Forecasting Database Usage During the Height of COVID-19
PDF

How to Cite

Sharpe, C., & Evans, D. (2022). Forecasting Database Usage During the Height of COVID-19. International Journal of Librarianship, 7(1), 21–29. https://doi.org/10.23974/ijol.2022.vol7.1.217
Received 2021-12-15
Accepted 2022-01-11
Published 2022-07-18

Abstract

As with other catastrophic events, the COVID-19 pandemic disrupted higher education and library services. The authors examine the effect of the COVID-19 pandemic on usage of health databases in 2020. They use time series analysis to create a forecast based on previous years’ activities, and then compare it with actual database usage during the pandemic. The results show an initial increase in searches for the first full month of the pandemic, but then match the expected forecast data and decrease during summer and early fall months. The authors conclude that time series analysis is a useful tool for understanding the impact of events and for planning purposes.

https://doi.org/10.23974/ijol.2022.vol7.1.217
PDF

References

Ahmadi, M., Dileepan, P., Murgai, S, & Roth, W. (2008). An exponential smoothing model for predicting traffic in the library and at the reference desk. The Bottom Line, 21(2) 37-48. https://doi.org/10.1108/08880450810898283

Aziz, A., Aamer, S., Khan, A. M., Sabqat, M., Sohail, M., & Majeed, F. (2020). A bumpy road to online teaching: Impact of COVID-19 on medical education. Annals of King Edward Medical University, 26, 181-186. https://annalskemu.org/journal/index.php/annals/article/view/3635

Cleland, J., Tan, E. C. P., Tham, K. Y., & Low-Beer, N. (2020). How Covid-19 opened up questions of sociomateriality in healthcare education. Advances in Health Sciences Education, 25(2), 479-482. http://dx.doi.org/10.1007/s10459-020-09968-9

Coombs, K. A. (2005). Lessons learned from analyzing library database usage data. Library Hi Tech, 23(4), 598-609. http://dx.doi.org/10.1108/07378830510636373

Emans, S. J., Ford, C. A., Irwin, C. E. J., Richardson, L. P., Sherer, S., Sieving, R. E., & Simpson, T. (2020). Early COVID-19 impact on adolescent health and medicine programs in the United States: LEAH program leadership reflections. Journal of Adolescent Health, 67(1), 11-15. https://doi.org/10.1016/j.jadohealth.2020.04.010

Featherstone, R. M., Boldt, R. G., Torabi, N., & Konrad, S. L. (2012). Provision of pandemic disease information by health sciences librarians: A multisite comparative case series. Journal of the Medical Library Association, 100(2), 104-112. https://dx.doi.org/10.3163%2F1536-5050.100.2.008

Gaus, J. M. (1947). Reflections on Public Administration. University of Alabama Press.

Gul, S., Ahmad Shah, T., & Ahmad, S. (2014). Digital user behaviour of academicians in a conflict zone, Kashmir: Comparing log analysis of electronic resources in the times of conflict and peace. Program: Electronic Library and Information, 48(2), 127-139. https://doi.org/10.1108/PROG-06-2013-0026

Jeong, S. H., & Kim, S. (2010) Core resources on time series analysis for academic libraries: A selected, annotated bibliography. Proceedings of the Charleston Library Conference, 229-238. http://dx.doi.org/10.5703/1288284314839

Khalil, R., Mansour, A. E., Fadda, W. A., Almisnid, K., Aldamegh, M., Al-Nafeesah, A., Alkhalifah, A., & Al-Wutayd, O. (2020). The sudden transition to synchronized online learning during the COVID-19 pandemic in Saudi Arabia: A qualitative study exploring medical students' perspectives. BMC Medical Education, 20(1), 285. https://doi.org/10.1186/s12909-020-02208-z

Lwoga, E. T., & Sukums, F. (2018). Health sciences faculty usage behaviour of electronic resources and their information literacy practices. Global Knowledge, Memory and Communication, 67(1/2), 2-18. https://doi.org/10.1108/GKMC-06-2017-0054

McGrath, W. E. (1996). Periodicity in academic library circulation: A spectral analysis. Journal of the American Society for Information Science, 47(2), 136-145. https://doi.org/10.1002/(SICI)1097-4571(199602)47:2<136::AID-ASI5>3.0.CO;2-%23

Murgai, S. R., & Ahmadi, M. (2007). A multiple regression model for predicting reference desk staffing requirements. The Bottom Line, 20(2), 69-76. https://doi.org/10.1108/08880450710773002

Singh, J. A., Bandewar, S. V. S., & Bukusi, E. A. (2020). The impact of the COVID-19 pandemic response on other health research. Bulletin of the World Health Organization, 98(9), 625-631. http://doi.org/10.2471/BLT.20.257485

Spurlock Jr., D. R. (2020). Scholarship during a pandemic: Secondary data analysis. Journal of Nursing Education, 59(5), 245-247. https://doi.org/10.3928/01484834-20200422-02

Tenopir, C., & Read, E. J. (2000). Database use patterns in public libraries. Reference & User Services Quarterly, 40(1), 39-52. https://www.jstor.org/stable/20863899

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2022 International Journal of Librarianship

Downloads

Download data is not yet available.