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Abstract AidData’s Global Chinese Development Finance Dataset (Version 3.0) provides detailed information about more than 20,000 development projects across 165 low- and middle-income countries financed by 791 official sector Chinese donors and lenders from 2000 to 2021. In this study, we introduce a methodology for identifying the geospatial features of these projects. Our application of the methodology has resulted in the Geospatial Global Chinese Development Finance Dataset (Version 3.0), which captures the geospatial features of 9,405 projects across 148 low- and middle-income countries supported by Chinese grant and loan commitments worth more than USD 830 billion. The dataset provides details for 6,266 projects containing spatial definitions of roads, railways, power plants, transmission lines, buildings, and other precisely geocoded features. It identifies approximate and administrative-level locations for 3,139 additional projects. The methodology, dataset, and the code used to construct the dataset have been made publicly available to facilitate replication and future applications.

Background Insufficient funding is hindering the achievement of malaria elimination targets in Africa, despite the pressing need for increased investment in malaria control. While Western donors attribute their inaction to financial constraints, the global health community has limited knowledge of China’s expanding role in malaria prevention. This knowledge gap arises from the fact that China does not consistently report its foreign development assistance activities to established aid transparency initiatives. Our work focuses on identifying Chinese-funded malaria control projects throughout Africa and linking them to official data on malaria prevalence. By doing so, we aim to shed light on China’s contributions to malaria control efforts, analysing their investments and assessing their impact. This would provide valuable insights into the development of effective financing mechanisms for future malaria control in Africa.Methods Our research used AidData’ s recently released Global Chinese Development Finance Dataset V.2.0 providing comprehensive coverage of all official sector Chinese development financing across Africa, from which we identify 224 Chinese-funded malaria projects in Sub-Saharan Africa (SSA) committed between 2002 and 2017. We conducted an analysis of the spending patterns by year, country and regions within Africa and compared it with data on population-adjusted malaria prevalence, sourced from the Malaria Atlas Project.Results Chinese-financed malaria projects Africa mainly focused on three areas: the provision of medical supplies (72.32%), the construction of basic health infrastructure (17.86%) and the deployment of anti-malaria experts (3.57%). Moreover, nearly 39% of the initiatives were concentrated in just four countries: the Democratic Republic of Congo, Central African Republic, Uganda and Liberia. Additionally, China’s development financing amount showed a weak negative correlation (−0.2393) with population-weighted malaria prevalence. We concluded that the extent and direction of China’s support are not adequately tailored to address malaria challenges in different countries.Conclusion With China’s increasing engagement in global health, it is anticipated that malaria control will continue to be a prominent priority on its development assistance agenda. This is attributed to China’s vast expertise in malaria elimination, coupled with its substantial contribution as a major producer of malaria diagnostics and treatments.

The motivations behind China's allocation of health aid to Africa remain complex due to limited information on the details of health aid project activities. Insufficient knowledge about the purpose of China's health aid hinders our understanding of China's comprehensive role in supporting Africa's healthcare system. To address this gap, our study aimed to gain better insights into China's health aid priorities and the factors driving these priorities across Africa. To achieve this, we utilized AidData's Chinese Official Finance Dataset and adhered to the Organisation for Economic Co-operation and Development (OECD) guidelines. We reclassified all 1,026 health projects in Africa, originally categorized under broad 3-digit OECD-DAC sector codes, into more specific 5-digit CRS codes. By analyzing the project count and financial value, we assessed the shifting priorities over time. Our analysis revealed that China's priorities in health aid have evolved between 2000 and 2017. In the early 2000s, China primarily allocated aid to basic health personnel and lacked diversity in sub-sectors. However, after 2004, China shifted its focus more toward basic infrastructure and reduced emphasis on clinical-level staff. Furthermore, China's interest in addressing malaria expanded both in scale and depth between 2006 and 2009. This trend continued in 2012 and 2014 when China responded to the Ebola outbreak by shifting its focus from basic infrastructure to infectious diseases. In summary, our findings demonstrate the changes in China's health aid strategy, starting with addressing diseases already eliminated in China and gradually transitioning towards global health security, health system strengthening, and shaping the governance mechanisms.

Mass transit systems are pivotal for fostering sustainable transportation and tackling urban mobility challenges. However, their efficacy hinges significantly on spatial characteristics, accessibility, and integration with the built environment. This study offers a blueprint for future Bus rapid transit station designs, aiming to boost ridership and broaden catchment areas to optimize mass transit planning within their surrounding context. Achieving this entails an exploration of human travel behaviors and their interplay with the built environment. To address these challenges, space syntax was utilized as a spatial analysis tool for mass transit system of Rawalpindi, Pakistan, considering its surrounding context. The study's outcomes are based on spatial comparative analysis and gate count analysis, assessing how accessibility impacts user flow to specific stations. The findings underscore the negative linear correlation between ridership and integration, with stations demonstrating higher integration experiencing lower ridership and vice versa. This underscores the significance of spatial analysis in optimizing mass transit networks, mitigating environmental impacts, and enhancing urban livability. Planners and policymakers can leverage these insights to tailor station designs, improving accessibility and flow. Additionally, integrating other transit modes can expand catchment areas, aligning with research emphasizing integration's importance. [ABSTRACT FROM AUTHOR]

This study aims to determine the impact of spatial attributes on the number of users of public parks and to propose baseline data for future park locations. Public green areas are essential for promoting social interaction and physical activity within communities. Beyond their recreational benefits, these spaces are crucial for maintaining ecological balance, acting as vital green lungs in urban environments. This study utilized spatial indices from space syntax and the gate count method, triangulated with primary data. A regression analysis was conducted for spatial indices and the number of visitors. The results indicate a linear correlation between spatial integration and the number of visitors, R² = 0.91 and p = 0.04. This means, parks with higher integration values tend to attract more visitors and vice versa. The findings of this research may be adopted by planners and policymakers for the strategic location of future parks and optimal resource utilization. [ABSTRACT FROM AUTHOR]