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. 2021 Sep 2;11(1):17625.
doi: 10.1038/s41598-021-96763-0.

Differences in the dynamics of community disaster resilience across the globe

Stefan Hochrainer-Stigler  1 , Stefan Velev  2 , Finn Laurien  2 , Karen Campbell  3   4 , Jeffrey Czajkowski  3   5 , Adriana Keating  2 , Reinhard Mechler  2
Affiliations

Differences in the dynamics of community disaster resilience across the globe

Stefan Hochrainer-Stigler et al. Sci Rep. .

Abstract

The consideration of disaster resilience as a multidimensional concept provides a viable and promising way forward for reducing risk and minimizing impacts today and in the future. What is missing is the understanding of the actual dynamics of resilience over time based on empirical evidence. This empirical understanding requires a consistent measure of resilience. To that end, a Technical Resilience Grading Standard for community flood resilience, was applied in a longitudinal study from 2016 to 2018 in 68 communities across the globe. We analyse the dynamics of disaster resilience using an advanced boosted regression tree modelling framework. The main outcome of our analysis is twofold: first, we found empirical evidence that the dynamics of resilience build on a typology of communities and that different community clusters experience different dynamics; and second, the dynamics of resilience follows transitional behaviour rather than a linear or continuous process. These are empirical insights that can provide ways forward, theoretically as well as practically, in the understanding of resilience as well as in regard to effective policy guidance to enhance disaster resilience.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
FRMT data implementation process. [Source: (Laurien et al.)].
Figure 2
Figure 2
Comparing BL and EL average grades for the five capitals.
Figure 3
Figure 3
Relating the average capital grades with Death and Injury due to flood (O01).
Figure 4
Figure 4
The 10 most important variables for cluster 1 and cluster 3 for the best fitted boosted regression tree model for financial capital.
Figure 5
Figure 5
ICE curves for clusters 1 (a) and 3 (b) for the most influential variable of the best BRT model. The x axis shows the values of the independent variable and the y axis shows the predicted (expected) change while conditionally holding all other variables at their original values. The average of the ICE curves (red line) indicates the average predicted change for the variable value.
See this image and copyright information in PMC

References

    1. CRED/UNISDR. Economic losses, poverty & disasters: 1998–2017. https://www.preventionweb.net/files/61119_credeconomiclosses.pdf (2018).
    1. UNDRR. Sendai Framework for Disaster Risk Reduction 2015–2030. https://www.preventionweb.net/files/43291_sendaiframeworkfordrren.pdf (2015).
    1. United Nations. Transforming our world: the 2030 Agenda for Sustainable Development. https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E (2015).
    1. Munich Re. Topics Geo: Natural catastrophes 2017. https://www.munichre.com/en/risks/natural-disasters-losses-are-trending-... (2018).
    1. Bouwer, L. M. Observed and projected impacts from extreme weather events: implications for loss and damage. In Loss and Damage from Climate Change (eds Mechler, R. et al.) 63–82 (Springer, 2019).

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