The Sendai Framework: Using data to meet health-based indicators

The Sendai Framework for Disaster Risk Reduction 2015-2030 was agreed in 2015.  Since then the global disaster risk reduction community has been working to implement the framework using the now UN General Assembly adopted global targets and indicators building on the success of Sendai’s predecessor, the Hyogo Framework.

Recognising that health resilience is promoted throughout the Sendai Framework, the role of health professionals continues to play a key role in disaster risk reduction (DRR).  Indeed several of the seven global targets within the framework relate directly to health, including:

(a) Substantially reduce global disaster mortality by 2030, aiming to lower the average per 100,000 global mortality rate in the decade 2020–2030 compared to the period 2005–2015;

(b) Substantially reduce the number of affected people globally by 2030, aiming to lower the average global figure per 100,000 in the decade 2020–2030 compared to the period 2005–2015;

In order to meet these ambitious targets, DRR practitioners must use a variety of methods to ensure effective monitoring and measurement of their programmes.  One such tool at their disposal is the effective collection and analysis of data collected before, during and after disaster events. 

The importance of data (including meta-data or ‘big-data’) has been recognised, and an open-ended intergovernmental expert working group was formed with stakeholders from Member States, NGOs, private sector and science and technology. The working group was tasked with defining the indicators and methods that would allow the measurement of the Framework's seven targets and its main goal - the substantial reduction of risk and losses due to disasters.

When deciding how to measure the impacts of health in disasters and how best to reduce mortality and those affected, a number of issues present themselves, namely:

• Temporality – deaths caused by a disaster can happen days, week or months after the ‘disaster’ has been declared over. In terms of data collection and analysis, how can healthcare professionals collect data that accurately attributes cause of death?  For historical events, does the data collected reflect the true cause of death and is it useable to form a baseline to measure future events?
• Thresholds – How many deaths or injuries constitute a disaster?  Some databases only include events with deaths greater than 10 people.  In this case, are we missing smaller scale disasters?  Are the causes of deaths being recorded accurately (see first point) and are disasters with deaths greater than 10 people being missed because of this?
• Terminology – The terminology behind many disasters remains debated.  What constitutes an affected person?  Is it someone who has suffered a direct loss caused by the disaster (e.g. suffered a broken leg due to a wall falling on them during an earthquake), or should we include those impacted indirectly (e.g. someone suffering from post-traumatic stress disorder and as such, are unable to work).  Data collection must recognise these issues to accurately measure the impact of different programmes.

A greater understanding of how these issues impact on data collection within disaster risk reduction is vitally important.  It impacts on how the data is analysed, the types of research and programmes which are funded, and the type of action taken on the ground by medics and other health professionals.  To that end, work has been ongoing on a number of projects that aim to build the DRR communities understanding of data and its uses within a health context, namely:

• The United Nations Office for Disaster Risk Reduction (UNISDR) are developing guidance on how countries can measure, analyse and most effectively utilise data to reduce risks caused by disaster events.
• A paper on the subject of health, indicators and the Sendai Framework
• The Institute of Health Metrics and Evaluation is providing analysis and research using the Global Burden of Disease to measure a population’s health and how it varies by different regions, socio-economic status, or ethnic groups in their country and what possible impacts natural or technological hazards might have.

Given the strong call throughout the Global Platform for Disaster Risk Reduction in Cancun, Mexico (22 – 26 May 2017) for robust and transparent data collection and analysis, we’re certain that having the correct terminology and methods to collect data accurately and uniformly around the world will mean a more coordinated and focused health response.

Kevin Blanchard is a Senior Environmental Scientist in Global Disaster Risk Reduction at Public Health England, where he supports its work on global disaster risk reduction research, policy and implementation. His focus is on advising and assisting with the development of policy, research and strategy at national and international levels to ensure the promotion of science and technology and public health within disaster risk reduction.

He is also Communication Coordinator for the Gender and Disaster Network (www.gdnonline.org), an educational and advocacy project initiated by women and men interested in gender relations in disaster contexts.