Dimensions Of Deprivation Research Articles

Dimensions of Housing Deprivation in Poland: A Rural-Urban Perspective

The paper focuses on severe housing deprivation and its components—overcrowding and housing conditions problems. It is based on the European Union Statistics on Income and Living Conditions (EU-SILC) 2019 survey data. The paper analyzes this data on households in Poland—a country with significant problems in terms of housing deprivation. Three dimensions of housing deprivation are examined: experiencing only overcrowding, experiencing only housing conditions problems, and being severely housing deprived. The study aims to investigate three-dimensional housing deprivation depending on the urbanization level of living places and other socioeconomic characteristics of Polish households. The multinomial logit model was used to assess relative risk ratios for explanatory variables to achieve these purposes. It was found that some socioeconomic characteristics significantly influenced one dimension but not another. Moreover, the relative risk ratios for given characteristics sometimes are greater than one for a particular dimension and less than one for another. Specifically, a significant difference in housing conditions problems between households living in towns and rural areas was found. However, there are no significant differences in overcrowding and severe housing deprivation, given that all other explanatory variables are fixed. Furthermore, considering the relative risk as a ratio of the probability of experiencing the given dimension of housing deprivation and the probability of not being housing deprived at all, households in cities compared with rural households were more likely to be overcrowded and to experience severe housing deprivation but less likely to have housing conditions problems.

Associations of threat and deprivation-related childhood exposures with children’s mental health and flourishing: The moderating role of family resilience

IntroductionThe association of adverse childhood experience (ACE) with physical and mental well-being is predominantly examined using a cumulative ACE score. However, less is known how different dimensions of adversity (e.g., threat and deprivation) may uniquely predict children’s mental health and development. We examined (i) whether two aspects of ACE – threat and deprivation – are differently associated with children’s anxiety, depression, and flourishing and (ii) whether family resilience and connection index (FRCI) moderates these associations. MethodsWe analyzed data from the National Survey of Children’s Health (2017–20). The analytic sample consisted of 81,626 children (6–17 years). Logistic regression with survey weights was used to obtain odds ratios (OR) and 95 % confidence intervals (CI) adjusting for sociodemographic factors. ResultsThe experience of threat-only ACE and deprivation-only ACE showed differential associations with anxiety, depression, and child flourishing. For example, children who experienced threat-only ACE had a 4.2-fold higher odds of depression (OR=4.2; 95 % CI: 3.37–5.24), and those who experienced deprivation-only ACE had a 2.4-fold (OR=2.4; 95 % CI: 1.98–2.92) higher odds of depression compared to those exposed to neither threat nor deprivation experience. Experiencing both a threat and deprivation showed larger than an additive association with all outcomes. Further, interaction models suggest that the associations of threat and deprivation-type ACE with all outcomes significantly differed by the levels of FRCI. ConclusionsThreat and deprivation dimensions of adversity were differentially associated with mental health and flourishing outcomes in childhood. Family resilience appears to be protective against the negative effect of threat and deprivation dimensions of ACE on children’s mental health and developmental outcomes.

Multidimensional Poverty Status in Rural Bangladesh and the Pathways of Sustainable Poverty Alleviation

Even though poverty is a social and economic phenomenon, it is nonetheless important to investigate the multidimensional character of poverty in the Global South. Hence, this study is an effort to determine the multidimensional poverty status in rural Bangladesh, decompose poverty, and investigate risk factors for poverty. To achieve the goal, primary data were collected from 350 rural farm households through the random sampling technique. The Alkire-Foster (A-F) method of multidimensional poverty estimation was applied considering four dimensions of deprivation. It was found that 11% of rural households were multidimensionally poor, whereas the multidimensional headcount of poor was 23% and their average intensity of poverty was 47%. When their poverty was decomposed, it was evidenced that the standard of living dimension has the highest contribution among the four dimensions to poverty. The result from ‘indicator-wise decomposition’ found that job seeking was the highest contributing indicator to poverty followed by school dropout and type of cooking fuel. A binomial logit regression model was used to explore the risk factors of poverty. Regression results revealed that larger household size has significantly increased the risk while, more income-earning persons, ownership of large livestock, and crop farming could significantly reduce the risk of poverty in rural farm households. The study findings could be used to implement a sustainable poverty reduction strategy. Also, the contextual factors need to be considered in poverty estimation and policy intervention should be implemented in such a way where the contribution of the dimensions and indicators of poverty get prime focus.

Early maladaptive schemas in autogenous and reactive subtypes of obsessive–compulsive disorder

Aims The aim of this study is to identify early maladaptive schemas in patients with obsessive–compulsive disorder (OCD) and to determine the use of these schemas in OCD autogenous and reactive subtypes. Methods The study population included 40 healthy volunteers, and 90 patients diagnosed with OCD. The Yale–Brown Obsession–Compulsion Scale (Y-BOCS) was administered to the OCD group to determine the severity of the disorder, and the Y-BOCS Symptom Checklist was applied to determine the patients with autogenous (n = 37) and reactive (n = 53) subtypes of OCD. Young Schema Questionnaire-Short Form 3 (YSQ-SF3) scales were applied to all participants. Results When autogenous and reactive subtype groups of OCD were compared with each other, the schema domains of disconnection (p = 0.004), high standards (p = 0.008), other-directedness (p < 0.001) and the schema dimensions of failure (p < 0.001), emotional deprivation (p < 0.001), defectiveness (p = 0.007), approval seeking (p = 0.007) and punishment (p = 0.001) were found to be more dominant in the autogenous group. Conclusions The findings of the study support that there are differences between autogenous and reactive subtypes of OCD in terms of dominant schemas. Therefore, its thought that the use of Schema Therapy methods in which schemas appropriate for subtypes are investigated in the treatment of OCD patients will contribute favorably to the treatment response.

CRITICAL REFLECTIONS ON HUMAN DEVELOPMENT IN HARYANA

The emphasis on GDP per capita has been long cross examined as the sole measure of development. Does this parameter offers holistic insights about the distributional efficiency and welfare assessment at all levels? Considering it, the paper tries to interpret HDI ‘with caution’ and gauge into the trickle-down effect of development process in general with special reference to Haryana while analysing attainment and deprivation dimensions in particular.

Social inequality and the changing patterns of travel in the pandemic and post-pandemic era

The COVID-19 pandemic has had an unprecedented impact on mobility patterns resulting in a significant literature investigating travel behaviours over the course of the pandemic. Missing from much existing work on pandemic mobility is an explicit handling of the time-of-day of travel, which in previous literature has been shown to be an important factor in understanding mobility and, importantly, in understanding the impact on transport networks. In this article, we present a novel analysis of anonymised individual daily mobility patterns in the UK over a 30-month period covering the COVID-19 pandemic using privacy-preserving mobile phone GPS data, collected via integration of software development kits (SDKs) into mobile apps. Our analysis is based on time series clustering of mobility profiles at an hourly level of resolution and enables us to characterize five distinct daily mobility patterns. This typology appears remarkably robust over time, albeit with varying levels of each pattern during the course of the study period. We analyse the relative frequency of these patterns in relation to two dimensions of neighbourhood deprivation in England, with a particular focus on understanding mobility post-lockdown and for over a year after the final restrictions were lifted in the UK. Our results show that although overall mobility patterns have largely returned to their pre-pandemic levels, there remain persistent inequalities in relation to ‘traditional commute’, ‘highly mobile’ and ‘out in the evening’ activity patterns. This finding is expected to have important ongoing policy implications.

Conspiracy Mentality: How it Relates to Populism, Relative Deprivation, Mistrust of Expertise and Voting Behaviour.

Studies utilised OSL regression and structural equation modelling. The overall regression was statistically significant. It was found that dimensions of populist attitudes (anti-elitism, sovereignty), relative deprivation and mistrust of expertise were significant predictors of conspiracy mentality. In line with the second research aim, the fitness of models was confirmed and results suggest mistrust of expertise is also a significant predictor of far-right voting. The contribution of the paper lies in connecting conspiracy mentality with not only attitudes but also with important behaviour outcome - voting behaviour. We propose future research should experimentally examine whether the reduction of some of the identified predictors could possibly lower levels of conspiracy mentality and whether this reduction translates into voting behaviour.

Pediatric Esophageal Foreign Bodies: The Role of Socioeconomic Status in Ingestion Patterns.

Pediatric esophageal foreign bodies (EFBs) are common and can result in serious complications. Little is known about the influence of socioeconomic status (SES) on EFB ingestion in children. The goal was to study SES as a risk factor for dangerous foreign body ingestion and in-hospital complications in children. This was a retrospective cohort study of children presenting to a tertiary care pediatric hospital with an esophageal foreign body from 2010 to 2021. SES was assessed for each patient by linking their postal code to the Ontario Marginalization Index to determine a quintile score across four dimensions of deprivation: residential instability, material deprivation, dependency, and ethnic concentration. Dangerous EFBs were defined as magnets, batteries, sharp objects, or bones. In-hospital complications included: intensive care unit admission, prolonged length of stay, and postoperative sequelae. A total of 680 patients were included. Dangerous EFB ingestion was higher for children with increased residential instability (odds ratio [OR], 2.1; 95% confidence interval [CI], 1.2-3.6) and increased material deprivation (OR, 2.2; CI, 1.9-2.8), which was similarly true for odds of complications. Odds of dangerous EFB ingestion were higher in older children (OR, 1.1; CI, 1.0-1.1) and odds of complications were higher in children with comorbidities (OR, 1.1; CI, 1.0-1.3). Higher levels of housing instability and material deprivation are associated with dangerous EFB ingestion and complications related to EFB ingestion. These findings emphasize the role that SES plays on child health outcomes and the need for initiatives to mitigate these disparities. 3 Laryngoscope, 134:2945-2953, 2024.

Housing Deprivation Among Polish Households: Prevalence and Associated Factors

Abstract Housing deprivation is a multidimensional concept that can be measured using various indicators. This study focuses on severe housing deprivation and its components – overcrowding and housing conditions problems. Severe housing deprivation means the failure to meet basic housing needs. Eurostat defines it as the simultaneous occurrence of overcrowding and housing conditions problems. All analyzed indicators of housing deprivation are based on European Union Statistics on Income and Living Conditions (EUSILC) 2019 survey data. The study covers households in Poland – a country facing serious problems of housing deprivation. In fact, three dimensions of housing deprivation are examined: experiencing only housing conditions problems, experiencing only overcrowding, and being severely housing deprived. The study aims to investigate the prevalence of three-dimensional housing deprivation and reveal which socioeconomic features of the household are associated with the analyzed phenomenon. To achieve these purposes, the multinomial logit model was used to assess the average marginal effects for explanatory variables. It was found that the significant factors associated with housing deprivation are tenure status, dwelling type, household income, average age of household members, their level of educational achievement, presence of disabled and unemployed people, and household type.

Spatial Hotspots and Sociodemographic Profiles Associated With Traumatic Brain Injury in Nova Scotia.

Traumatic brain injury (TBI) is a leading cause of death and disability, primarily caused by falls and motor vehicle collisions (MVCs). Although many TBIs are preventable, there is a notable lack of studies exploring the association of geographically defined TBI hotspots with social deprivation. Geographic information systems (GIS) can be used to identify at-risk neighborhoods (hotspots) for targeted interventions. This study aims to determine the spatial distribution of TBI by major causes and to explore the sociodemographic and economic characteristics of TBI hotspots and cold spots in Nova Scotia. Patient data for TBIs from 2003 to 2019 were obtained from the Nova Scotia Trauma Registry. Residential postal codes were geocoded and assigned to dissemination areas (DA). Area-based risk factors and deprivation status (residential instability [RI], economic dependency [ED], ethnocultural composition [EC], and situational vulnerability [SV]) from the national census data were linked to DAs. Spatial autocorrelation was assessed using Moran's I, and hotspot analysis was performed using Getis-Ord Gi* statistic. Differences in risk factors between hot and cold spots were evaluated using the Mann-Whitney U test for numerical variables and the χ2 test or Fisher's exact test for categorical variables. A total of 5394 TBI patients were eligible for inclusion in the study. The distribution of hotspots for falls exhibited no significant difference between urban and rural areas (p = 0.71). Conversely, hotspots related to violence were predominantly urban (p = 0.001), whereas hotspots for MVCs were mostly rural (p < 0.001). Distinct dimensions of deprivation were associated with falls, MVCs, and violent hotspots. Fall hotspots were significantly associated with areas characterized by higher RI (p < 0.001) and greater ethnocultural diversity (p < 0.001). Conversely, the same domains exhibited an inverse relationship with MVC hotspots; areas with low RI and ethnic homogeneity displayed a higher proportion of MVC hotspots. ED and SV exhibited a strong gradient with MVC hotspots; the most deprived quintiles displayed the highest proportion of MVC hotspots compared with cold spots (ED; p = 0.002, SV; p < 0.001). Areas with the highest levels of ethnocultural diversity were found to have a significantly higher proportion of violence-related hotspots than cold spots (p = 0.005). This study offers two significant contributions to spatial epidemiology. First, it demonstrates the distribution of TBI hotspots by major injury causes using the smallest available geographical unit. Second, we disentangle the various pathways through which deprivation impacts the risk of main mechanisms of TBI. These findings provide valuable insights for public health officials to design targeted injury prevention strategies in high-risk areas.

Measuring child vulnerability to poverty: Material and psychosocial deprivation

The analysis and measurement of what makes children vulnerable to falling into or remaining in poverty is key to ensure equality of opportunities across children, as well as fostering the sustainability of the societal well-being for future generations. This study aims at analysing the child vulnerability to poverty as a broader concept than child poverty because, besides the material deprivation, it also considers the psychosocial deprivation as a result of the relationships of children with their closest environments. We propose to address this issue by means of a multidimensional fuzzy approach. Following the 1989 United Nations Convention on the Rights of the Child, we measure the propensity to be deprived in six dimensions of material deprivation and four of psychosocial deprivation in 32 countries. We use the International Survey of Children's Well-Being (wave 2016–2019), in which 10-years-old children are the respondents. Our study finds that whereas children in developed countries experience more psychosocial than material deprivation, in developing countries there is no clear pattern. Based on the above evidence, we would argue that material and psychosocial deprivation do not go hand in hand and their joint analysis represents a promising tool for a better understanding of children well-being to plan more effective policy measures.

Comparative Analysis of Had Kifayah and Multidimensional Poverty Index as Poverty Measurement in Malaysia

The measurement of poverty is an essential instrument for comprehending the socio-economic well-being of a nation’s population and devising effective strategies to mitigate it. Currently, zakat institutions in Malaysia rely on the Had Kifayah (HAK) method to categorise an individual's poverty status by classifying their asnaf status. On a larger scale, the establishment of the Multidimensional Poverty Index (MPI) presents an alternative method for assessing poverty, emphasising the non-monetary dimensions of deprivation that individuals may experience. This study conducts a comparative analysis of two distinct poverty measurement frameworks, namely, HAK and the MPI to assess their applicability and effectiveness in capturing the multifaceted nature of poverty in Malaysia. The study employed an extensive literature review and comparative analysis of the two different poverty measurement tools. The findings of this study contribute to the ongoing debate surrounding the choice of poverty measurement tools in Malaysia. It sheds light on the advantages and shortcomings of both Had Kifayah and the MPI in capturing the complex and evolving nature of poverty in the country. The study recommends that zakat institutions complement the HAK method by incorporating the MPI, which can effectively measure the degree of deprivation that an asnaf may encounter.

Extend of Multidimensional Poverty Index in Haryana: A Multidimensional Approach

To quantify poverty merely monetary approach does not provide a true representation of deprivations or wellbeingness of households. Multidimensional Poverty Index measures multiple dimensions of deprivation of poverty that gives a more complete picture of poverty. For the study MPI status of Haryana and India as a whole the secondary data on India National Multidimensional Poverty Index, Baseline Report, Based on National Family Health Survey-4 (NFHS) 2015-16 published in 2021 has been used. Main objective of the paper is to study the status of Multidimensional Poverty Index of India and the position of Haryana as it’s in top states with respect to per capita income from 2006 to 2021. The district wise deprivation and counting of different types of deprivations that individuals experience at the same time has been discussed. The study observed that Haryana stands in better position in Multidimensional poverty index (value 0.055) and less deprived in all the indicators of three dimensions of Multidimensional poverty index compare the average status of India as a whole (0.118). District level results revealed the district Mewat, Palwal, Sirsa and Rohtak, Mahendragarh have higher level of multidimensional poverty districts whereas Ambala stands at first rank in lowest head count ratio 1.99%, followed by Panchkula with 2.47%. Comparatively in third dimension of MPI status of Haryana is far better like in electricity. Its deprivation is 0.75 percent compare to 8.29 percent in India. Results show that there is inter district disparity among the indicators which has been reduced. Few districts are above in all indicators due to economic factors and few are deprived in all indicators like Mewat , which is just 58 km far from millennium city of India. Status of health, education and standard of living is worsening in Mewat. Causes are many Like Religion, political, socio orthodox and Illiteracy.

Childhood Neglect rather than Abuse Is More Strongly Associated with Anhedonia across Major Depression and Obsessive-Compulsive Disorder Patients and University Students

Background. According to the dimensional model of adversity, the deprivation and threat dimensions of CT influence distinct neural circuits and have different developmental outcomes. The present study compared neglect and abuse subtypes which are representative of deprivation and threat dimensions of CT prediction of anhedonia in MDD and OCD patients and university students. Methods. A total of 305 patients with MDD, 152 patients with OCD, and 2110 university students fulfilled the Childhood Trauma Questionnaire to identify neglect and abuse subtypes of CT. Different aspects of anhedonia were measured. Hierarchical linear regression analysis was conducted to identify subtypes of trauma as predictors of different aspects of anhedonia in MDD and OCD patients and university students, respectively. Results. Childhood neglect, not abuse, showed association with anticipatory and state anhedonia in OCD patients and anticipatory, consummatory, physical, and state anhedonia in MDD patients and university students. Both childhood neglect and abuse were associated with social anhedonia in university students, but the neglect type showed greater magnitude. In terms of more specific categories, emotional neglect was the type of CT demonstrating strongest magnitude of association with most of the anhedonia aspects. Conclusions. Findings revealed that deprivation, rather than threat, was the more influential adversity dimension for the individuals’ anhedonia presentations.

Optimizing development aid allocation: A data-driven approach using unsupervised machine learning and multidimensional indices

Development aid, often termed foreign assistance, involves the voluntary transfer of resources like goods, services, or capital from governments and international aid agencies to support the development of recipient countries or their people. This practice holds significant importance in international relations and the national economy of many nations. It is also a heavily researched area in economics due to its potential to create a safer, more equitable, environmentally sustainable, and prosperous world. However, it's observed that donor interests often take precedence over recipient needs in aid allocation decisions. Since these allocations are determined by national policies, there is limited room for external input. Consequently, the success of Sustainable Development Goals (SDGs) relies heavily on donor interests. To address this challenge, we propose data-driven approaches to ensure recipient needs are considered and aligned with SDGs. This involves balancing the legitimate interests of donors, recipients, and disadvantaged individuals. In our study, we utilize multidimensional poverty measures to better understand the hardships people face. This approach offers a more accurate representation than traditional monetary indicators, which can miss important dimensions of deprivation. We employ unsupervised machine learning to analyze this data objectively and recommend countries most in need of aid. Such systems can assist donor countries and agencies in efficiently allocating aid, ensuring that the needs of beneficiaries and targeted development goals remain well-aligned.

Impact of Neighborhood Social Deprivation on Health Care Costs Associated With TAVR

BACKGROUND: Cumulative costs of transcatheter aortic valve replacement (TAVR) differ in the referral, procedural and postprocedural phases depending on patient comorbidities, type of procedure, and procedural complications. Our goal was to determine the association between neighborhood measures of social deprivation and TAVR costs in each of the 3 phases. METHODS: Demographics, patient comorbidities, procedural details, in-hospital complications, and costs for adults undergoing TAVR between 2017 and 2020 in Ontario, Canada were obtained from administrative databases and linked to social deprivation data using the Ontario Marginalization Index. The 3 dimensions of social deprivation assessed were (1) material deprivation, (2) residential instability, and (3) ethnic concentration. Hierarchical generalized linear models were used to determine the association between neighborhood social deprivation and cumulative TAVR costs, reported in 2018 Canadian dollars. RESULTS: We identified a total of 7617 TAVR referrals with 3784 patients undergoing TAVR within our study period. Cumulative mean costs in the referral, procedural and postprocedural phases were $8116±$11 374, $32 790±$17 766, and $18 901±$32 490, respectively. After adjustment for clinical and demographic variables, higher factor scores in residential instability were associated with greater cumulative costs in the postprocedural phase, whereas higher factor scores in the other 2 dimensions of marginalization were not significantly associated with higher costs in any of the 3 phases. CONCLUSIONS: This analysis shows that residential instability is associated with higher cumulative costs in the postprocedural phase of TAVR. This lays the foundation for future studies to understand the mechanism of this finding and identify potential mitigation policies.

Socio-economic accounting of inequalities in excess weight: a population-based analysis

BackgroundThe prevalence of excess weight has been increasing globally in the last decades, affecting disproportionally adults from low socio-economic backgrounds and putting undue pressure on health systems and societal resources. In England, tackling unfair and unjust health inequalities is at the heart of national public health policy, and a prerequisite for enabling these decision makers to set policy priorities is an understanding of the prevalence and determinants of excess weight inequalities in their local population.MethodsWe conducted both pooled (England) and regional-level (nine regions: North-East, North-West, Yorkshire and Humber, East Midlands, West Midlands, East of England, London, South East and South West) analyses of individual level data from a nationally representative sample of adults (N = 6,387). We used the Corrected Concentration Index (CCI) to measure absolute inequalities in excess weight across three dimensions of socio-economic deprivation: neighbourhood-level deprivation, occupational status and educational qualification. We used a Shapley decomposition method to evaluate their relative contribution to inequality.ResultsAt a national level, all three dimensions of socio-economic deprivation were found to be positively associated with excess weight across the adult population, as measured by the CCI, with educational qualification ranking first [CCI: -0.090, p < 0.01], closely followed by neighbourhood-level deprivation [CCI: -0.050, p < 0.01]. Large variation was found between regions and genders, with inequality being either considerably higher or exclusively patterned among women. The strongest independent factor contributing to excess weight inequalities was having a long-lasting limiting illness, especially among women and towards the right tail of the excess weight spectrum. Heterogeneous patterns of contribution across the excess weight spectrum were found, however age played a dominant role toward the left tail of the distribution.ConclusionsWhile socio-economic inequalities in excess weight exist in the English adult population, our findings underscore the importance of considering multiple dimensions of deprivation and the unique needs of different populations when developing policies to address overweight and obesity. Targeted interventions for adults with overweight and obesity with long-lasting illnesses and women can generate both short-term and long-term economic benefits, by reducing healthcare costs and increasing workforce productivity.

Equity dimensions in initiatives promoting urban health and wellbeing in east and southern Africa.

Urbanisation in east and southern Africa (ESA) has brought opportunity and wealth together with multiple dimensions of deprivation. Less well documented in published literature on the ESA region are features of urban practice that promote health equity. This work thus aimed to explore features of urban initiatives aimed at improving health and wellbeing in ESA countries and their contribution to different dimensions of health equity. A thematic analysis was implemented on evidence gathered from 52 documents from online searches and 10 case studies from Harare, Kampala, Lusaka, and Nairobi. Most of the initiatives found focused on social determinants affecting low income communities, particularly water, sanitation, waste management, food security and working and environmental conditions, arising from longstanding urban inequalities and from recent climate and economic challenges. The interventions contributed to changes in social and material conditions and system outcomes. Fewer reported on health status, nutrition, and distributional outcomes. The interventions reported facing contextual, socio-political, institutional, and resource challenges. Various enablers contributed to positive outcomes and helped to address challenges. They included investments in leadership and collective organisation; bringing multiple forms of evidence to planning, including from participatory assessment; building co-design and collaboration across multiple sectors, actors and disciplines; and having credible brokers and processes to catalyse and sustain change. Various forms of mapping and participatory assessment exposed often undocumented shortfalls in conditions affecting health, raising attention to related rights and duties to promote recognitional equity. Investment in social participation, organisation and capacities across the initiatives showed participatory equity to be a consistent feature of promising practice, with both participatory and recognitional equity acting as levers for other dimensions of equity. There was less evidence of distributional, structural and intergenerational equity. However, a focus on low income communities, links made between social, economic and ecological benefit, and investment in women and young people and in urban biodiversity indicated a potential for gains in these areas. The paper discusses learning on local process and design features to strengthen to promote these different dimensions of equity, and issues to address beyond the local level to support such equity-oriented urban initiatives.

Fine-scale mapping of urban malaria exposure under data scarcity: an approach centred on vector ecology

BackgroundAlthough malaria transmission has experienced an overall decline in sub-Saharan Africa, urban malaria is now considered an emerging health issue due to rapid and uncontrolled urbanization and the adaptation of vectors to urban environments. Fine-scale hazard and exposure maps are required to support evidence-based policies and targeted interventions, but data-driven predictive spatial modelling is hindered by gaps in epidemiological and entomological data. A knowledge-based geospatial framework is proposed for mapping the heterogeneity of urban malaria hazard and exposure under data scarcity. It builds on proven geospatial methods, implements open-source algorithms, and relies heavily on vector ecology knowledge and the involvement of local experts.MethodsA workflow for producing fine-scale maps was systematized, and most processing steps were automated. The method was evaluated through its application to the metropolitan area of Dakar, Senegal, where urban transmission has long been confirmed. Urban malaria exposure was defined as the contact risk between adult Anopheles vectors (the hazard) and urban population and accounted for socioeconomic vulnerability by including the dimension of urban deprivation that is reflected in the morphology of the built-up fabric. Larval habitat suitability was mapped through a deductive geospatial approach involving the participation of experts with a strong background in vector ecology and validated with existing geolocated entomological data. Adult vector habitat suitability was derived through a similar process, based on dispersal from suitable breeding site locations. The resulting hazard map was combined with a population density map to generate a gridded urban malaria exposure map at a spatial resolution of 100 m.ResultsThe identification of key criteria influencing vector habitat suitability, their translation into geospatial layers, and the assessment of their relative importance are major outcomes of the study that can serve as a basis for replication in other sub-Saharan African cities. Quantitative validation of the larval habitat suitability map demonstrates the reliable performance of the deductive approach, and the added value of including local vector ecology experts in the process. The patterns displayed in the hazard and exposure maps reflect the high degree of heterogeneity that exists throughout the city of Dakar and its suburbs, due not only to the influence of environmental factors, but also to urban deprivation.ConclusionsThis study is an effort to bring geospatial research output closer to effective support tools for local stakeholders and decision makers. Its major contributions are the identification of a broad set of criteria related to vector ecology and the systematization of the workflow for producing fine-scale maps. In a context of epidemiological and entomological data scarcity, vector ecology knowledge is key for mapping urban malaria exposure. An application of the framework to Dakar showed its potential in this regard. Fine-grained heterogeneity was revealed by the output maps, and besides the influence of environmental factors, the strong links between urban malaria and deprivation were also highlighted.

Multidimensional Deprivation from Labor Market Opportunities in Armenia: Evidence from 2018 and 2020.

This paper explores the multidimensional deprivation from labor market opportunities in Armenia by constructing a Quality of Employment measure. Using Labor Force Survey datasets for the years 2018 and 2020, we conduct a comparative analysis for a group of job-separated individuals. The identified dimensions of deprivation from labor market opportunities prior to and after the onset of COVID-19 are reasons for separating from a job, reasons for not looking for a job, and main obstacles in finding a job. These dimensions enable to study employee-level (supply factors) and job-related characteristics (demand factors). Our study shows that demand factors are the primary drivers of amplified deprivation in times of the pandemic. Also, we observe that the gender gap in the labor market deprivation has been increased during the pandemic, further amplified for married women. Interestingly, gender gap in deprivation is invariant to the occupational composition.