TL;DR: The Social Vulnerability Index (SoVI) as discussed by the authors is an index of social vulnerability to environmental hazards based on county-level socioeconomic and demographic data collected from the United States in 1990.
Abstract: Objective. County-level socioeconomic and demographic data were used to construct an index of social vulnerability to environmental hazards, called the Social Vulnerability Index (SoVI) for the United States based on 1990 data.
Methods. Using a factor analytic approach, 42 variables were reduced to 11 independent factors that accounted for about 76 percent of the variance. These factors were placed in an additive model to compute a summary score—the Social Vulnerability Index.
Results. There are some distinct spatial patterns in the SoVI, with the most vulnerable counties clustered in metropolitan counties in the east, south Texas, and the Mississippi Delta region.
Conclusion. Those factors that contribute to the overall score often are different for each county, underscoring the interactive nature of social vulnerability—some components increase vulnerability; others moderate the effects.
TL;DR: In this article, the authors developed the Livelihood Vulnerability Index (LVI) to estimate climate change vulnerability in the Mabote and Moma districts of Mozambique, and collected data on socio-demographics, livelihoods, social networks, health, food and water security, natural disasters and climate variability.
Abstract: We developed the Livelihood Vulnerability Index (LVI) to estimate climate change vulnerability in the Mabote and Moma Districts of Mozambique. We surveyed 200 households in each district to collect data on socio-demographics, livelihoods, social networks, health, food and water security, natural disasters and climate variability. Data were aggregated using a composite index and differential vulnerabilities were compared. Results suggest that Moma may be more vulnerable in terms of water resources while Mabote may be more vulnerable in terms of socio-demographic structure. This pragmatic approach may be used to monitor vulnerability, program resources for assistance, and/or evaluate potential program/policy effectiveness in data-scarce regions by introducing scenarios into the LVI model for baseline comparison.
TL;DR: The preparedness and vulnerability of African countries against their risk of importation of COVID-19 is evaluated, finding that countries with the highest importation risk have moderate to high capacity to respond to outbreaks and countries at moderate risk have variable capacity and high vulnerability.
TL;DR: The conceptual requirements for an adequate CSI are: (i) to consider environmental, economic and social aspects from the viewpoint of strong sustainability; (ii) to capture external impacts (leakage effects) of city on other areas beyond the city boundaries particularly in terms of environmental aspects; (iii) to create indices/indicators originally for the purpose of assessing city sustainability; and (iv) to be able to assess world cities in both developed and developing countries using CSI as discussed by the authors.
TL;DR: In this paper, several link importance indices and site exposure indices are derived, based on the increase in generalised travel cost when links are closed, for the road network of northern Sweden.
Abstract: The reliability and vulnerability of critical infrastructures have attracted a lot of attention recently. In order to assess these issues quantitatively, operational measures are needed. Such measures can also be used as guidance to road administrations in their prioritisation of maintenance and repair of roads, as well as for avoiding causing unnecessary disturbances in the planning of roadwork. The concepts of link importance and site exposure are introduced. In this paper, several link importance indices and site exposure indices are derived, based on the increase in generalised travel cost when links are closed. These measures are divided into two groups: one reflecting an “equal opportunities perspective”, and the other a “social efficiency perspective”. The measures are calculated for the road network of northern Sweden. Results are collected in a GIS for visualisation, and are presented per link and municipality. In view of the recent great interest in complex networks, some topological measures of the road network are also presented.