The Sendai Framework for Disaster Risk Reduction and Its Indicators—Where Does Health Fit in?

Rishma Maini*, Lorcan Clarke, Kevin Blanchard, Virginia Murray

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

55 Citations (Scopus)

Abstract

The Sendai Framework for Disaster Risk Reduction 2015–2030 recognizes the strong connection between health and disasters and promotes the concept of health resilience throughout. Several of the seven global targets stated in the Sendai Framework are directly related to health in terms of reducing disaster mortality, the number of affected people, disaster damage to critical infrastructure, and disruption of basic services such as health facilities. The Sendai Framework also maintains close coordination with other United Nations landmark agreements relevant to health such as the Sustainable Development Goals. However, the measurement of health-related indicators is challenging. Issues arise, for example, in linking deaths to disasters because of the complex interplay between exposure, risk, vulnerability, and hazards. The lack of a universal classification of disasters also means that recording of health data in disasters is not standardized. Developing the guidelines to enable data on the indicators to be collected and reported to support the Sendai targets requires detailed thinking, time, and consultation with a diverse range of stakeholders. Strong collaboration and partnership will be vital to achieving success.

Original languageEnglish
Pages (from-to)150-155
Number of pages6
JournalInternational Journal of Disaster Risk Science
Volume8
Issue number2
DOIs
Publication statusPublished - 1 Jun 2017

Bibliographical note

Publisher Copyright:
© 2017, The Author(s).

Keywords

  • Disaster risk reduction
  • Global health targets
  • Health indicators
  • Sendai Framework

Fingerprint

Dive into the research topics of 'The Sendai Framework for Disaster Risk Reduction and Its Indicators—Where Does Health Fit in?'. Together they form a unique fingerprint.

Cite this