Cori, A., Donnelly, C. A., Dorigatti, I., Ferguson, N. M., Fraser, C., Garske, T., Jombart, T., Nedjati-Gilani, G., Nouvellet, P., Riley, S., Van Kerkhove, M. D., Mills, H. L., & Blake, I. M. (2017). Key Data for Outbreak Evaluation: Building on the Ebola Experience. Philosophical Transactions of the Royal Society B: Biological Sciences, 372, Article ID: 20160371.
https://doi.org/10.1098/rstb.2016.0371

has been cited by the following article:

• TITLE: Inter-Organizational Data Sharing during COVID-19 Health Emergency: Lesson Learnt from Veneto and Lombardy Regions

  AUTHORS: Valeria M. Urbano, Giovanni Azzone, Marika Arena

  KEYWORDS: Data Sharing, COVID-19, Public Health, Inter-Organizational Data Sharing, Bio-Surveillance

  JOURNAL NAME: Journal of Service Science and Management, Vol.15 No.6, December 27, 2022

  ABSTRACT: The importance of data driven decision making in evidence based public health has significantly risen with the aim of answering today’s challenges and of providing new sustainable solutions. However, the advent of big data and data sciences techniques poses new challenges in terms of data sharing as multiple sources of data imply multiple stakeholders involved. Although the potential impact of data sharing among public organizations is widespread, several initiatives of cross-organizations information sharing fail. While revealing the necessity of cooperation between organizations to cope with the health emergency, the current pandemic COVID-19 has shed light on the complexity of inter-organizational data practices. In the last few years, several attempts have been made by the authors to identify factors affecting information sharing in the public sector. The framework developed by Yang and Maxwell (2011) summarizes the main insights from existing literature, providing a comprehensive overview of factors impacting data sharing initiatives and classifying them into technological, organizational and political factors. The aim of this research study is to investigate factors that hinder data sharing initiatives put in place to deal with the health emergency. To this end, we rely on multiple case studies. The Lombardy and Veneto regions were selected because the epidemic was initially concentrated in these two regions. The first hotspots of COVID-19 cases were identified in two geographical areas located in the Lombardy and Veneto regions, and stringent measures were introduced to contain the epidemic. The analysis of the case study is used to gain concrete, in-depth knowledge about inter-organizational data sharing in the context of epidemics. The findings of this research study confirm some of the relationships between technological and organizational factors and the success of the data sharing initiatives in the context of an emergency, as well as extend the proposed framework exploring further sources of complexity.