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Coastal zones are characterized by a complex interaction between continental and marine ecosystems. They are often subject to anthropogenic and natural pressures such as urbanization, pollution, erosion, storms, and the impact of climate change. It is an environment that requires sustainable management to preserve its biodiversity and ecosystem services. This study focuses on assessing coastal vulnerability to erosion in the Bay of Agadir, one of Morocco's main tourist attractions. The methodology adopted is based on geomatic science such as GIS and geospatial remote sensing. This approach involved the preparation of a database for the study area, relating mainly to geomorphological parameters, topography, sea level rise, and shoreline change data. The latter was assessed using DSAS (Digital Shoreline Analysis System) tools and then all data were integrated into a GIS software to evaluate the Coastal Vulnerability Index (CVI). The first result shows that the EPR (endpoint rate) index reveals an erosion trend over the 8.3 km studied area. Over the 262 transects analyzed, the variations show a predominant erosion (92%) with rates of up to -13.5 m/year over 46 years. This justifies the use of the LRR (Linear Regression Rate-of-Change) index rather than the EPR for kinematic analysis of the coastline. The results of the CVI index show that 2.58 km of the coastal zone, and 1.68 km of the Bay are successively highly and very highly vulnerable to coastal erosion (20-60%). This study can be considered as a basic document, providing crucial information to guide decision-makers and planners in the implementation of effective coastal conservation strategies. [ABSTRACT FROM AUTHOR]

The vulnerability assessment of the species of howler monkey (Alouatta palliata palliata) in Playa Hermosa, Guanacaste, Costa Rica was possible through the application of a Vulnerability Index (VI) that integrates the 4 axes of Sustainable Development. Vulnerability for this species was found to be high (63%). Mainly in the economic and political-institutional criteria, while the social and environmental contribute 50% [S (14%) + A (15%) + E (17%) + PI (17%) = IV (63%)]. In this way, the lines of action should focus on the implementation of policies and management plans that incorporate the howler monkey as a focal species and infrastructure intervention present in its habitat, such as power lines and roads. [ABSTRACT FROM AUTHOR]

This research aims to prove whether empirically self-compassion has a role in the resource index and vulnerability index (as a resilience score index) in first-year university students. A descriptive quantitative approach was used to see existing correlation and role, with simple linear regression analysis as the primary statistical test. The subjects were 81 first-year students (12 males and 69 females) at universities in Central Java, obtained through convenience sampling. Data collection was carried out using the Indonesian version of the Resiliency Scale for Children and Adolescents (RSCA) and the self-compassion scale. Self-compassion plays a positive role in the resource index (R= .36, p< .001) with an effective contribution of 13.2% (R2= .132) and a negative role in the vulnerability index (R=- .49, p< .001) with an effective contribution of 24.4% (R2= .244). Self-compassion has been shown to play an essential role in the resilience of first-year university students. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study results and recommendations will have a paramount significance for policymakers, policy advocates, development planners and practitioners who may be in need of such information for reconsideration, evaluation and inclusion into their respective development and humanitarian programming and operational strategies. Above all, the study result has further provided the local community with viable adaptation strategies to climate-induced changes in the study area. Design/methodology/approach: This study was conducted to measure the livelihood vulnerability of Borana pastoralists to climate change and variability in southern Ethiopia. Pastoralists' households were sampled using multistage sampling techniques. A total of 27 socio-economic and biophysical indicators were used to reflect vulnerability components: adaptive capacity, exposure and sensitivity. Principal component analysis was used to develop weights for indicators and to produce livelihood vulnerability index to classify households according to their level of vulnerability. Ordinal logistic regression was used to identify the determinants of vulnerability to climate-induced stresses. Findings: The results showed that 24.4% of households were highly vulnerable, 60.3% were moderately vulnerable and 15.3% of households were less vulnerable to climate-induced stresses. Factor estimates of the logistic model further revealed that early warning information, bush encroachment, coping strategy, temperature, drought frequency, provision of humanitarian services and food shortage during the normal season of the year have a significant influence on vulnerability in the study area. Social implications: The study's results and recommendations will be of great significance to policymakers, development planners, and practitioners who require such information for reconsideration, evaluation, and inclusion in their respective development and humanitarian program and operational strategies. Most importantly, the study's findings have provided the local community with practical adaptation strategies to climate-induced changes in the study area. Originality/value: The study explored pastoralist perception of climate change and variability and measured the livelihood vulnerability of pastoralists' households to climate change and variability and finally investigated viable adaptation and coping strategies in the study area. [ABSTRACT FROM AUTHOR]

The outbreaks of a new pandemic in 2019 let humankind face a new type of challenge. People and groups in vulnerable situations were especially affected. Increasing urbanization, climate change, and global travel raise the likelihood of pandemics. COVID-19 has shown that sustainable and well-planned pandemic management is necessary, which also includes and identifies people in vulnerable situations. In this study, a socio-economic vulnerability assessment (VA) for supporting improved pandemic/epidemic risk management at the municipality level in Austria was conducted. The VA provides a holistic overview of the vulnerability under pre-event conditions in Austria, which can be used to support pandemic management. Therefore, we calculated a composite indicator with expert-based weighting. The necessary indicators were defined through a literature review and an expert consortium consisting of practical and scientific members. As a result, an interactive map containing the vulnerability index (VI) for each municipality was created, making it possible to also assess underlying vulnerable factors to support decision-making. The applicability of the VA was shown in the relationship between a high VI in a municipality and a high number of deaths. A limiting factor to the VA was the missing data for health indicators for the whole of Austria. Hence, we provide a list with recommendations on which data should be collected to improve the VA in the future. [ABSTRACT FROM AUTHOR]

COVID-19 has had an impact on the entire humankind and has been proved to spread in deadly waves. As a result, preparedness and planning are required to better deal with the epidemic's upcoming waves. Effective planning, on the other hand, necessitates detailed vulnerability assessments at all levels, from the national to the state or regional. There are several issues at the regional level, and each region has its own features. As a result, each region needs its own COVID-19 vulnerability assessment. In terms of climate, terrain and demographics, the state of Uttarakhand differs significantly from the rest of India. As a result, a vulnerability assessment of the next COVID-19 variation (Omicron BA.2) is required for district-level planning to meet regional concerns. A total of 17 variables were chosen for this study, including demographic, socio-economic, infrastructure, epidemiological and tourism-related factors. AHP was used to compute their weights. After applying min–max normalisation to the data, a district-level quantitative SWOT is created to compare the performance of 13 Uttarakhand districts. A COVID-19 vulnerability index (normalised Ri) ranging between 0 and 1 was produced, and district-level vulnerabilities were mapped. Quantitative SWOT results depict that Dehradun is a best performing district followed by Haridwar, while Bageshwar, Rudra Prayag, Champawat and Pithoragarh are on the weaker side and the normalised Ri proves Dehradun, Nainital, Champawat, Bageshwar and Chamoli to be least vulnerable to COVID-19 (normalised Ri ≤ 0.25) and Pithoragarh to be the most vulnerable district (normalised Ri > 0.90). Pauri Garwal and Uttarkashi are moderately vulnerable (normalised Ri 0.50 to 0.75). [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has renewed concerns about social and structural factors related to health disparities, including those related to HIV. As a partial response to an urgent need to understand whether elevated risk of COVID-19 disease and mortality among persons living with HIV (PLWH) results from related risk behaviors, a higher burden of comorbidities, and/or social determinants of health, the Lens was created by the UCLA Center for Neighborhood Knowledge in partnership with the Southern California HIV/AIDS Policy Research Center. The Lens: HIV Prevalence and COVID-19 Vulnerabilities data-mapping tool (Lens) can help decision-makers, community-based organizations and other stakeholders to access critical neighborhood-level information about the intersection of socio-economic and health vulnerabilities and HIV. The Lens portal also contains information on COVID-19 case rates for counties where such information is available. We hope this information helps guide overstretched public health and health systems in recasting, prioritizing, and improving HIV prevention and treatment services in the time of COVID. The authors thank the California Department of Public Health, Office of AIDS for their input. The authors also thank UCLA Center for Neighborhood Knowledge staff and Chhandara Pech for their support. Lastly, we thank Joana Munoz for designing and laying out this report. Funding for this project was provided by the California HIV/AIDS Research Program.

The COVID-19 pandemic has had enormous economic impacts, including creating financial difficulties for many homeowners. While foreclosures have been lower during the public health crisis, primarily due to the current moratorium in place, many homeowners are still receiving pre-foreclosure notices with a disproportionate share going to disadvantaged communities. Many analysts and housing advocates fear that there will be a new wave of home losses once temporary protections.This brief outlines the development of an Owner Vulnerability Index (OVI) to assist public agencies and community organizations in implementing homeowner protection policies and any COVID-19 mortgage relief programs and to help identify those neighborhoods with the most at-risk homeowners. The OVI is a useful analytical and policy tool for identifying and prioritizing neighborhoods at higher risk of foreclosure to preserve homeownership and promote neighborhood stabilization.The project developed an interactive web map of the OVI for California. The web map is accessible at: https://arcg.is/1zTfnu This report was made possible by the generous support from the Chan Zuckerberg Initiative and UCLA Ziman Center for Real Estate’s Rosalinde and Arthur Gilbert Program in Real Estate, Finance and Urban Economics.

Ethiopia, despite contributing minimally to global greenhouse gas emissions, is consistently cited as one of the most vulnerable countries, not only in Sub-Saharan Africa regions but also globally, to climate variability and change. The country's farming households are most vulnerable because of their climate-sensitive livelihoods and limited resources to finance adaptation measures. This study aimed to assess the livelihood vulnerability of communities reliant on a mixed crop-livestock agricultural system and natural resources in the Central Rift Valley sub-basin of Ethiopia to climate variability and change. Structured interviews were used to collect quantitative data from 339 randomly selected households. Livelihood Vulnerability Index was developed to assess the degree of livelihood vulnerability between the two districts. The survey results were supported and substantiated by focus group discussions. The findings show that farm households living in the sub-basin experience different levels of vulnerability to climate variability and change because of their varying adaptive capacities. Considering the aggregate Livelihood Vulnerability Index, Arsi Negele district is considered to be more vulnerable to climate variability and change. The livelihood Vulnerability Index-Intergovernmental Panel on Climate Change results also show that Arsi Negele is more vulnerable since its exposure scores exceed its adaptive capacity. Several factors contribute to the weak adaptive capacity of farmers in Arsi Negele. These factors include lesser adoption of agricultural technology, a low level of knowledge and education, insufficient social networks, less diversification of livelihood strategies, and higher socio-demographic vulnerability. In contrast, Adami Tullu Jido Kombolcha district has a higher sensitivity score due to its limited access to potable water, housing, and land ownership. Strategies that minimize households' degree of sensitivity and enhance their adaptive capacity should be promoted. Such strategies should include the adoption of improved agricultural technologies, strengthening awareness and technical capacity, promoting better soil and water management, accessing credit options, and building community networks. Diversifying household income and establishing alternative livelihoods should also be encouraged.

Place-based vulnerability indices are valuable analytical tools that policy makers could use to prioritize the most-at-risk neighborhoods for interventions, including the distribution of COVID-19 vaccines. The indicators, nonetheless, may not be appropriate for many at-risk populations, particularly smaller groups that tend to be less geographically concentrated.To better understand the limitations of four vulnerability indicators, out new brief assesses their relative ability to include American Indians, Pacific Islanders and select Asian American ethnic subgroups (Cambodians, Filipinos and Koreans). These groups have factors that potentially place them at greater risk from the pandemic because of their jobs, low socioeconomic status and poor living conditions.  Despite these heightened risks, many members of these groups do not reside in neighborhoods designated as being highly vulnerable places by the indicators. The indicators perform relatively better for American Indians and Cambodians.

This report by UCLA Center for Neighborhood Knowledge, UCLA Center for Health Policy Research, and Ong & Associates assesses four vulnerability indicators that are being used by public agencies as policy tools to select the most vulnerable neighborhoods for interventions. These indicators can play a role in prioritizing the provision of pandemic resources and services; consequently, they have implications for how many people of color and minority neighborhoods are served.This study compares three pre-pandemic indicators and a more recently developed indicator based on pre-existing health conditions. The analysis focuses on the numbers of people of color residing in designated high-vulnerability neighborhoods, and the relative number of minority neighborhoods that fall into the high-vulnerability areas. Race/ethnicity is important because people of color encounter multiple dimensions of inequality that are only partially reflected in the indicators.The findings show noticeable differences in the groups and places designated as being vulnerable, thus the choice of which indicator to use has highly consequential implications in terms of who is served and who is not along racial lines.

Introduction: Masonry minarets in Old Cairo are highly susceptible to earthquake damage, particularly those not designed or updated to withstand seismic loads. Therefore, regular monitoring is necessary to ensure their safety and detect any deterioration or reduction in seismic performance. The direct loss of a minaret can lead to the collapse or severe damage to the structure itself. The cascading impacts of partial or complete minaret failure can have significant consequences for the immediate vicinity and the broader community. By studying the effects of earthquakes on minarets and developing mitigation strategies, countries can take proactive measures to protect these structures and ensure the safety of people. Objective: This study focuses on a specific type of Islamic architecture: the historic minarets in Cairo. The research aims to evaluate the seismic vulnerability of eight cultural heritage minarets in Cairo, identifying the parameters influencing their seismic behaviour and susceptibility to earthquake damage. Methods: The research utilizes empirical seismic vulnerability methods and ambient vibration measurements on eight minarets. An empirical approach compatible with the nature and style of the minarets is employed to evaluate their vulnerability using index values and curves. The method's validity is assessed, and areas of conformity and limitations are identified. Ambient vibration tests (AVTs) are also conducted using a temporary seismic network installed at various heights inside each minaret to determine their dynamic characteristics. Results: The seismic vulnerability Index (I_V) is calculated for the selected minarets based on the state of each vulnerability parameter. The contribution of each parameter to the final I_V values of the minarets are presented. Vulnerability curves are developed for each minaret, interpreting the conventional vulnerability indexes in terms of mean damage grades for seismic events with varying intensity on the EMS-98 scale. These mean damage grades can also indicate the expected damage levels of structural and non-structural minaret elements for events with different seismic intensity levels. AVTs are conducted at various heights on the selected minarets, and the dynamic characteristics are extracted from the recorded data. Variations in these characteristics are considered significant for structural health monitoring analysis. The peak-picking method is employed to directly extract each minaret's natural frequencies and mode shapes, as changes in dynamic characteristics are relevant to health monitoring analyses. Conclusions: The recent study examined the seismic vulnerability assessment of eight masonry minarets in the historic Old Cairo district. The assessment revealed vulnerability index values ranging from 10.3 to 26.1, indicating a concerning susceptibility to seismic events among these structures. Vulnerability curves were constructed for each minaret, visually representing potential damage scenarios across different levels of the EMS-98 intensity scale. These outcomes are significant as they facilitate prioritizing interventions to safeguard the most vulnerable minarets. Additionally, a novel empirical period equation was introduced to estimate the fundamental period of minarets in Old Cairo based on their heights. The equation was validated against field measurements and data from the literature. The study is limited by its focus on a specific category of minarets, specifically the historical masonry minarets in Old Cairo. Furthermore, limitations arise from the need for detailed finite element models to capture these minarets' dynamic responses accurately. Therefore, ongoing research involves the development of detailed finite element models and calibrating fundamental periods for the selected minarets. The anticipated results hold the potential to enhance our understanding of the structural dynamics of historical minarets, ultimately guiding the formulation of tailored seismic retrofitting and preservation strategies. These strategies, aimed at preserving these cherished cultural heritage assets, represent our collective commitment to ensure the endurance of these timeless landmarks for future generations. [ABSTRACT FROM AUTHOR]

The vulnerability study of the water–energy–food–ecosystem (WEFE) system in the Yangtze River Economic Belt (YREB) is of great significance for ensuring water, energy, food, and ecological security. In this study, the concept of vulnerability of WEFE systems is explained, and then its mechanism is analyzed. Based on the vulnerability concept of the WEFE system and combined with the pressure–state–response (PSR) framework and the exposure–sensitivity–adaptability (ESA) capacity model, this study constructs an evaluation index system for the vulnerability of the WEFE system. The cross-efficiency data envelopment analysis (CE-DEA) method, which considers both self-evaluation and peer evaluation efficiency, is used to calculate the vulnerability from 2005 to 2020. The spatiotemporal dynamic characteristics are explored using the hot spot analysis and spatial autocorrelation model. The results show that the overall vulnerability of the WEFE system in the YREB has fluctuated and increased during the study period, with a spatial pattern characterized by "high in the middle and low on both sides." Over time, the spatial evolution tends to be centralized and non-equilibrium, forming a relatively independent spatial pattern. [ABSTRACT FROM AUTHOR]

Background: Most COVID-19 vulnerability indices rely on measures that are biased by rates of exposure or are retrospective like mortality rates that offer little opportunity for intervention. The Moore-Hill Vulnerability Index (MHVI) is a precision public health early warning alternative to traditional infection fatality rates that presents avenues for mortality prevention. Methods: We produced an infection-severity vulnerability index by calculating the proportion of all recorded positive cases that were severe and attended by ambulances at small area scale for the East Midlands of the UK between May 2020 and April 2022. We produced maps identifying regions with high and low vulnerability, investigated the accuracy of the index over shorter and longer time periods, and explored the utility of the MHVI compared to other common proxy measures and indices. Analysis included exploring the correlation between our novel index and the Index of Multiple Deprivation (IMD). Results: The MHVI captures geospatial dynamics that single metrics alone often overlook, including the compound health challenges associated with disadvantaged and declining coastal towns inhabited by communities with post-industrial health legacies. A moderate negative correlation between MHVI and IMD reflects spatial analysis which suggests that high vulnerability occurs in affluent rural as well as deprived coastal and urban communities. Further, the MHVI estimates of severity rates are comparable to infection fatality rates for COVID-19. Conclusions: The MHVI identifies regions with known high rates of poor health outcomes prior to the pandemic that case rates or mortality rates alone fail to identify. Pre-hospital early warning measures could be utilised to prevent mortality during a novel pandemic. [ABSTRACT FROM AUTHOR]

Increased occurrences of climate extremes are one of the primary indicators to identify climate change. From agricultural perspectives, vulnerability is the proneness of a region to extreme climate events which cause crop loss, yield reduction eventually leading to the decline in farmers income. An extreme weather event becomes a disaster when the society or ecosystems are unable to cope with it effectively. The vulnerability of agriculture in the Lower Vellar River sub-basin has been quantitatively assessed which can help provide guidelines to improve the adaptive capacities of the farming communities in the sub-basin. The vulnerability has been assessed with a total of 36 indicators categorised under three dimensions, namely sensitivity, exposure, and adaptive capacities, for the years, 2011 and 2015 which experienced extreme precipitation events, Cyclone Thane and the Deep Depression of Bay of Bengal, respectively. The vulnerability index results highlight that the sensitivity of coastal blocks, namely Parangipettai, Keerapalayam, and Mel Bhuvanagiri to precipitation extremes is higher when compared to the interior blocks Nallur, Mangalur, and Virudhachalam. The exposure of the coastal blocks to the extreme events in the years 2015 and 2011 was high, with the year 2011 having lower exposure values than 2015. The main cause for low exposure values in 2011 for the coastal blocks can be attributed to high temperature trends and subsequent high exposure index values in Mangalur which is an interior block in the basin. The adaptive capacities in the coastal blocks are very less making them highly vulnerable. In general, the coastal regions have medium–high vulnerability than the interior regions which have low-medium to medium vulnerability. [ABSTRACT FROM AUTHOR]

Groundwater is an important drinking water source increasingly threatened by reduced groundwater recharge and direct or indirect contamination. Aquifers recharged by surface water bodies can get contaminated through seepage from already impacted surface water bodies. In the present study, various models were used to assess the vulnerability of groundwater intended for public use to contamination by local wastewater-receiving ponds (WRPs). The water quality parameters and water quality index (WQI) were analyzed for two WRPs (Sites A and B) and hand pumps located in their vicinity. Fourteen water quality parameters were measured for both the groundwater and WRPs and compared with the vulnerability models for the two WRPs. Four vulnerability models—GOD, DRASTIC, ASSIGN, and LeGrand models that used the land-use characteristics, depth to groundwater, soil type, slope, and precipitation data—were employed. The results of the vulnerability assessment agreed with the WQI (p-value < 0.05) for the LeGrand model. The performance of GOD, DRASTIC, and ASSIGN models was disappointing. The water quality was unsuitable for human use in both the WRPs and the groundwater sampled from their vicinity. The WQI ranged from 49 to 62, indicating poor-to-medium water quality for both groundwater aquifers. The results of LeGrand's model confirmed that Sites A and B were vulnerable to water quality deterioration because of surface water contamination. There was a significant negative correlation between WQI and LeGrand's vulnerability index for Site A (p-value = 0.0145, r = −0.682) (Pearson's correlation) and Site B (p-value = 0.0013, r = −0.813) (Pearson's correlation). It better suits to represent transient conditions of the groundwater, that is, varying groundwater levels and water table gradients. [ABSTRACT FROM AUTHOR]

To help slow the spread of COVID-19 and save lives, UCLA Center for Neighborhood Knowledge and UCLA BRITE Center for Science, Research, and Policy developed vulnerability indicators aimed at identifying which neighborhoods in California are at most risk of becoming impacted by COVID-19 infections. The map includes four important indicators known to significantly increase a person’s medical vulnerability to COVID-19 infection: 1) pre-existing health conditions, 2) barriers to accessing services, 3) built-environment risk and 4) social vulnerability.

this new report by CNK consists of a series of policy briefs covering the social and economic impacts of COVID-19 on neighborhoods throughout California. The project focuses on identifying the broad vulnerabilities to COVID-19 and their disparities across neighborhoods in California. For this analysis, the census tract is the basic unit of analysis and serves as a reasonable proxy for neighborhood bounds. This analysis examines five dimensions of vulnerability across five tracts.

Climate change and urbanization are likely to increase the vulnerability of cities by increasing the intensity of flooding, which causes damage to the communities. The objective of this research is to estimate the Flood Vulnerability Index (FVI) for Alexandria City to assist decision-makers develop priority urban flood plans and identify methods for reducing flood risk. In this study, the FVI is generally estimated throw three components: social, physical, and environmental. Moreover, eleven major indicators are used to represent each of these three components, and they are classified according to the three flood factors: exposure, susceptibility, and resilience. Geographic information system (GIS), and remote sensing (RS) are applied to obtain the required data and develop maps for identifying the urban flood indictors. The study area has been divided to 16 zones regarding its administrative classification The 16 zones in Alexandria city's Vulnerability Index for the three components (social, physical , and environmental ) and the overall FVI have been estimated. Population, population density, population access to sanitation, and warning system are used as the four indicators for the social component, whereas the four indicators used for the physical components, are approximately of stream, elevation, rainfall amount , and slope. The environmental component, is evaluated by using three indicators , land use, urban growth, and flood recovery time. The index assigns a number among 0 and 1, indicating relatively low or high urban flood vulnerability. The findings demonstrate that FVI offers a way to assess flood vulnerability and obtain appropriate adaptation choices.

Abstract The interactions between vulnerability and human activities have largely been regarded in terms of the level of risk they pose, both internally and externally, for certain groups of disadvantaged individuals and regions/areas. However, to date, very few studies have attempted to develop a comprehensive composite regional vulnerability index, in relation to travel, housing, and social deprivation, which can be used to measure vulnerability at an aggregated level in the social sciences. Therefore, this research aims to develop a composite regional vulnerability index with which to examine the combined issues of travel, housing and socio-economic vulnerability (THASV index). It also explores the index’s relationship with the impacts of the COVID-19 pandemic, reflecting both social and spatial inequality, using Greater London as a case study, with data analysed at the level of Middle Layer Super Output Areas (MSOAs). The findings show that most of the areas with high levels of composite vulnerability are distributed in Outer London, particularly in suburban areas. In addition, it is also found that there is a spatial correlation between the THASV index and the risk of COVID-19 deaths, which further exacerbates the potential implications of social deprivation and spatial inequality. Moreover, the results of the multiscale geographically weighted regression (MGWR) show that the travel and socio-economic indicators in a neighbouring district and the related vulnerability indices are strongly associated with the risk of dying from COVID-19. In terms of policy implications, the findings can be used to inform sustainable city planning and urban development strategies designed to resolve urban socio-spatial inequalities and the potential related impacts of COVID-19, as well as guiding future policy evaluation of urban structural patterns in relation to vulnerable areas.

Predicting the impact of earthquakes on buildings and structures requires understanding the dynamics of their behavior. The procedures adopted for this purpose are quite complex and tedious in terms of cost, time and execution, especially when the studies are concerned with spatial domains rather than individual buildings. Assessing seismic vulnerability using available resources is of great importance. Vulnerability index and capacity spectrum-based methods used to assess expected physical damage in dwellings have been reviewed and their main advantages and disadvantages have been analyzed and discussed. Then a method based on vulnerability index is used to assess the expected damage in Ardabil. Risk analysis for seismic scenarios defined by macroseismic intensities of V, V-VI, VI, VI-VII and VII has been performed to design seismic emergency plans. According to the country's seismic regulations, the peak of the initial acceleration of the earth for a 475-year return period is 0.04g, which is related to the intensity of VII. Therefore, while quantifying physical damage, its impact on the population and other quantities such as debris, the number of homeless and the economic cost have been investigated. In spite of the low-to-moderate seismic hazard in Ardabil, the results show that the risk is high, due to the high exposure and vulnerability of the built environment. [ABSTRACT FROM AUTHOR]

In Colombia, the first case of COVID-19 was confirmed on 6 March 2020. On 13 March 2023, Colombia registered 6,360,780 confirmed positive cases of COVID-19, representing 12.18% of the total population. The National Administrative Department of Statistics (DANE) in Colombia published in 2020 a COVID-19 vulnerability index, which estimates the vulnerability (per city block) of being infected with COVID-19. Unfortunately, DANE did not consider multiple factors that could increase the risk of COVID-19 (in addition to demographic and health), such as environmental and mobility data (found in the related literature). The proposed multidimensional index considers variables of different types (unemployment rate, gross domestic product, citizens' mobility, vaccination data, and climatological and spatial information) in which the incidence of COVID-19 is calculated and compared with the incidence of the COVID-19 vulnerability index provided by DANE. The collection, data preparation, modeling, and evaluation phases of the Cross-Industry Standard Process for Data Mining methodology (CRISP-DM) were considered for constructing the index. The multidimensional index was evaluated using multiple machine learning models to calculate the incidence of COVID-19 cases in the main cities of Colombia. The results showed that the best-performing model to predict the incidence of COVID-19 in Colombia is the Extra Trees Regressor algorithm, obtaining an R-squared of 0.829. This work is the first step toward a multidimensional analysis of COVID-19 risk factors, which has the potential to support decision making in public health programs. The results are also relevant for calculating vulnerability indexes for other viral diseases, such as dengue. [ABSTRACT FROM AUTHOR]

Melon farming faces difficulties due to climate change causing unstable conditions, which make the plants more vulnerable to viruses like Begomovirus, leading to lower melon yields. To tackle this problem and guarantee a stable food supply, it is crucial to create melon varieties that possess resistance to these viruses by utilizing breeding techniques. Kinaya is a new genotype being developed as a Begomovirus tolerant variety for future prospects. Further observations are needed on the initial identification of biological responses to Begomovirus infection and the presence of candidate resistance genes in Kinaya. The research was conducted in open farmland in Jamusan, Yogyakarta, Indonesia, from April to August 2021. Observations and data were collected using the plant leaf infection scoring method based on the severity of symptoms in the Kinaya population. Melon and virus genomes were isolated from melon leaves exhibiting Begomovirus symptoms and from healthy plant leaves. We employed a set of 8 melon samples for dual objectives: identifying Begomovirus using Krusty-Homer primers and detecting Begomovirus resistance genes through SCAR primers linked to candidate resistance genes targeting Begomovirus. Observations showed symptoms of infection with yellow spot and leaf curling with tolerant susceptibility. Molecular identification with Krusty-Homer confirmed the presence of Begomovirus infection in all infected samples. Over 90% sequence similarity of the coat protein DNA virus was found in different Begomovirus species. SLCCV and ToLCNDV isolates from Indonesia were found to be closely related. Based on the developed SCAR markers, the DNA band of 900 bp was found in all healthy samples. Kinaya shows potential to be developed into a leading virus-resistant melon variety in Indonesia, although further research is needed to stabilize its resistant traits. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this study is to evaluate the impact of food access and other vulnerability measures on the COVID-19 progression to inform the public health decision-makers while setting priority rules for vaccine schedules. Design/methodology/approach – In this paper, the authors used the Supplemental Nutrition Assistance Program (SNAP) data combined with the Centers for Disease Control and Prevention (CDC)’s social vulnerability score variables and diabetes and obesity prevalence in a set of models to assess the associations with the COVID-19 prevalence and case-fatality rates in the United States (US) counties. Using the case prevalence estimates provided by these models, the authors developed a COVID-19 vulnerability score. The COVID-19 vulnerability score prioritization is then compared with the pro-rata approach commonly used for vaccine distribution. Findings – The study found that the population proportion residing in a food desert is positively correlated with the COVID-19 prevalence. Similarly, the population proportion registered to SNAP is positively correlated with the COVID-19 prevalence. The findings demonstrate that commonly used pro-rata vaccine allocation can overlook vulnerable communities, which can eventually create disease hot-spots. Practical implications – The proposed methodology provides a rapid and effective vaccine prioritization scoring. However, this scoring can also be considered for other humanitarian programs such as food aid and rapid test distribution in response to the current and future pandemics. Originality/value – Humanitarian logistics domain predominantly relies on equity measures, where each jurisdiction receives resources proportional to their population. This study provides a tool to rapidly identify and prioritize vulnerable communities while determining vaccination schedules.

The Special Region of Yogyakarta is one of the areas impacted by the 2006 earthquake which damaged vital infrastructures, including water distribution networks (WDN). The vulnerability of these networks increases because the design process does not consider the mitigation strategy of natural disasters. This region does not have any tools to estimate the infrastructure vulnerability for underground lifeline facilities, including WDN. Therefore, this study aimed to develop a framework to generate a Seismic Vulnerability Index for Water Distribution Network (SVI-WDN) for the Special Region of Yogyakarta which has been known to be exposed to many earthquake incidences. The framework presents a process to develop a SVI-WDN which consist of three steps. First step, to obtain the criteria, sub-criteria, their value range and the corresponding score for each value. Second step, to normalize the sub-criteria score. The third step, to obtain the criteria and sub-criteria weight by using the analytical hierarchy process (AHP). Lastly, the calculation of a vulnerability index for water distribution. Additional steps for visualizing the index are by generating a geographical information system map representing index value. Thus, this study presents a reproducible framework that can assist water authorities to prioritize the water distribution pipe segment which requires more intensive handling and maintenance. HIGHLIGHTS To develop a conceptual framework for a seismic vulnerability index for water distribution network.; Weighting method in this study uses AHP and involves three group of experts, they are a government official, academics and a water supply specialist.; The vulnerability index was visualized through a geographical information system (GIS) map.; The index can be used to prioritize the pipe segment which requires intensive handling and maintenance.;

To avoids the moribund path of most of the earlier implemented agricultural-based J. interventions in Nigeria. Anchor Borrowers' program was introduced to contribute meaningfully to the economy. The study investigated on rice fanners' technical efficiency and level of poverty in Nigeria with evidence from the Anchor borrower program. Primary data were analyzed using Descriptive analysis, Gini coefficient. Stochastic production Frontier model. Regression analysis, and Vulnerability Index. Evidence from the result revealed that the average yield per hectare of paddy rice for the beneficiaries (70%) majorly was 4500 kg while non-beneficiaries (52%) was 3500kg. The production function showed that the coefficient of regression for herbicides, seed and fertilizer was positively significant at 5% and %, respectively. The factors that influencing technical inefficiency (farm organization farm size, farm experience and ABP loan) were found to be negatively significant. The logistic regression model estimate revealed that factors influence loan acquisitions of respondents include: (farm organization extension agent visit, age of household, and farm size) which were positively statistically significant and this is important in explaining ABP credit acquisition access among households. The results of the Gini coefficient also indicated that income inequality was higher in ABP beneficiaries than non- beneficiaries. Vulnerability index results showed that ABP non-beneficiaries were more vulnerable to poverty than beneficiaries. Additionally, the non-beneficiaries have a poorer population than beneficiaries. However, these results indicate that the Anchor borrower program lias a positive impact on beneficiaries' welfare. [ABSTRACT FROM AUTHOR]

The Messaad plateau is part of the arid zones, located in the region of the South Algerian steppes, with annual precipitation of around 150 mm. This area includes the Barremian aquifer, which plays a very important role in the supply of drinking water and irrigation water. The objective of this work is to assess the vulnerability of groundwater to pollution. The results obtained by the application of the DRASTIC method, show that the areas with high pollution potential are located in the extreme southwest of the watershed, in the south near the Oued Messaad, and in the north at the level of the Ain Naga area. The rest of the area characterized by low to medium vulnerability. The sensitivity analysis after removing one or more maps shows that the vulnerability of groundwater to pollution is largely influenced by the impact of the vadose zone (I), this is confirmed by the single parameter sensitivity analysis, where the effective weight of the impact of the vadose zone (I 29.74%) exceeds the theoretical weight determined by DRASTIC (I 21.7%). [ABSTRACT FROM AUTHOR]

The seismic vulnerability of a city is a degree of its intrinsic susceptibility or predisposition to sustain damage or losses stemming from seismic events. In terms of physical vulnerability, one of the most important factors for assessing seismic risk, especially, for estimating losses, is the exposure of structures, particularly those structures intended for residential use. The present article outlines a methodology for classifying residential buildings based on the structural and non-structural components that ultimately determine the building typology and control the seismic performance. The proposed methodology is divided into three steps: first, spatial data are analysed using an official database that is supplemented by remote field work to verify, validate, and identify construction typologies and urban modifiers after incorporating the new observable data. During the second step, machine learning techniques based on Two-Step cluster analysis and neural networks are used to identify building typologies, using a multilayer perceptron to assess the representativeness of the building typologies identified. Finally, each building typology is defined, a vulnerability assessment is carried out, and vulnerability classes are ranked based on the macroseismic scale. The above-mentioned steps were applied to 7631 residential buildings in the city of Murcia, Spain. The methodology is scalable and may be automated, so it may be replicated in other urban areas with similar characteristics or adapted to different urban settings. This may help save time and reduce the cost of carrying out seismic risk studies, providing valuable information for both civil protection and regional and local governments. [ABSTRACT FROM AUTHOR]

Factors associated with structural racism, disenfranchisement, poverty, and other persistent sources of inequity are associated with vulnerability and exposure to environmental hazards. Social, demographic, and environmental factors associated with vulnerability to environmental hazards have been used by many researchers to produce indexes of hazard vulnerability. In preparation for a climate change health risk assessment for Washington state, we compared methods and results from six indexes designed to support environmental health risk assessment. Production of these indexes varies in the number of variables considered, calculation complexity, and exposure of local causal pathways. Results for these indexes are generally very similar, especially at the highest decile of vulnerability, the exception being the Environmental Health Disparities index, the only one to consider hazard exposure. Some indexes used methods that hide causal pathways. Those that exposed causal pathways limited model structure. Results indicate that simpler indexes may be more appropriate for use in decision support tools as they require less overhead for data updates and scenario analysis and that other methodologies may provide a more useful framework for index generation. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Sciences is the property of Faculty of Engineering - Assiut University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Erzincan University Journal of Science & Technology is the property of Erzincan Binali Yildirim Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Damaging and accelerated anthropization in coastal areas, as well as the need to adapt to climate change, means we must concentrate on improving management plans based on the diagnoses provided by coastal studies. Among these studies is the vulnerability assessment, obtained from evaluating a set of variables or indicators, which contribute to sustainable development. Since there is no single list of variables to consider in determining coastal vulnerability, 60 vulnerability studies from a period of 29 years (1994–2023), from across the globe, were consulted, and through a statistical mode method, the variables most used by multidisciplinary authors were identified. These studies were organized into groups: ecological, geomorphological, maritime climate, socioeconomic and legislative; creating sets categorized as the minimum indispensable, acceptable, and ideal variables. The results showed that most studies use between six and seven variables from only the maritime climate and geomorphological information groups. The number of variables used by individual studies, on the other hand, was not directly related to the scales (global, national, regional, local), but to the risks, such as flooding and erosion, it resolved. Only two studies included the minimum essential information for the legislative group, which is the presence of protected natural areas. Coastline displacements was the variable most used (43 studies), followed by the geoform type and the rate of sea level change (36), the wave regime (35) and the tidal range (33). The DSSs (Decision Support Systems) for coastal management were also reviewed, showing that these systems focus on a topic with a greater number of variables.

In this study, the effects of some geotechnical parameters on the surface settlement curves due to mechanized tunneling and the corresponding risk on surface buildings are investigated through numerical analysis. The advanced constitutive law of Plastic Hardening is utilized to accurately reflect the Soil behavior in unloading. Using the surface settlement curves obtained from numerical analysis, the risk category of surface buildings are calculated and the effectiveness of each parameter on the risk level is investigated. The results show that the cohesion and friction angle do not have a remarkable effect on surface settlement and the corresponding risk. However, the amount of overburden and the soil elastic modulus considerably affect the surface settlement and the risk level subjected to the surface buildings. Recognizing the role of each parameter makes it possible to predict the potential risk on surface buildings and to optimize the approaches for mitigating these risks.