, Volume 103, Issue 2, pp 337–353 | Cite as

Evolutionary longitudinal network dynamics of global zoonotic research

  • Liaquat Hossain
  • Faezeh Karimi
  • Rolf T. Wigand
  • John W. Crawford


At global and local levels, we are observing an increasing range and rate of disease outbreaks that show evidence of jumping from animals to humans, and from food to humans. Zoonotic infections (i.e. Hendra, swine flu, anthrax) affect animal health and can be deadly to humans. The increasing rate of outbreaks of infectious diseases transferring from animals to humans (i.e. zoonotic diseases) necessitates detailed understanding of the education, research and practice of animal health and its connection to human health. These emerging microbial threats underline the need to exploring the evolutionary dynamics of zoonotic research across public health and animal health. This study investigates the collaboration network of different countries engaged in conducting zoonotic research. We explore the dynamics of this network from 1980 to 2012 based on large scientific data developed from Scopus. In our analyses, we compare several properties of the network including density, clustering coefficient, giant component and centrality measures over time. We also map the network over different time intervals using VOSviewer. We analyzed 5182 publication records. We found United States and United Kingdom as the most collaborative countries working with 110 and 74 other countries in 1048 and 599 cases, respectively. Our results show increasing close collaboration among scientists from the United States, several European countries including United Kingdom, Italy, France, Netherland, Switzerland, China and Australia with scientists from other parts of the world.


Collaboration Evolution Network dynamics Longitudinal study Zoonotic research 


Conflict of interest



  1. Abbasi, A., & Hossain, L. (2011). Investigating attachment behavior of nodes during evolution of a complex social network: A case of a scientific collaboration network. In Knowledge-based and intelligent information and engineering systems (Vol. 6882, pp. 256–264). Lecture notes in computer science.Google Scholar
  2. Abbasi, A., Hossain, L., Uddin, S., & Rasmussen, K. J. R. (2011). Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis. Scientometrics, 89, 687–710.CrossRefGoogle Scholar
  3. Bliziotis, I. A., Paraschakis, K., Vergidis, P. I., Karavasiou, A. I., & Falagas, M. E. (2005). Worldwide trends in quantity and quality of published articles in the field of infectious diseases. BMC Infectious Diseases, 5, 16.CrossRefGoogle Scholar
  4. Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27, 55–71.CrossRefGoogle Scholar
  5. Easley, D., & Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  6. Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social Networks, 1, 215–239.CrossRefGoogle Scholar
  7. Garg, K. C., Kumar, S., Madhavi, Y., & Bahl, M. (2009). Bibliometrics of global malaria vaccine research. Health Information and Libraries Journal, 26, 22–31.CrossRefGoogle Scholar
  8. Leydesdorff, L. (2007). Betweenness centrality as an indicator of the interdisciplinarity of scientific journals. Journal of the American Society for Information Science and Technology, 58, 1303–1319.CrossRefGoogle Scholar
  9. Patra, S. K., & Chand, P. (2007). HIV/AIDS research in India: A bibliometric study. Library and Information Science Research, 29, 124–134.CrossRefGoogle Scholar
  10. Ramos, J. M., Gutierrez, F., Masia, M., & Martin-Hidalgo, A. (2004). Publication of European Union research on infectious diseases (1991–2001): A bibliometric evaluation. European Journal of Clinical Microbiology and Infectious Diseases, 23, 180–184.CrossRefGoogle Scholar
  11. Ramos, J. M., Masia, M., Padilla, S., & Gutierrez, F. (2009). A bibliometric overview of infectious diseases research in European countries (2002–2007). European Journal of Clinical Microbiology and Infectious Diseases, 28, 713–716.CrossRefGoogle Scholar
  12. Ramos, J. M., Padilla, S., Masia, M., & Gutierrez, F. (2008). A bibliometric analysis of tuberculosis research indexed in PubMed, 1997–2006. International Journal of Tuberculosis and Lung Disease, 12, 1461–1468.Google Scholar
  13. Romo-Fernández, L. M., Guerrero-Bote, V. P., & Moya-Anegón, F. (2013). Co-word based thematic analysis of renewable energy (1990–2010). Scientometrics, 97(3), 743–765.Google Scholar
  14. Scott, J. (2000). Social network analysis: A handbook. Beverly Hills: SAGE Publications.Google Scholar
  15. Takahashi-Omoe, H., & Omoe, K. (2012). Worldwide trends in infectious disease research revealed by a new bibliometric method. In P. K. Roy (Ed.), Insight and control of infectious disease in global scenario. Croatia: Intech Open Science Publishers.Google Scholar
  16. Taylor, L. H., Latham, S. M., & Woolhouse, M. E. J. (2001). Risk factors for human disease emergence. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences, 356, 983–989.CrossRefGoogle Scholar
  17. Uthman, O. A. (2008). HIV/AIDS in Nigeria: A bibliometric analysis. BMC Infectious Diseases, 8(1), 19.Google Scholar
  18. van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84, 523–538.CrossRefGoogle Scholar
  19. van Eck, N. J. & Waltman, L. 2013. VOSviewer manual [Online]. Accessed 26 Nov 2013.
  20. Waltman, L., van Eck, N. J., & Noyons, E. C. M. (2010). A unified approach to mapping and clustering of bibliometric networks. Journal of Informetrics, 4, 629–635.CrossRefGoogle Scholar
  21. WHO. 1959. Zoonoses. World Health Organization Technical Report Series, Geneva.Google Scholar
  22. WHO. 2013a. Disease outbreak news (DONs) [Online]. Accessed 26 Nov 2013.
  23. WHO. 2013b. Zoonoses and the human–animal–ecosystems interface [Online]. Accessed 26 Nov 2013.

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2015

Authors and Affiliations

  • Liaquat Hossain
    • 1
    • 2
  • Faezeh Karimi
    • 2
  • Rolf T. Wigand
    • 3
  • John W. Crawford
    • 4
  1. 1.Information Management, Division of Information and Technology StudiesUniversity of Hong KongPokfulamHong Kong
  2. 2.Center for Complex Systems ResearchUniversity of SydneySydneyAustralia
  3. 3.Information ScienceUniversity of ArkansasLittle RockUSA
  4. 4.Sustainable Systems ResearchRothamsted ResearchHarpendenUK

Personalised recommendations