International Journal of Disaster Risk Reduction

The MATLAB codes are designed to simulate the proposed framework for quantitatively assessing the effect of catastrophe insurance on community recovery.

The bibliographic records were retrived from the WoS Core Collection Database on 11th April 2018. The search query was public emergency OR public crisis OR public risk OR catastrophe OR disaster AND governance by themes from 1993-2018. The search results were again filtered by literature type "Article and Review papers" and Category "Environmental studies, public administration, political science, planning development, sociology/social science interdisciplinary, social issues/social works". The final dataset include 1,354 records with 67,646 references. The data analysis and visualisation employed tools including VOSviewer, CiteSpace, and Leximancer.

This dataset includes 27,116 landslide risk polygons distributed in 443 Brazilian municipalities. In each of these risk areas, the vulnerability index was calculated according to the methodology of the article.

We have carried out Principal Component Analysis (PCA) for the Coastal Area of Bangladesh at Union and Mouza level (south-eastern part of the coastal region). The excel files contain the score of PCs and also the composite score. We have uploaded the do file for the Stata software as well as the data file which is readable in Stata software.

Use the real data from actual disaster rescue activities to build a decision table, as shown in Table 2

By collecting 36 years of accident investigation reports from 1983 to 2018 from news websites, emergency management department and tourism websites around the world, seventy-five typical emergency cases of scenic areas were screened.The criterion of case collection is directly or indirectly related to the security of scenic areas.The scenic areas involved are located in the United States, the United Kingdom, China, Thailand, Japan, Malaysia, Singapore and various other countries. They include 9 types of accidents: traffic accidents, amusement facilities accidents, cable car accidents, natural disasters, accidents involving collapses and trampling, fire accidents, accidents involving animals attacking humans, drowning accidents and social safety accidents.

This dataset was provided by Reconstruction Agency on November 16, 2018. The following URL covers more detailed dataset on disaster public housing for the municipalities affected by the 2011 Great East Japan Earthquake, which was used in the article. http://www.reconstruction.go.jp/topics/main-cat1/sub-cat1-12/20181114094606.html

SPSS data file

<The files we uploaded> We uploaded four excel files; “Population_2019.02.25.xlsx”, “AMI_2019.02.25.xlsx”, “Fukushima_pop_2019.02.25.xlsx”, and “Fukushima_AMI_2019.02.25.xlsx”. Each file is explained in detail below. I. “Population_2019.02.25.xlsx” is composed of five sheets. i. Model population: The Japanese model population in 1985, reported by age group. ii. Japan: Population in Japan, from 2008 to 2016, reported by age group. iii. Iwate: Population in Iwate Prefecture, from 2008 to 2016, reported by age group. iv. Miyagi: Population in Miyagi Prefecture, from 2008 to 2016, reported by age group. v. Fukushima: Population in Fukushima Prefecture, from 2008 to 2016, reported by age group. II. “AMI_2019.02.25.xlsx” is composed of four sheets. i. Japan: The number of death due to AMI in Japan, from 2008 to 2016, reported by age group. ii. Iwate: The number of death due to AMI in Iwate Prefecture, from 2008 to 2016, reported by age group. iii. Miyagi: The number of death due to AMI in Miyagi Prefecture, from 2008 to 2016, reported by age group. iv. Fukushima: The number of death due to AMI in Fukushima Prefecture, from 2008 to 2016, reported by age group. III. “Fukushima_pop_2019.02.25.xlsx” is composed of six sheets. These sheets report the population in each district in Fukushima Prefecture, by age group and the ID codes to the districts. This excel file is divided into six sheets by the years from 2009 to 2016, one by one. IV. “Fukushima_AMI_2019.02.25.xlsx” is composed of one sheet. The sheet, named by Fukushima, reports the number of death due to AMI in each district in Fukushima Prefecture, by the years from 2009 to 2014 and the ID codes to the districts. <ID code> 1) Fukushima Prefecture is represented by ID: 7000. 2) The evacuation area is composed of six districts (ID: 7543, 7545, 7546, 7547, 7548, 7564). 3) The eastern area is composed of seven districts (ID: 7204, 7209, 7212, 7541, 7542, 7544, 7561). 4) The middle area is composed of 29 districts (ID: 7201, 7203, 7205, 7207, 7210, 7211, 7213, 7214, 7301, 7303, 7308, 7322, 7342, 7344, 7461, 7464, 7465, 7466, 7481, 7482, 7483, 7484, 7501, 7502, 7503, 7504, 7505, 7521, 7522). 5) The western area is composed of 17 districts (ID: 7202, 7208, 7362, 7364, 7367, 7368, 7402, 7405, 7407, 7408, 7421, 7422, 7423, 7444, 7445, 7446, 7447).

Data and replication instructions found here can be used to replicate the results presented in: Scherzer, Sabrina, Päivi Lujala and Jan Ketil Rød (2019). A community resilience index for Norway: An adaptation of the Baseline Resilience Indicators for Communities (BRIC). International Journal for Disaster Risk Reduction. For reproduction of the vulnerability indices (Rød et al. 2015) included in the dataset, please contact Jan Ketil Rød (jan.rod@ntnu.no). All other queries regarding the data or replication instructions, please contact Sabrina Scherzer (sabrina.scherzer@ntnu.no)