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Informing policy through evidence: a scoping review of factors that influence enrolment in community-based health insurance in East Africa
Get PDFBackground Community-based health insurance (CBHI) has emerged as a promising option to enhance the attainment of Universal Health Coverage in Low- and middle-income countries and Sub-Saharan Africa. However, CBHI schemes in Africa particularly in the eastern regions, grapple with chronic low enrolment, jeopardizing their sustainability and intended impact. Understanding the determinants of enrolment in these schemes is critical for designing effective strategies to boost participation. In this scoping review, we categorized and discussed these determinants across socio-ecological levels. Methods We conducted a scoping review of literature using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extended for Scoping Review checklist. Literature searches were conducted across academic databases to identify studies on determinants of enrolment to CBHI schemes in East Africa in June 2023 and updated in June 2025. Peer-reviewed, English-language studies using cross-sectional, case-control, qualitative, case studies, or mixed-methods designs were included which were conducted in East Africa and reported primary outcomes on determinants of CBHI enrolment (2000–2025). Excluded studies were reviews, non-peer reviewed articles, willingness to pay/willingness to enrol studies, and those on satisfaction, dropouts, or compulsory schemes (e.g., Rwanda post-2007, Seychelles as a high-income country). Data extraction and thematic analysis guided by a socio-ecological model framework were performed on the data. Results A total of thirty articles met the inclusion criteria. The findings unveiled a broad spectrum of determinants influencing CBHI enrolment. At the individual level, key factors included awareness, socio-demographics, and personal predisposition. At the household level, household characteristics, social capital, and cohesion played significant roles. Community-level determinants included cultural beliefs, religion, and geographical location, while system-level factors were stakeholder influence, governance, benefit package design, premium structure, human resource management, supply chain, access to care, and referral systems. Conclusions The findings emphasize the need for a holistic and multi-level approach to enhancing enrolment. Policymakers and stakeholders should integrate these determinants into interventions to strengthen CBHI schemes, expand healthcare access, and reinforce financial protection. Further studies are needed to explore the interplay between these factors
Autoregressive hypergraph
No full textTraditional graph representations are insufficient for modelling real-world phenom ena involving multi-entity interactions, such as collaborative projects or protein complexes, necessitating the use of hypergraphs. While hypergraphs preserve the intrinsic nature of such complex relationships, existing models often overlook tem poral evolution in relational data. To address this, we introduce a first-order autore gressive (i.e. AR(1)) model for dynamic non-uniform hypergraphs. This is the first dynamic hypergraph model with provable theoretical guarantees, explicitly defining the temporal evolution of hyperedge presence through transition probabilities that govern persistence and change dynamics. This framework provides closed-form ex pressions for key probabilistic properties and facilitates straightforward maximum likelihood inference with uniform error bounds and asymptotic normality, along with a permutation-based diagnostic test. We also consider an AR(1) hypergraph stochastic block model (HSBM), where a novel Laplacian enables exact and effi cient latent community recovery via a spectral clustering algorithm. Furthermore, we develop a likelihood-based change-point estimator for the HSBM to detect struc tural breaks. The efficacy and practical value of our methods are comprehensively demonstrated through extensive simulation studies and compelling applications to a primary school interaction data set and the Enron email corpus, revealing insightful community structures and significant temporal changes
A difference-in-difference approach to detecting AI-generated image
No full textDiffusion models are able to produce AI-generated images that are almost indistinguishable from real ones. This raises concerns about their potential misuse and poses substantial challenges for detecting them. Many existing detectors rely on reconstruction error — the difference between the input image and its reconstructed version — as the basis for dis tinguishing real from fake images. However, these detectors become less effective as modern AI-generated images be comeincreasingly similar to real ones. To address this chal lenge, we propose a novel difference-in-difference method. Instead of directly using the reconstruction error (a first order difference), we compute the difference in reconstruc tion error– a second-order difference– for variance reduc tion and improving detection accuracy. Extensive exper iments demonstrate that our method achieves strong gen eralization performance, enabling reliable detection of AI generated images in the era of generative A
Macroeconomic impacts of changes in land use in an agricultural-commodity exporting country: the case of Argentina, 2003–23
Get PDFPiloting climate storylines in adaptation finance as a tool to shift the political economy of adaptation policy and bankability
Get PDFAssociation of avian biodiversity and West Nile Virus circulation in Culex mosquitoes in Emilia-Romagna, Italy
Get PDFWest Nile Virus (WNV) is a zoonotic arbovirus maintained in a transmission cycle between Culex mosquitoes and birds, occasionally spilling over into humans. The impact of avian biodiversity on WNV circulation remains debated, with studies reporting both negative and positive correlations (dilution and amplification effects respectively) across different settings. In Europe, this relationship remains largely unexplored, particularly in regions with high WNV transmission, such as Emilia-Romagna in Northern Italy. We explored the association between avian biodiversity and WNV circulation in Culex mosquitoes in Emilia-Romagna using 11 years (2013-2023) of entomological surveillance data paired with two avian data sources. We calculated avian biodiversity indices (Shannon's, Simpson's, and Chao2) from observation records from the Farmland Bird Index project and applied linear regression models to assess their relationship with WNV detection frequency. Moreover, we used Bayesian spatiotemporal regression models and gridded weekly avian abundance estimates from the eBird project to analyse the associations between avian species richness indices and WNV transmission risk quantified by vector index (VI) at 68 geolocated mosquito traps across the region. We observed consistent negative associations between WNV detection frequency in the Culex population and avian biodiversity indices, supporting the dilution effect hypothesis (DEH). We found that non-passerine species richness was negatively associated with VI while passerine species richness showed a positive association after adjusting for covariates and spatial random effects. These findings suggest that passerines may amplify WNV transmission, whereas the presence of non-passerine species is associated with reductions in WNV circulation. This study provides the first empirical evidence supporting the DEH for WNV in Europe. These findings have important implications for biodiversity conservation and integrated public health surveillance activities across Europe. [Abstract copyright: Copyright: © 2026 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Mapping policies related to problematic usage of the internet in seven European countries: Netherlands, Spain, Hungary, Lithuania, Portugal, Estonia and Switzerland
No full textThis work presents a policy analysis regarding Problematic Usage of the Internet (PUI) across seven countries (Netherlands, Spain, Hungary, Lithuania, Portugal, Estonia, and Switzerland) belonging to or associated with the European Union (EU). I It examines legislative instruments addressing PUI and its multifaceted impacts on society, including social, economic, and political dimensions. Despite the growing prevalence of PUI, particularly among adolescents, and its association with various mental health concerns, the study reveals a notable gap in direct policy interventions targeting PUI within these countries. Existing regulations largely focus on broader digital governance issues like data protection, cybersecurity, and market regulation, offering only indirect approaches to mitigating PUI's adverse effects. Our findings highlight a pressing need for innovative policy frameworks that incorporate mental health considerations into digital governance, promoting a balanced approach that fosters market innovation while ensuring robust public health protections. Building on the policy discourse examined in this study, future research should focus on developing targeted, multidimensional strategies to mitigate the risks associated with problematic internet use (PUI), with particular emphasis on safeguarding the well-being of vulnerable populations
Kicking away the green ladder: the asymmetric sovereign risk from nature degradation
Get PDFThis paper investigates the uneven consequences of nature and biodiversity loss for the cost of sovereign government borrowing. A growing literature documents the adverse economic consequences of climate change. However, little attention has been devoted to the influence of nature degradation on sovereign bond yield spreads, which determine government’s funding costs and fiscal policy space. Employing panel interactive fixed effects and quantile regressions with latent factors, we extend the literature to the nature context with three proxies for countries’ nature-related financial vulnerability. Across 28 advanced and 25 emerging economies over the 2000-2020 period and 2, 5, and 10-year bond maturities, our results indicate substantial average impacts from within-country degradation for sovereign borrowing costs whilst controlling for conventional economic and institutional determinants, and common global financial factors. Our second-stage heterogeneity analysis reveals significant variation in impacts. We find that countries with elevated sovereign risk are disproportionally impacted by nature vulnerability, up to three times the average marginal effect of forty-to-fifty basis points for countries in the 90th percentile of borrowing costs. Our novel empirical results underline the asymmetric macro-criticality of nature for sovereign borrowing costs with disproportional effects that exacerbate existing macro-financial fragilities. Yet the financial effects are unlikely to be confined to debt-distressed, high-risk and nature-dependent countries, considering the integrated nature of global supply chains and sovereign debt markets