article

Managing Emerging Infectious Diseases with Information Systems: Reconceptualizing Outbreak Management Through the Lens of Loose Coupling

Authors:

Susan A. Brown,

Paul Jen-Hwa Hu,

Chwan-Chuen King,

Hsinchun ChenAuthors Info & Claims

Information Systems Research, Volume 22, Issue 3

Pages 447 - 468

https://doi.org/10.1287/isre.1110.0376

Published: 01 September 2011 Publication History

Abstract

Increasing global connectivity makes emerging infectious diseases (EID) more threatening than ever before. Various information systems (IS) projects have been undertaken to enhance public health capacity for detecting EID in a timely manner and disseminating important public health information to concerned parties. While those initiatives seemed to offer promising solutions, public health researchers and practitioners raised concerns about their overall effectiveness. In this paper, we argue that the concerns about current public health IS projects are partially rooted in the lack of a comprehensive framework that captures the complexity of EID management to inform and evaluate the development of public health IS. We leverage loose coupling to analyze news coverage and contact tracing data from 479 patients associated with the severe acute respiratory syndrome (SARS) outbreak in Taiwan. From this analysis, we develop a framework for outbreak management. Our proposed framework identifies two types of causal circles---coupling and decoupling circles---between the central public health administration and the local capacity for detecting unusual patient cases. These two circles are triggered by important information-centric activities in public health practices and can have significant influence on the effectiveness of EID management. We derive seven design guidelines from the framework and our analysis of the SARS outbreak in Taiwan to inform the development of public health IS. We leverage the guidelines to evaluate current public health initiatives. By doing so, we identify limitations of existing public health IS, highlight the direction future development should consider, and discuss implications for research and public health policy.

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cover image Information Systems Research

Information Systems Research Volume 22, Issue 3

09 2011

266 pages

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INFORMS

Linthicum, MD, United States

Publication History

Published: 01 September 2011

Received: 09 February 2009

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Cited By

Ketter WSchroer KValogianni K(2023)Information Systems Research for Smart Sustainable MobilityInformation Systems Research10.1287/isre.2022.116734:3(1045-1065)Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1287/isre.2022.1167
Marin EGuo RShakarian P(2020)Measuring Time-Constrained Influence to Predict Adoption in Online Social NetworksACM Transactions on Social Computing10.1145/33727853:3(1-26)Online publication date: 31-May-2020
https://dl.acm.org/doi/10.1145/3372785
Hassan Zadeh AZolbanin HSharda RDelen D(2019)Social Media for Nowcasting Flu ActivityInformation Systems Frontiers10.1007/s10796-018-9893-021:4(743-760)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s10796-018-9893-0
Barrett MDavidson EPrabhu JVargo S(2015)Service innovation in the digital ageMIS Quarterly10.25300/MISQ/2015/39:1.0339:1(135-154)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.25300/MISQ/2015/39%3A1.03
Zhou FJiao JLei B(2015)A linear threshold-hurdle model for product adoption prediction incorporating social network effectsInformation Sciences: an International Journal10.1016/j.ins.2015.02.027307:C(95-109)Online publication date: 20-Jun-2015
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