scholarly journals Benchmarking Community Disaster Resilience in Nepal

2020 ◽  
Vol 17 (6) ◽  
pp. 1985 ◽  
Author(s):  
Sanam K. Aksha ◽  
Christopher T. Emrich
Keyword(s):  
Disaster Response ◽  
Census Data ◽  
Local Level ◽  
Recovery Period ◽  
Principal Component ◽  
Large Earthquake ◽  
Capital City ◽  
Disaster Resilience ◽  
Recovery Capacity ◽  
Community Disaster Resilience

Building disaster resilience is a stated goal of disaster risk reduction programs. Recent research emphasizes a need for a greater understanding of community disaster response and recovery capacity so that communities can absorb shocks and withstand severe conditions and progress through the recovery period more efficiently. Nepal, which is prone to a multitude of hazards and having recently experienced a large earthquake in 2015, provides a unique opportunity for exploring disaster resilience in the developing world context. To date, no study investigating community disaster resilience across the entire country of Nepal exists. This study quantifies disaster resilience at Nepal’s village level, primarily using census data. Guided by the Disaster Resilience of Place (DROP) model, 22 variables were selected as indicators of social, economic, community, infrastructure, and environmental resilience. Community resilience was assessed for 3971 village development communities (VDCs) and municipalities while using a principal component analysis. Additionally, a cluster analysis was performed to distinguish spatial patterns of resilience. Analyses reveal differential community disaster resilience across the country. Communities in the capital city Kathmandu and in the western and far western Hill are relatively resilient. While the entire Tarai region, which holds the greatest proportion of Nepal’s population, exhibits relatively low levels of resilience when compared to the rest of the county. The results from this analysis provide empirical evidence with the potential to help decision-makers in the allocation of scarce resources to increase resilience at the local level.

Informational capital and disaster resilience: the case of Jalin Merapi

2016 ◽  
Vol 25 (3) ◽  
pp. 395-411 ◽  
Author(s):  
Justyna Tasic ◽  
Sulfikar Amir
Keyword(s):  
Social Capital ◽  
Information Technology ◽  
Disaster Management ◽  
Disaster Response ◽  
Disaster Mitigation ◽  
Disaster Resilience ◽  
Community Based ◽  
Content Type ◽  
Grassroots Groups ◽  
Community Disaster Resilience

Purpose – The purpose of this paper is to present a concept of informational capital to explain the interplay between social capital and information technology in community-based disaster management. It aims to discuss the role and formation of informational capital in community disaster resilience. Design/methodology/approach – Based on an exploratory case study focusing on the 2010 eruption of Merapi volcano in Central Java, Indonesia, the paper seeks to analyse the emergence of disaster response fully organized by grassroots groups in Yogyakarta. In advancing the concept of informational capital, this paper analyses how the grassroots groups were able to mobilize resources for disaster mitigation, through which social capital became the foundation of community-based disaster response and recovery. Furthermore, the mobilization of social capital was significantly enhanced by mutual interactions facilitated by the use of information technology. This is evident in the role of Jalin Merapi, a web-based organization formed to respond to the crisis after the volcano eruption. Findings – The concept of informational capital revolves around the ways in which social capital and information act as crucial assets when a disaster strikes. Through informational capital, strong community bonds and ties are transformed into organized information that effectively facilitates collective action to face the emergency crisis. Originality/value – This paper presents a new concept of informational capital and highlights its key role in facilitating disaster management processes and contribution to community disaster resilience.

Socio-economic factors that predict psychiatric admissions at a local level

1999 ◽  
Vol 29 (5) ◽  
pp. 1235-1241 ◽  
Author(s):  
SIÂN KOPPEL ◽  
PETER McGUFFIN
Keyword(s):  
Census Data ◽  
Local Level ◽  
Common Factor ◽  
Psychiatric Morbidity ◽  
Capital City ◽  
Economic Factors ◽  
Psychiatric Admission ◽  
Psychiatric Admissions ◽  
Deprivation Indices ◽  
Socio Economic Factors

Background. The aim of the study was to confirm the predictive relationship between socio-economic factors and psychiatric admissions at a fine grain geographical level. The strength of association was compared with those of other studies that have looked at separate diagnostic groups.Method. Psychiatric admissions were from electoral wards of the County of South Glamorgan, which encompasses the capital city of Wales, Cardiff. Standardized psychiatric admission ratios (SAR) for different diagnostic groups were calculated for a 5-year period. The ecological association with deprivation indices and with single variables at the level of electoral ward was examined. Of a total of 15266 psychiatric admissions, 11296 were analysed.Results. Psychiatric morbidity, reflected in SAR was inversely related to socio-economic deprivation for both sexes. This applied to all diagnostic groups except organic disorders. The relationship was most marked for schizophrenia, delusional disorders and substance abuse, closely followed by personality disorders, and less for affective and neurotic disorders. Little difference existed between three composite indices of deprivation (Carstairs, Jarman, Townsend), but the marginally best predictor was that designed by Jarman. However, low rates of car ownership and high unemployment were as good at predicting SAR as any of the compound indices.Conclusion. Socio-economic factors account for almost 50% of the variance in psychiatric admission rates between electoral wards. The degree of association between psychiatric morbidity and deprivation varies between diagnostic groups, arguing against a common factor linking deprivation and psychiatric admissions generally. Frequently updated unemployment figures provide nearly as useful and more immediate information than 10-yearly Census data used to calculate the deprivation indices. These figures may be used for needs assessment and targeting resources at a local level.

scholarly journals Real-time automatic uncertainty estimation of coseismic single rectangular fault model using GNSS data

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Keitaro Ohno ◽  
Yusaku Ohta ◽  
Satoshi Kawamoto ◽  
Satoshi Abe ◽  
Ryota Hino ◽  
...  
Keyword(s):  
Real Time ◽  
Disaster Response ◽  
Order Approximation ◽  
Nonlinear Problems ◽  
Large Earthquake ◽  
Fault Model ◽  
Deformation Monitoring ◽  
Model Parameters ◽  
The Sea Of Japan ◽  
Plate Interface

AbstractRapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time.

scholarly journals Twitter Use in Hurricane Isaac and Its Implications for Disaster Resilience

2021 ◽  
Vol 10 (3) ◽  
pp. 116
Author(s):  
Kejin Wang ◽  
Nina S. N. Lam ◽  
Lei Zou ◽  
Volodymyr Mihunov
Keyword(s):  
Census Data ◽  
Situational Awareness ◽  
Research Question ◽  
Community Resilience ◽  
Disaster Resilience ◽  
Positive Correlations ◽  
Social Environmental ◽  
Use Of Social Media ◽  
Resilience Indicators ◽  
Three Phases

Disaster resilience is the capacity of a community to “bounce back” from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With increasing use of social media, new data sources such as Twitter could be utilized to monitor human response during different phases of disasters to better understand resilience. An important research question is: Does Twitter use correlate with disaster resilience? Specifically, will communities with more disaster-related Twitter uses be more resilient to disasters, presumably because they have better situational awareness? The underlying issue is that if there are social and geographical disparities in Twitter use, how will such disparities affect communities’ resilience to disasters? This study examines the relationship between Twitter use and community resilience during Hurricane Isaac, which hit Louisiana and Mississippi in August 2012. First, we applied the resilience inference measurement (RIM) model to calculate the resilience indices of 146 affected counties. Second, we analyzed Twitter use and their sentiment patterns through the three phases of Hurricane Isaac—preparedness, response, and recovery. Third, we correlated Twitter use density and sentiment scores with the resilience scores and major social–environmental variables to test whether significant geographical and social disparities in Twitter use existed through the three phases of disaster management. Significant positive correlations were found between Twitter use density and resilience indicators, confirming that communities with higher resilience capacity, which are characterized by better social–environmental conditions, tend to have higher Twitter use. These results imply that Twitter use during disasters could be improved to increase the resilience of affected communities. On the other hand, no significant correlations were found between sentiment scores and resilience indicators, suggesting that further research on sentiment analysis may be needed.

scholarly journals Spatial Conditions Supporting Sustainable Development of Enterprises on Local Level

2021 ◽  
Vol 13 (4) ◽  
pp. 2292
Author(s):  
Aneta Ptak-Chmielewska ◽  
Agnieszka Chłoń-Domińczak
Keyword(s):  
Social Insurance ◽  
Small And Medium Enterprises ◽  
Local Level ◽  
Principal Component ◽  
Sources Of Information ◽  
Clustering Methods ◽  
Significant Information ◽  
The Status ◽  
Medium Enterprises ◽  
High Share

Micro, small and medium enterprises (MSMEs) represent more than 99% of enterprises in Europe. Therefore, knowledge about this sector, also in the spatial context is important to understand the patterns of economic and social development. The main goal of this article is an analysis of spatial conditions and the situation of MSMEs on a local level using combined sources of information. This includes data collected in the Social Insurance Institution and Tax registers in Poland, which provides information on the employment, wages, revenues and taxes paid by the MSMEs on a local level as well as contextual statistical information. The data is used for a diagnosis of spatial circumstances and discussion of conditions influencing the status of the MSMEs sector in a selected region (voivodeship) in Poland. Taxonomy methods including factor analysis and clustering methods based on k-means and SOM Kohonen were used for selecting significant information and grouping of the local units according to the situation of the MSMEs. There are eight factors revealed in principal component analysis and five clusters of local units distinguished using these factors. These include two clusters with a high share of rural local units and two clusters with a high share of rural-urban and urban local units. Additionally, there was an outstanding cluster with only two dominant urban local units. Factors show differences between clusters in the situation of MSMEs sector and infrastructure. Different spatial conditions in different regions influence the situation of MSMEs.

Resource access mechanisms in networks and SME survival in Ghana

2018 ◽  
Vol 12 (5) ◽  
pp. 611-631 ◽  
Author(s):  
George Acheampong ◽  
Raphael Odoom ◽  
Thomas Anning-Dorson ◽  
Patrick Amfo Anim
Keyword(s):  
Census Data ◽  
Local Level ◽  
Directed Network ◽  
Resource Access ◽  
Content Type ◽  
Structural Hole ◽  
One Year ◽  
Global And Local ◽  
Access Mechanisms ◽  
Global Influence

Purpose The study aims to determine the resource access mechanism in inter-firm networks that aids SME survival in Ghana. Design/methodology/approach The authors collect census data on a poultry cluster in Ghana and construct a directed network. The network is used to extract direct and indirect ties both incoming and outgoing, as well as estimate the structural holes of the actors. These variables are used to estimate for survival of SMEs after a one-year period using a binary logit model. Findings The study finds that out-indirect ties and structural hole have a significant influence on SME survival. This works through the global influence and the vision advantage that these positions and ties offer the SMEs. Originality/value The study offers SMEs a choice of whom to collaborate with for information (resources) in the form of outgoing and incoming ties at both the global and local level.

Enhancing Community Disaster Resilience Through Mass Sporting Events

2011 ◽  
Vol 5 (4) ◽  
pp. 310-315 ◽  
Author(s):  
Danielle M. McCarthy ◽  
George T. Chiampas ◽  
Sanjeev Malik ◽  
Kendra Cole ◽  
Patricia Lindeman ◽  
...  
Keyword(s):  
Emergency Management ◽  
Disaster Preparedness ◽  
Disaster Response ◽  
Federal Emergency Management Agency ◽  
Disaster Resilience ◽  
Sporting Events ◽  
Practical Application ◽  
Complex Action ◽  
Management Agency ◽  
Communication And Coordination

ABSTRACTDisaster response requires rapid, complex action by multiple agencies that may rarely interact during nondisaster periods. Failures in communication and coordination between agencies have been pitfalls in the advancement of disaster preparedness. Recommendations of the Federal Emergency Management Agency address these needs and demonstrate commitment to successful disaster management, but they are challenging for communities to ensure. In this article we describe the application of Federal Emergency Management Agency guidelines to the 2008 and 2009 Chicago Marathon and discuss the details of our implementation strategy with a focus on optimizing communication. We believe that it is possible to enhance community disaster preparedness through practical application during mass sporting events.(Disaster Med Public Health Preparedness. 2011;5:310–315)

scholarly journals Regional Sustainable Development – Czech Region Ranking UsingMulti-criteria Decision Analysis

2013 ◽  
Vol 2 (4) ◽  
pp. 253 ◽  
Author(s):  
Lenka Hudrlikova ◽  
Ludmila Petkovova
Keyword(s):  
Sustainable Development ◽  
Decision Analysis ◽  
Principal Component ◽  
Composite Indicator ◽  
Capital City ◽  
Development Indicators ◽  
Border Regions ◽  
Advantages And Disadvantages ◽  
Linear Aggregation ◽  
Regional Sustainable Development

The aim of the paper is to provide a ranking of the Czech NUTS 3 regions based onsustainable development indicators. The original list of indicators was published by theCzech Statistical Office in 2008 and reviewedin 2010. In the analysis the same set ofindicators with the latest data was used. The indicators in each pillar are merged by meansof linear aggregation withweights derived from the principal component analysis.Because three pillars of sustainable development (environmental, economic and social)are assumed to be non-compensable, the multiple-criteria decision analysis is applied on apillar level in the final composite indicator. Both two main approaches – Borda andCondorcet were considered. Since the Borda approach leads to the compensability of theindicators, the Condorcet approach was in the spotlight. Advancedrules and adjustmentfor Condorcet approach were employed. Advantages and disadvantages of the methodsare provided. As a result more final rankings exist. The deep discussion about the resultsis provided. The special attention is paid to the capital city Prague, border regions, andindustrial regions. In addition, the correlation between final ranking and other indicatorsis tested.

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