Building climate change adaptation indicator set for Moc Hoa district, Long An province

To date, work in the field of climate change adaptation has resulted in many strategies for adaptation. In Vietnam, there have been many climate change adaptation activities implemented but has not been evaluated fully on effectiveness so that we can modify or make a replica of them systematically. In order to evaluate the effectiveness of carried out climate change adaptation activities, it is necessary to assess the current status of climate change adaptation for each local. In this paper, a set of CCA status evaluation indicators was developed and appreciated for Moc Hoa district, Long An province, to support a comprehensive assessment of the adaptation ability of this study area, the validity of investment resources allocation, and vulnerability to expose suitable policies. This set includes three indicators which are natural environment resilience, climate change vulnerability and climate change risk mitigation. The results showed that the environmental resilience indicators and the risk mitigation indicators were arranged at the medium level, while the climate change vulnerability indicators were high.

Residential Vulnerability of Barcelona: Methodology Integrating Multi-Criteria Evaluation Systems and Geographic Information Systems

This article presents the methodology and results of a pioneering investigation in the determination and mapping of socio-residential vulnerability in the city of Barcelona according to a multi-criteria synthetic analysis. The methodology followed is based on a system of indicators elaborated from the exploitation of habitual statistical Open Data complemented with specific unprecedented data elaborated and supplied by the Barcelona City Council. The analysis is based on secondary data and it is structured in georeferenced axes, components, and indicators, which allow determination of the sociodemographic, socioeconomic, and urban and residential space characteristics at neighborhood, population census unit, and urban block level. The objective of the research was to detect, determine, and establish a measure of differentiation relative to the degree of residential vulnerability of some neighborhoods with respect to others, in order to seek prioritization measures for action in the most vulnerable areas. The results of the research provide a series of maps that allow us to define the areas where the highest levels of vulnerability indicators coincide according to a synthetic multi-criteria analysis.

A Comparison of Vulnerability Risks and Conservation Perceptions between Mariculture, Fishery and Ecotourism Livelihood Groups in a Multi-Use MPA in Indonesia

Different livelihoods have different vulnerability risks and influences on the management of marine protected areas (MPAs). This research aimed to compare the seasonal, trend and shock livelihood vulnerability indicators (LVIs) of three dominant livelihood groups and the groups’ perceptions towards supporting MPA conservation efforts. The Anambas Archipelago MPA was selected as the study site. A total of 66 respondents from the three major groups were selected using stratified random sampling and interviewed using a questionnaire containing 14 LVIs. The responses were standardised and aggregated using functional relationships. The groups’ perceptions were determined using frequency distribution and thematic analyses (NVIVO 10). The LVI composite values showed that fishers were the most vulnerable (0.65), followed by fish farmers (0.62) and ecotourism operators (0.47). Fishers and fish farmers expressed high vulnerability due to their dependency on the coastal resources. The ecotourism operators had low vulnerability due to their lower dependency on natural resources, smaller impacts from seasonal weather, low involvement in resource conflicts and greater political support. The three groups supported the MPA regimes despite differences in their knowledge of the MPA restrictions on their livelihood practices. The study’s findings provide key alternative strategies to address the vulnerability risks of the three major groups and to increase their support for conservation goals in similar MPAs.

Determining the Level of Vulnerability to Landslides in Banyubiru Sub-District of Semarang Regency, Central Java, Indonesia

Based on historical record, Semarang Regency in Central Java, Indonesia frequently experiences landslides. Therefore, this study was conducted in Banyubiru Sub District, Semarang Regency, Central Java. The purpose of this study is to determine the variation of field vulnerability to lanslides in the Sub District and also to establish the efforts that must be made to reduce vulnerability in order to decrease losses during the occurance of landslides. Vulnerability includes physical, social, economic and environmental variables. Each region has varying levels, types and characteristics of vulnerability. So as to be refined, the original three classes of the vulnerability index criteria were modified into five criteria i.e. very low vulnerability index criterion (1.00- <1.40), low vulnerability index (1.40-<1.80), moderate vulnerability index (1.80<2.20), high vulnerability index (2.20-<2.40) and very high vulnerability index (2,40- < = 3,0). The results show that the vulnerability level of landslide is divided into 2 parts according to vulnerability indicators in Perka BNPB No.2/2012. Banyubiru sub-district has a moderate and high level of vulnerability. The average of vulnerability rate belongs to the moderate category with an index value of 2,17. The lowest rate is owned by Rowoboni Village while Sepakung village has the highest vulnerability.

Development of a Local, Integrated Disaster Risk Assessment Framework for Malaysia

This study developed an integrated disaster risk assessment framework (IDRAF) to measure disaster risk at the local administrative boundaries in Malaysia. The proposed framework can enhance government effort for disaster risk reduction by implementing an integrated disaster risk framework and guiding decision makers to properly evaluate and analyze risk for mitigation, preparedness, and planning. The framework was developed, expanding from the multi-hazard spatial overlapping and Methods for the Improvement of Vulnerability Assessment in Europe (MOVE) theoretical framework. There are five significant phases to develop this framework: problem formulation, data collection, multi-hazard characterization, multi-dimensional vulnerability characterization, and weightage determination. The IDRAF proposed for Malaysia consists of eight hazards and six vulnerability dimensions, which consist of 16 factors (or vulnerability group) and 54 indicators. The multi-hazard characterization has two components: frequency of occurrence and spatial interaction. The multidimensional vulnerability characterization reduces vulnerability indicators using principal component analysis (PCA). Measuring integrated risk is an effective strategy at the local level or national level to assess the potential disaster impacts in detail and accurately. This study will offer explicit knowledge and boost community competency, creating techniques and tools to analyze various risk factors and vulnerability indicators for decision makers and practitioners.

Identifying At-Risk Communities and Key Vulnerability Indicators in the COVID-19 Pandemic

Throughout the COVID-19 pandemic, certain communities have been disproportionately exposed to detrimental health outcomes and socioeconomic injuries. Quantifying community needs is crucial for identifying testing and service deserts, effectively allocating resources, and informing funding and decision making. We have constructed research-driven metrics measuring the public health and economic impacts of COVID-19 on vulnerable populations. In this work we further examine and validate these indices by training supervised models to predict proxy outcomes and analyzing the feature importances to identify gaps in our original metric design. The indices analyzed in this work are unique among COVID-19 risk assessments due to their robust integration of disparate data sources. Together, they enable more effective responses to COVID-19 driven health inequities.

Estudo e magnitude, transcedência e vulnerabilidade das doenças a partir da mortalidade do Rio Grande do Sul

Adapting statistical criterials, in order to get the magnitude, transcedency and vulnerability indicators from the morthality of Rio Grande do Sul in the year of 1973, is presented a hierardrichal criterian in order to establisch priorities, and wich can be adapted in Odontology with some modifications.

Born in Brussels screening tool: the development of a screening tool measuring antenatal psychosocial vulnerability

Background Antenatal psychosocial vulnerability is a main concern in today’s perinatal health care setting. Undetected psychosocially vulnerable pregnant women and their unborn child are at risk for unfavourable health outcomes such as poor birth outcomes or mental state. In order to detect potential risks and prevent worse outcomes, timely and accurate detection of antenatal psychosocial vulnerability is necessary. Therefore, this paper aims to develop a screening tool ‘the Born in Brussels Screening Tool (ST)’ aimed at detecting antenatal psychosocial vulnerability. Methods The Born in Brussels ST was developed based on a literature search of existing screening tools measuring antenatal psychosocial vulnerability. Indicators and items (i.e. questions) were evaluated and selected. The assigned points for the answer options were determined based on a survey sent out to caregivers experienced in antenatal (psychosocial) vulnerability. Further refinement of the tool’s content and the assigned points was based on expert panels’ advice. Results The Born in Brussels ST consists of 22 items that focus on 13 indicators: communication, place of birth, residence status, education, occupational status, partner’s occupation, financial situation, housing situation, social support, depression, anxiety, substance use and domestic violence. Based on the 168 caregivers who participated in the survey, assigned points account between 0,5 and 4. Threshold scores of each indicator were associated with adapted care paths. Conclusion Generalied and accurate detection of antenatal psychosocial vulnerability is needed. The brief and practical oriented Born in Brussels ST is a first step that can lead to an adequate and adapted care pathway for vulnerable pregnant women.

Role of Multi-resolution Vulnerability Indices in COVID-19 spread: A Case Study in India

Introduction The outbreak of COVID-19 has differentially affected countries in the world, with health infrastructure and other related vulnerability indicators playing a role in determining the extent of the COVID-19 spread. Vulnerability of a geographical region/country to COVID-19 has been a topic of interest, particularly in low- and middle-income countries like India to assess the multi-factorial impact of COVID-19 on the incidence, prevalence or mortality data. Datasets and Methods Based on publicly reported socio-economic, demographic, health-based and epidemiological data from national surveys in India, we compute contextual, COVID-19 Vulnerability Indices (cVIs) across multiple thematic resolutions for different geographical and spatial administrative regions. These multi-resolution cVIs were used in regression models to assess their impact on indicators of the spread of COVID-19 such as the average time-varying instantaneous reproduction number. Results Our observational study was focused on 30 districts of the eastern Indian state of Odisha. It is an agrarian state, prone to natural disasters and one of the largest contributors of an unprotected migrant workforce. Our analyses identified housing and hygiene conditions, availability of health care and COVID preparedness as important spatial indicators. Conclusion Odisha has demonstrated success in containing the COVID-19 infection to a reasonable level with proactive measures to contain the spread of the virus during the first wave. However, with the onset of the second wave of COVID, the virus has been making inroads into the hinterlands and peripheral districts of the state, burdening the already deficient public health system in these areas. The vulnerability index presented in this paper identified vulnerable districts in Odisha. While some of them may not have a large number of COVID-19 cases at a given point of time, they could experience repercussions of the pandemic. Improved understanding of the factors driving COVID-19 vulnerability will help policy makers prioritise resources and regions leading to more effective mitigation strategies for the COVID-19 pandemic and beyond.

Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security

Future freshwater security relies on hydroclimatic (HC) shifts and regimes for sustainable development. The approximation of the HC system faces major uncertainties and complexities due to the incorporation of heavy datasets, characteristics, and constraints. The proposed study focused on the parallel computing of emulator modeling-based spatial optimization to enhance the HC systems with the perspective of future freshwater security in the Upper Chattahoochee River basin (UCR). Here, the framework compiles both physical and machine learning concepts with adaptive technology for the replication of real-world scenarios. Besides, it contains 2Emulator Model Fitting, Spatial Optimization, Parallel Computing, and Initial and Adaptive sampling to upgrade model efficiency. While UCR has inadequate groundwater and the assessment of freshwater security in UCR is more necessary for varying future climatic conditions. The results displayed that the proposed spatial optimization algorithm proved to be an effective and efficient approach in the approximation of HC models. The assessment of water security in UCR was showed in terms of scarcity and vulnerability indicators for median and low-level conditions, respectively. Moreover, this study provides the potential framework for the enhancement of physical model predictions with the incorporation of hybrid concepts for problem-solving technology which can provide significant information on HC issues.