Subnational Areas Research Articles

The Demographic Causes of European Sub-National Population Declines

Population decline is now established at the continental scale in Europe, occurring in abundance across sub-national areas and outweighing population growth. This represents an unfamiliar pathway of demographic change and is set to present unique challenges to the functioning of societies and economies. The nature of these challenges will be influenced by the demographic cause of population decline. Typically, low fertility is cited as the primary instigator, though it remains unclear of the ways in which unique interactions between fertility, mortality and migration have shaped contemporary population decline outcomes. This study empirically analyses the demographic causes of population decline in 732 sub-national areas extending across 33 European countries. Drawing on data derived from national statistics from 2000–2018, we employ a novel methodological approach consisting of decomposition, multivariate functional principal component analysis, and k-medoid clustering to identify the dominant demographic processes underpinning European depopulation. Our analysis reveals five unique signatures, encoding nuanced contributions from fertility, mortality and migration changes. Population decline is found to be a multi-causal process, with natural deficits and negative rates of net-migration both operating depopulations in most instances. We conclude that natural deficits are ubiquitous in causing sub-national population declines with net-migration patterns responsible for determining annual rates of population loss. We model the relationship between these signatures and wider demographic, socio-economic and geo-spatial attributes, finding that a distinct combination of contextual factors are associated with different demographic causes of population decline.

Geospatial mapping of drug-resistant tuberculosis prevalence in Africa at national and sub-national levels.

Geospatial mapping of drug-resistant tuberculosis prevalence in Africa at national and sub-national levels.

Estimating program coverage in the treatment of acute malnutrition using population-based cluster survey methods: results from surveys in Burkina Faso, Chad, Democratic Republic of the Congo, and Niger.

Despite their utility for program planning, acute malnutrition treatment coverage estimates at the national and sub-national levels are rarely available. Prior work has identified methodological concerns with current approaches. We estimated the point prevalence and treatment coverage of acute malnutrition in 11 districts (or similar subnational areas) across four high-burden countries in Africa using representative cluster-based population survey methods and compared these estimates to those derived from administrative data and other direct methods where available. We also aimed to assess information about risk factors for malnourished children by coverage status. The point estimate of coverage suggests that <20% of eligible children with severe acute malnutrition (SAM) were enrolled in treatment in nine administrative areas. We found that in some contexts, coverage estimates derived using administrative data are useful, while in others, they are not - and that their accuracy can vary by month and year. By comparison, coverage estimates from other direct methods were overestimated and/or outdated, and practitioners tended to overestimate coverage. Coverage did not differ significantly by sex or age of the child but did vary by mid-upper arm circumference (MUAC) at assessment. Measured SAM coverage did not correlate either with measured SAM prevalence or with expected coverage estimated a priori by program staff. Our findings suggest that in the assessed high-burden countries, many more children are eligible for treatment than are enrolled. We present this methodology as an alternative to existing primary methods and a complement to coverage estimates from routine program and population data.

African households: National and subnational trends from censuses and surveys

Using census and survey microdata from 49 African countries across 415 subnational areas, we offer a comprehensive overview of household size and composition in Africa. The study emphasizes the potential of these data for understanding family dynamics through co-residential units. Clear regional patterns emerge, showcasing a wide range of household sizes across the continent. We find that household size is linked primarily to the number of children and secondarily to the presence of other family and non-family members beyond the nuclear household. The analysis of household composition also highlights the uneven influence of polygyny and extended families. This research is a first step in examining harmonized census and survey data to delve into the structure and dynamics of households across Africa from a demographic perspective.

A Bayesian Approach to Produce Subnational Population Estimates Using a Population Base Statistical Register

Subnational Population Estimates (SPE) in Latin America are useful to implement new public policies in subnational areas with internal armed conflicts or difficult to access. In this work, we propose to combine a Population Base Statistical Register (PBSR) and the Official Population Projections (OPP) using a Bayesian approach to produce SPE. Our proposed procedures are useful for computing SPE of the population size or the SPE of the population size in percentage SPE (%). However, we focused on SPE (%) due to some data restrictions and to ensure data confidentiality. In this article, the PBSR is constructed using multiple administrative sources with registers from the health, education, vital statistics systems, tax registration, and, more importantly, the registers of the victims of the current internal armed conflict in Colombia. We also propose new fast Markov chain Monte Carlo algorithms to produce SPE (%) using data augmentation procedures to address the complications caused by the resulting joint posterior containing gamma functions. We implement our proposal to compute SPE (%) by age and sex groups in the municipality of Jamundí in Colombia which is currently affected by poverty, forced displacement, and the internal armed conflict and evaluate the accuracy with a Population Census.

Accelerating Progress in Women’s Sexual and Reproductive Health and Rights Decision-Making: Trends in 32 Low- and Middle-Income Countries and Future Perspectives

In 1994, the International Conference on Population and Development (ICPD) Programme of Action established the empowerment and autonomy of women as fundamental to achieving sustainable economic and social progress. Three decades later, significant strides have been made in enhancing sexual and reproductive health and rights (SRHR). However, deep-rooted gender inequality continues to impede substantial progress for many. We assess the advancements made under the Sustainable Development Goals, specifically through indicator 5.6.1, which measures women's SRHR decision-making. Using data from 76 Demographic and Health Surveys and 1 Multiple Indicator Cluster Survey in 32 low- and middle-income countries from 2006 to 2022, the study analyzed trends in women's SRHR decision-making and its subcomponents of autonomy on reproductive health care, contraceptive use, and sexual relations-among married or in-union women aged 15-49 years currently using contraception. The analysis also examined trends in decision-making disparities related to household wealth quintiles, women's education levels, and area of residence, using disaggregated population-weighted percentages. Analysis revealed a generally positive trend in women's SRHR decision-making, with gains observed in Eastern and Southern Africa and notable declines in West and Central Africa. Subindicator disparities showed variations in autonomy across health care, contraception, and the ability to refuse sex. An inequality analysis highlighted that while some countries saw a narrowing wealth gap in decision-making, others faced growing disparities. Educational and urban-rural divides also shifted, reflecting a complex landscape of progress and challenges in improving women's SRHR decision-making. The analysis underscores a patchwork of progress in women's SRHR decision-making while also exposing deep disparities. These data suggest a critical need for interventions tailored to cultural and socioeconomic contexts, particularly in countries and subnational areas lagging behind. Forward-thinking strategies must prioritize enhancing women's reproductive agency, ensuring interventions are informed by community-tailored priorities and global human rights standards.

Maternal health planning and prioritization in Chad: developing a supportive tool.

The Republic of Chad has one of the highest rates of maternal mortality in the world. With scarce resources to respond to competing demands, pragmatic evidence-based planning tools are needed to aid planning and support priority setting. This action research aimed to develop a tool to support maternal health (MH) planning and prioritization decisions and identify priority regions/provinces for intervention in Chad based on aggregate MH coverage gap scores (Target-Coverage = Coverage Gap). A rapid review was conducted to identify key indicators and relevant national targets. The 2019 Multiple Indicator Cluster Survey and other national surveys were the data sources for selected indicators at the provincial level. Aggregate MH coverage gaps were calculated and displayed using geographic information system software to visualize variations by province. Eleven key informant interviews (KIIs) and six focus group discussions (FGDs) were conducted with clinicians and administrators to understand existing MH planning, prioritization, and maternal mortality risks in Chad. Wide provincial variation in aggregate MH coverage gaps was identified (mean score 374.3, SD: 77.4). Indicators contributing the most to coverage gaps include emergency obstetric care, adolescent births, tetanus vaccination, and delivery by skilled health personnel. Two weighting scenarios for the coverage gap scores are also considered. KIIs and FGDs revealed that existing MH planning in Chad differs provincially and by health system level, with no clear prioritization processes identified. Main themes regarding MH risks reported by stakeholders included challenges relating to the health system, policy landscape, country and population-specific factors, along with specific MH threats. Current centralized planning approaches may benefit from greater consideration of provincial differences to support more efficient and equitable resource distribution. This multi-indicator assessment offers an adaptable approach for evidence-based MH resource allocation to prioritize subnational areas with worst health indicators in resource-limited settings, although further research is needed to test its impact.

Ethnic diversity and political trust at the onset of the COVID-19 pandemic

Abstract Current research faces challenges in explaining how contextual factors account for variations in the rally effect in political trust during the COVID-19 pandemic. While systematic explanations of country-level differences are hard to establish by means of cross-sectional comparisons, we propose to compare subnational areas within a country to learn more about the role of contextual factors. In this research note, we argue that ethnic diversity is a crucial contextual factor that helps researchers understand differences in political trust at the onset of the pandemic. Specifically, we propose that the rally effect should be restricted to ethnically more homogeneous contexts. An analysis of geocoded household panel data from the Netherlands reveals a strong rally effect in ethnically homogenous areas, while political trust in ethnically diverse contexts appears not to respond to the pandemic. This suggests an entrenched geography of political trust, which is associated with ethnic divides and is even maintained under crisis.

Investigating precipitation pattern and variability in the Niger Delta: a statistical analysis of trends and change points (1972–2022)

There has been significant variation in precipitation in different parts of the world, and increasingly this has been attributed to climate change. Despite reliance on rain-fed agriculture, detailed analysis of regional precipitation trends within specific sub-national areas, such as the Niger Delta, remains scant. This study examines annual rainfall trends over 51 years (1972–2022) across seven stations in the Niger Delta using different statistical methods. Descriptive statistics show different patterns among stations, some showing upward trends, others declines. Mean annual rainfall ranges from 1,969.05 mm in Akure to 2385.04 mm in Port Harcourt, showing significant regional variability. Linear regression and LOWESS analysis show mixed trends; Mann–Kendall and Spearman’s Rho tests showed significant increase in Owerri, while Sen’s slope analysis confirms varying trends across the region. Pettitt test results confirms Owerri’s significant increase in precipitation. This study contributes to a greater understanding of precipitation trends in the Niger Delta.

Mapping sugarcane globally at 10 m resolution using Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2

Abstract. Sugarcane is an important source of food, biofuel, and farmer income in many countries. At the same time, sugarcane is implicated in many social and environmental challenges, including water scarcity and nutrient pollution. Currently, few of the top sugar-producing countries generate reliable maps of where sugarcane is cultivated. To fill this gap, we introduce a dataset of detailed sugarcane maps for the top 13 producing countries in the world, comprising nearly 90 % of global production. Maps were generated for the 2019–2022 period by combining data from Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2 (S2). GEDI data were used to provide training data on where tall and short crops were growing each month, while S2 features were used to map tall crops for all cropland pixels each month. Sugarcane was then identified by leveraging the fact that, among all non-tree species grown in cropland areas, sugarcane is typically tall for the largest fraction of time. Comparisons with field data, pre-existing maps, and official government statistics all indicated high precision and high recall of our maps. Agreement with field data at the pixel level exceeded 80 % in most countries, and subnational sugarcane areas from our maps were consistent with government statistics. Exceptions appeared mainly due to problems in underlying cropland masks or due to under-reporting of sugarcane area by governments. The final maps should be useful in studying the various impacts of sugarcane cultivation and producing maps of related outcomes such as sugarcane yields. The dataset is available on Zenodo at https://doi.org/10.5281/zenodo.10871164 (Di Tommaso et al., 2024a).

Climate-driven interannual variability in subnational irrigation areas across Europe

Irrigation profoundly impacts ecology and agricultural productivity, with irrigated areas varying across regions and years. Interannual dynamics of irrigation extent are lacking, particularly in humid regions of Europe. We analyzed the response of irrigated areas to drought conditions in areas equipped for irrigation and used the derived relationships to estimate annual irrigated areas for 32 European countries in the period 1990–2020. Interannual variability of irrigated areas varied notably, particularly in more humid Northern and Western Europe. In most humid regions, irrigated area is larger in dry years, whereas in more arid regions like Spain, it is larger in wet years. The largest irrigated area across Europe occurred in dry years 2003 and 2018 (11.93 and 11.77 million hectares), while the smallest is estimated for the wet years 2002 and 2014 (10.71 and 10.31 million hectares). The findings of this study help to improve scenario development and water resources management.

Adjusting mobile phone data to account for children’s travel and the impact on measles dynamics in Zambia

Models of measles transmission can be used to identify areas of high risk to tailor immunization strategies. Estimates of spatial connectivity can be derived from data such as mobile phone records, but it is not clear how this maps to the movement of children who are more likely to be infected. Using travel surveys across 2 districts in Zambia and national mobile phone data, we compared estimates of out-of-district travel for the population captured in the mobile phone data and child-specific travel from travel surveys. We then evaluated the impact of unadjusted and adjusted connectivity measures on simulated measles virus introduction events across Zambia. The number of trips made by children from the travel survey was 3 to 5 times lower than the general population estimates from mobile phone data. This decreased the percentage of districts with measles virus introduction events from 78% when using unadjusted data to 51% to 64% following adjustment. Failure to account for age-specific heterogeneities in travel estimated from mobile phone data resulted in overestimating subnational areas at high risk of introduction events, which could divert mitigation efforts to districts that are at lower risk.

EHerbarium: A Global Platform for Exploring and Sharing Herbarium and Live Plant Images to Enhance Biodiversity Preservation

Historically, herbaria have been instrumental in preserving and studying plant biodiversity. The widespread use of smartphones has led to a surge in the digital documentation of plants. Over the last decade, herbarium digitizing projects are also underway. Many of the digitized herbarium images are available online through different portals. The examples of these portals include Kew Gardens and New York Botanic Garden Herbarium. Combining the latest mobile, cloud and AI technologies as well as plant taxonomy and herbarium artifacts, the mission of eHerbarium*1 is to provide an accessible digital platform for plant enthusiasts, including botanists, researchers, students, as well as the general public around the world, to collect, identify and share live plant and herbarium images. It promotes data collection and data sharing around the globe for biodiversity preservation. It further provides educational benefits about plants and the plant biodiversity around us and the world. eHerbarium offers access to an extensive collection of herbarium images from Kew’s Herbarium at the Royal Botanic Gardens, Kew. The platform is also extensible, allowing it to host images from other herbaria. In addition, this platform provides high-quality botanical visuals, enabling users to capture and share live plant photos or herbarium images, or upload from existing collections. Customizable licensing options facilitate community use and enhance collaborative botanical research. The platform’s AI-powered tools streamline plant identification, offering autocomplete suggestions for taxonomy details such as scientific name, family name or common names. Our proprietary technology ensures seamless and accurate botanical data entry by automatically retrieving corresponding scientific or common names. Additionally, eHerbarium enriches botanical records by automatically associating image locations with Biodiversity Information Standards (TDWG) Level 2 regions. TDWG Level 2 regions are specific geographical areas defined by TDWG to standardize the recording and reporting of biodiversity data. These regions, which typically correspond to large countries or significant subnational areas, help ensure consistent and accurate geographical referencing in botanical studies and herbarium records, while also respecting image owners' location privacy. eHerbarium has more than 40,000 worldwide downloads since its debut less than six months ago on March 18, 2024. We encourage further collaborations to expand our repositories for herbarium and live plant images. We also welcome partnerships to tailor the application to specific needs for natural history and biodiversity data collection.

GLocal: A global development dataset of subnational administrative areas

The purpose of the GLocal dataset is to enable research in international development that requires both global scope and local precision. Leveraging modern geospatial analysis tools, we process a diverse array of sources to provide researchers with a growing set of economic, demographic, ecological and socio-political variables for geographic units relevant to public policy. We provide separate data files for different levels of administrative and periodic aggregation, along with ad-hoc files with more detailed information on specific topics. In this data descriptor paper, we discuss both our data processing methodologies and validation pipelines, and provide a short case study to illustrate the research potential of the dataset. We also introduce a simple web app, glocal.streamlit.app, which offers a user-friendly interface for exploring and visualizing the dataset. Given the growing number of public and granular sources of relevance for international development research, we hope to continue adding features and expand the GLocal dataset in the future.

The Relationship Between Climate Change and Indonesia's Malaria Burden

ABSTRACTMalaria has been with humans for thousands of years. It is caused by parasites of the genus Plasmodium that are transmitted by female Anopheles mosquitoes. The variation of global malaria distribution has recently been associated with changing climatic conditions, such as temperature, precipitation, windspeed, and humidity. One country where malaria transmission remains high in select subnational areas is Indonesia. Founded upon previous findings on the relationship between climate change and malaria, this research delves into the same equation for the case of Indonesia through a structural model which overcomes the variable co‐interaction between temperature, precipitation, windspeed, and humidity. This study follows an ecological study design with yearly longitudinal data (t = 20, n = 432). The method of analysis employed is a structural equation modelling approach for panel datasets with an output of factor loading values to determine association levels. The independent variable is a climate change construct of maximum, minimum, and average values from temperature, windspeed, relative humidity and precipitation as observables taken from the NASA Langley Research Center (LaRC) POWER Project. Meanwhile, the dependent variable is yearly malaria incidence rates at the city and regency level extracted from the Malaria Atlas Project dataset. All variables are standardized to account for unit differences. The SEM results indicate a standardized relationship between a latent climate variable with malaria incidence in a statistically significant manner. However, differences in coefficient directions between the three models indicate that the relationship remains elusive. In the maximum value model, a standard deviation increase in the climate change construct from its mean is associated with a 0.04 standard deviation increase in malaria incidence from its own mean (p &lt; 0.001). On the other hand, in the minimum and average value models, a standard deviation increase in limate change construct from its mean is associated with a 0.12 and 0.09 standard deviation decrease of malaria incidence from its own mean respectively (p &lt; 0.001). Although statistical significance was established across all models which indicated relatively good fit across select indices, the standardized coefficient values presented in this study suggest that any associations between long term climatic variations (measured by yearly data) and malarial incidences are modest at best. The results of the structural equation models also indicate that other factors are at play when it comes to malaria case variations—as explained by the residual terms across all models.

Unravelling factors influencing demand for modern contraception and evaluating coverage progress since 2015 in Ethiopia, Kenya, and Nigeria: insights from multilevel and geostatistical modelling

IntroductionThe United Nations established the Sustainable Development Goals (SDGs) in 2015 to enhance global development. In this study, we examine an SDG indicator: the percentage of women aged 15–49 whose family planning needs are met by modern contraception (mDFPS). We evaluate both the factors influencing its coverage and its progress since 2015.MethodsWe used nationally representative surveys data (Demographic and Health Surveys (DHS) and Performance Monitoring for Action (PMA)) from Ethiopia, Kenya, and Nigeria. We assessed predictors of mDFPS. We also computed mDFPS coverage across countries and subnational areas, assessing coverage changes from the SDGs onset to the most recent period, using a Bayesian model-based geostatistical approach. We assessed whether the subnational areas exceeded the minimum recommended WHO mDFPS coverage of 75%.ResultsVaried individual and community-level determinants emerged, highlighting the countries’ uniqueness. Factors such as being part of a female-headed household, and low household wealth, lowered the odds of mDFPS, while rural-residence had low odds only in Ethiopia and Nigeria. The results indicate mDFPS stagnation in most administrative areas across the three countries. Geographic disparities persisted over time, favouring affluent regions. The predicted posterior proportion of mDFPS and exceedance probability (EP) for WHO target for Ethiopia was 39.85% (95% CI: [4.51, 83.01], EP = 0.08) in 2016 and 46.28% (95% CI: [7.15, 85.99], EP = 0.13) in 2019. In Kenya, the adjusted predicted proportion for 2014 was 30.19% (95% CI: [2.59, 80.24], EP = 0.06) and 44.16% (95%CI: [9.35, 80.24], EP = 0.13) in 2022. In Nigeria, the predicted posterior proportion of mDFPS was 17.91% (95% CI: [1.24, 61.29], EP = 0.00) in 2013, and it was 23.08% (95% CI: [1.80, 56.24], EP = 0.00) in 2018. None of the sub-national areas in Ethiopia and Nigeria exceeded the WHO target. While 9 out of 47 counties in Kenya in 2022 exceeded the WHO mDFPS target.ConclusionThe study unveils demographic, geographic, and socioeconomic mDFPS disparities, signalling progress and stagnation across administrative areas. The findings offer policymakers and governments insights into targeting interventions for enhanced mDFPS coverage. Context-specific strategies can address local needs, aiding SDG attainment.

The Subnational Corruption Database: Grand and petty corruption in 1,473 regions of 178 countries, 1995–2022

This data descriptor presents the Subnational Corruption Database (SCD), which provides data on corruption in 1,473 subnational areas of 178 countries. The SCD includes a comprehensive overall corruption index, the Subnational Corruption Index (SCI), and its two components: the Subnational Grand Corruption Index (SGCI) and Subnational Petty Corruption Index (SPCI). The SCD is constructed by combining data of 807 surveys held in the period 1995–2022 and includes the corruption experiences and perceptions of 1,326,656 respondents along 19 separate dimensions. The data are available for multiple years, allowing longitudinal analyses. At the national level, the SCI correlates strongly with established corruption indices, like the Transparency International Corruption Perceptions Index (CPI) and the World Bank Control of Corruption Index (CCI). We create subnational estimates of the CPI and CCI by superimposing the subnational variation of the SCI around the national averages of these indices. The presentation of subnational data in the SCD and the separation between grand and petty corruption significantly broaden the global knowledge base in the field of corruption.

Validating the indicator "maternal death review coverage" to improve maternal mortality data: A retrospective analysis of district, facility, and individual medical record data.

Understanding causes and contributors to maternal mortality is critical from a quality improvement perspective to inform decision making and monitor progress toward ending preventable maternal mortality. The indicator "maternal death review coverage" is defined as the percentage of maternal deaths occurring in a facility that are audited. Both the numerator and denominator of this indicator are subject to misclassification errors, underreporting, and bias. This study assessed the validity of the indicator by examining both its numerator-the number and quality of death reviews-and denominator-the number of facility-based maternal deaths and comparing estimates of the indicator obtained from facility- versus district-level data. We collected data on the number of maternal deaths and content of death reviews from all health facilities serving as birthing sites in 12 districts in three countries: Argentina, Ghana, and India. Additional data were extracted from health management information systems on the number and dates of maternal deaths and maternal death reviews reported from health facilities to the district-level. We tabulated the percentage of facility deaths with evidence of a review, the percentage of reviews that met the World Health Organization defined standard for maternal and perinatal death surveillance and response. Results were stratified by sociodemographic characteristics of women and facility location and type. We compared these estimates to that obtained using district-level data. and looked at evidence of the review at the district/provincial level. Study teams reviewed facility records at 34 facilities in Argentina, 51 facilities in Ghana, and 282 facilities in India. In total, we found 17 deaths in Argentina, 14 deaths in Ghana, and 58 deaths in India evidenced at facilities. Overall, >80% of deaths had evidence of a review at facilities. In India, a much lower percentage of deaths occurring at secondary-level facilities (61.1%) had evidence of a review compared to deaths in tertiary-level facilities (92.1%). In all three countries, only about half of deaths in each country had complete reviews: 58.8% (n = 10) in Argentina, 57.2% (n = 8) in Ghana, and 41.1% (n = 24) in India. Dramatic reductions in indicator value were seen in several subnational geographic areas, including Gonda and Meerut in India and Sunyani in Ghana. For example, in Gonda only three of the 18 reviews conducted at facilities met the definitional standard (16.7%), which caused the value of the indicator to decrease from 81.8% to 13.6%. Stratification by women's sociodemographic factors suggested systematic differences in completeness of reviews by women's age, place of residence, and timing of death. Our study assessed the validity of an important indicator for ending preventable deaths: the coverage of reviews of maternal deaths occurring in facilities in three study settings. We found discrepancies in deaths recorded at facilities and those reported to districts from facilities. Further, few maternal death reviews met global quality standards for completeness. The value of the calculated indicator masked inaccuracies in counts of both deaths and reviews and gave no indication of completeness, thus undermining the ultimate utility of the measure in achieving an accurate measure of coverage.

Where have Ukrainian refugees gone? Identifying potential settlement areas across European regions integrating digital and traditional geographic data

Abstract The escalation of conflict in Ukraine has triggered the largest refugee crisis in Europe since WWII. As of early April 2024, over 5.9 million people have fled Ukraine. Large‐scale efforts have been made to identify the major receiving countries. However, less is known about the subnational areas within host countries where refugees have migrated. Identifying these areas is key for the appropriate allocation of humanitarian aid. By combining digital Facebook API data and traditional data from Eurostat, this paper aims to identify and characterise potential settlement areas of Ukrainians across the main destination countries in Europe. We identify high concentrations of Ukrainians in urban areas with a preexisting diaspora and tight labour market conditions across southern, northern‐west and central Poland and the city of Prague in the Czech Republic. We also find potential settlements in key urban agglomerations with a moderate diaspora and high levels of unemployment in Spain. Only in Romania, refugees seem to have settled in rural areas which show a moderate diaspora but low levels of unemployment. Potential settlement areas in Germany, Italy and the United Kingdom are spread across the country. Surprisingly, we do not identify potential settlement areas in bordering regions with Ukraine within neighbouring countries, suggesting that refugees may have used them as transit points. Our findings point out that different packages of humanitarian assistance may be needed according to the number of refugees and the characteristics of settlement areas.

Estimating the relationship between ethnic inequality, conflict and voter turnout in Africa using geocoded data

Estimating the relationship between ethnic inequality, conflict and voter turnout in Africa using geocoded data