The data gap: An analysis of data availability on disaster losses in sub-Saharan African cities

Osuteye, Emmanuel; Johnson, Cassidy; Brown, Donald A.

doi:10.1016/j.ijdrr.2017.09.026

Cited by 73 publications

(51 citation statements)

References 8 publications

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“…More than 100 nations, primarily in low-and middle-income countries, lack functioning CRVS systems, with only 57% of countries, territories, and areas assessed by the UN Statistical Division having at least 90% death registration coverage in 2014 (Byass 2007; World Bank and WHO 2014). A CRVS scaling-up investment plan has set a goal of universal civil registration Although all countries are vulnerable to disasters and loss of life, there is generally a higher exposure to disasters and the risk of death in low-and middleincome countries, which are the same countries that tend to lack vital registration data-further magnifying the data gap (Osuteye et al 2017). This is summarized in Fig.…”

Section: Death Datamentioning

confidence: 99%

Challenges with Disaster Mortality Data and Measuring Progress Towards the Implementation of the Sendai Framework

Green

Lysaght

Saulnier

et al. 2019

Int J Disaster Risk Sci

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Disasters exact a heavy toll globally. However, the degree to which we can accurately quantify their impact, in particular mortality, remains challenging. It is critical to ensure that disaster data reliably reflects the scale, type, and distribution of disaster impacts given the role of data in: (1) risk assessments; (2) developing disaster risk management programs; (3) determining the resources for response to emergencies; (4) the types of action undertaken in planning for prevention and preparedness; and (5) identifying research gaps. The Sendai Framework for Disaster Risk Reduction 2015-2030s seven global disaster-impact reduction targets represent the first international attempt to systematically measure the effectiveness of disaster-impact reduction as a means of better informing policy with evidence. Target A of the Sendai Framework aims to ''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.'' This article provides an overview of the complexities associated with defining, reporting, and interpreting disaster mortality data used for gauging success in meeting Target A, acknowledging different challenges for different types of hazard events and subsequent disasters. It concludes with suggestions of how to address these challenges to inform the public health utility of monitoring through the Sendai Framework.

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Section: Death Datamentioning

confidence: 99%

Challenges with Disaster Mortality Data and Measuring Progress Towards the Implementation of the Sendai Framework

Green

Lysaght

Saulnier

et al. 2019

Int J Disaster Risk Sci

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“…Yet many of the records providing this type of information that are normally available in wealthier cities are absent or partial in many sub-Saharan African cities (Osuteye et al, 2016). Yet many of the records providing this type of information that are normally available in wealthier cities are absent or partial in many sub-Saharan African cities (Osuteye et al, 2016).…”

Section: Methodological Deficitmentioning

confidence: 99%

“…An analysis of DesInventar data from Kampala, Nairobi, Niamey, Dakar and Freetown (Osuteye et al, 2016) suggested that the major losses in urban disasters were from flooding, epidemics, fires and accidents, and to a smaller extent structural collapse, industrial disasters, drowning and storms. It initially began in Latin America in the 1990s, but has subsequently been applied in more than 90 countries around the world.…”

Section: Documentary and Institutional Analysismentioning

confidence: 99%

A spectrum of methods for a spectrum of risk: Generating evidence to understand and reduce urban risk in sub‐Saharan Africa

Dodman

Adelekan

Brown

et al. 2018

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Many African towns and cities face a range of hazards, which can best be described as representing a “spectrum of risk” of events that can cause death, illness or injury, and impoverishment. Yet despite the growing numbers of people living in African urban centres, the extent and relative severity of these different risks is poorly understood. This paper provides a rationale for using a spectrum of methods to address this spectrum of risk, and demonstrates the utility of mixed‐methods approaches in planning for resilience. It describes activities undertaken in a wide‐ranging multi‐country programme of research, which use multiple approaches to gather empirical data on risk, in order to build a stronger evidence base and provide a more solid base for planning and investment. It concludes that methods need to be chosen in regard to social, political economic, biophysical and hydrogeological context, while also recognising the different levels of complexity and institutional capacity in different urban centres. The paper concludes that as well as the importance of taking individual contexts into account, there are underlying methodological principles – based on multidisciplinary expertise and multi‐faceted and collaborative research endeavours – that can inform a range of related approaches to understanding urban risk in sub‐Saharan Africa and break the cycle of risk accumulation.

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“…Such an approach is no longer a realistic one to take [16], as environmental issues are increasingly becoming subjects of far-reaching commercial, regulatory and social policies (cf. the Paris Agreement), and of serious public interest and debate, with examples around the world such as floods in the UK [17] and sub-Saharan Africa [18], and droughts in Australia [19] and California [20], to name but a few. In this article, we report on the experiences of the Environmental Virtual Observatory pilot (EVOp) project [21] in addressing many of the above issues by not just developing a cloud-based system for integrating multi-sourced data and models, but also adopting development and stakeholder engagement practices that maximise the impact of the developed technology.…”

Section: Introductionmentioning

confidence: 99%

Widening the Circle of Engagement Around Environmental Issues using Cloud-based Tools

Elkhatib

Gemmell

Vitolo

et al. 2019

2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)

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Environmental data are being generated and collected at unprecedented rates. However, the diversity in form and format of these environmental assets poses challenges for collaborative and reproducible science. Moreover, access constraints that surround environmental data lead to difficulty in use and interpretation of results. Cloud computing offers high potential to break down such barriers and engender collaboration, attribution, reuse, and reproducibility. In this article we review the design of the Environmental Virtual Observatory pilot (EVOp) that was conceived as a cloud-enabled virtual research space for different users interested in environmental science, ranging from domain specialists to the general public. We discuss the key technologies and processes used: a hybrid cloud infrastructure; standard service interfaces; a unified service delivery platform; and a test-driven development cycle. We also discuss the methodology by showcasing one of the exemplars developed in EVOp, stressing the importance of weaving stakeholder engagement from the beginning and throughout the process. We also briefly highlight some of the lessons learnt of working in an interdisciplinary team.

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The data gap: An analysis of data availability on disaster losses in sub-Saharan African cities

Cited by 73 publications

References 8 publications

Challenges with Disaster Mortality Data and Measuring Progress Towards the Implementation of the Sendai Framework

Challenges with Disaster Mortality Data and Measuring Progress Towards the Implementation of the Sendai Framework

A spectrum of methods for a spectrum of risk: Generating evidence to understand and reduce urban risk in sub‐Saharan Africa

Widening the Circle of Engagement Around Environmental Issues using Cloud-based Tools

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