Could the COVID-19 Open Data Strategy be Adapted to Address Other Global Health Threats Effectively A Bibliometric Analysis of the Literature

Authors

  • Federico Monaco Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Leopoldo Sarli Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Evelina Ceccato Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Paola Masuzzo Institute for Globally Distributed Open Research and Education (IGDORE), 9042 Ghent, Belgium
  • Rosangela De Simone Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Elisa Minardi Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Paolo Giorgi Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Arianna Ghezzo Department of Medicine and Surgery, University of Parma, 43125 Parma PR, Italy
  • Antonio Bonacaro School of Health and Sports Sciences, University of Suffolk, Ipswich, IP4 1QJ, United Kingdom

DOI:

https://doi.org/10.31674/mjn.2023.v15i01.017

Abstract

Background: In the wake of the pandemic, open data has made possible mapping, evaluating, and monitoring the COVID-19 rate of transmission at a local, national, and global level. Such a strategy follows WHO's efforts to provide updated and useful information in order to tackle public health issues and provide resources for research in the health sciences. Methods: A bibliometric analysis of the literature was conducted. Results: Published papers on open data impact on infection risk dramatically increased in the observed period of time (2018–21). Furthermore, it becomes apparent that, while COVID-19-related literature led to such a "critical mass" of publications in 2018–21, papers about open data, but antimicrobial resistance and healthcare associated infections are very few or absent. Conclusion: An open data strategy is beneficial in tracking, studying, and adopting measures not only for Covid-19 but also for providing nurses and allied healthcare professionals with firm evidences upon which to develop health plans.

Keywords:

Antimicrobial Resistance, COVID-19, Healthcare Associated Infection, Infection Control, Open Data

Downloads

Download data is not yet available.

References

Allegranzi, B., Nejad, S. B., Combescure, C., Graafmans, W., Attar, H., Donaldson, L., & Pittet, D. (2011). Burden of Endemic Health-Care-Associated Infection in Developing Countries: Systematic Review and Meta-Analysis. The Lancet, 377(9761), 228-241. https://doi.org/10.1016/s0140-6736(10)61458-4

Al-Tawfiq, J. A., & Tambyah, P. A. (2014). Healthcare Associated Infections (HAI) Perspectives. Journal of Infection and Public Health, 7(4), 339–344. https://doi.org/10.1016/j.jiph.2014.04.003

Althaus, C. (2020). Estimating Case Fatality Ratio of COVID-19 from Observed Cases Outside China. https://github.com/calthaus/ncov-cfr . Accessed on February 5th, 2023.

Anderson, M., Schulze, K., Cassini, A., Plachouras, D., & Mossialos, E. (2019). A Governance Framework for Development and Assessment of National Action Plans on Antimicrobial Resistance. The Lancet Infectious Diseases, 19(11), e371-e384. https://doi.org/10.1016/S1473-3099(19)30415-3

Antimicrobial Resistance Collaborators. (2022). Global Burden of Bacterial Antimicrobial Resistance in 2019: A Systematic Analysis. The Lancet, 399(10325), 629–655. https://doi.org/10.1016/S0140-6736(21)02724-0

Besançon, L., Peiffer-Smadja, N., Segalas, C., Jiang, H., Masuzzo, P., Smout, C., ... & Leyrat, C. (2021). Open Science Saves Lives: Lessons from the COVID-19 Pandemic. BMC Medical Research Methodology, 21(1), 1-18. https://doi.org/10.1186/s12874-021-01304-y

Blake, M., Murray, R. C., Williams, J., Gara, J., Belros, D., & Choudhury, S. (2022). A Role for the Library in Public Research: The Global COVID-19 Dashboard. portal: Libraries and the Academy, 22(1), 7-25. https://doi.org/10.1353/pla.2022.0007

Cassini, A., Plachouras, D., Eckmanns, T., Abu Sin, M., Blank, H. P., Ducomble, T., ... & Suetens, C. (2016). Burden of Six Healthcare-Associated Infections on European Population Health: Estimating Incidence-Based Disability-Adjusted Life Years Through a Population Prevalence-Based Modelling Study. PLoS Medicine, 13(10), e1002150. https://doi.org/10.1371/journal.pmed.1002150

CDC (Centers for Disease Control and Prevention). (2021). CDC Antibiotic Resistance Threats in the United States, 2019. https://www.cdc.gov/drugresistance/biggest-threats.html. Accessed on February 1st, 2023.

Chretien, J. P., Rivers, C. M., & Johansson, M. A. (2016). Make Data Sharing Routine to Prepare for Public Health Emergencies. PLoS Medicine, 13(8), e1002109. https://doi.org/10.1371/journal.pmed.1002109

Christenson, E. C., Cronk, R., Atkinson, H., Bhatt, A., Berdiel, E., Cawley, M., ... & Bartram, J. (2021). Evidence Map and Systematic Review of Disinfection Efficacy on Environmental Surfaces in Healthcare Facilities. International Journal of Environmental Research and Public Health, 18(21), 11100. https://doi.org/10.3390/ijerph182111100

de Jesus, J.G., Sacchi, C., Claro, I., Salles, F., Manulli, E., da Silva, D., de Paiva, T.M., Pinho, M., Afonso, A.M.S., Mathias, A., Prado, L., de Carvalho Avelino, A.L., de Oliveira Santos, K.C., Romero, F., dos Santos, F., Gonçalves, C., Timenetsky, M.C., Quick, J., Pybus, O.G.,Faria, N.R. (2020). First Cases of Coronavirus Disease (COVID-19) in Brazil, South America Virological. https://virological.org/t/first-cases-of-coronavirus-disease-covid-19-in-brazil-south-america-2-genomes-3rd-march-2020/409 . Accessed on January 20th, 2023.

Desai, A. N., Kraemer, M. U., Bhatia, S., Cori, A., Nouvellet, P., Herringer, M., ... & Lassmann, B. (2019). Real-Time Epidemic Forecasting: Challenges and Opportunities. Health Security, 17(4), 268-275. https://doi.org/10.1089/hs.2019.0022

Dong, E., Du, H., & Gardner, L. (2020). An Interactive Web-Based Dashboard to Track COVID-19 in Real Time. The Lancet Infectious Diseases, 20(5), 533-534. https://doi.org/10.1016/s1473-3099(20)30120-1

Gkiouras, K., Nigdelis, M. P., Grammatikopoulou, M. G., & Goulis, D. G. (2020). Tracing Open Data in Emergencies: The Case of the COVID‐19 Pandemic. European Journal of Clinical Investigation, 50(9), e13323. https://doi.org/10.1111/eci.13323

Grantz, K., Metcalf, C. J. E., & Lessler, J. (2020). Dispersion vs. Control. https://hopkinsidd.github.io/nCoV-Sandbox/DispersionExploration.html. Accessed on January 22nd, 2023.

Haque, M., Sartelli, M., McKimm, J., & Bakar, M. A. (2018). Health Care-Associated Infections– An Overview. Infection and Drug Resistance, 11, 2321–2333. https://doi.org/10.2147/idr.s177247

Kennelly, B., O'Callaghan, M., Coughlan, D., Cullinan, J., Doherty, E., Glynn, L., ... & Queally, M. (2020). The COVID-19 Pandemic in Ireland: An Overview of The Health Service and Economic Policy Response. Health Policy and Technology, 9(4), 419-429. https://doi.org/10.1016/j.hlpt.2020.08.021

Kraemer, M. U., Yang, C. H., Gutierrez, B., Wu, C. H., Klein, B., Pigott, D. M., ... & Scarpino, S. V. (2020). The Effect of Human Mobility and Control Measures on The Covid-19 Epidemic in China. Science, 368(6490), 493-497. https://doi.org/10.1126/science.abb4218

Kucharski, A. J., Funk, S., & Eggo, R. M. (2020). The COVID-19 Response Illustrates that Traditional Academic Reward Structures and Metrics do not Reflect Crucial Contributions to Modern Science. PLoS Biology, 18(10), e3000913. https://doi.org/10.1371/journal.pbio.3000913

Laxminarayan, R. (2022). The Overlooked Pandemic of Antimicrobial Resistance. The Lancet, 399(10325), 606-607. https://doi.org/10.1016/s0140-6736(22)00087-3

Laxminarayan, R., Duse, A., Wattal, C., Zaidi, A. K., Wertheim, H. F., Sumpradit, N., ... & Cars, O. (2013). Antibiotic Resistance—The Need for Global Solutions. The Lancet infectious diseases, 13(12), 1057-1098. https://doi.org/10.1016/s1473-3099(13)70318-9

Li, R., von Isenburg, M., Levenstein, M., Neumann, S., Wood, J., & Sim, I. (2021). COVID-19 Trials: Declarations of Data Sharing Intentions at Trial Registration and at Publication. Trials, 22, 1- 5. https://doi.org/10.1186/s13063-021-05104-z

Lucas-Dominguez, R., Alonso-Arroyo, A., Vidal-Infer, A., & Aleixandre-Benavent, R. (2021). The Sharing of Research Data Facing The COVID-19 Pandemic. Scientometrics, 126(6), 4975-4990. https://doi.org/10.1007/s11192-021-03971-6

Marchetti, A., & Rossiter, R. (2013). Economic Burden of Healthcare-Associated Infection in US Acute Care Hospitals: Societal Perspective. Journal of Medical Economics, 16(12), 1399-1404. https://doi.org/10.3111/13696998.2013.842922

Masuzzo, P. (2022, April 29). The Data I Would Like: How I Would Like Them. Zenodus. https://doi.org/10.5281/zenodo.6503962

Modjarrad, K., Moorthy, V. S., Millett, P., Gsell, P. S., Roth, C., & Kieny, M. P. (2016). Developing Global Norms for Sharing Data and Results During Public Health Emergencies. PLoS Medicine, 13(1), e1001935. https://doi.org/10.1371/journal.pmed.1001935

Moran, K. R., Fairchild, G., Generous, N., Hickmann, K., Osthus, D., Priedhorsky, R., ... & Del Valle, S. Y. (2016). Epidemic Forecasting is Messier than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast. The Journal of Infectious Diseases, 214(suppl_4), S404-S408. https://doi.org/10.1093/infdis/jiw375

Morgan, O. (2019). How Decision Makers can Use Quantitative Approaches to Guide Outbreak Responses. Philosophical Transactions of the Royal Society B, 374(1776), 20180365. https://doi.org/10.1098/rstb.2018.0365

Pecoraro, F., & Luzi, D. (2021). Open Data Resources on COVID-19 in Six European Countries: Issues and Opportunities. International Journal of Environmental Research and Public Health, 18(19), 10496. https://doi.org/10.3390/ijerph181910496

Peters, A., Schmid, M. N., Parneix, P., Lebowitz, D., De Kraker, M., Sauser, J., ... & Pittet, D. (2022). Impact of Environmental Hygiene Interventions on Healthcare-Associated Infections and Patient Colonization: A Systematic Review. Antimicrobial Resistance & Infection Control, 11(1), 38. https://doi.org/10.1186/s13756-022-01075-1

Prestinaci, F., Pezzotti, P., & Pantosti, A. (2015). Antimicrobial Resistance: A Global Multifaceted Phenomenon. Pathogens and Global Health, 109(7), 309-318. https://doi.org/10.1179/2047773215y.0000000030

Priyantini, D., Irawandi, D., & Poddar, S. (2022). Psychological Impact of Coping Strategies and Nurse Performance During the Covid-19 Pandemic at Rspal Dr. Ramelan Surabaya. The Malaysian Journal of Nursing (MJN), 14(2), 109-116. https://doi.org/10.31674/mjn.2022.v14i02.018

Sachdeva, H., Benusic, M., Ota, S., Stuart, R., Maclachlan, J., Dubey, V., & Andonov, A. (2019). Open Science/Open Data: Community Outbreak of Hepatitis a Disproportionately Affecting Men Who Have Sex with Men in Toronto, Canada, January 2017–November 2018. Canada Communicable Disease Report, 45(10), 262. https://10.14745/ccdr.v45i10a03. Accessed on February 3rd, 2023.

Salzo, A., Ripabelli, G., Sammarco, M. L., Mariano, A., Niro, C., & Tamburro, M. (2021). Healthcare-Associated Infections and Antibiotics Consumption: A Comparison of Point Prevalence Studies and Intervention Strategies. Hospital Topics, 99(3), 140-150. https://doi.org/10.1080/00185868.2021.1902758

Theodi. (2022). How to Publish Open Data: A List of Advice and Tools. The Open Data Institute. https://github.com/theodi/data-publish-list. Accessed on January 13th, 2023.

Tung, L.T. & Thanh, P. T. (2020). Survey Data on Government Risk Communication and Citizen Compliance during the COVID-19 Pandemic in Vietnam. Data in Brief, 33, 106348. https://doi.org/10.1016/j.dib.2020.106348

Uohara, M. Y., Weinstein, J. N., & Rhew, D. C. (2020). The Essential Role of Technology in the Public Health Battle against COVID-19. Population Health Management, 23(5), 361-367. https://doi.org/10.1089/pop.2020.0187

World Health Organization (2020). Who Coronavirus Disease (COVID-19) Dashboard: World Health Organization, 2020. WHO Coronavirus Disease (COVID-19) Dashboard. https://covid19.who.int/ . Accessed on January 27th, 2023.

World Health Organization (2022). Global Report on Infection Prevention and Control. World Health Organization. https://www.who.int/publications/i/item/9789240051164 . Accessed on January 10th, 2023.

Xu, B., & Kraemer, M. U. (2020). Open Access Epidemiological Data from the COVID-19 Outbreak. The Lancet Infectious Diseases, 20(5), 534. https://doi.org/10.1016/s1473- 3099(20)30119-5

Xu, B., Gutierrez, B., Mekaru, S., Sewalk, K., Goodwin, L., Loskill, A., ... & Kraemer, M. U. (2020). Epidemiological Data from the COVID-19 Outbreak, Real-Time Case Information. Scientific Data, 7(1), 106. https://doi.org/10.1038/s41597-020-0448-0

Zimlichman, E., Henderson, D., Tamir, O., Franz, C., Song, P., Yamin, C. K., ... & Bates, D. W. (2013). Health Care–Associated Infections: A Meta-Analysis of Costs and Financial Impact on The US Health Care System. JAMA Internal Medicine, 173(22), 2039-2046. https://doi.org/10.1001/jamainternmed.2013.9763

Published

15-07-2023

How to Cite

Monaco, F., Sarli, L., Ceccato, E., Masuzzo, P., De Simone, R., Minardi, E., Giorgi, P., Ghezzo, A., & Bonacaro, A. (2023). Could the COVID-19 Open Data Strategy be Adapted to Address Other Global Health Threats Effectively A Bibliometric Analysis of the Literature. The Malaysian Journal of Nursing (MJN), 15(1), 152-160. https://doi.org/10.31674/mjn.2023.v15i01.017

Metrics