A Proposal to Combine Different Disaster Impact Indicators into a Single Index and Its Application for Countries Supported by the WMO EW4All Initiative
Osvaldo Luiz Leal de Moraes
International Journal of Disaster Risk Science ›› : 1 -16.
A Proposal to Combine Different Disaster Impact Indicators into a Single Index and Its Application for Countries Supported by the WMO EW4All Initiative
In 2022, the United Nations launched the “Early Warnings for All” (EW4All) initiative, which aims to ensure that early warning systems are available to all inhabitants of the world by 2027. It is a response to the fact that climate-related disasters are increasing and many countries still do not have effective systems in place. For EW4All, the World Meteorological Organization (WMO) has selected 30 countries whose meteorological and hydrological services will be supported to strengthen their monitoring capacities for recurrent climate-related hazards in their country. This work aims to assess the impact of disasters in the period from January 2000 to November 2024 for the 30 EW4All countries using a composite scale representing a combination of different impact indicators. The unique feature of this work is that the different societal impacts are summarized in a single index. In this way, a comparative assessment of impacts between countries can be made, which can serve as a basis for action beyond that undertaken by the WMO and purely academic interest. This is a tool that can help decision makers to implement risk management measures. For this study, we selected the Emergency Events Database (EM-DAT) from the available global datasets because it is the only dataset with a time series long enough to fulfill the statistical criteria of this study and also uses a common disaster recording protocol for all countries.
Disaster assessment / Disaster impacts / Disaster risk reduction / Early Warnings for All
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
CRED (Centre for Research on the Epidemiology of Disasters). 2025b. EM-DAT documentation. Introduction. Brussels, Belgium: CRED. https://doc.emdat.be/docs/introduction/. Accessed 5 May 2025. |
| [6] |
CRED (Centre for Research on the Epidemiology of Disasters). 2025b. EM-DAT documentation. Introduction. Brussels, Belgium: CRED. https://doc.emdat.be/docs/introduction/. Accessed 5 May 2025 |
| [7] |
ECLAC (Economic Commission for Latin America and the Caribbean). 2023. Handbook for estimating the socio-economic and environmental effects of disasters. https://reliefweb.int/report/world/handbook-estimating-socio-economic-and-environmental-effects-disasters. Accessed 6 Aug 2025. |
| [8] |
Foster,V., A. Rana, and N. Gorgulu. 2022. Understanding public spending trends for infrastructure in developing countries. Policy Research Working Paper 9903. Washington, DC: World Bank Group. |
| [9] |
Foster, V., N. Gorgulu, S. Straub, and M. Vagliasindi. 2023. The impact of infrastructure on development outcomes: A qualitative review of four decades of literature. Policy Research Working Paper 10343. Washington, DC: World Bank. |
| [10] |
|
| [11] |
Hong, B., B.J. Bonczak, A. Gupta, and C.E. Kontokosta. 2021. Measuring inequality in community resilience to natural disasters using large-scale mobility data. Nature Communications 12: Article 1870. |
| [12] |
IDMC (Internal Displacement Monitoring Centre). 2021. Global report on internal displacement 2021. https://www.internal-displacement.org/global-report/grid2021/. Accessed 8 Jul 2025. |
| [13] |
Jones, R.L., A. Kharb, and S. Tubeuf. 2023. The untold story of missing data in disaster research: A systematic review of the empirical literature utilising the Emergency Events Database (EM-DAT). Environmental Research Letters 18: Article 103006. |
| [14] |
|
| [15] |
|
| [16] |
Liz, T., R. Below, and D. Guha-Sapir. 2006. An analytical review of selected data sets on natural disasters and impacts. In Proceedings of the NDP/CRED Workshop on Improving Compilation of Reliable Data on Disaster Occurrence and Impact, 2–4 April 2006, Bangkok, Thailand. |
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, et al. 2021. Weather and climate extreme events in a changing climate. In Climate change 2021: The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, ed. V. Masson-Delmotte, P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, et al., 1513–1766. Cambridge, UK: Cambridge University Press. |
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
UN (United Nations). 2022. Early Warnings for All. https://www.un.org/en/climatechange/early-warnings-for-all. Accessed 30 May 2025. |
| [29] |
UNDRR (United Nations Office for Disaster Risk Reduction). 2015. Global assessment report on disaster risk reduction (GAR). https://www.undrr.org/publication/global-assessment-report-disaster-risk-reduction-2015. Accessed 30 Sept 2025. |
| [30] |
UNDRR (United Nations Office for Disaster Risk Reduction). 2022a. Global assessment report on disaster risk reduction (GAR). https://www.undrr.org/gar/gar2022-our-world-risk-gar. Accessed 15 Jun 2025. |
| [31] |
UNDRR (United Nations Office for Disaster Risk Reduction). 2022b. The human cost of disasters: An overview of the last 20 years (2000–2019). https://www.undrr.org/publication/human-cost-disasters-overview-last-20-years-2000-2019. Accessed 15 Jun 2025. |
| [32] |
WEF (World Economic Forum). 2015. How can we measure the impact of natural disasters? Geo-Economics and Politics, 16 March 2015. https://www.weforum.org/agenda/2015/03/how-can-we-measure-the-impact-of-natural-disasters/. Accessed 2 Mar 2025. |
| [33] |
WHO (World Health Organization). 2008. The global burden of disease: 2004 update. Geneva: WHO. https://www.who.int/publications/i/item/9789241563710. Accessed 5 May 2025. |
| [34] |
WMO (World Meteorological Organization). 2021a. Climate and weather related disasters surge five-fold over 50 years. 1 September 2021. https://wmo.int/media/news/climate-and-weather-related-disasters-surge-five-fold-over-50-years. Accessed 7 May 2025. |
| [35] |
WMO (World Meteorological Organization). 2021b. Atlas of mortality and economic losses from extremes of weather, climate and water (1970–2019). https://wmo.int/publication-series/atlas-of-mortality-and-economic-losses-from-weather-climate-and-water-related-hazards-1970-2021. Accessed 11 Jan 2025. |
| [36] |
WMO (World Meteorological Organization). 2023. Early Warnings for All in focus: Hazard monitoring and forecasting (2023). https://wmo.int/files/early-warnings-all-focus-hazard-monitoring-and-forecasting. Accessed 5 Apr 2025. |
| [37] |
|
| [38] |
|
| [39] |
|
The Author(s)
/
| 〈 |
|
〉 |