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Understanding Compound, Interconnected, Interacting, and Cascading Risks: A Holistic Framework


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In recent years, there has been a gradual increase in research literature on the challenges of interconnected, compound, interacting, and cascading risks. These concepts are becoming ever more central to the resilience debate. They aggregate elements of climate change adaptation, critical infrastructure protection, and societal resilience in the face of complex, high‐impact events. However, despite the potential of these concepts to link together diverse disciplines, scholars and practitioners need to avoid treating them in a superficial or ambiguous manner. Overlapping uses and definitions could generate confusion and lead to the duplication of research effort. This article gives an overview of the state of the art regarding compound, interconnected, interacting, and cascading risks. It is intended to help build a coherent basis for the implementation of the Sendai Framework for Disaster Risk Reduction (SFDRR). The main objective is to propose a holistic framework that highlights the complementarities of the four kinds of complex risk in a manner that is designed to support the work of researchers and policymakers. This article suggests how compound, interconnected, interacting, and cascading risks could be used, with little or no redundancy, as inputs to new analyses and decisional tools designed to support the implementation of the SFDRR. The findings can be used to improve policy recommendations and support tools for emergency and crisis management, such as scenario building and impact trees, thus contributing to the achievement of a system‐wide approach to resilience.
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Understanding Compound, Interconnected, Interacting and
Cascading Risks: A Holistic Framework
Gianluca Pescaroli(1) and David Alexander (1)
Corresponding author: G. Pescaroli, gianluca.pescaroli
This is the pre-printed and pre-edited version of the following article:
Pescaroli, G., & Alexander, D. E. (2018). Understanding Compound, Interconnected,
Interacting and Cascading Risks: A Holistic Framework”. Risk Analysis, doi:
10.1111/risa.13128 . It has been published in final form at:
This article may be used for non-commercial purposes in accordance with Conditions
for Self-Archiving and Green Open Access. Please refer and cite the edited version
available on Risk Analysis’s website. Please also note that this version may still have
some inconsistencies e.g. in the text and in the references.
1) Institute for Risk and Disaster Reduction, University College London, London, United
In recent years there has been a gradual increase in research literature on the challenges of
interconnected, compound, interacting, and cascading risks. These concepts are becoming
ever more central to the resilience debate. They aggregate elements of climate change
adaptation, critical infrastructure protection and societal resilience in the face of complex, high-
impact events. However, despite the potential of these concepts to link together diverse
disciplines, scholars and practitioners need to avoid treating them in a superficial or
ambiguous manner. Overlapping uses and definitions could generate confusion and lead to
the duplication of research effort. This paper gives an overview of the state of the art regarding
compound, interconnected, interacting, and cascading risks. It is intended to help build a
coherent basis for the implementation of the Sendai Framework for Disaster Risk Reduction
(SFDRR). The main objective is to propose a holistic framework that highlights the
complementarities of the four kinds of complex risk in a manner that is designed to support
the work of researchers and policy makers. This paper suggests how compound,
interconnected, interacting and cascading risks could be used, with little or no redundancy, as
inputs to new analyses and decisional tools designed to support the implementation of the
SFDRR. The findings can be used to improve policy recommendations and support tools for
emergency and crisis management, such as scenario building and impact trees, thus
contributing to the achievement of a system-wide approach to resilience.
Key Words: compounding risk, interconnected risk, interacting risk, cascading risk, societal
resilience, critical infrastructure, Sendai Framework for Disaster Risk Reduction.
1. Introduction
The development of concepts that describe compound, interconnected, interacting and
cascading risks is part of the process of creating new knowledge in order to increase societal
resilience. Since the 1990s and the International Decade for Natural Disaster Reduction, our
understanding of risk in the community has been influenced by the evolving role of science
and technology (Aitsi-Selmi et al., 2016). Different perspectives from disciplines such as
engineering and social sciences were merged together to provide a coherent approach to risk
analysis, using a basis of knowledge about system performance and uncertainty assessments
(Aven and Kristensen, 2005). Events such as the 2004 Indian Ocean Tsunami lead to the
development of the Hyogo Framework for Action, which provided an international plan
endorsed by the United Nations (UN) to reduce disaster losses and build resilience between
2005 and 2015. According to the United Nations Office for Disaster Risk Reduction (UNISDR),
disaster risk can be defined as: "The potential loss of life, injury, or destroyed or damaged
assets which could occur to a system, society or a community in a specific period of time,
determined probabilistically as a function of hazard, exposure, vulnerability and capacity”
(www., updated 2 February 2017). Here, vulnerability is defined as those
“conditions determined by physical, social, economic and environmental factors or processes
which increase the susceptibility of an individual, a community, assets or systems to the
impacts of hazards” (www., updated 2 February 2017).
The main consequence of this is a degree of circularity, in which the vulnerability of a system
makes it more sensitive to risk, reflecting the complexity of socio-economic factors that interact
with the physical aspects of hazard (Alexander, 1993; Intergovernmental Panel on Climate
Change, 2012; United Nations Strategy for Disaster Risk Reduction, 2015). The work of the
Society for Risk Analysis has highlighted the existence of other multidisciplinary aspects that
have been used for models and theoretical frameworks, recommending a broad qualitative
definition of risk and considering different types of ways of describing risk (Aven, 2010; 2016).
At the same time, it has been suggested that there is a tendency in the engineering community
to associate the definition of risk with the quantification of probabilities, but in order to be
effective, the analysis of systemic accidents and unexpected events must address also
uncertainties and their root causes (Aven, 2010). However, the literature suggests that further
development is needed especially in relation to situations of large or deep uncertainty and
emerging risk (Aven, 2016).The complexity of networked society and the uncertainties
inherent in threats, such as geomagnetic storms, challenge our approach to crisis
management. After a long debate on unknown, low-probability, and high-impact events, it has
been suggested that extreme scenarios could be more common that was previously
supposed, and that this requires us to develop a new understanding of their drivers (Sornette,
The problem involves the whole anthropogenic domain. It cannot be limited to the analysis of
hazards and must combine different human and natural factors that affect the magnitude of
risks. It has also been shown that crises challenge the process of governance. They cross
borders and involve many different aspects of society and the environment (Ansell et al., 2010;
Boin et al., 2014; Galaz et al., 2011). On the other hand, global networks are becoming more
interdependent and it is becoming harder to understand their vulnerabilities. In approaching
safety issues and risk analysis strategies, a paradigm shift is required (Helbing, 2013). There
is a need for a system-wide approach to resilience that is capable of employing penetrating
analyses, innovative methods, and new tools in order to improve the operational management
of complexity (Linkov et al., 2014).
In this context, in 2015 the UN member states adopted the Sendai Framework for
Disaster Risk Reduction (SFDRR), which was designed to improve upon the Hyogo
Framework for Action. This document identifies seven targets and four priorities areas to
“prevent new and reduce existing disaster risk”, including better action to reduce exposure
and vulnerabilities. The SFDRR defines “the need for improved understanding of disaster
risk in all its dimensions of exposure, vulnerability and hazard characteristics”. The strategy
for implementing the SFDRR requires innovation in this field and highlights the need to
create policies on key topics such as the security of critical infrastructure and the mitigation
of contextual factors in crisis situations (UNISDR, 2015).
Notwithstanding the rise of three factormulti-hazard approaches, multidisciplinary
integrations and holistic knowledge sharing (Aitsi-Selmi et al., 2016)--there are persistent
gaps in the research and they need to be addressed. Our limited background knowledge
of emerging risks suggests the need to improve assessment tools, and to achieve an
adaptive balance between different strategies and mitigation measures (Aven, 2016). The
fragmentation of the literature on compound, interconnected, interacting and cascading
risks can be seen as a part of this challenge, and obstacles must be overcome as the field
develops (Kappes et al., 2012; Leonard et al., 2014; Pescaroli and Alexander, 2015).
Although concepts are very different in their possible applications, there is a tendency to
use them as synonyms, which tends to cause redundancy and confusion.
This paper aims to highlight the complementarities and differences inherent in compound,
interconnected, interacting and cascading risks. It aims to be compatible with the
implementation of the SFDRR by supporting a better understanding of disaster risk and
clarifying the underlying risk drivers. New forms of risk are still addressed generically in the
framework and more clarity and precision are needed. Indeed, as noted in the literature,
“the way we understand and describe risk strongly influences the way risk is analysed and
hence it may have serious implications for risk management and decision making” (Aven,
2016). Our aim is to produce a holistic framework that can support focused actions and
research that will help reduce exposure and vulnerability and increase possible
complementarities instead of duplicating efforts in research and practice. This is essential
in order to maximise the impact and effectiveness of new political and practical
recommendations that are steps in the implementation of SFDRR. as shown in the recently
published Words into Action Guidelines on National Disaster Risk Assessment where all
the relevant elements are included (UNISDR, 2017). In other words, the scope of this paper
is to help scholars and practitioners to distinguish the different components of complex
events that tend to overlap, supporting more focused actions in terms of measures for
operational resilience and risk modelling.
To begin with, this paper focuses on compound events, which have been associated mostly
with natural hazards and climate change. Secondly, it approaches the fundamentals of
interconnected and interacting risks, in which the environmental and human drivers
overlap. Thirdly, cascading risk is explained, distinguishing the complementarities of the
social domain from the failure of critical infrastructure. The concluding section of this paper
presents a holistic framework that can be used to maximize the impact of future research
and policies.
2. Compound risk
Compound risk is a well-known topic of discussion by scholars and practitioners who are
interested in climate change. It involves both physical components, such as the
understanding of environmental trends, and statistical ones, such as the implications of
concurrence in forecasting and modelling. In contrast to interconnected and cascading
risks, compound risks and disasters have been defined in official documentation as a clear
area of competence. For example, the 2012 Special Report of the Intergovernmental Panel
on Climate Change (Intergovernmental Panel on Climate Change, 2012) reported
compounding drivers to be the possible sources of extreme impacts and associated them
very clearly with the hazard component of crisis management. In other words, compound
risk has been referred to as “a special category of climate extremes, which result from the
combination of two or more events, and which are again ‘extreme’ either from a statistical
perspective or associated with a specific threshold” (Intergovernmental Panel on Climate
Change, 2012). The concept is fully explained in a section of the work in which its
correspondence with the idea of “multiple” events is pointed out. Compound events could
be: (a) extremes that occur simultaneously or successively; (b) extremes combined with
background conditions that amplify their overall impact; or (c) extremes that result from
combinations of “average” events. The examples reported include high sea-level rise
coincident with tropical cyclones, or the impact of heat waves on wildfires. First,
compounding events such as flooding that occurs in saturated soils may impact the
physical environment. Secondly, health issues due to particular environmental conditions
such as humidity can affect human systems.
Although compound risk can involve events that are not causally correlated, some
exceptions have to be made for common driving forces, such as different phenomena that
interact during El Niño, or when system-wide feedbacks between different components
strengthen each other, as when drought and heat waves occur in regions that oscillate
between dry and wet conditions. Understanding and assessing this level of interaction
presents different challenges in relation to the forecasting and modelling of such
phenomena. It has been suggested that, because of its implications in terms of discrete
classes and artificial boundaries, the IPCC definition may be problematic for the
quantification of risk. It could be better to promote a more general approach in which
compound events are intended as extremes derived statistically from drivers with multiple
dependencies (Leonard et al., 2014). Indeed, climate change could increase the complexity
of the system and the possible sources of non-stationarity in the distribution of extremes,
such as variable and dynamic combinations. With regard to impacts and dependencies
between systems, these may need to be considered in a multidisciplinary way (Leonard et
al., 2014).
A slightly different point of view is reported in the SFDRR (United Nations Strategy for
Disaster Risk Reduction, 2015), in which compounding drivers are associated with both the
creation of new disaster risk and the need to reduce both exposure and vulnerability.This
seems to contextualise cascading risk more than separate it completely from what
explained earlier, The Words into Action Guidelines on National Disaster Risk Assessment
(UNISDR, 2017) refer to compounding factors as part of “underlying risk drivers”, such as
climate change or urbanisation, but the use of the term 'compound effects' in two different
chapters intends that it mostly be employed in line with the IPCC definition of concurrence
and combined extreme events (e.g. riverine floods and coastal storms surges).
The next section will explain better the areas of convergence and complementarities with
interacting and interconnecting risk. It will also discuss the causal background of cascades.
3. Interacting and interconnected risk
The literature on interacting and interconnected risk focuses on how physical dynamics
develop through the existence of a widespread network of causes and effects. Although
the two concepts are intuitively very similar, interacting risks have been studied more in the
context of earth sciences, while interconnected risks have generally been tackled under the
headings of globalisation and systems theory. The literature associated with this field has
two main foci. It tends to overlap with compound risk in the hazard domain, and with
cascading risk in the social and technological domains. A similar terminology is used in
research on risk factors in health (Price and Macnicoll, 2015). Overall, the topic has
particular implications for disaster risk reduction, complexity science, and emergency
management. Common ground for improving the understanding of the composite nature of
disasters has been a relevant part of disaster management and hazard assessment
processes since the 1980s, for example with respect to earthquake-induced landsliding
(Alexander, 1993). However, events such as the 2011 tsunami, and the storm surge
triggered by Hurricane Sandy, have increased the need to improve forecasting strategies
and early warning methods by those public and private stakeholders who are in charge of
critical infrastructure protection. Although the SFDRR (United Nations Strategy for Disaster
Risk Reduction, 2015) does not refer directly to interacting or interconnected risk, it refers
to the need to strengthen capacity to assess “sequential effects” on ecosystems.
In the case of interacting risks, the mechanisms and combinations of hazards have
been analysed in their temporal and spatial domains, including reciprocal influences
between different factors and coincidences among environmental drivers (Tarvainen et al.,
2006). Empirical studies have elucidated the relationships between primary hazardous
events and secondary natural hazards of the same category or different categories
(Marzocchi et al., 2009). Progress in this sector requires both risk assessment strategies
and understanding of the components of earth systems and their multiple-hazard
perspectives to be improved(Kappes et al., 2012). For example, Gill and Malamud (Gill
and Malamud, 2014) studied systematically interactions between 21 natural hazards. They
found that geophysical and hydrological hazards are receptors that can be triggered by
most of the other types of hazard, while geophysical and atmospheric causes are the most
common triggers. The results of such studies support a wider understanding of complex
interactions that could be integrated into early warning systems and rapid response tools.
Other studies have created new models based on the analysis of trigger factors, which
enables them to understand relationships among hazards that are interdependent, mutually
reinforcing, acting in parallel or acting in series (Liu et al., 2016).
However, for multiple-risk assessment to be effective, the complex nature of interacting
and interconnected relationships between different triggers needs to be integrated into a
holistic framework. Some allowance must be made for the social construction of disasters
in a global systems perspective, including reciprocal influences among the social sphere
and the built and natural environments (Hewitt, 1995; Mileti and Noji, 1999). In other words,
risk can be understood as the result of interaction between changing physical systems and
society, which also evolves over time (Weichselgartner, 2001). In various studies, Helbing
(Helbing, 2013; Helbing et al., 2006) analysed the interconnected causality chains that
generate and amplify disasters, framing the impacts of triggering events on both
ecosystems and anthropogenic systems. In this sense, the paths of complex risks that
generate secondary events are determined by physical elements (for example, a landslide
triggered by an earthquake), the build environment (for instance, critical infrastructure) and
people (hence, behaviour). The level of interconnection and interdependency may be
determined by interactive causality chains which can spread out in space and time.
However, improved understanding of physical interactions has tended to shift national risk
assessment towards multiple-hazard approaches, further attention should be given to
contemporary society and the built environment. The global interdependency of human,
natural and technological systems can produce hazards and disasters, but it is increasingly
hard to comprehend and control (Perry and Quarantelli, 2005). Networks have different
levels of interaction and interconnection, perhaps with multiple sources of disruption and
systemic failure (World Economic Forum, 2016). When events are triggered, the pathways
that determine the scale of the impacts are influenced by the interlinkages between different
domains, for example the interactions by which an earthquake leads to a tsunami, along
with the climate change drivers, and the components of infrastructure such as lifelines
(OECD, 2011).
As the next step towards the derivation of a holistic framework, the following section
will clarify the specific features of cascading risk.
4. Cascading risk
Among the phenomena analysed in this article, cascading risk is the broadest. For many
years, it was referred to vaguely as 'uncontrolled chain losses'. Its early diffusion occurred
in the 1980s, when it was used to refer to measurable links and nodes that could
compromise information flows in networked systems (Millen, 1988). In the same period, in
order to define the consequences of organizational failures that happen in tightly coupled
and complex technological systems, cascades were included in the theory of 'normal
accidents', or 'systemic accidents' (Perrow, 1999). The literature has associated cascades
with the metaphor of toppling dominoes”, which since the late 1940s has been used in the
chemical processing industry to refer to sequential accidents (Abdolhamidzadeh et al.,
2011; Khan and Abbasi, 1998). This idea has been integrated into the early literature on
NaTech disasters, interacting risk, and cascading events (Cruz et al., 2004; Ma, 2007), but
recently it has been pointed out that it could be an oversimplification and it could also
decontextualise the problem (Pescaroli and Alexander, 2015; Van Eeten et al., 2011).
In the early 2000s, events such as Hurricane Katrina and the terrorist attacks on the
World Trade Centre shifted the focus of research on cascading risk to the protection of
critical infrastructure, which is understood to be those systems or assets that are vital to
the functioning of society. Millennial literature has approached cascading risk from the point
of view of how one can model causal interdependencies and mitigate breakdowns (Millen
and Schwartz, 1988), how one can study the processes that could cause blackouts and
trigger cross-scale failures in power grids (Newman et al., 2005). Networked infrastructure
was portrayed in both its functional and social domains, including hardware, services, and
the secondary and tertiary effects of disruption (Little, 2002). However, cascading risk
remained a fragmented subject that lacked both official definition and an intergovernmental
dimension. It usually referred to a branching structure that originated with a primary trigger
(May, 2007).
Although new models were used to defined thresholds and mitigation strategies, their
applicability was limited by the absence of testing in real scenarios and networks (Peters
et al., 2008). In political analyses, although the presence of cascading effects was seen as
a driver that could explain the scale of crises, but it remained marginal to any broader
considerations of resilience to extreme events with cross-border dimensions (Ansell et al.,
2010; Boin and McConnell, 2007). The ecological debate focused on the implications of
cascading risk for climate by associating it with complex causal chains, non-linear changes
and recombination potential. The question of how to manage such crises was not solved
(Galaz et al., 2011).
Only in the late 2000s were empirical data used to demonstrate that cascading failures
are not as rare as was believed. When they were driven by disruptions to the energy,
telecommunications and internet sectors, they were generally stopped quickly (Luiijf et al.,
2009; Van Eeten et al., 2011). After highimpact events such as the eruption of
Eyjafjallajökull volcano (2010), the triple disaster in Japan (2011) and Hurricane Sandy
(2012), the field evolved towards a greater understanding of the wider implication of
cascades. A wider range of case studies provided new evidence of the disruption of social,
cultural and economic life, including cross-scale implications for global supply chains and
humanitarian relief (Alexander, 2013; Berariu et al., 2015; Sharma, 2013). Improved
technology stimulated a new phase in modelling the complexity of interactions and
interdependencies among networked systems. It promoted a more coherent approach to
climate, society, economics, the built environment and cross-sector decision support
systems (Greenberg et al., 2011; Havlin et al., 2012). In order to understand both random
failures and terrorist attacks on lifelines, critical factors began to be ranked (Buldyrev et al.,
2010; Zio and Sansavini, 2011). Attempts were made to assess cascading disruptions on
a cross-national basis (Galbusera et al., 2016; Jonkeren et al., 2015). In order to assess
the possible impact of cascading risk on emergency management and to translate it into
generic tools that could raise awareness and information sharing in particular on electricity
disruptions, the risk managers looked for practical and repicable approaches (Hogan,
2013). A few of the official scenarios tackled the loss of power supply caused by non-
conventional triggers such as solar storms, but, in everyday reality, practice was still
distinguished by a lack of buffering strategies and well-codified contingency plans
(Pescaroli and Alexander, 2016).
The promotion of strategies designed to increase the autonomy and adaptive capacity
of systems could be seen as a partial answer to these problems. In decision-making and
planning, decentralisation and greater empowerment were sought (Helbing, 2015).
However, guidelines for the adoption of coherent mitigation actions are still limited in their
availablity. In this sense, the Sendai Framework for Disaster Risk Reduction can be
regarded as a first step (UNISDR, 2015) . This document reflects the perception that, in
order to reduce damage to critical infrastructure and loss of vital services, hardware and
software are the joint adjuncts of policies and mitigation actions.
In the projects supported by the European Commission, in particular by the Seventh
Framework Programmes such as FP7 FORTRESS, FP7 CASCEFF, FP7 SNOWBALL,
FP7CIPRNet, or FP7 STREST, other drivers of research have emerged.Lack of awareness
of critical infrastructure dependencies among planners and responders could be associated
with extended impact of emergencies, requiring different levels of actions for mitigating
worst case scenarios and operational challenges (Luiijf and Klaver, 2013). Assessment and
modelling of cascading failures in networks can be complemented by greater attention to
the strategies that are required when disruption happens, as we suggested in some of our
previous works (Nones and Pescaroli, 2016; Pescaroli and Alexander, 2016; 2015;
Pescaroli and Kelman, 2017, Pescaroli and Nones, 2016;Pescaroli et al., 2018).
In particular, our approach proposed that 'cascading risk' should distinguish between
'cascading effects' and 'cascading disasters', considering that, as time progresses, non-
linear escalation of a secondary emergency could become the main centre of crisis
(Pescaroli and Alexander, 2015). This shifts significantly from the “toppling dominos
metaphor”, which, as suggested earlier (Little, 2002; Boin and McConnell, 2007; Newman
et al., 2005; Peters et al., 2008; Van Eeten et al., 2011), has mostly been employed in the
context of the process industry shifting attention to critical infrastructure, complex theory
and to the understanding of societal and organisational resilience in policy making and
emergency management. Figure 1, taken from a previous work of ours (Pescaroli and
Alexander, 2016), shows that cascading events can be viewed as the manifestation of
vulnerabilities accumulated at different scales, including socio-technological drivers. The
possible environmental triggers, shown at the top of the figures, can be associated with
compounding and interconnected risk, while critical infrastructure and complex adaptive
systems (CAS) may be the drivers that amplify the impacts of the cascade.
Figure 1- Vulnerability path of cascading disasters, scales interactions, and escalations in time and in
space (source: Pescaroli and Alexander 2016).
First, together with the literature on the loss of services, scholars suggested other possible
drivers of escalation such as NaTech events, which considers that up to 5 per cent of industrial
accidents are caused by natural triggers that involve hazardous facilities (Krausmann et al.,
2011). In both cases, gaps have been found in the existing legislative frameworks, where it is
necessary to integrate different levels of risk and critical infrastructure mapping to increase
the effectiveness of mitigation strategies for multiple-scale events (Nones and Pescaroli,
2016). Secondly, in order to increase the effectiveness of deployment and the organization of
procurement in disaster relief, new datasets are needed. The analysis of different case studies
suggests that the disruption of critical infrastructure can impact the logistics of emergency
relief (Berariu et al., 2015). It also has the potential to orient international aid in order to rectify
a shortfall of emergency goods and expertise caused by the disruption (Pescaroli and Kelman,
2017). Finally, it has been pointed out that cascading risk may require a change in methods
of scenario building and contingency planning. Our previous work suggested that flexibility of
response can be increased by considering possible escalation paths that are common to
different categories of triggering event (Pescaroli and Alexander, 2016; Pescaroli et al., 2018).
This approach is complementary to the perspective of broad impact-tree analysis (Macfarlane,
2015). Shifting from a focus on hazards to one on vulnerability assessment enables one to
recognise the sensitive nodes that may cause secondary events to escalate. On the one hand,
tipping points, or thresholds, can be associated with an increased demand for products and
services during events such as blackouts. This drives the prioritization of recovery actions and
introduces new questions and issues regarding coordination between public and private
stakeholders(Münzberg and Schultmann, 2017). On the other hand, in order to consider the
different components of risk in relation to one another, it is essential to introduce good
practices into emergency planning and scenario building (Alexander, 2016; Pescaroli et al.,
2018). The next section will propose a holistic framework that may be used by scholars and
practitioners as the basis for improved work in this field.
5. A holistic framework for compound, interconnected, interacting and
cascading risk
In order to identify complementarities and minimise the duplication of efforts in research,
policies, and practices, this paper has given a brief overview of compound, interacting,
interconnected and cascading risks. However,more discussion is needed to increase our
understanding of areas in which the concepts overlap.
Despite the presence of a very clear definition released by the IPCC, some literature on
compound risk associates or uses it interchangeably with the concepts of 'interconnected' and
'cascading' risks. Prior to the work of IPCC, Perry and Quarantelli (2005) referred to compound
dynamics as the combination of different losses or vulnerabilities, for which the background
conditions are coupled with changes in society and the built environment. In the work of
Kawata (2011), compound disasters were reported as a form of amplification of sequential
events, such as the 1923 great Kanto Earthquake and fire, and the collapse one year later
during a typhoon of some levees damaged by the earthquake. This approach was integrated
by other authors to describe possible compounding features, including multiple, coincidental
and simultaneous or near simultaneous events, sequential and progressive events, random
and related hazards, and infrastructure failures (Eisner, 2014). Although some parts of this
description are in line with the IPCC approach on compounding risk, other elements tend to
overlap with cascading and interacting risk, including their operational tools in terms of multi-
hazard assessment, safety standards and the redundancy of lifelines. Other literature (Liu and
Huang, 2014) has used both approaches (Eisner, 2014; Kawata, 2011) in order to show that
compound disasters could be a “subset of cases” in which extensive losses are associated
with a compounding process that includes both physical and human factors. According to this
perspective, the critical challenge for emergency management and strategic preparedness
policies lies in defining the interaction between the components (Liu and Huang, 2014).
However, in this case, compound risk has been associated with the linkages between natural
hazards and technology without taking into account other studies, such as those that refer to
technological disasters triggered by natural hazards (NATECH) (Santella et al., 2011) .
Interacting and interconnected risks tend to overlap with cascading risk. First, interactions
among hazards have been associated with the physical and environmental domains, by which
we mean a chain of hazardous events in which one manifestation triggers another, as when
a storm causes a flood(Gill and Malamud, 2014; Liu et al., 2016). This is clearly different from
the use of the “toppling dominos metaphor” in the chemical industry process explained earlier
(Khan and Abbasi, 1998; Abdolhamidzadeh et al., 2011; Cruz et al., 2004; May, 2007),
increasing the confusion. Secondly, interconnected and interacting risks can be seen as
precursors of the appearance of cascading effects and disasters (Helbing, 2013; Helbing et
al., 2006; World Economic Forum, 2016). In interactive complex systems, the speed of
cascading events (meaning their capacity to influence other components) can be the measure
or manifestation of 'tight coupling' (Perrow, 1999). In studies of the interdependency between
critical infrastructure and the built environment, cascading risks can be seen as one of the
possible categories of failure that are part of the infrastructure interdependency dimension
(Rinaldi et al., 2001). In other words, cascading effects can be seen as caused by
dependencies and interdependencies associated with infrastructure domain (Luiijf et al., 2009;
Luiijf and Klaver, 2013). In the literature on risk and resilience, this aspect has been
developed for infrastructure systems and disruptions that spread out from one network to
others through the many components of systems (Buldyrev et al., 2010; Galbusera et al.,
2016; Guikema et al., 2015).
The overlapping areas in the centre of Figure 2 reflect the descriptions reported in this paper
and have the following attributes:-
- They include a reference to the built environment. The vagueness in the early use of
concepts could be associated with duplication of efforts, for example extending the area
of interest of a certain risk (Intergovernmental Panel on Climate Change, 2012), and a
common lack of inter-agency agreements (May, 2007). It is clear that standard definitions
should be more widely adopted in order to help increase the effectiveness of research and
practice, and to avoid confusion and duplication of effort in the analysis of the built
- They include elements of interdependencies. On the one hand, this leads to problems
such as the oversimplifying of ideas such as the “toppling dominoes” metaphor (Pescaroli
and Alexander, 2015). On the other, it makes some progress towards integrating multi-
disciplinary research on the anthropogenic dimension of disasters (Alexander, 1993;
Helbing et al., 2006; Perry and Quarantelli, 2005; Weichselgartner, 2001).
- They point to the existence of an amplification process that that could be associated with
the higher complexity of the system and the wider impacts of possible disasters (Helbing,
2013; Pescaroli and Alexander, 2016; Sornette, 2009). The identification of amplification
dynamics may reflect the cross-disciplinary manifestation of increased complexity at the
system level.
They are complex risks which maintain high potential for surprise and non-linear evolution,
and this has to be considered in the assessment process. They include different levels of
consequence and uncertainty (Aven and Kristensen, 2005). Due to their level of complexity,
the quantification of risk and probabilistic assessment have a large degree of arbitrarieness,
where important drivers could have been ignored, underestimated, or are not available in the
form of datasets, which would require the integration of qualitative data (Aven, 2010).These
relationships are shown in Figure 2, which is intended to be a synthetic framework for use in
future studies.
Figure 2 derives the following characteristics for each risk:-
Compound risk can refer to the environmental domain, or to the concurrence of
natural events. Eventually it can be correlated with different patterns of extreme
impacts caused by climate change. Institutional definitions tend to focus more
narrowly on the hazard component of disaster risk.
Interacting risk refers to the domain of physical relations developed in the natural
environment and to its and casual chains. They focus on the area in which hazard
interacts with vulnerability to create disaster risk. The study of interacting risk may
be the focus of disciplines such as geophysics and physical geography, while
giving space to multiple risk assessment tools and strategies For example, the
study of the dynamics of interacting risk may can be translated into simulations
and models for the energy industry, thus defining better hazard maps .
Interconnected risk tends to be used more often in network science and in studies
of global inter-linkages It can include the complex interactions between human,
environment, and technological systems, which can be translated, for example,
into coherent multiple risk assessments or network analysis. Interconnected risk
may be referred to as the physical interdependencies that allows societal
interactions, and thus a pre-condition for cascading risk.
Cascading risk is associated mostly with the anthropogenic domain and the
vulnerability component of risk. This results in a disaster escalation process. In
other words, it focuses mainly on the management of social and infrastructure
nodes. With respect to triggering events, while interconnected risk can be seen as
one of the preconditions for the manifestation of cascades, compound and
interacting dynamics can influence its magnitude.
Figure 2. A framework for compound, interacting, interconnected and cascading risks
In the analysis of case studies, some examples will help to clarify the approach to
cross-risk interaction and how to apply the framework shown in Figure 1. This has been
developed bearing in mind the needs of the SFDRR (United Nations Strategy for Disaster Risk
Reduction, 2015) and the methodologies of decision support for emergency and crisis
management, such as scenario building (Macfarlane, 2015). The first event to consider is the
eruption of the Icelandic volcano Eyjafjallajökull in April 2010. It demonstrates how recurrent
compounding processes can have extensive impacts on the interconnected system, spreading
its cascading effects to the wider cross-border scale (Alexander, 2013; Pescaroli and
Alexander, 2016). The volcanic hazard itself became a problem because it was “coincident
with north to north-westerly air flow between Iceland and North West Europe, which prevails
for only 6 per cent of the time” (Sammonds et., 2011). In other words, together with the
eruption, the other determining factor was weather conditions, thus creating compound risk
(which was atypical but not entirely unusual). In contrast to other cases in which the impact
was limited, in 2010 the ash spread out over an area with a high concentration of essential
transportation system nodes. It affected global networks that are highly dependent on aviation,
thus creating interconnected risk. Although the direct physical damage was limited, disruption
of the infrastructure and its cascading effects on society were subject to non-linear escalation
and became the primary source of crisis that needed to be managed (i.e., cascading risk).
The second example is the triple disaster that struck Japan on the 11th March 2011. In
two different ways it explains how interacting and interconnected features can overlap with
social vulnerabilities and thus contribute to the cascading escalation of the event (Pescaroli
and Alexander, 2015; National Diet of Japan, 2012). First, an earthquake that triggered a
tsunami represented an interacting hazard, which affected highly coupled infrastructure
(interconnected risk), and provoked a wide range of non-linear secondary emergencies, such
as the extensive loss of vital services and the creation of NaTech events (cascading risk).
Secondly, the earthquake triggered a small and localised landslide (interacting risk) that cut
off the Fukushima power plant from the main electric grid (interconnected risk), exacerbated
existing vulnerabilities at the site and led to a full-blown nuclear meltdown (cascading risk). In
both cases, the disruption of critical infrastructure orientated the progress of emergency relief
towards mitigating the escalation of secondary emergencies (Pescaroli and Kelman, 2017),
while the meltdown of the Fukushima Dai'ichi plant was regarded as a man-made disaster that
could have been predicted and avoided were it not for the prevalence of negligence (National
Diet of Japan, 2012).
Hurricane Sandy, also known as Super-Storm Sandy, is our last case. It encompasses
all the possible joint effects of compounding, interacting, interconnected and cascading risks
(Kunz et al., 2013; Pescaroli and Alexander, 2016). Its relevance mainly lies in climate change
scenarios, in which the primary nature of the event triggers may be subject to intensification.
Hurricane Sandy made landfall in the United States on 29th October 2012. The storm winds
not only wreaked direct damage, but also contributed to the generation of a storm surge that
caused flood damages (interacting risk), while concurrent cold air flowing from the Arctic
intensified cold weather and caused snow storms inland (compounding risk). Sandy impacted
a geographical area of strategic importance to the US economy. It has a dense population and
a high concentration of industrial plants and financial networks, such as the New York Stock
Exchange (interconnected risk).
The composite nature of the hazard and the loss of highly-ranked critical infrastructure
triggered a wide range of secondary crises that escalated in a non-linear manner. While the
emergency responders had to tackle leaks from refineries and chemical plants, or fires in
houses, the President of the USA made a new declaration of emergency regarding the
prolonged power outages and the damage to the production and distribution chain of gasoline
and distillates (cascading risk). An official report (Blake et. al., 2013) attributed around 50
deaths to the joint effect of extended power outages and cold weather (interaction of
compounding and cascading risk).
However, this clarification is simply not enough to translate the conceptual framework into a
tool that can be used to understand, manage and predict events. Taking back the conceptual
equation used for the definition of risk, and the complementary works cited in the introduction,
it may be useful to subject Figure 3 to further discussion.
Our review shows that the compound, interacting, interconnected, and cascading risk tend to
be different component of hazards and vulnerabilities. While compound risk can be mostly
associated with the physical dimension of hazards, interacting and interconnected risk
gradually increase the focus on the vulnerability component. Thus they become the centre of
cascading risk. The analysis of root causes and consequences use different tools. On the one
hand the work mostly involves physical modelling and forecasting. On the other hand it
focuses on network analysis and resilience assessment in the broader sense. Those tools are
complementary and can be used together, while common areas of interaction and overlapping
can be indentified in the build environment and in mechanisms such as early warning systems.
As noted, in all of these cases, there is a common background of wide uncertainties in the
environmental, physical, technological and social dimensions, that can challenge risk
assessment and management with the existence of weak background knowledge. This
influence the tools that are needed, but it also affects the assessment process and the possible
policy outcomes, as there may be different emphases on hazards and vulnerabilities. In order
to maximise the efficiency of the process of risk analysis and risk assessment, it is essential
to understand the differences and complementarities inherent in compound, interacting,
interconnected and cascading events. .
Figure 3- Overview of the relations of Compound, interacting, interconnected, and cascading risk with
hazard, vulnerability, uncertainties and analytical tools.
6. Conclusion
This paper has developed a common framework for compound, interacting, interconnected
and cascading risk, which aims to support a better visualization and understanding of high-
impact events. It develops these ideas in line with the SDFF, and characterizes complex
events in a way that should support a more highly focused analysis (Aven, 2016; Linkov et al.
2014; Greenberg et., 2011; Pescaroli and Alexander, 2016). This is in line with the perceived
need for new strategies designed to integrate systemic risks in research, policies and
management that has been frequently highlighted in the literature (Aitsi-Selmi et al., 2016;
Helbing, 2013;Linkov et al 2014; Mileti, 1999;Helbing 2015;Alexander 2016).
Despite a general perception of overlap between the four concepts dealt with in this paper, we
have shown that very specific issues have been addressed in compound, cascading,
interacting and interconnected risk. These have not always been assimilated in research and
management, and this requires better coordination in order to improve the complementarities
of forecasting tools, the flexibility of mitigation measures, and the ability to adapt to emergency
We have defined boundaries that can help to produce more focused risk estimations and
better tools, which will, we trust, help stakholders and academics to improve description,
visualization and communication, as suggested in some of the literature and in the SFDRR
itself (UNISDR, 2015; Aven 2016). There are significant limitations to this perspective that
must be considered. First the readers, should note that this article does not pretend to be an
exhaustive review of all the literature in the field.Instead, it provides a synthetic framework and
guidelines for those readers who are interested in the topic. Although we have tried to define
as much as possible the boundaries of each category, futher work is needed in order to define
the specific boundaries and their significance as “tipping points” for risk assessment. Future
research should better consider qualitative implications for practical management of such
situations in terms of scenario building and the broadening of impact trees, which must be
complementary to the methodologies and tools that have already been identified in the
literature (Aven, 2016: Helbing, 2013; Linkov et al., 2014; Pescaroli and Alexander, 2016). In
other words, new research should be developed on how to predict and address
interdependencies, together with advice on what actions should be taken once
interdependencies are triggered. The translation of theoretical frameworks into practice is one
of the most important challenges that need to be addressed in the furtherance of disaster risk
7. Acknowledgements
This work has been carried out under the aegis of the EC FP7 FORTRESS project.
FORTRESS is funded by the European Commission within FP7- Area 10.4.1 Preparedness,
prevention, mitigation and planning, TOPIC SEC-2013.4.1-2 SEC-2013.2.1-2, Grant 607579.
The authors gratefully acknowledge Igor Linkov (USACE), Dirk Helbing (ETHZ), Georgios
Giannopulos (JRC) and Luca Galbusera (JRC) for their precious questions, feedbacks and
suggestions during our workshops.
Abdolhamidzadeh, B., Abbasi, T., Rashtchian, D., and Abbasi, S.A. (2011). Domino effect in
process-industry accidents - An inventory of past events and identification of some
patterns. J Loss Prev Process Ind, 24(5), 57593.
Aitsi-Selmi, A., Murray, V., Wannous, C., Dickinson, C., Johnston, D., Kawasaki, A., ... and
Yeung, T. (2016). Reflections on a science and technology agenda for 21st century
disaster risk reduction. International Journal of Disaster Risk Science, 7(1), 1-29.
Alexander, D.E. (1993). Natural disasters. Kluwer Academic Publishers, Boston, MA.
Alexander, D.E. (2013). Volcanic ash in the atmosphere and risks for civil aviation: A study in
European crisis management. Int J Disaster Risk Sci,4(1),919.
Alexander, D.E. (2016). How to write an emergency plan. Dunedin Academic Press, London.
Ansell, C., Boin, A., and Keller, A. (2010). Managing transboundary crises: Identifying the
building blocks of an effective response system. J Contingencies Cris
Aven, T. (2010). On how to define, understand and describe risk. Reliab Eng Syst Saf, 95(6),
Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their
foundation. Eur J Oper Res, 253(1), 113.
Aven, T., and Kristensen, V. (2005). Perspectives on risk: review and discussion of the basis
for establishing a unified and holistic approach. Reliability Engineering & System
Safety, 90(1), 1-14.
Berariu, R., Fikar, C., Gronalt, M., and Hirsch, P. (2015). Understanding the impact of cascade
effects of natural disasters on disaster relief operations. Int J Disaster Risk Reduct,12,
Blake, E.S., Kimberlain, T.B., and Berg, R.J.(2013). Tropycal Cyclone Report Hurricane Sandy
(AL182012), 11-29 October 2012. National Hurricane Centre, Miami, Florida Available
Boin, A., and McConnell, A. (2007). Preparing for critical infrastructure breakdowns. J
Contingencies Cris Manag, 15(1), 509.
Boin, A., Rhinard, M., and Ekengren, M. (2014). Managing transboundary crises: The
emergence of European Union capacity. J Contingencies Cris Manag, 22(3), 13142.
Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H.E., and Havlin, S. (2010).Catastrophic
cascade of failures in interdependent networks. Nature, 464(7291), 10258.
Cruz, A.M., Steinberg, L.J., Vetere Arellano, A.L., Nordvik, J.P., and Pisano, F. (2004). State
of the art in Natech risk management (EUR 21292 EN). EU JRC, Ispra. Available from:
Eisner, R. (2014). Managing the risk of compounding disasters. In: Davis, I. (Ed.) Disaster risk
management in Asia and the Pacific. Routledge, London, 13768.
Galaz, V., Moberg, F., Olsson, E., Paglia, E., and Parker, C. (2011). Institutional and political
leadership dimensions of cascading ecological crises. Public Adm, 89(2),36180.
Galbusera, L., Azzini, I., Jonkeren, O., and Giannopoulos, G. (2016). Inoperability Input-
Output modeling : Inventory optimization and resilience estimation during critical
events. ASCE-ASME J Risk Uncertain Eng Syst Part A Civ Eng,2(3), 110.
Gill, J., and Malamud, B. (2014). Reviewing and visualizing the interactions of natural hazards.
Rev Geophys, 52, 680722.
Greenberg, M.R., Lowrie, K., Mayer, H., and Altiok, T. (2011). Risk-based decision support
tools: Protecting rail-centered transit corridors from cascading effects. Risk Analysis,
31(12), 184958.
Guikema, S., Mclay, L., and Lambert, J.H. (2015). Infrastructure systems, risk analysis, and
resilience-research gaps and opportunities. Risk Analysis, 35(4), 5601.
Havlin, S., Kenett, D.Y., Ben-Jacob, E., Bunde, A., Cohen,R., Hermann, H., et al. (2012).
Challenges in network science: Applications to infrastructures, climate, social systems
and economics. Eur Phys J Spec Top, 214(1), 27393.
Helbing, D. (2015). Responding to complexity in socio-economic systems: How to build a
smart and resilient society? SSRN Electron J, 2331. Available from:
Helbing, D. (2013). Globally networked risks and how to respond. Nature, 497(7447), 519.
Helbing, D., Ammoser, H., and Kühnert, C. (2006). Disasters as extreme events and the
importance of network interactions for disaster response management. In: Albeverio,
S., Jentsch, V. and Kantz, H. (Eds.) The Unimaginable and Unpredictable: Extreme
Events in Nature and Society. Springer, Berlin, 319348.
Hogan, M. (2013). Anytown : Final Report . London Resilience, London. Available from:
Intergovernmental Panel on Climate Change (2012). Managing the risks of extreme events
and disasters to advance climate change adaptation. IPCC,Geneva. Available from:
Jonkeren, O., Azzini, I., Galbusera, L., Ntalampiras, S., and Giannopoulos, G. (2015). Analysis
of critical infrastructure network failure in the European Union: A combined systems
engineering and economic model. Networks Spat Econ, 15(2), 25370.
Kappes, M.S., Keiler, M., von Elverfeldt, K., and Glade,T. (2012). Challenges of analyzing
multi-hazard risk: A review. Nat Hazards, 64(2),192558.
Kawata, Y. (2011). Downfall of Tokyo due to devastating compound disaster. Journal of
Disaster Research, 6 (2), 176-184.
Khan, F.I., and Abbasi, S.A. (1998). Models for domino effect analysis in chemical process
industries. Process Saf Prog, 17(2), 10723.
Krausmann, E., Cozzani, V., Salzano, E., and Renni, E. (2011). Industrial accidents triggered
by natural hazards: An emerging risk issue. Nat Hazards Earth Syst Sci, 11(3). 9219.
Kunz, M., Muhr, B., Kunz-Plapp, T., Daniell, J.E., Khazai , B., Wenzel ,F., et al. (2013).
Investigation of superstorm Sandy 2012 in a multi-disciplinary approach. Nat Hazards
Earth Syst Sci., 13(10), 2579-2598.
Leonard, M., Westra, S., Phatak, A., Lambert, M., van den Hurk, B., Mcinnes, K., et al. (2014).
A compound event framework for understanding extreme impacts. Wiley Interdiscip
Rev Clim Change, 5(1), 11328.
Linkov, I., Bridges, T., Creutzig, F., Decker ,J., Fox-Lent, C., Kröger, W., et al. (2014) Changing
the resilience paradigm. Nat Clim Change, 4(6), 4079.
Little, R.G. (2002). Controlling cascading failure: Understanding the vulnerabilities of
interconnected infrastructures. J Urban Technol, 9(1), 10923.
Liu, B., Siu, Y.L., and Mitchell, G. (2016). Hazard interaction analysis for multi-hazard risk
assessment: A systematic classification based on hazard-forming environment. Nat
Hazards Earth Syst Sci., 16(2),62942.
Liu, M., and Huang, M.C. (2014). Compound disasters and compounding process. UNISDR
Geneva. Available from:
Luiijf, H.A.M., and Klaver, M.H.A (2013). Expand the Crisis? Neglect Critical Infrastructure!
Insights and recommendations. Jahresfachtagung der Vereinigung zur Förderung des
Deutschen Brandschutzes, CRISE 2013, 27.-29. Mai 2013, Weimar, Germany, 293
Luiijf, H.M., Nieuwenhuijs, A.H., Klaver, M.H., Van Eeten, M.J., and Cruz, E. (2009) Empirical
findings on European critical infrastructure dependencies. Int J Syst Syst Eng,
Macfarlane, R. (2015). Decision support tools for risk, emergency and crisis management: An
overview and aide memoire. Emergency Planning College, London. Available from:
Marzocchi, W., Mastellone, M.L., Di Ruocco, A., Novelli, P., Romeo, E., and Gasparini, P.
(2009).Principles of multi-risk assessment. European Commission. EU JRC, Ispra.
May, F. (2007). Cascading disaster models in Postburn flash flood. In: Butler, B.W., Cook W.
(Eds.). The Fire Environment Innovations, Management and Policy; Conference
Proceedings. US Department of Agriculture Forest Service. 44663. Available from:
Mileti, D., Noji, E.K. (1999). Disasters by Design. Joseph Henry Press,Washington. Available
Millen, J. K., and Schwartz, M. W. (1988). The cascading problem for interconnected
networks. In: Aerospace Computer Security Applications Conference, 1988, Fourth,
Münzberg, T., Wiens, M., and Schultmann, F. (2017). A spatial-temporal vulnerability
assessment to support the building of community resilience against power outage
impacts. Technol Forecast Soc Change, 121, 99-118.
Newman, D.E., Nkei, B., Carreras, B., Dobson, I., Lynch, V.E.,and Gradney, P. (2005).Risk
assessment in complex interacting infrastructure systems. Thirty eight Hawaii
International Conference on System Science. Big Island, Hawaii, 110. Available from:
Nones, M., and Pescaroli,G. (2016). Implications of cascading effects for the EU Floods
Directive. Int J River Basin Manag, 14(2), 195204.
OECD (2011). Future global shocks. OECD, Paris. Available from:
Perrow, C. (1999). Normal accidents:Living with high risk technologies -Updated edition.
Princeton University Press, Princeton, PJ.
Perry, R.W., and Quarantelli, E. (2005). What is a disaster? New answers to old questions.
Xilibris Press, Philadelphia.
Pescaroli, G., and Alexander, D. E. (2015). A definition of cascading disasters and cascading
effects: Going beyond the “toppling dominos” metaphor. Planet@Risk, Glob Forum
Davos,3(1), 5867.
Pescaroli, G., and Alexander, D.E. (2016). Critical infrastructure, panarchies and the
vulnerability paths of cascading disasters. Nat Hazards. Springer, 82(1),17592.
Pescaroli, G., and Kelman, I. (2017). How Critical Infrastructure Orients International Relief
in Cascading Disasters. J Contingencies Cris Manag, 25(2), 56 67.
Peters, K., Buzna, L., and Helbing, D. (2008). Modelling of cascading effects and efficient
response to disaster spreading in complex networks. Int J Crit Infrastructures, 4(1/2),
Price, B., and Macnicoll, M. (2015). Multiple interacting risk factors: On methods for allocating
risk factor interactions. Risk Analysis, 35(5),93140.
Rinaldi, B.S.M., Peerenboom, J.P., and Kelly, T.K. (2001). Identifying, understanding, and
analyzing critical infrastructure interdependencies. IEEE Control Syst, 21(6),1125.
Sammonds, P., McGuire, B., and Edwards S. (2011). Volcanic hazard from Iceland. Institute
for Risk and Disaster Reduction, University College London. London. Available from:
Santella, N., Steinberg, L.J., and Aguirra, G.A. (2011). Empirical estimation of the conditional
probability of Natech events within the United States. Risk Analysis, 31(6), 95168.
Sharma, A. (2013). The social and economical challences. In: Davis, I. (Ed.). Disaster risk
management in Asia and the Pacific. Routledge,London, 10934.
Sornette, D. (2009). Dragon-kings, black swans, and the prediction of crises. Int J Terrasp Sci
Eng, 2(1),118.
Tarvainen, T., Jarva, J., and Greiving, S. (2006). "Spatial pattern of hazards and hazard
interactions". In: Schmidt-Thome, P. (Ed). Natural and technological hazards and risks
affetting the spatial development of European regions. Special Paper 42. Geological
Survey of Finland, Espoo.
The National Diet of Japan (2012). The Fukushima Nuclear accident Independent
Investigation Commission. National Diet Japan . The National Diet of Japan, Tokio.
Available from:
UNISDR (2017). National Disaster Risk Assessment. UNISDR, Geneva. Available from:
UNISDR (2015). Sendai Framework for disaster risk reduction. UNISDR, Geneva. Available
Van Eeten, M., Nieuwenhuijs, A., Luiijf, E., Klaver, M., and Cruz, E. (2011). The state and the
threat of cascading failure across critical infrastructures: The implications of empirical
evidence from media incident reports. Public Adm, 89(2), 381400.
Weichselgartner, J. (2001). Disaster mitigation: the concept of vulnerability revisited. Disaster
Prev Manag, 10(2),8595.
World Economic Forum (2016). The Global Risks Report 2016 11th Edition. Insight Report.
World Economic Forum. Available from:
Zio, E., Sansavini, G. (2011). Component criticality in failure cascade processes of network
systems. Risk Analysis, 31(8), 1196210.
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In the present paper, we will explore how artificial intelligence (AI) and big data analytics (BDA) can help address clinical public and global health needs in the Global South, leveraging and capitalizing on our experience with the “Africa-Canada Artificial Intelligence and Data Innovation Consortium” (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face. “Clinical public health” can be defined as an interdisciplinary field, at the intersection of clinical medicine and public health, whilst “clinical global health” is the practice of clinical public health with a special focus on health issue management in resource-limited settings and contexts, including the Global South. As such, clinical public and global health represent vital approaches, instrumental in (i) applying a community/population perspective to clinical practice as well as a clinical lens to community/population health, (ii) identifying health needs both at the individual and community/population levels, (iii) systematically addressing the determinants of health, including the social and structural ones, (iv) reaching the goals of population’s health and well-being, especially of socially vulnerable, underserved communities, (v) better coordinating and integrating the delivery of healthcare provisions, (vi) strengthening health promotion, health protection, and health equity, and (vii) closing gender inequality and other (ethnic and socio-economic) disparities and gaps. Clinical public and global health are called to respond to the more pressing healthcare needs and challenges of our contemporary society, for which AI and BDA can help unlock new options and perspectives. In the aftermath of the still ongoing COVID-19 pandemic, the future trend of AI and BDA in the healthcare field will be devoted to building a more healthy, resilient society, able to face several challenges arising from globally networked hyper-risks, including ageing, multimorbidity, chronic disease accumulation, and climate change.
... Multi-hazard interactions can influence the overall hazard level, and alter the vulnerability of the elements at risk (Kappes et al., 2012b;Luo et al., 2020b). Although the multi-hazard analysis considering possible hazard interactions receives increasing attention (Gill and Malamud, 2014;Liu et al., 2015;Gallina et al., 2016;Pescaroli and Alexander, 2018;Tilloy et al., 2019), effects of hazard interactions on vulnerability are rarely considered and studies on multi-vulnerability of buildings to landslide hazards are even less. In the literature, the types and effects of hazard relations on the resulting vulnerability are classified by triggering, temporal and spatial relations of multi-hazards (Kappes et al., 2012b;Luo et al., 2020b). ...
Risks to shared water resources in the Murray–Darling Basin are reviewed after the report by CSIRO on the same topic in 2006. CSIRO outlined six major risks to shared water resources in the Basin. Herein, six groups of researchers have reviewed the risks of climate change, forest growth, groundwater, water infrastructure, water quality, and governance. These reviews bring an updated understanding of risk assessment and management that can contribute to the forthcoming reviews of the Water Act and Basin Plan in 2024–26. Drawing on these six papers, the authors synthesise knowledge of the risks to shared water resources and identify policy and management options and information gaps. We find that few risk factors have decreased in significance. Most risks remain and new risks are identified. Water managers must plan for a significant decrease in water availability and governments need to actively manage these risks under conditions of increasing uncertainty.
In this article, we study the framing activities of Scandinavian climate-active non-governmental organizations (NGOs) during the early phases of the 2020 coronavirus pandemic. Building on theories of focusing events, crisis exploitation and Ulrich Beck’s global risks, we develop and apply the concept of inter-risk framing contests to the case. Empirically, we analyse all climate- and corona-related tweeting activity of a broad selection of green NGOs in Denmark (17 NGOs, 874 tweets), Norway (22 NGOs, 2575 tweets) and Sweden (15 NGOs, 920 tweets), respectively. Methodologically, we employ quantitative text analysis to map socio-symbolic constellations of NGO-term relations using principal component analysis, while complementing this via online ethnographic observation to increase interpretative validity. Overall, the analysis demonstrates similarities and differences in how green NGOs have variously responded to the ambiguous challenges and symbolic opportunities of the coronavirus event, in ways resonant with path-dependent dynamics of the three national green civil societies.
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The growing complexity of global interconnected risk suggests that a shift has occurred in the way emergency planners need to improve preparedness and response to cascading events. With reference to the literature from the physical, social and political sciences, this paper analyses extreme space weather events and cyberattacks. The goal of this work is to produce a replicable scenario-building process, based on cross-disciplinary understanding of vulnerability, that could be complementary to probabilistic hazard assessment. Our hypothesis is that the technological and human component of critical infrastructure could be the primary vector for the escalation of secondary emergencies. While not themselves having direct implications in terms of loss of life, elements that are common to different risks could provide particular challenges for disaster management. Our findings identify some vulnerable nodes, such as Global Navigation Satellite System technology and remote-control systems, that could act as paths for the escalations of events. We suggest that these paths may be common to various known and unknown threats. We propose two scenarios of Massive, OveRwhelming Disruption of OpeRations (M.OR.D.OR.) that could be used for testing emergency preparedness strategies, and increasing the response to highly complex, unknown events. The conclusions highlight the open challenges of seeking to increase societal resilience. The limitations of this work are described, as are the possible challenges for future research.
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Critical infrastructure and facilities are central assets in modern societies, but their impact on international disaster relief remains mostly associated with logistics challenges. The emerging literature on cascading disasters suggests the need to integrate the non-linearity of events in the analyses. This article investigates three case studies: the 2002 floods in the Czech Republic, Hurricane Katrina in 2005, and the 2011 Tohoku earthquake, tsunami, and Fukushima meltdown in Japan. We explore how the failure of critical infrastructure can orient international disaster relief by shifting its priorities during the response. We argue that critical infrastructure can influence aid request and delivery, changing needs to address the cascades and contain cascading technology-based events. The conclusions propose remaining challenges with applying our findings.
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The adoption of the European Floods Directive (2007/60/EC) represented a crucial improvement in the management of watercourses and coastlines. However, the beginning of a new phase of implementation requires the assessment of which emerging topics may be included in the review process. The aim of our research is to understand the existence of any legislative gaps that could limit the preparedness to cascading events and critical infrastructures breakdowns. First, we provide a review of the Floods Directive, the cascading phenomena and the vulnerability of critical infrastructures in the European legislation. Secondly, we analyse some case studies to test the present approach and to improve the work of decision makers. Our results suggest that the Floods Directive tends to focus on localized flood impacts at smaller time scale and it could be ineffective to address the cross-scale impact of cascading events. Although some of the corrective actions may not be of competence of the Directive, we argue that their inclusion could limit uncertainties in the attribution of responsibilities and the coordination among different institutional levels. © 2016 International Association for Hydro-Environment Engineering and Research.
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The first international conference for the post-2015 United Nations landmark agreements (Sendai Framework for Disaster Risk Reduction 2015–2030, Sustainable Development Goals, and Paris Agreement on Climate Change) was held in January 2016 to discuss the role of science and technology in implementing the Sendai Framework for Disaster Risk Reduction 2015–2030. The UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030 aimed to discuss and endorse plans that maximize science’s contribution to reducing disaster risks and losses in the coming 15 years and bring together the diversity of stakeholders producing and using disaster risk reduction (DRR) science and technology. This article describes the evolution of the role of science and technology in the policy process building up to the Sendai Framework adoption that resulted in an unprecedented emphasis on science in the text agreed on by 187 United Nations member states in March 2015 and endorsed by the United Nations General Assembly in June 2015. Contributions assembled by the Conference Organizing Committee and teams including the conference concept notes and the conference discussions that involved a broad range of scientists and decision makers are summarized in this article. The conference emphasized how partnerships and networks can advance multidisciplinary research and bring together science, policy, and practice; how disaster risk is understood, and how risks are assessed and early warning systems are designed; what data, standards, and innovative practices would be needed to measure and report on risk reduction; what research and capacity gaps exist and how difficulties in creating and using science for effective DRR can be overcome. The Science and Technology Conference achieved two main outcomes: (1) initiating the UNISDR Science and Technology Partnership for the implementation of the Sendai Framework; and (2) generating discussion and agreement regarding the content and endorsement process of the UNISDR Science and Technology Road Map to 2030.
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This paper develops a systematic hazard interaction classification based on the geophysical environment that natural hazards arise from - the hazard-forming environment. According to their contribution to natural hazards, geophysical environmental factors in the hazard-forming environment were categorized into two types. The first are relatively stable factors which construct the precondition for the occurrence of natural hazards, whilst the second are trigger factors, which determine the frequency and magnitude of hazards. Different combinations of geophysical environmental factors induce different hazards. Based on these geophysical environmental factors for some major hazards, the stable factors are used to identify which kinds of natural hazards influence a given area, and trigger factors are used to classify the relationships between these hazards into four types: independent, mutex, parallel and series relationships. This classification helps to ensure all possible hazard interactions among different hazards are considered in multi-hazard risk assessment. This can effectively fill the gap in current multi-hazard risk assessment methods which to date only consider domino effects. In addition, based on this classification, the probability and magnitude of multiple interacting natural hazards occurring together can be calculated. Hence, the developed hazard interaction classification provides a useful tool to facilitate improved multi-hazard risk assessment.
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Cascading effects and cascading disasters are emerging fields of scientific research. The widespread diffusion of functional networks increases the complexity of interdependent systems and their vulnerability to large-scale disruptions. Although in recent years studies of interconnections and chain effects have improved significantly, cascading phenomena are often associated with the ‘‘toppling domino metaphor’’, or with high-impact, low-probability events. This paper aimed to support a paradigm shift in the state of the art by proposing a new theoretical approach to cascading events in terms of their root causes and lack of predictability. By means of interdisciplinary theory building, we demonstrate how cascades reflect the ways in which panarchies collapse. We suggest that the vulnerability of critical infrastructure may orientate the progress of events in relation to society’s feedback loops, rather than merely being an effect of natural triggers. Our conclusions point to a paradigm shift in the preparedness phase that could include escalation points and social nodes, but that also reveals a brand new field of research for disaster scholars.
Power outages are among the most serious Critical Infrastructure (CI) disruptions and require effective disaster management with collaboration of affected CI providers and disaster management authorities. To support building community resilience, we introduce a vulnerability assessment which allows an enhanced spatial-temporal understanding of initial power outage impacts. Using the assessment enables planers to better identify which and when CIs become vulnerable and how important they are in comparison to other CIs before the overall crisis situation escalates and unmanageable cascading effects occur. The assessment addresses the initial phase of a power outage and corresponding early measures of local risk and crisis management organizations according to the German disaster management system. The assessment is an indicator-based approach which is extended to consider time-depending effects through time-referenced demand and the depletion of Coping Capacity Resources (CCR). The estimation of the relevance of CIs regarding the provision of vital services and products is addressed by a modified Delphi method. In addition, an expert survey was conducted to shed light on the evaluation of coping resources. In this paper, we describe the components of the assessment and propose different aggregation approaches which each enhances the understanding of spatial-temporal impacts of a power outage, and, hence, increases the forecasting capability for disaster management authorities. For demonstration purposes, the assessment is implemented for the case of the city of Mannheim, Germany.
Compound disasters are defined as double- or triplepunch disasters. As such, they cause more serious cumulative damage than individual disasters occurring independently. The independent occurrence of Tokyo metropolitan inland earthquakes is expected to kill 11,000 and cause ¥112 trillion in damage. An earthquake in Tokyo would also destroy river levees, coastal dikes, and disaster measure facilities such as water gates and locks due to liquefaction. Following such a earthquake, river flooding by the Tone and Arakawa rivers or storm surge overflow around Tokyo bay could easily occur along with strong typhoons. An Edo period (1603-1868) compound disaster involved the 1855 Ansei Edo earthquake and the 1856 Ansei Edo storm surge. With global warming progressively worsening, huge floods and storm surges are increasingly likely to occur independently. The risk that they will occur as part of a compound disaster is also increasing. Catastrophic disasters are characterized by being super-wide in area damage, compound in combining disasters, and prolonged in recovery. With the vast sea-level or low areas in Tokyo, long-term submergence due to inundation will be unavoidable. The most difficult problem, however, will be how to evacuate over 1 million people.