文章基本信息
- 标题：Antibiotic resistance and R&D failure: The need for near real-time disaster research
- 本地全文：下载
- 作者：Chris W. Callaghan ; Oren Dayan
- 期刊名称：Jàmbá : Journal of Disaster Risk Studies
- 印刷版ISSN：1996-1421
- 电子版ISSN：2072-845X
- 出版年度：2020
- 卷号：12
- 期号：1
- 页码：795-803
- DOI：10.4102/jamba.v12i1.795
- 出版社：AOSIS
- 摘要：Increasing antibiotic resistance across the world seems to reflect a failure of research and development (R&D) to keep pace with societally important disaster risks. This article uses the example of steadily increasing antibiotic resistance to question whether current R&D systems are able to timeously deal with certain societally important research problems. A review and discussion of new theoretical developments is offered, to suggest how novel technologies might be applied to improve the efficiency and effectiveness of health-related disaster risk research. This article seeks to make a conceptual contribution through a critical review and synthesis of novel theory. Theoretical propositions are derived from conceptual analysis. Four key challenges are related to the derived propositions, to derive guidelines for how the disaster risk management process can be supplemented to improve its near real-time research capability. The theoretical propositions derived here relate to certain overarching challenges facing disaster risk research. The theoretical arguments made in this article seek to offer a heuristic perspective that may be useful to those seeking to apply novel technologies in disaster risk research to address societally important research problems such as antibiotic resistance. This research identifies evidence of the failure of the contemporary research system to solve problems like antibiotic resistance. On the basis of a synthesis of novel literature and theory, conclusions suggest certain useful avenues for the improvement of the research process. Urgency is recommended because of mounting societal costs of slow research responses to societal problems.© 2020. The Authors.
- 关键词：disaster; disaster risk research; antibiotic resistance; innovation; R& D; probabilistic innovation theory.
