) of scientific production of research fields based on 420 days from April 2020 to June 6th 2021. COVID-19 = Coronavirus Disease 2019; COPD = Chronic Obstructive Pulmonary Disease Table 3 suggests that in the research field of COVID-19, an increase of 1 day, it increases the expected number of publications by about 360 units (p-value < 0.001), whereas in the research field of COPD by about 13 units (p-value < 0.001), finally in the research field of Lung Cancer, the expected number of publications increases by about 85 units (p-value < 0.001). This result confirms the unparalleled growth of scientific production in the research field of COVID-19. Finally, the Independent Samples t-Test compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means of ΔDocs (from April to December 2020) are significantly different (2021 is excluded in this statistical analysis because the research field of COVID-19 is ongoing). The p-value of Levene's test is significant, and we have to reject the null hypothesis and conclude that variances in groups under study are significantly different (i.e., Equal variances are not assumed), except arithmetic mean of between COPD and LC that has p-value < 0.27 and as a consequence Equal variances are assumed (Table 4).
Table 3

Parametric estimates of the relationship of scientific production in research fields as function of time (T = 420 days, from April 2020 to June 2021)

Model linear COVID-19Model linear COPDModel linear lung cancer
Constant α − 7619.01***1102.74***7209.64***
(St. Err.)(323.46)(3.78)(30.34)
Coefficientβ (time) (St. Err.)359.56*** a (1.33)12.54*** a (.016)85.08*** a (.13)
F72,915.44***651,540.61***464,061.02***
R2.9940.99.99

***p-value < 0.001

a = predictor is a progressive series (N) indicating the time from 1 (1st day), 2 (2nd day) … to 420 (420th day) from April 2020 to 6th June 2021

Table 4

Independent samples test

Levene’s Test for equality of variancest-test for equality of Means
FSigtdfSig. (2-tailed)Mean DifferenceStd. Error Difference
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right)$$\end{document}ΔDocs%, COVID-19/COPDEqual variances assumed35.530.0014.6905100.0011.186.2528
Equal variances not assumed4.690264.8090.0011.186.2528
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right)$$\end{document}ΔDocs%, COVID-19/LCEqual variances assumed37.280.0014.7275100.0011.194.2524
Equal variances not assumed4.727263.1180.0011.194.2524
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta Docs \left(\%\right)$$\end{document}ΔDocs%, COPD/LCEqual variances assumed1.2040.273.161510.872.00758.0470
Equal variances not assumed.161505.496.872.00758.0470

N = 256 days over April-December 2020 period. Δ = increment; Docs = documents

Parametric estimates of the relationship of scientific production in research fields as function of time (T = 420 days, from April 2020 to June 2021) ***p-value < 0.001 a = predictor is a progressive series (N) indicating the time from 1 (1st day), 2 (2nd day) … to 420 (420th day) from April 2020 to 6th June 2021 Independent samples test N = 256 days over April-December 2020 period. Δ = increment; Docs = documents Table 4 shows that: There was a significant difference in mean between research fields of COVID-19 and COPD (t264.809 = 4.69, p < 0.001), suggesting a different evolution of research fields associated with crisis- and problem-driven factors. There was a significant difference in mean between research fields of COVID-19 and Lung cancer (t263.118 = 4.727 p < 0.001)¸ also suggesting a different evolution of these research fields associated with crisis- and problem-driven factors. Whereas, arithmetic mean of between research fields of COPD and Lung cancer is not different but it is rather similar (t505.496 = 0.161 p < 0.872), suggesting a similar evolution of these research fields that are not driven by crisis but both by endogenous factors to science. The conclusion of these statistical analyses is that the rate of evolutionary growth of the research field of COVID-19 (crisis-driven) is statistically different from other research fields, such as COPD and Lung cancer (based on problem-driven factors). Hence, crisis-driven research field of COVID-19 has an accelerated and disproportionate growth compared to problem-driven research fields with the potential to lead to manifold scientific and technological breakthroughs in a short period of time.

Results to explain the second and third research question on characteristics of research field and on research behavior in the presence of turbulent crisis

The evolution of the crisis-driven research field of COVID-19 reveals some characteristics to understand the dynamics of science and research behavior in a period of crisis. The most productive research areas in the research field of COVID-19 are mainly related to life science (Table 5). Of the top 10 research areas, more than 53% of documents published on COVID-19 research is in medicine; biochemistry; genetics and molecular biology has more than 8%, and immunology and microbiology has more than 5% (cf., Zhang et al., 2020). In the top ten areas, there is also social sciences (more than 9%) and environmental science (about 3.5%) because manifold studies analyze possible relations between ecology of the COVID-19, environment and society (Coccia, 2020a). The comparison of two periods in 2020 and 2021 shows the growth of computer science in 2021 (associated with simulation models of pandemic diffusion) and of psychology likely associated with side effects of containment policies on mental health of population (Coccia, 2021a). This research field of COVID-19 confirms the properties of science dynamics by Coccia (2018a, b) that the emergence of a research field is in critical (parent) disciplines (e.g., medicine, biochemistry, genetics and molecular biology in the case study of COVID-19), and subsequently the evolution is driven mainly by few disciplines (3–5) that generate more than 80% of documents (concentration of scientific production).
Table 5

Top ten areas supporting the evolution of the research field of COVID-19

Ranking31 December 2020 Documents published, DisciplinesN%6 June 2021 Documents published, DisciplinesN%
1Medicine57,84257.62Medicine97,23653.36
2Social sciences93779.34Social sciences19,21010.54
3Biochemistry, Genetics and molecular biology85608.53Biochemistry, Genetics and molecular biology15,0458.26
4Immunology and Microbiology54725.45Immunology and Microbiology95685.25
5Nursing37233.71Computer science84014.61
6Pharmacology, Toxicology and Pharmaceutics35543.54Environmental sciences74444.09
7Environmental sciences35023.49Nursing69363.81
8computer science30543.04Engineering66793.67
9Engineering28192.81Pharmacology, Toxicology and Pharmaceutics60583.32
10Neuroscience24802.47Psychology56463.10
Total100,383100.00182,223100.00
Top ten areas supporting the evolution of the research field of COVID-19 Table 6 shows the top ten journals that have published more contributions in the COVID-19 research. Five of the top ten journals are related to medicine (parent discipline; cf. Coccia, 2018a, 2018b). In the top ten, there are also journals related to environmental and sustainability science for investigating relationships between environmental pollution and the spread of COVID-19 (cf., also Coccia, 2020a, b, 2021b, 2021c, 2021d, 2021f, 2022; Zhang et al., 2020). In the top ten, it is also important to note the presence of the journal “Medical Hypothesis” because in the initial phase of pandemic crisis generated by a novel coronavirus hardly known, a lot of scholars suggest multiple working hypotheses (cf., Coccia, 2018c) to explain likely determinants of transmission dynamics, effective treatments and policy responses to reduce the negative impact of COVID-19 pandemic in society (cf. also, Haghani & Bliemer, 2020). The evolution of this research field in 2021, compared to 2020, is also driven by journals of psychology and interdisciplinary periodicals (e.g., Scientific Reports) that enter in the top ten list having a higher number of contributions.
Table 6

Top ten journals leading the evolution of the research field of COVID-19

Ranking31 December 2020 Documents published in JournalsN%6 June 2021 Documents published in JournalsN%
1International Journal of environmental research and public health73714.87International Journal of environmental research and public health170218.43
2Journal of medical virology64813.07Plos ONE146515.87
3BMJ Clinical research from British Medical Association61512.41Journal of medical virology102511.10
4BMJ from British Medical Association57611.62BMJ8969.70
5Plos ONE56211.34BMJ Clinical research8759.48
6Lancet4138.33Sustainability (Switzerland)7197.79
7International Journal of Infectious diseases3998.05International Journal of Infectious diseases6707.26
8Medical Hypotheses3547.14Scientific Reports6587.13
9Science of the total environment3276.60Frontiers in Psychology6306.82
10Sustainability3266.58Lancet5946.43
Total4957100.009234100.00
Top ten journals leading the evolution of the research field of COVID-19 The most prolific institutions in the COVID-19 research are Harvard Medical School and Chinese academic organizations (e.g., Huazhong University of Science and Technology, and Tongji Medical College). In the year 2021, University of Toronto and INSERM play a main role in the scientific production. The top 10 active institutions in COVID-19 research are mainly academic institutions of advanced countries: 1 in the USA, 2 in China, 3 in England, 2 in Italy, 1 in France and 1 in Canada (Table 7).
Table 7

The top ten prolific institutions in the production of COVID-19 research 

Ranking31 December 2020 Documents published, Research Institutions/AffiliationsN%6 June 2021, Documents published Research Institutions/AffiliationsN%
1Harvard Medical School, USA142215.56Harvard medical school232515.76
2Huazhong University of Science and Technology, China111112.16Huazhong University of Science and Technology159110.78
3Tongji Medical College, China105611.56University of Toronto157910.70
4The Institut national de la santé et de la recherche médicale, INSERM, the French National Institute of Health and Medical Research98310.76INSERM, France150810.22
5University of Toronto, Canada9089.94Tongji Medical College147710.01
6Università degli Studi di Milano, Italy7768.49University of Oxford13959.45
7University of Oxford, England7618.33University College London12898.74
8Università di Roma la Sapienza, Italy7558.26Imperial College London12238.29
9University College London, England7047.71Università degli Studi di Milano12098.19
10Massachusetts General Hospital, USA6607.22Università di Roma La Sapienza11597.85
Total9136100.0014,755100.00
The top ten prolific institutions in the production of COVID-19 research The top ten funding organizations that have supported the COVID-19 research are located in the USA, China, the UK, Europe (with European Commission) and Brazil. In particular, at December 2020, institutions in the USA have funded about 43% of published studies among top ten institutions, in China about 35% of total top ten, in the UK roughly 12.5% of studies and finally in Brazil about 9%. In June 2021, funding role of US institutions is reinforced in the top ten with about 47%, China, UK and Brazil have a slightly reduction. In 2021, a supranational institution given by European commission enters in the top ten of funding institutions with about 6%. Results also show that the top funding institutions in scientific production of COVID-19 are mainly public organizations, except Wellcome Trust that is a global charitable foundation located in London (UK). In particular, Table 8 shows the driving role of public funding organizations in two large countries given by the USA and China that have funded more than 78% of documents on COVID research among top ten institutions (cf., also Zhang et al., 2020). De Roeck (2016) argues that scientific discovery is also due to main role of funding of governments and funding agencies. In fact, these countries (the USA and China) have developed the first COVID-19 vaccines.
Table 8

Top ten institutions that have funded studies in the research field of COVID-19

Ranking31 December 2020Documents/studies funded byN%6 June 2021Documents/studies funded byN%
1National Natural Science Foundation of China190130.84National Institutes of Health, USA399227.01
2National Institutes of Health, USA164126.62National Natural Science Foundation of China368924.96
3National institute for health research, UK4226.85U.S. Department of health and human services11407.71
4National Science Foundation, USA4116.67National institute for health research, UK10056.80
5Wellcome Trust, UK3465.61National Science Foundation, USA9636.52
6National Institute of allergy and infectious disease, USA3445.58National Key research and Devel program of China9126.17
7Conselho nacional desenvolvimento Cient, Brazil3265.29European Commission8815.96
8Fundamental Research Funds for the Central Universities, China2774.49National Institute of Allergy and infectious disease, USA8165.52
9National heart, Lung and Blood institute, USA2564.15Wellcome Trust, UK7094.80
10Coordenecao de aperfeicoamento de pessoal de Nivel Superior, Brazil2403.89Conselho nacional desenvolvimento Cient, Brazil6724.55
Total6164100.0014,779100.00
Top ten institutions that have funded studies in the research field of COVID-19 The evolution of research field of COVID-19 is driven mainly by scientific production in advanced and rich countries that have published about 78% of documents; the list of top ten countries also includes China with about 13% and India with 8% (Table 9). This result further confirms the concentration of scientific production in specific geo-economic areas given by rich countries (Coccia, 2018a, b). Coccia (2019a, b, c) argues that nations produce science advances and new technology to endorse a socio-economic power and leadership directed to take advantage of important opportunities or to cope with environmental threats in competitive settings (Coccia, 2019a, b, 2020c). In general, underlying motivations of nations to produce science advances and new technology in society, in the presence of environmental threats (e.g., COVID-19), can be: achieve and/or sustain endogenous power and leadership in international system, higher reputation in the international system with challenges in big science and path-breaking technologies, support of economic growth and wellbeing of citizens (Coccia, 2019a, b, c).
Table 9

Top ten countries with the highest number of documents produced in the research field of COVID- 19

Ranking31 December 2020Countries of productionN%6 June 2021Countries of productionN%
1United States21,28530.37United States38,15531.06
2China929313.26United Kingdom15,97513.01
3United Kingdom900412.85China15,09212.29
4Italy776511.08Italy12,66410.31
5India58858.40India10,6548.67
6Spain35855.11Spain65055.30
7Canada35425.05Canada63575.18
8Germany32744.67Germany62275.07
9France32534.64Australia57184.65
10Australia32094.58France54894.47
Total70,095100.00122,836100.00
Top ten countries with the highest number of documents produced in the research field of COVID- 19 Finally, a comparative analysis of crisis-driven research field and problem-driven research fields shows some main characteristics of the research behavior in a period of crisis (Table 10).
Table 10

Characteristics of publication in crisis-driven (COVID-19) research and not crisis-driven research fields (COPD and Lung Cancer), using data on 6th June 2021

COVIDCOPDLung cancer
Number% of totalNumber% of totalNumber% of total
Total publication June 2021152,97060,798449,875
Open access116,20375.9624,61640.49162,70336.17
Type of documents
Article93,56361.1644,03972.43333,98674.24
Letter18,20111.9012812.1113,0892.91
Review16,79510.98864514.2255,78212.40
Note87695.7312272.0286431.92
Conference3070.2022563.7113,8003.07
Characteristics of publication in crisis-driven (COVID-19) research and not crisis-driven research fields (COPD and Lung Cancer), using data on 6th June 2021 Results show that research behavior in crisis is mainly open access for a widespread diffusion of scientific results for a higher impact in scientific communities and society; in fact, products in COVID-19 research have about 76% of open access, whereas in COPD is 40% and Lung cancer is 36%. In addition, scientific production of research field driven by a crisis (COVID-19) has a higher publication density based on short communication given by letters (about 12%) versus 2–3% in COPD and Lung Cancer studies; notes have higher frequency of about 6% in COVID-19 research, whereas is about 2% for COPD and Lung cancer studies. Overall, then, the research behavior in a crisis-driven research field is directed to short contributions for providing concise, clear and new results for a rapid and vast diffusion in science and society.

Discussion

The study here, based on empirical analyses of COVID-19 research, has theoretical implications to explain the dynamics of science and research behavior in periods of crisis that generate scientific discoveries and technological advances. This study suggests that (Table 11):
Table 11

Characteristics of the evolution of problem-driven and crisis-driven research fields in science

OriginProblem-driven research fieldsCrisis-driven research fields
Type of evolutionLinear in short and long runExponential in the short run, linear in the long run
Growth of scientific products in the initial phase of developmentArithmetic incrementGeometric/Exponential increment
Active institutionsPublic research organizations and public/private universitiesPublic research organizations and public/private universities
Funding institutionsPublic funding institutions and foundationsPublic funding institutions and foundations
Prolific countriesRich countriesRich countries
Open AccessLow intensityHigh intensity
Document typeArticles and conferencesArticles, letters and notes
Discoveries and paradigm shiftsLong-runShort-run
Example of research fieldsCOPD, Lung CancerCOVID-19
Problem-driven research fields are guided by problems in nature and/or society (e.g., lung cancer, Alzheimer disease, environmental pollution, etc.) and the evolution is mainly due to endogenous processes in science (e.g., social interaction between groups of scholars and scientific communities) that generate discoveries and science advances in the medium-long run (Sun et al., 2013). Crisis-driven research fields are due to exogenous factors, which generate environmental threats in society, which stimulate scientific research to find solutions in a limited amount of time before can permanently damage socioeconomic systems (e.g., pandemic, war, etc.). The evolution of crisis-driven research fields has, in the starting phase, an exponential growth that fosters science advances and scientific discoveries in the short run. Characteristics of the evolution of problem-driven and crisis-driven research fields in science In particular, some unique characteristics of the evolution of crisis-driven research fields can be systematized with following empirical properties of the dynamics of science under crisis: Drivers of environmental threat. Evolution of crisis-driven research field is due to a new and consequential environmental threat in human society to be solved in the short run, such as COVID-19 global pandemic crisis, supporting a high average rate of growth of scientific production. Remark: Evolution of research field not driven by crisis, called here problem - driven, has an average rate of growth of scientific production equal to about 0.4% daily. Concentration of scientific production. Evolution of crisis-driven research fields is pulled by few (parent) disciplines (3–5) that generate more than 80% of documents. In the case study of COVID-19, critical disciplines are given by medicine, biochemistry, genetics and molecular biology. This crisis-driven research field of COVID-19 confirms the property of science dynamics by Coccia (2018a, b). High production of public and private research organizations. The most active institutions in crisis-driven research are mainly public research labs and public/private universities localized in advanced countries. Public funding. Main funding institutions in scientific production of crisis-driven research field are public organizations of rich nations and global charitable foundations. Remark: Data show that in June 2020, in the initial phase of COVID-19 pandemic, premier biopharmaceutical companies (e.g., AstraZeneca, Merck, Novartis, Pfizer, Roche, etc.) timely funded scientific research for this global health issue and some of them have generated scientific and technological breakthroughs given by novel vaccines and new oral antiviral COVID-19 drugs to treat this new infectious disease (cf., Coccia, 2017c). Global leadership. Scientific production of crisis-driven research fields is due to rich countries that generate about 78% of documents direct to support their global leadership (cf., Coccia, 2015a, 2017a, b). Remark: This result is due to high levels of R&D investments in rich countries that support scientific and technological advances (Coccia, 2009, 2012, 2018a; Kealey, 1996; Price de Solla, 1986). These results can be due to critical socioeconomic factors of leading countries in supporting the research in a period of crisis, such as the research field of COVID-19, as explained by Coccia (2019a, b, 2019c): Science advances and new technology are a source of socioeconomic power for countries to take advantage of important opportunities or to cope with consequential environmental threats in society. Science advances and new technology are drivers of economic and productivity growth for nations and of a higher wellbeing of citizens. Science advances and new technology increase reputation and recognition of nations worldwide to support an endogenous power in international system based on a scientific and technological superiority that endorses their leadership and affects other geo-economic regions to take advantage of commercial and political opportunities (cf., Coccia, 2015a, 2015b). Open source production. Research behavior of crisis-driven research field is mainly based on scientific publications having open access for a vast diffusion of results to increase impact in science and society. Short communication. Scientific production of crisis-driven research field has a higher density of short communications with letters and notes to systematize quickly findings to publish and spread worldwide. In general research fields evolve with accumulation of “normal science” (e.g., COPD and lung cancer) that generates discontinuous transformations in the long run that support the transition from an existing scientific paradigm to an emerging one (Kuhn, 1996). However, what this study adds is that in the presence of environmental threats in human society (such as, COVID-19 global pandemic crisis), the evolution of research has accelerated rates of growth that generate discoveries and science advances in the short run to solve new problems and/or reduce their negative impact in society. In fact, crisis-driven research field of COVID-19 has accelerated the transition towards innovative types of drugs, e.g. mRNA vaccines, generating a paradigm shift to treat infectious diseases (Abbasi, 2020; Coccia, 2021a, 2021b, 2021c, 2021d, 2021e, 2021f, 2021g; Heaton, 2020; Jeyanathan et al., 2020). Finally, research behavior in the presence of crisis management is also based on systematic and improvised activities directed to the use of inventive analogies (e.g., innovative drug of other diseases applied for COVID-19, see the monoclonal antibody Tocilizumab ) for supporting solutions of complex problems in a limited amount of time (Ardito et al., 2021; Bonnardel, 2000).

Conclusions and limitations

Social studies of science show that factors determining the evolution of research fields are due to endogenous factors in science, such as the interaction between scientific communities (Leydesdorff, 2015; Sun et al., 2013). However, this study reveals that the evolution of research fields can be also due to crisis, such as the research field of COVID-19 originated in 2019. In particular, environmental threats and unpredictable crisis can support the origin and accelerated evolution of research directed to explain and solve unknown problems, by generating discoveries, and also scientific and technological paradigm shifts (cf., Becsei-Kilborn, 2010). These conclusions are of course tentative. A limitation of this study is that sources under study may only capture certain aspects of the on-going dynamics of science in a period of crisis. In addition, high production rate and high publication frequency in the research field of COVID-19 can be also due to the fact that in the presence of emergency and crisis, studies associated with COVID-19 have been published without formal procedures of publication. This technical issue may have increased publication frequency, and as a consequence control factors need to be considered in future development of this study. Overall, then, there is need for much more detailed research with additional data to clarify the relations and scientific change underlying the evolution of research in the presence of crises and environmental threats, such as to consider also collaboration intensity, openness of products, intellectual property rights, different sources/procedures of academic publications, different motivations associated with research funding, etc. To conclude, this study is a preliminary analysis that is going to be developed over time.
  29 in total

1.  Lung-Function Trajectories Leading to Chronic Obstructive Pulmonary Disease.

Authors:  Peter Lange; Bartolome Celli; Alvar Agustí; Gorm Boje Jensen; Miguel Divo; Rosa Faner; Stefano Guerra; Jacob Louis Marott; Fernando D Martinez; Pablo Martinez-Camblor; Paula Meek; Caroline A Owen; Hans Petersen; Victor Pinto-Plata; Peter Schnohr; Akshay Sood; Joan B Soriano; Yohannes Tesfaigzi; Jørgen Vestbo
Journal:  N Engl J Med       Date:  2015-07-09       Impact factor: 91.245

Review 2.  Treatment of COPD: the sooner the better?

Authors:  Marc Decramer; Christopher B Cooper
Journal:  Thorax       Date:  2010-09       Impact factor: 9.139

Review 3.  Global burden of COPD: systematic review and meta-analysis.

Authors:  R J Halbert; J L Natoli; A Gano; E Badamgarav; A S Buist; D M Mannino
Journal:  Eur Respir J       Date:  2006-04-12       Impact factor: 16.671

4.  How scientific research reacts to international public health emergencies: a global analysis of response patterns.

Authors:  Lin Zhang; Wenjing Zhao; Beibei Sun; Ying Huang; Wolfgang Glänzel
Journal:  Scientometrics       Date:  2020-06-09       Impact factor: 3.238

5.  Scientific discovery and scientific reputation: the reception of Peyton Rous' discovery of the chicken sarcoma virus.

Authors:  Eva Becsei-Kilborn
Journal:  J Hist Biol       Date:  2010       Impact factor: 0.818

6.  Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID.

Authors:  Mario Coccia
Journal:  Sci Total Environ       Date:  2020-04-20       Impact factor: 7.963

7.  Scientometric analyzing the output of researchers and organizations on COVID-19 for better conducting the scientific efforts: with a glance to endocrinology.

Authors:  Rasha Atlasi; Abdolreza Noroozi Chakoli; Aboozar Ramezani; Ozra Tabatabaei-Malazy; Bagher Larijani
Journal:  J Diabetes Metab Disord       Date:  2021-01-29

8.  Preparedness of countries to face covid-19 pandemic crisis: Strategic positioning and underlying structural factors to support strategies of prevention of pandemic threats.

Authors:  Mario Coccia
Journal:  Environ Res       Date:  2021-07-16       Impact factor: 6.498

9.  Bibliometric Evidence for a Hierarchy of the Sciences.

Authors:  Daniele Fanelli; Wolfgang Glänzel
Journal:  PLoS One       Date:  2013-06-26       Impact factor: 3.240

Review 10.  Natural history of COVID-19 and current knowledge on treatment therapeutic options.

Authors:  Wagner Gouvea Dos Santos
Journal:  Biomed Pharmacother       Date:  2020-07-03       Impact factor: 6.529

View more
  5 in total

1.  Improving preparedness for next pandemics: Max level of COVID-19 vaccinations without social impositions to design effective health policy and avoid flawed democracies.

Authors:  Mario Coccia
Journal:  Environ Res       Date:  2022-05-31       Impact factor: 8.431

2.  Scientific Developments and New Technological Trajectories in Sensor Research.

Authors:  Mario Coccia; Saeed Roshani; Melika Mosleh
Journal:  Sensors (Basel)       Date:  2021-11-24       Impact factor: 3.576

3.  COVID-19 pandemic over 2020 (withlockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors.

Authors:  Mario Coccia
Journal:  Environ Res       Date:  2022-01-13       Impact factor: 8.431

4.  Scientific laws of research funding to support citations and diffusion of knowledge in life science.

Authors:  Melika Mosleh; Saeed Roshani; Mario Coccia
Journal:  Scientometrics       Date:  2022-03-05       Impact factor: 3.801

5.  Short-Term Associations between Size-Fractioned Particles and Cardiopulmonary Function in COPD Patients: A Panel Study in Shanghai, China, during 2014-2021.

Authors:  Lu Zhou; Yingmin Tao; Xiaozhen Su; Xiyin Chen; Liang Li; Qingyan Fu; Juan Xie; Renjie Chen
Journal:  Int J Environ Res Public Health       Date:  2022-09-30       Impact factor: 4.614

  5 in total

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