UCL Institute for Risk and Disaster Reduction


Research Objectives

Natural, technological, socio-economic and intentional disasters are of great concern to humanity as their impact is increasing due to climate change, population growth and globalization.

Most importantly, vulnerabilities are increasing as a result of poverty, marginalization, lack of rights, poor governance, urbanization, land-use change and stress upon ecosystems.

Key Research Questions

Given the need to quantify and reduce the risk of disasters, some key research questions are:

  • How can we conceptualize and model the changing rate of natural, environmental and health catastrophes to reduce uncertainty?
  • What will be the effects of environmental change?
  • What scientific, technological and medical advances can reduce the impact of disasters?
  • How should society organize itself in response to risk, in order to increase the resilience of vulnerable communities and manage disasters more effectively?
  • How do we transfer scientific and technical knowledge to those who need it?
  • How can we better understand vulnerability and exposure to disaster risk in complex human communities around the world?
  • What are our legal or ethical responsibilities?

There is increasing evidence that disaster response planning and mitigation must take account of 'fat-tailed' distributions: in other words, high-magnitude events seem likely to be more common and devastating than was previously expected. Moreover, climate change may well worsen this situation with respect to meteorological and health hazards. Preparation for such contingencies is expensive, complex and challenging. Moreover, standard hazard assessments can be grossly misleading. Hence it may well be that vulnerability has been seriously underestimated in the world's principal hazard zones. These include a serious risk of major earthquake casualties and damage in mega-cities such as Tokyo and Tehran, exceptional cyclone hazards in Bangladesh and the Caribbean, flood hazards in Thailand and South Asia, drought in the Horn of Africa and Sub-Saharan countries, and many other cases of extreme risk. Finally, the earthquake, tsunami and nuclear radiation release in Japan in March 2011 has refocused attention upon cascading and multiple hazards.

It may be argued that slow onset disease causes more deaths, but sudden onset natural catastrophes can bring economic disaster as well as mortality. In the case of the 2010 earthquake in Haiti, losses exceeded annual GDP. The disruption and damage may take a generation to overcome, especially if economic development and healthcare are both inadequate. After a disaster, recovery can be prolonged by inadequate understanding of what exactly is needed in order to rebuild complex social and productive systems. Moreover, in recent times the effectiveness of the international relief system has repeatedly been called into question. Hence, there is considerable potential for research and teaching to contribute to better management of disasters and disaster risk.

There is an urgent need to establish a multi-hazard, cross-disciplinary theoretical framework in which research into disasters can make progress, based on understanding them as complex non-linear systems, which are tractable with the tools of modern physics, mathematics, statistics and health and social research. This can be done, as was demonstrated by successful prediction of the location and magnitude of an earthquake in Sumatra in 2005, warning against a cyclone in Bangladesh in 2007 and social organization of preparedness in Sumatra in 2009, all of which saved thousands of lives. Our new understanding offers the opportunity to use laboratory and numerical experiments, satellite-based observation and social survey to make significant progress, providing this is pursued in a problem-based, interdisciplinary manner. Advances in statistical prediction, engineering, development planning, health maintenance and the social and political understanding of disasters, suggest that the goal of increased preparedness is eminently achievable.