A framework to assess quality and uncertainty in disaster loss data

Romão, Xavier; Paupério, Esmeralda

doi:10.1007/s11069-016-2364-3

Cited by 11 publications

(10 citation statements)

References 79 publications

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“…In spite of the differences in uncertainties across different actors, scholars argue that epistemological differences amongst different study areas have contributed even more to the difficulty in finding a consensus regarding uncertainty. Additionally, different articles use different names for the same thing, or the opposite (the same name for different things) when talking about uncertainty (Romao and Pauperio 2016). The various existing uncertainty definitions and typologies hinder clear communication and, consequently, the understanding of existing uncertainties in the field of natural hazards according to (Kunz et al 2011).…”

Section: Theoretical and Conceptual Backgroundmentioning

confidence: 99%

“…Speaking of incomplete knowledge, the majority of the authors (Levin et al 2004, Han 2012, Kox et al 2015, Romao and Pauperio 2016 see it as a source (i.e. cause or originating place of uncertainty) rather than a state or condition.…”

Section: Definition Of Uncertaintymentioning

confidence: 99%

“…cause or originating place of uncertainty) rather than a state or condition. Such sources of uncertainty mainly include uncertainties arising due to lack of knowledge (Thompson 2002, Levin et al 2004; due to randomness or variability (Kox et al 2015, Romao andPauperio 2016); from the complexity of understanding different phenomena, from the difficulties encountered in decision-making processes (Laes et Epistemic uncertainty is mainly related to the unknowns (Doyle et al 2014). It is defined as a state of mind and a reflection of our own incomplete knowledge (Thompson 2002, Eiser et al 2012, Harris 2015.…”

Section: Definition Of Uncertaintymentioning

confidence: 99%

See 2 more Smart Citations

Radiation risks and uncertainties: a scoping review to support communication and informed decision-making

et al. 2020

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Although radiation protection is challenged by many uncertainties, there is no systematic study investigating the definitions and types of these uncertainties. To address this gap, in this paper we offer a scoping review to comprehensively analyse, for the first time, peer-reviewed scientific articles (n = 33) related to uncertainties in the following radiation exposure situations: nuclear emergencies, decommissioning of nuclear/radiological installations and long-term radiological exposure situations (e.g. naturally occurring radioactive materials). The results suggest that firstly, there is no agreement regarding definitions of uncertainty, which is mainly defined based on its sources, types or categories rather than by its meaning. Secondly, different actors are faced with different types of uncertainties. Uncertainties of the scientific community are mostly data and methodology-driven (e.g. dose-response relationships), those of the decision-makers are related to the likely consequences of decision options and public reactions, while laypeople’s uncertainties are mainly related to the trustworthiness of experts or the emotional potential of specific risk exposures. Furthermore, the majority of articles focus on the uncertainties of the scientific community, while those of the information receivers (i.e. decision-makers and laypeople) receive much less consideration. Finally, there was no difference in types of uncertainties across the different risk-related study areas analysed (radiation versus other risks). Based on these findings, we provide some preliminary recommendations regarding research on uncertainty related to radiation protection, as well as communication practices.

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Section: Theoretical and Conceptual Backgroundmentioning

confidence: 99%

Section: Definition Of Uncertaintymentioning

confidence: 99%

Section: Definition Of Uncertaintymentioning

confidence: 99%

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Radiation risks and uncertainties: a scoping review to support communication and informed decision-making

et al. 2020

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“…n any given year, one type of disaster might be costlier than the others. Much of the discussion of uncertainty concerning billion-dollar disasters focuses on uncertainty in estimating the losses from disasters (Romão & Paupério, 2016). A combined approach to all the billion-dollar disasters is hard to nd.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the financial risk of billion-dollar disasters in the United States: Simulating the frequency and economic costs of U.S. natural disasters

Shukla

MacKenzie

2022

Preprint

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The number of billion-dollar natural disasters in the United States has increased from 28 in 1980-1989 to 105 in 2010-2018. During these same time periods, the total cost of these natural disasters increased from $172 billion to $755 billion. Generating probabilistic assessments of the cost of these billion-dollar natural disasters can provide insight into the financial risks posed by these disasters while accounting for the uncertainty and variation in these disasters. This article simulates the frequency and cost of billion-dollar disasters and analyzes the financial risk of these disasters in the United States. We use a probabilistic approach to quantify and create five models. These models are created by fitting probability distributions to the historical cost of billion-dollar disasters. The cost of each billion-dollar natural disaster and U.S. GDP from 1980 to 2018 are analyzed and used. The model that perhaps fits the data best and accounts for the recent increase in the cost and frequency of billion-dollar disasters forecasts that the expected annual cost of these disasters is $91 billion, with about a 1% chance that the annual costs could exceed $500 billion. Simulating the costs and frequency of natural disasters provides an understanding of the risks of different types of disasters to the United States. It helps policymakers allocate resources effectively to build a resilient nation.

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“…description (Romã o, 2016), and there is a relative lack of quantitative research. Qualitative description is the most widely used method to describe the uncertainty in disaster estimation (Van Asselt 2000).…”

Section: Introductionmentioning

confidence: 99%

Quantification of uncertainty in rapid estimation of earthquake fatalities based on scenario analysis

Zhang

Zhao

Wang

et al. 2018

Preprint

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Abstract. The rapid estimation of earthquake fatalities using earthquake parameters is the core basis for emergency response. However, there are numerous factors affecting earthquake fatalities, and it is impossible to obtain an accurate estimation result. The key to solve this problem is quantifying the uncertainty. In this paper, we proposed a new method to estimate earthquake fatalities and quantify the uncertainty based on basic earthquake emergency scenarios. The accuracy of the model is verified by earthquake that occurred during recent year. The preliminary analysis and comparison results show that the model is more effective and reasonable and can also provide a theoretical basis for post-earthquake emergency response.

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A framework to assess quality and uncertainty in disaster loss data

Cited by 11 publications

References 79 publications

Radiation risks and uncertainties: a scoping review to support communication and informed decision-making

Radiation risks and uncertainties: a scoping review to support communication and informed decision-making

Analyzing the financial risk of billion-dollar disasters in the United States: Simulating the frequency and economic costs of U.S. natural disasters

Quantification of uncertainty in rapid estimation of earthquake fatalities based on scenario analysis

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