This study aims to identify gaps in Indonesia’s national social health insurance scheme (Jaminan Kesehatan Nasional or JKN) in meeting the right to health for disabled persons in the country and to propose strategies to mitigate the gaps. This study employed descriptive qualitative methodologies. A questionnaire survey and structured interviews were undertaken from the period of October to December 2021, with a purposive sample of 317 disabled persons at their working age. Data collection also included on-site observations to sample of healthcare providers in six provinces and focused group discussions with key stakeholders. This study found that JKN is the primary source of hope for disabled persons. Nevertheless, approximately ten percent of disabled persons have been omitted from the scheme. Moreover, respondents of the survey expressed notably lower satisfaction level compared to the national average. Meanwhile, 25% of them also reported that JKN did not cover certain disability-specific benefits. The findings suggest that the national social health insurance scheme is not well prepared to offer disability-inclusive services. Thereby, policymakers should implement various interventions to improve the admission processes for disabled persons and to develop a system to identify disabled members based on their specific disabilities. Additionally, stipulating standards for disability-friendly minimum services for healthcare providers and incorporating the standards into the credentialing systems, providing regular training on disability-friendly services for healthcare personnel, also enhancing benefits coverage for disabled members in the Indonesian Case Base Groups (INA-CBGs) are the necessary strategies to mitigate the gaps.

This study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.

This paper tries to understand economic, social and legal implications of the introduction and usage of MediSearch (AI search engine) in the Indian healthcare context. Discussing the economic ramifications, the paper highlights the potential for cost savings, the influence on healthcare accessibility, and the shifts in traditional medical paradigms. On the social side, the study explains ability of AI based platforms to bridge healthcare disparities, with a potential for enhancing general health literacy among the general population. From a legal standpoint, study highlights the concerns related to data privacy, regulatory issues, and possible malpractice implications. With the integration of these perspectives, the study also explains opportunities, challenges and future of MediSearch from the Indian health perspective.

The increase in energy consumption is closely linked to environmental pollution. Healthcare spending has increased significantly in recent years in all countries, especially after the pandemic. The link between healthcare spending, greenhouse gas emissions and gross domestic product has led many researchers to use modelling techniques to assess this relationship. For this purpose, this paper analyzes the relationship between per capita healthcare expenditure, per capita gross domestic product and per capita greenhouse gas emissions in the 27 EU countries for the period 2000 to 2020 using Error Correction Westerlund, and Westerlund and Edgerton Lagrange Multiplier (LM) bootstrap panel cointegration test. The estimation of model coefficients was carried out using the Augmented Mean Group (AMG) method adopted by Eberhardt and Teal, when there is heterogeneity and cross-sectional dependence in cross-sectional units. In addition, Dumitrescu and Hurlin test has been used to detect causality. The findings of the study showed that in the long run, per capita emissions of greenhouse gases have a negative effect on per capita health expenditure, except from the case of Greece, Lithuania, Luxembourg and Latvia. On the other hand, long-term individual co-integration factors of GDP per capita have a positively strong impact on health expenditure per capita in all EU countries. Finally, Dumitrescu and Urlin’s causality results reveal a significant one-way causality relationship from GDP per capita and CO₂ emissions per capita to healthcare expenditure per capita for all EU countries.

Sanitation challenges are growing at unprecedented rates in the Middle East and North Africa (MENA) region, specifically in the country of Jordan, where more adversities are faced in the provision of inclusive and sustainable sanitation for marginalized communities. The overloaded water supply systems, strained by high population density in the face of political instability manifests itself in poor public health. How countries in the MENA region plan to handle these problems and improve the sanitation infrastructure is the starting point for this work. We aim to develop a comprehensive and multidisciplinary framework between stakeholders, aligned with the Sustainable Development Goals (SDGs), with a specific emphasis on SDG 6, for providing feasible, community-oriented approaches to sanitation issues in disenfranchised communities in Jordan through the Initiative Sanitation and Hygiene Networking in Jordanian Poverty Pockets (ISNJO) project. The findings will be used to formulate strategic guidelines and inform the development and subsequent initiation of innovative and multidisciplinary initiatives to tackle the sanitation and water scarcity challenges at hand.

The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.