Search Results (115)

This study aims to evaluate the sustainability performance of EU regions through a comprehensive and data-driven Environmental, Social, Governance (ESG) framework, addressing the increasing demand for regional-level analysis in sustainable finance and policy design. Leveraging Partial Least Squares (PLS) regression and cluster analysis, we construct composite ESG indicators that adjust for economic size using GDP normalization and LOESS smoothing. Drawing on panel data from 2010 to 2023 and over 170 indicators, we model the determinants of ESG performance at both the national and regional levels across the EU-27. Time-based ESG trajectories are assessed using Compound Annual Growth Rates (CAGR), capturing resilience to shocks such as the COVID-19 pandemic and geopolitical instability. Our findings reveal clear spatial disparities in ESG performance, highlighting the structural gaps in governance, environmental quality, and social cohesion. The model captures patterns of convergence and divergence across EU regions and identifies common drivers influencing sustainability outcomes. This paper introduces an integrated framework that combines PLS regression, clustering, and time-based trend analysis to assess ESG performance at the subnational level. The originality of this study lies in its multi-layered approach, offering a replicable and scalable model for evaluating sustainability with direct implications for green finance, policy prioritization, and regional development. This study contributes to the literature by applying advanced data-driven techniques to assess ESG dynamics in complex economic systems. Full article

Property crime is a pressing issue in maintaining social order and urban sustainability, particularly in regions marked by pronounced socioeconomic disparity. While the link between socioeconomic stress and crime is well established, regional variations in Thailand have not been fully examined. Therefore, the purpose of this research was to examine spatial patterns of property crime and identify the potential associations between property crime and socioeconomic environment across Thailand. Using nationally compiled property-crime data from official sources across all provinces of Thailand, we employed geographic information system (GIS) tools to conduct a spatial cluster analysis at the sub-national level across 76 provinces. Both global and local statistical techniques were applied to identify spatial associations between property-crime rates and neighborhood-level socioeconomic conditions. The results revealed that property-crime clusters are primarily concentrated in the south, while low-crime areas dominate parts of the north and northeast regions. To analyze the spatial dynamics of property crime, we used geospatial statistical models to investigate the influence of socioeconomic variables across provinces. We found that property-crime rates were significantly associated with monthly income, areas experiencing high levels of household debt, migrant populations, working-age populations, an uneducated labor force, and population density. Identifying associated factors and mapping geographic regions with significant spatial clusters is an effective approach for determining where issues concentrate and for deepening understanding of the underlying patterns and drivers of property crime. This study offers actionable insights for enhancing safety, resilience, and urban sustainability in Thailand’s diverse regional contexts by highlighting geographies of vulnerability. Full article

Background: Micronutrient deficiencies, particularly among pregnant women and children under five years old, remain a significant public health challenge in Nigeria. Despite existing policies and programmes, national data on prevalence and risk factors are fragmented. Objective: To synthesise the current evidence on the prevalence of key micronutrient deficiencies and associated risk factors among pregnant women and children under five years old in Nigeria. Methods: A systematic review and meta-analysis were conducted using peer-reviewed studies that were published between 2008 and 2024. The databases searched included PubMed, Scopus, and African Journals Online. After screening 1207 studies, 37 studies were included: 27 were conducted among pregnant women and 10 were among children. A meta-analysis was conducted to estimate the anaemia prevalence using a random-effects model. A narrative synthesis was conducted to synthesise evidence on other micronutrients (i.e., magnesium, copper, and vitamins C and E) due to the limited data and risk factors. Results: The pooled prevalence of anaemia was 56% among children and 54% among pregnant women. The prevalence of other micronutrient deficiencies varied widely, with a high prevalence of zinc (86.4%), magnesium (94%), and vitamin D (73.3%) deficiencies in certain regions. The identified risk factors included poor dietary diversity, lower socioeconomic status, low maternal education, infection burden, and early or high parity. Most studies were facility-based and sub-national, limiting the generalisability. Conclusions: This review highlights a high prevalence of anaemia and micronutrient deficiencies among pregnant women and children in Nigeria. Key risk factors included a poor diet, low maternal education, infections, and reproductive health challenges. Targeted, multisectoral policies are urgently needed to address these gaps and improve health outcomes. Full article

This study investigates the spatial relationship between population distribution and tree cover loss in Nepal from 2000 to 2020, using satellite-based forest cover and population data along with statistical and geospatial analysis. Two statistical methods—linear regression (LR) and Geographically Weighted Regression (GWR)—were used to assess the influence of population on forest cover change. The correlation between total population and forest loss at the national level suggested little to no direct impact of population growth on forest loss. However, sub-national analysis revealed localized forest degradation, highlighting the importance of spatial and regional assessments to uncover land cover changes masked by national trends. While LR showed a weak national-level correlation, GWR revealed substantial spatial variation, with the coefficient of determination values increasing from 0.21 in 2000 to 0.59 in 2020. In some regions, local R² exceeded 0.75 during 2015 and 2020, highlighting emerging hotspot clusters where population pressure is strongly linked to deforestation, especially along major infrastructure corridors. Using very high-resolution spatial data enabled pixel-level analysis, capturing fine-scale deforestation patterns, and confirming hotspot accuracy. Overall, the findings emphasize the value of spatially explicit models like GWR for understanding human–environment interactions guiding targeted land use planning to balance development with environmental sustainability in Nepal. Full article

Meteorological variables play a significant role in the transmission of viruses such as influenza and the coronavirus pandemic (COVID-19). Previous studies have identified the relationship between changes in meteorological variables, humidity, rainfall, and temperature, and the infection rate of COVID-19 at the national level in Pakistan. However, the current study applied the logistic regression analysis technique to determine such a relationship on a more detailed scale, that is, subnational levels in addition to the national level in Pakistan, using a long-term analysis of two years of COVID-19 data. At the subnational level, the logistic regression analysis technique was applied, with infection rate as the predictive variable. The results showed an increase in the infection rate of COVID-19 with increasing humidity levels. In contrast, an increase in temperature has slowed the spread of COVID-19 cases at both the national and subnational levels. The minimum temperature was statistically significant (p < 0.001) for provinces, KPK and Sindh. Also, two federal territories, AJK and Islamabad, showed statistically significant p-values. At the national level, both maximum temperature and humidity showed such values that is, p < 0.001. We believe that this is the first study conducted in Pakistan to explore the direct and indirect relationship between variables such as temperature (min and max), humidity, and rainfall as predictive parameters for COVID-19 infection rates at a detailed level. The pattern observed in this study can help us predict the future spread of COVID-19, subject to climatic parameters in Pakistan at both the national and subnational levels. Full article

Weak sustainability (WS) requires that the inclusive wealth (IW) of a place (e.g., the world, a nation, or a sub-national region) be non-decreasing over a long time. The WS framework provides a more complete account of the sustainability of a place than do sustainability indicators or conventional economic measures, such as gross domestic product. However, while many decisions that affect sustainability are made at regional and local levels, the abstract theory of WS was developed without explicit recognition of the porosity of geographic boundaries and the interdependencies of regions. In this paper, we make three contributions: a carefully reasoned defense of IW per capita as the WS criterion, an improved understanding of the relationship between mobility, labor productivity, and regional economic growth, and an empirical application to US counties that demonstrates the feasibility of empirical regional WS assessment by summarizing Jones’ research. This analysis, extending the framework developed by Arrow and co-authors, accounts for more region-specific factors related to population, most notably the labor productivity component of health capital, and assesses IW per capita for all 50 states and 3108 counties in the US from 2010 to 2017. These improved methods revealed substantially more states and counties that were not WS relative to results using the Arrow et al. framework. The not-WS counties exhibited a distinct rural bias, as regional scientists have suspected but, nevertheless, the majority of rural counties were WS. Our work demonstrated that regional WS assessment is feasible, produces results that are consistent with prior expectations based on reasoning and empirical research, and has the potential to provide fresh insights into longstanding questions of regional development. Full article

Under the global climate governance framework, the Paris Agreement and the China–U.S. Glasgow Joint Declaration established a non-negotiable target of limiting 21st-century temperature rise to 1.5 °C. To date, over 130 nations have pledged carbon neutrality by mid-century, with agricultural activities contributing 25% of global greenhouse gas (GHG) emissions. The spatiotemporal dynamics of these emissions critically determine the operational efficacy of carbon peaking and neutrality strategies. While China’s Nationally Determined Contributions (NDCs) commit to achieving carbon peaking by 2030, a policy gap persists regarding differentiated implementation pathways at the county level. Addressing this challenge, this study selects the Three Gorges Reservoir (TGRA)—a region characterized by monocultural cropping systems and intensive fertilizer dependency—as a representative case. Guided by IPCC emission accounting protocols, we systematically evaluate spatiotemporal distribution patterns of agricultural CH₄ and N₂O emissions across 18 county-level units from 2006 to 2020. The investigation advances through two sequential phases: Mechanistic drivers analysis: employing the STIRPAT model, we quantify bidirectional effects (positive/negative) of critical determinants—including agricultural mechanization intensity and grain productivity—on CH₄/N₂O emission fluxes. Pathway scenario prediction: We construct three developmental scenarios (low-carbon transition, business-as-usual, and high-resource dependency) integrated with regional planning parameters. This framework enables the identification of optimal peaking chronologies for each county and proposes gradient peaking strategies through spatial zoning, thereby resolving fragmented carbon governance in agrarian counties. Methodologically, we establish a multi-scenario simulation architecture incorporating socioeconomic growth thresholds and agroecological constraints. The derived decision-support system provides empirically grounded solutions for aligning subnational climate actions with global mitigation targets. Full article

Amid China’s “dual carbon” goals of achieving carbon peaking and carbon neutrality, understanding the spatial dynamics of carbon emissions is essential for promoting coordinated regional decarbonization. This study takes a systems perspective to investigate the drivers and network structures of carbon emissions across 31 Chinese provinces from 2000 to 2022. Utilizing a Spatial Durbin Model (SDM) alongside social network analysis (SNA), it examines both the spatial spillover effects of key economic and innovation-related factors and the structural characteristics of interprovincial carbon transmission networks. The main findings include the following: (1) a significant spatial autocorrelation in provincial carbon emissions, indicating strong cross-regional spillover effects; (2) a nonlinear, inverted U-shaped relationship between green innovation and carbon emissions, where emissions initially rise before declining as innovation matures; (3) a dual impact of human capital, which increases local emissions but reduces emissions in neighboring regions through knowledge diffusion; and (4) the identification of key provinces such as Shaanxi, Henan and Hubei as central nodes within the carbon emission network, acting as influential hubs in the transmission of carbon emissions. This study highlights the importance of differentiated policy design based on regional network centrality and advocates for a systemic governance framework that promotes technology diffusion, talent mobility, and collaborative emission control across provinces. The integrated SDM-SNA approach provides a novel perspective for understanding the complexity of carbon governance in large economies and offers a flexible framework that can be adapted to other national or subnational settings. Full article

Biodiversity loss is a global environmental concern, mainly driven by human-induced factors, encompassing both direct and indirect drivers. This study investigates the long-term relationship between either the Human Footprint Index (HFI), which measures the extent of human pressures (i.e., direct drivers), or the Gross Domestic Product (GDP), a measure of economic growth (i.e., indirect driver) and biodiversity change, using bird population trends as indicators. The analysis was based on time-series data for Portugal (2004–2023) aggregated at national and sub-national scales, representative of different socio-economic contexts. Multi-species indices were regressed against either the HFI or GDP using Autoregressive Distributed Lag (ARDL) to identify long-run relationships. Bird population trends varied by species group (common, agricultural, and forest birds) and socio-economic context underscoring the importance of sub-national assessments. The HFI and GDP had varying predictive value across species groups and socio-economic contexts, with the HFI showing greater consistency, particularly as a predictor for agricultural birds. While most models showed a negative association between species abundance and either the HFI or GDP, revealing a signal of socio-economic pressures on bird populations at sub-national scales, some models suggested mixed results, indicating that conservation policies must take local contexts into account. Full article

Place-specific socioeconomic features are unique and, unlike first-nature geography, are shaped and reshaped by human and institutional interactions. In Ethiopia, however, policy thinking has not progressed much beyond first-nature geography, overlooking the multidimensional socio-spatial formations of rural areas. This study, based on nationally representative socioeconomic panel data from 2018/19 and 2021/22, used a place-based framework to explore the complex nature of rural development and its relationship with multidimensional, place-specific key determinants, namely rurality and entrepreneurial ecosystems. Indices for the key variables were developed by reducing their dimensions using Principal Component Analysis to measure multidimensional variables, including rural development, and undertake subsequent examinations. The study examines the effects of the key determinants on rural development using the Fixed Effects Instrumental Variables–Two-Stage Least Squares regression model, owing to endogeneity concerns with the key determinants. The study shows significant effects of both rurality and entrepreneurial ecosystems on rural development. It offers insights into the complex socio-spatial formations and explanatory power of rural contexts and contributes to the understanding of a place-based approach to rural development. The study also contributes to national and sub-national strategies to address rural challenges in Ethiopia and beyond. Full article

The relationship between inflation and foreign direct investment (FDI) is not clear-cut in theory. In the U.S., rising inflation coupled with increased economic recovery boosted FDI immediately after the COVID-19 pandemic but suppressed it afterwards. To shed light on the relationship between inflation and the resulting contractionary monetary policy and FDI, three key propositions were put forth for investigation. The propositions rely on relevant scientific literature showing that (1) although the connection between FDI and inflation is complex, a high and sustained inflation depresses incoming FDI due to increases in uncertainty and guarding government policies; (2) there exist significant location-based differences in how this connection manifests; and (3) high inflation and subsequent policies motivate FDI-related strategic action. Thus, we propose that new FDI is expected to be negatively affected by the rising entry cost associated with an inflationary economy that adopts anti-inflationary policies. Second, there exists heterogeneity in the effects of inflation on new FDI across subnational economies with various local characteristics. Third, existing FDI demonstrates strategic actions and expansion at the subnational location and beyond, even under inflationary pressure. We employ a positive comparative analysis based on descriptive statistics and qualitative interpretation of data to examine the status and activities of both new FDI (using subnational aggregated data) and existing foreign businesses (using firm-level data) in the state of New Hampshire during the recent inflation surge of 2022–2023. Our analysis provides empirical evidence supporting our propositions. Key implications are that, during challenging times of inflation and recovery, business leaders and economic development professionals should anticipate strategic actions to expand markets, products, operations, and partnerships. Leaders and professionals should act to take advantage of business actions outside the subnational location, as more companies look to strengthen and diversify their national and international networks. Full article

Background: Measles elimination strategies include supplementary immunization activities (SIAs) to rapidly fill immunity gaps. Post-campaign coverage surveys (PCCSs) are recommended to assess SIA coverage. We characterized selected PCCSs performed following recent SIAs, highlighting specific challenges and strengths, and provide recommendations for improvement. Methods: We extracted national SIA data from the global measles/MR SIA database for the period of 2020–2023 and reviewed PCCS reports available at the World Health Organization headquarters. We extracted selected information on PCCS implementation, including information about the implementer, sampling, and main results. Results: Only 15 of 66 countries (23%) with a national-level SIA performed since 2020 had a PCCS report available. We reviewed those reports, plus six more, following three 2019 SIAs with a delayed PCCS and two PCCSs following large subnational SIAs (Kenya 2021 and Yemen 2023). All 24 PCCS reports available were from Gavi-eligible countries, with 15 from South Saharan Africa (Cameroon, the Democratic Republic of the Congo, and Ethiopia had two PCCSs). Eleven (45.8%) PCCSs were conducted within three months of the end of the SIA. All included sampling information and most had percentage of participation. Description of the interviewers’ profiles varied but was limited. PCCS coverage was lower than administrative data in all but two instances. All PCCSs collected data on previous measles vaccination status that would allow exploring indicators on the SIA reaching previously measles zero-dose children. Of the 12 PCCSs reporting coverage among previously measles zero-dose children, nine reported coverage among this group of more than 50% (range: 12% and 91.6%). Conclusion: Even though a PCCS following an SIA is recommended and a requirement in Gavi-supported countries, most SIAs are not followed by a PCCS and, when performed, the timeliness of survey implementation needs improvement. Recent PCCSs were independently conducted and reports included basic survey information, but analysis and presentation of survey results vary particularly for measles zero-dose-related indicators. More guidance and technical support on how to implement PCCSs, including standardization of reports and more in-depth PCCS analyses, may help improve reporting and use of available PCCS data. Full article

Sub-national governments (SNGs) in developing countries have increasingly explored green municipal bonds as a financing tool, driven by promises of lower borrowing costs, enhanced reputation, and support for sustainable economic development. This study aims to critically examine these claims by analysing the actual costs and complexities associated with green municipal bonds (GMBs). The research involves a comparative analysis of traditional municipal bonds and GMBs, focusing on the financial and operational challenges faced by SNGs. Detailed case studies from Mexico City and Cape Town are used to illustrate the practical implications of issuing GMBs. The findings reveal that, despite similar or slightly lower interest rates, GMBs often entail higher issuance costs due to the need for certification, monitoring, and reporting of green projects. These additional costs, coupled with the necessity of hiring external consultants, make GMBs more expensive and difficult to replicate after initial transactions. Furthermore, the study highlights that the demand from investors has not met initial expectations. While green-aligned investors show a higher appetite for GMBs, they constitute only a small portion of the finance market. Traditional investors, primarily focused on financial returns, are less inclined to invest in GMBs solely based on their green label. Consequently, many SNGs are increasingly turning to traditional “vanilla” municipal bonds as a more viable option for financing green initiatives. This shift underscores the practical challenges of GMB issuance in developing countries and calls for a strategic approach to balance the use of GMBs with other financing options to promote sustainable economic development. Full article

Tick-borne encephalitis (TBE) is a viral infection affecting the central nervous system (CNS) with potential long-term consequences including neurological sequelae. Vaccination is critical to reduce TBE morbidity and mortality, as no antiviral treatment is available. The World Health Organization (WHO) defines areas with an incidence of ≥5 cases/100,000 PPY as highly endemic and recommends that vaccination is offered to all individuals in these areas. However, access to TBE vaccination depends on recommendations and funding by national or subnational decision-makers. We assessed if TBE vaccination could offer good value for money at incidences below this threshold. Methods: A closed-cohort Markov model was developed to estimate the cost-effectiveness of TBE vaccination. We compared primary vaccination applied to the whole population (aged above 1 year) and to a subpopulation aged between 60 and 85 years to a scenario without vaccination. Since TBE incidence is often underestimated, we included under-ascertained TBE cases and non-CNS TBE infections. Germany was used as a case study due to the availability of detailed incidence data. Results: Our incidence threshold analysis showed that TBE vaccination offers good value for money well below the WHO threshold in most of the analyzed scenarios. Conclusions: Our results support a recommendation for TBE vaccination even in settings with low numbers of reported cases, especially for older patients. Furthermore, this analysis identified major research gaps regarding the costs, utilities, and clinical progression of TBE. Full article

Introduction: The Democratic Republic of Congo (DRC) does not have national prevalence data for arterial hypertension (HTN) or diabetes (type I and II combined) to aid evidence-based decision-making, despite the assumption of epidemiological transition in low- and middle-income countries. The aim of this study was to estimate a proxy of prevalence for HTN and diabetes. Methodology: This study used routine monthly reported data pertaining to HTN and diabetes from the District Health Information Software 2 (DHIS2), spanning 2019–2023. Data underwent quality assessment and adjustments using standardization before analysis. Equity analyses were carried out at the national and sub-national levels. Epidemiological curves and maps were produced to analyze trends in the prevalence of HTN and diabetes among adults aged 18 and over. Permission to use the data was obtained from the regulatory authority. Results: Over five years, incidence of HTN increased from 13.23% (CI 95%: 13.22–13.24) to 15.23% (CI 95%: 15.22–15.24) (+15.1% relative increase), and diabetes rose from 2.73% (CI 95%: 2.72–2.74) to 3.345% (CI 95%: 3.34–3.35) (+16.3% relative increase), with provincial variations observed. Conclusions: In the DRC, hypertension and diabetes are advancing rapidly. Primary and preventative healthcare services and public health interventions must prioritize these diseases. Full article