Central Data Catalog

Citation Information

Type Conference Paper - The 8th annual international conference of the international institute or infrastructure renewal and reconstruction
Title Integrated Vulnerability and Risk Assessment: Case Study in Coastal Communities, Jamaica
Publication (Day/Month/Year) 2012
City Kumamoto
Country/State Japan
URL http://iiirr.ucalgary.ca/files/iiirr/B6-2_.pdf
A risk index model is proposed and applied in this st
udy as a case study. The index model is a compilation
and modification of existing models and takes into
account four factors of risk: hazards, exposure,
vulnerability and capacities and measures. The model
utilizes a combination of quantitative, qualitative and
contextual analyses to carry out a comprehensive assessment of vulnerability in the community of Portland
Cottage, Clarendon, Jamaica. The disc
ussions are generated from prim
ary data collected via questionnaires
administered during a field survey as well as observatio
nal recordings. The findings revealed high levels of
spatial risk and vulnerability. Relationships among so
cial, economic, and demographic variables were
identified as well as the influences of these vulnerabilit
ies on risk and vulnerability. Reduced vulnerabilities
were directly linked to increases in capacities an
d measures, and increased vulnerabilities were related to
weakened capacities and measures. Physical vulnerability was related to the geography of the site but has
been aggravated by anthropogenic factors. Social vulnerab
ility is largely a function of demography, poverty,
tenure of property and perceptions. In the case of percep
tions recent experiences have served to inform and
modify corresponding attitudes and responses. This risk
index model can be further used as an assessment
measure which when applied readily informs communities of
their risk level, highlights high risk areas that
require governmental assistance as well as indicate those ar
eas that require improved capacity and measures
inputs. The results of the index model can be used to
inform policy, augment the existing database in disaster
management and enlighten the decision making process for disaster mitigation.

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