Prof. Guoqiang Shen Ph.D (U.S.)

Professor in Regional and City Planning (Collage of Architecture)

University of Oklahoma.

 

Field:

Urban and Regional Planning

 

Research interest:

urban transportation planning, freight transportation and logistics,
urban spatial analysis, GIS, applied operations research, regional science,
urban design and physical planning, real estate development, and
comparative international urban and planning issues (particularly in the USA and China).

 

Global Risk Indexes and Socio-Economic Factors for Country-Level Multi-Disasters

 

Abstract:

   This research first develop a portfolio-based risk model and applies it to global natural and technological disaster recorded for the 1900-2015 period in the EM-DAT database developed by the Centre for Research on the Epidemiology of Disaster (CRED). Disaster risk, measured as country-level expected values of historical fatality, injury, people affected, and damage are computed for nearly 200 nations. Relevant measure of each county's expected risk, such as its standard deviation, coefficient of variance, range, and rank are also calculated and used together with the expected risk to assess a country's overall risk. Social-economic-physical factors from the World Development Index developed by the United Nations (UN) and relevant yo natural and tech disaster occurrences and risk are then identified using multivariate regression with high R-square values at 95% to 99% confidence intervals.

   The result show that high natural and tech risk concentrate in a small number of countries, which are typically large in population, fast in development or well advance in industrialization and technology, with the top ones such as China, India, Bangladesh in Asia, U.S., Mexico, Canada in North America, Turkey, Russia, France, Germany in Europe, and Algeria, Egypt and Ethiopia in Africa. Also, important social, economic, and physical factors, such as population, territory, GDP, income, transportation and CO2 emission, are strong in explaining and predicting country-level natural and tech risk.

 

Keywords:

Natural and technological disaster; country-level risk; fatality, injury, affected, and damage; risk index, socio-economic factor