Assessment Of Infrastructure Research Articles

A unified approach for measuring the level of service of transport infrastructure

This article aims to discuss the problem of road traffic management and the criteria for its measurement. The article uses the concept of service level as the most important characteristic in the assessment of transport infrastructure. The differences in approaches to determining the level of service in the world practice are considered. The problem is outlined of non-uniform metrics used to measure the level of service for various road elements in existing methodologies. A comparison is made of the assessment of the level of service of a traffic lane in the Russian and foreign approaches in the choice of coefficients and the method of their calculation. Changes are proposed to the existing Rosavtodor methodology for assessing the capacity of a lane, a roundabout, an unregulated and regulated intersection, which can simplify the assessment of the level of service. As a result, an example of the application of the proposed unified approach in calculating the capacity of a controlled intersection is given. Finally, a conclusion is drawn about the need for a new approach, the advantages of using unified metrics for the level of service assessment are highlighted, and the vector of future research on this problem is also outlined.

The IRRADIA research project for the advanced management of infrastructures

AISICO and ‘Sapienza’ University of Rome are working on the project IRRADIA, a research program aiming to investigate the use of Artificial Intelligence for the structural assessment of railway and road infrastructures. The starting point is the BRIGHT method (BRIdGes Health Testing method, patented by AISICO), already applied on a large data set of information, and essentially based on the automatic detection of damages on structural elements of bridges and viaducts. The results carried out on 80 railway bridges provide new ideas to the sector of monitoring and control of existing infrastructures in terms of automatization. Then, the BRIGHT method, built on the railway specifications described by DOMUS, has been recently expanded to meet the requirements of the 2022 Italian Guidelines for existing road bridges and viaducts (DM 204, 1/07/2022). These require to fulfill several defect sheets for each structural element (e.g., beams, transversal beams, slabs, piers, abutments, supports, and so on), with a proper evaluation, for each defect, of type, extension and intensity. It follows that the damage evaluation requires usually a large number of operations with a high level of repetitiveness. Therefore, the use of AI techniques is a promising tool for the near future, to acquire and collect the images with unmanned aerial vehicle, from one hand, and to fulfill the defect sheets, from the other one, reducing time and cost. In this framework, one of the main goals of the cited IRRADIA research project is the investigation of the results obtained with the BRIGHT method extended to 2022 Italian Guidelines, that is, to road infrastructures. In this contribution the first results obtained on two bridges, the first in reinforced concrete and the second with a masonry structure, are presented and discussed.

Resilience assessment of critical infrastructures using dynamic Bayesian networks and evidence propagation

Resilience assessment of critical infrastructures using dynamic Bayesian networks and evidence propagation

ОЦЕНКА СОВРЕМЕННОГО СОСТОЯНИЯ РАСТИТЕЛЬНОГО ПОКРОВА Г. ОБЛУЧЬЕ ПО МУЛЬТИСПЕКТРАЛЬНЫМ ДАННЫМ

A sustainable development of regional towns and small settlements demands the urban modern landscape infrastructure study and assessment. For this purpose, geoinformation systems and remote sensing data are widespread used. The aim of the study was to analyze the green spaces in the small town of Obluchye (Jewish Autonomous region) using multispectral data with an assessment of indicators of the town sustainable development. The sources of information were as follows: Sentinel-2A multispectral products, the Rules of land use and development for Obluchye, field research materials, ICARP FEB RAS stock materials, special literature. The identification and analysis of green spaces distribution in Obluchye are based on calculation results of the normalized vegetation index (NDVI). It is stated that the NDVI value of 0.55 or more is the boundary value for the allocation of green spaces in Obluchye; 0.75 or more - for woody vegetation. The NDVI boundary value of 0.55...0.74 is for herbaceous and shrubby vegetation on lawns, unsettled areas, as well as for natural and produced meadows. The NDVI values of 0.75 or more in the image determine the forest vegetation of the Obluchye recreation zone, tree and shrub thickets along riverbeds and floodplain forests, and woodlands in the town built-up zone. The green spaces distribution across the town functional zones is uneven. The high and very high landscaping areas are characteristic of the Obluchye periphery and correspond to the zones of recreational and residential development. In most cases, tree plantations are located in a recreational area, mainly outside the town. However, all urban development zones have high values of landscaping average level (from 71 to 93%). The calculated indicators of sustainable development in Obluchye show, on the one hand, a significant exceeding level of landscaping (53%), as compared to the established norms (at least 40%). On the other hand, the share of green areas of common use in the total area of green spaces in Obluchye is very low – only 1.6%. Thus, there is a need in a qualitative improvement of green infrastructure in the town of Obluchye.

Local Government Unit Initiative on Implementing Marine Protected Areas in Barangay Kamanga and Colon, Maasim Sarangani Province

This study assessed local government unit initiatives in implementing Marine Protected Areas (MPAs) in Maasim, Sarangani Province. The evaluation focused on the effectiveness of MPA program implementers using the Management Effectiveness Assessment Tool (MEAT), collected secondary data on coral reefs and reef fish conditions, conducted a community perception survey, and assessed socioeconomic impacts. Despite the establishment of MPAs and the adoption of related policies, knowledge gaps persist regarding their actual effectiveness in achieving conservation objectives. This study evaluated the management performance of two MPAs: Kamanga Marine Ecotourism Park and Sanctuary and Colon Marine Sanctuary. Employing a descriptive design, MEAT was used to assess their effectiveness. Results indicate that both MPAs were well-established, with robust stakeholder involvement and legal enforcement. However, Kamanga Marine Ecotourism Park and Sanctuary outperformed Colon Marine Sanctuary in areas such as patrolling, infrastructure, institutional support, and impact assessment. Kamanga Marine Ecotourism Park and Sanctuary received an "excellent" rating, while Colon Marine Sanctuary was rated "very good." Both MPAs have stable funding, but Colon Marine Sanctuary requires monitoring, communication, public engagement, and financial management improvements. The study also identified challenges from natural factors and human activities, including pollution and fishing. However, there is positive community awareness about MPAs, and fishers report benefits such as increased fish stocks.

Seismic Hazard Map of ASEAN Countries towards Risk Assessment and Sustainability of Structures and Infrastructures

This study contains the most recent seismic hazard map of Southeast Asia. This area is located to the south of the Eurasian plate. The Ring of Fire that surrounds the region makes it one of the most active in terms of earthquakes and volcanoes. Malaysia, Indonesia, Thailand, Singapore, the Philippines, Myanmar, Vietnam, Laos, Cambodia, and Brunei are among the countries being studied. The goals of this project are to provide Peak Ground Acceleration (PGA) values for all regions in ASEAN countries, and then to create seismic zoning maps for these countries so that zones with non-seismic regions can be identified and zones with no special steel reinforcement-detailing requirements can be specified. The final step is to create design response spectra. Based on each nation's most recent body of literature, the PGA hazard map is created. There are two maps that need to be created, one for 10% and one for 2% probability of exceeding. The PGA contours of all the compiled maps were then reconstructed, and the baseline colours were compared to an Indonesia seismic hazard map. The maximum PGA value for Southeast Asia is as high as 0.8g at 10% and 2.0g at 2% probability of exceedance, respectively, whereas the minimum PGA value is typically equal to 0.0g at both 10% and 2% probability of exceedance. The design response spectrum distribution of the stable with moderate earthquake region from 0 to 4 s (including West Malaysia, Sabah and Sarawak of East Malaysia) and the distribution of spectra for active earthquake regions including Indonesian cities (including Acheh, Padang and Palu) are plotted. Then, the design response spectra for the selected cities in regions of moderate seismicity and active earthquakes are integrated.

COMMUNITY EVALUATION OF MOSQUE FACILITIES IMPACTING CONGREGATIONAL PRAYER ATTENDANCE AND IMPLEMENTATION IN MOSQUES IN KELANTAN

Infrastructure is a fundamental service and facility needed for every aspect of development and progress. This includes the mosque's facilities such as prayer spaces, both inside and outside the mosque, cleanliness, and other factors that are crucial for the community to perform congregational prayers in the mosques. However, studies related to mosque infrastructure have received insufficient attention. Therefore, this study aims to assess the level of mosque infrastructure based on the assessment of mosque congregants and the influence of mosque infrastructure on the attendance and implementation of congregational prayers in mosques in the state of Kelantan. A total of 618 data were obtained from mosque congregants in Kelantan, which were analyzed using SPSS and SmartPLS 3.0 software. The study findings indicate that a) the community's assessment of mosque infrastructure is high (M=6.12 to 6.38; SD: 0.940 to 1.113), and b) there is a positive and significant influence of mosque infrastructure on the implementation of congregational prayers in mosques (ß=.711, t=20.974, p<0.01, f2=0.122). Based on the IPMA analysis in PLS, religious activity facilities and equipment are the most important factors of mosque infrastructure that influence the attendance and implementation of congregational prayers in mosques, followed by cleanliness, cheerfulness, and safety of mosque facilities, visitor-friendly mosque facilities, and efficient mosque staff management. These findings demonstrate that all these elements of mosque infrastructure influence the congregants' attendance for performing congregational prayers in mosques in the state of Kelantan. It is recommended that mosque management and relevant authorities prioritize these aspects to encourage more congregants to attend mosques in Kelantan.

Evaluating the digitalization capability and display of KPIs for two fertilizer plants of Petrovietnam

The study partially funded by the Vietnam Oil and Gas Group (Petrovietnam) assesses the infrastructure, OT/IT systems, and data handling at two fertilizer plants. Although well-equipped with automation control technology, the plants lack seamless integration, connectivity, and encounter limitations in communication between systems. To address these issues, the study advocates for the integration of digital technology, emphasizing its potential for enhancing efficiency, facilitating optimal management, and guiding strategic direction. Following an assessment of infrastructure, key performance indicator (KPI) system requirements, and data management, the study proposes an initial application of digital technology to link KPI displays. The outlined scope, initial costs, investment phases, and implementation schedule indicate a total initial investment of around VND 37 - 39 billion, accompanied by annual maintenance costs ranging from VND 3.7 to 4.1 billion. Expected economic and social benefits involve improved management at both Petrovietnam and plant levels through the KPI system, with an estimated energy cost savings of 1%, equivalent to roughly VND 44.6 billion. The project aims to position the fertilizer plants and Petrovietnam as leaders in technology, contributing to sustainability and enhancing their global industry reputation.

Enhancing a Quality Teaching and Learning Environment in Large Classes in South African Universities: a Theoretical Exposition

The perpetual increase in students’ enrolment in higher education institutions, worldwide, has recently emerged as a key concern for both students, educators, parents, policy makers and educational policy analysts alike. This phenomenon has been borne out of a global trend of massification of higher education as many countries begin to consider the importance of education and skills development in economic growth and social development. On the other hand, it has been triggered by the perceived pattern of commodification of higher education services in which student intake and teaching outputs are intricately linked to the financial sustainability of higher education institutions. In this paper, a critical examination of literature pertaining to Large Class Pedagogy and Learning Theories is undertaken with a view to determine how one could teach and ensure quality learning in large classes within a South African higher education context. Anchored within a critical qualitative frame of analysis, the assessment draws from existing literature on Large Class Pedagogy (LCP), learning theories, teaching approaches and learning styles to provide a conceptual lens in which the challenges associated with large class environments can be mitigated to offer an educational experience of acceptable quality. The paper provides a synthesis of pertinent issues that have arose in the critical examination of LCP and appropriate Learning Theories in a developing country context as that of South Africa. It appears that government funding to higher education institutions should be increased through adoption of large class size reduction policies, equitable allocation of resources to faculties and academic departments by universities, rigorous assessment of staff-student ratios and infrastructure when new academic programs are introduced, monitoring of adherence to approved yearly student enrolment targets in academic programme, adoption of collaborative learning methods by academic staff in which self-directed learning styles in students are encouraged and supported, optimal use of educational technologies through systematic integration of digitization in the learning and teaching environment, enhanced administrative psycho-social support to students and lecturers are some of the macro, mesa and micro level strategies required to enhance quality teaching and learning with increasing class sizes.

Planning and Design Strategies for Green Stormwater Infrastructure from an Urban Design Perspective

With the rapid advancement of ecological civilization construction, prioritizing green stormwater infrastructure to address urban stormwater management issues has become an important strategy for ecological priority and green development in sustainable urban development. Green stormwater infrastructure, as a major facility in the construction of sponge cities, can reduce the generation and external discharge of runoff and play a purification role. However, there are various types of green stormwater infrastructure, each with different control effects and applicable conditions. Therefore, to facilitate the planning, design, acceptance, assessment, and monitoring evaluation of sponge city green stormwater infrastructure, this study proposes the “sponge equivalent” method. By comparing the control effects of different facilities with bioretention facilities, the method standardizes the effects, making them easier to understand and apply. Taking a typical area of Beijing and its urban roads as examples, the study analyzed and applied planning and design control strategies. The results show that for a residential area of 1 km2, to achieve the annual runoff total control rate target of 85%, the method of converting runoff volume control equivalents, using bioretention pools as a benchmark, allows for the calculation of various combinations of areas of different types of green stormwater infrastructure, such as sunken green spaces, permeable paving bricks, green roofs, and water storage tanks. This optimizes the planning index of Beijing, which mandates stormwater detention facilities for new projects with a hardened surface area of 2000 m2 or more. The sponge equivalent method can optimize the planning and design control strategy of green stormwater infrastructure, allowing for rapid assessment and application of the design scale of green stormwater infrastructure in areas during the planning and design stage, providing theoretical and technical support for ecological and green urban stormwater management. The application of this research method helps promote green development and ecological priority in urban sustainable development strategies, and the conclusions provide valuable references for decision-makers and practitioners in related fields.

Multi-hazard risk assessment of rail infrastructure in India under local vulnerabilities towards adaptive pathways for disaster resilient infrastructure planning

“Lifeline of the nation” is the motto of Indian Railways as it connects through a common thread, billion plus population in one way or the other. The National Rail Plan for India – 2030 focuses on creating a ‘future ready’ Railway system by 2030 by suitably integrating new railway systems like high-speed rails. However, rail infrastructure is exposed to multi-hazards and disasters sometimes disrupt safe rail operations. This study explores rail infrastructure risk assessment at a national scale utilizing the UNDRR framework and synthesized application of geospatial technologies with a focus on disentanglement of local vulnerabilities of the rail infrastructure assets utilizing factors of health of bridges, visibility obstruction to level crossings, labour wages & their regions and GSDP under multi-hazard scenarios. The results revealed that the NR and NFR were identified as high-risk routes under the risk analysis of physical and social vulnerability scenarios, followed by CR Railways. The average annual frequencies of emergency cases in each zone show a correlation r (17) = 0.4758 with the combined mean risk ranks for each zone. In comparison to socioeconomic factors, which contribute to indirect losses, physical factors directly affect safety and contribute to direct losses. Further, outcomes depict more accidents on Indian Railways during the monsoon (nearly 50%) and cold weather (29%) seasons. The study suggests that with the participation of key stakeholders, including urban and transport planners, an integrated approach is helpful in identifying critical rail routes towards risk-informed adaptive disaster-resilient infrastructure planning for providing safety, continuity and reliability of essential rail services.

A novel lightweight CF decision-making approach for highway reconstruction and operation

Road infrastructure is a major emitter of greenhouse gases (GHGs), contributing significantly to the overall carbon emissions of many countries. Due to their importance in the life-cycle carbon footprint (CF) assessment of highway projects, highway reconstruction, rehabilitation, and operation have garnered increased attention. Existing highway CF studies have relied heavily on on-site data. They were often limited by a handful of operation or reconstruction scenarios. Most existing highway CF studies focused solely on mitigating the infrastructure CF and ignored the potential savings of highway traffic CF resulting from different traffic behaviour and technology options. A comprehensive CF saving potential comparison between the highway infrastructure and traffic for the city- or nation-wide policy decision-making is needed. Moreover, the loss of design and operation information for many existing highway projects with long operational periods necessitates a new approach to assess and manage the CF of highway reconstruction, rehabilitation, and operation. As a result, this study has proposed a new lightweight CF decision-making approach to help highway reconstruction, rehabilitation, and traffic operation management with informative stage-based highway decision-making supporting framework and digital platform that enable the comparison between highway infrastructure and traffic CF's potential savings. With the help of the developed framework and platform, the project decision-maker and government policymaker can leverage better information support and dynamically compare CF decision-making scenarios regarding different highway infrastructure and traffic options. This study contributes to knowledge in three ways: (1) evaluating and validating an informative highway CF decision-making framework for highway infrastructure and traffic assessment and management, (2) proving the applicability of using a lightweight data collection and model building method for highway infrastructure CF assessment and management practice, and (3) providing an applicable way of building a highway CF digital twins (DT) platform for visualisation, decision-making, and management of the highway infrastructure and traffic.

UAV-driven approach for assisting structural health monitoring of port infrastructure

Port engineering planning and management seek to confront challenges affecting the functional and structural capacity of port systems. To achieve this, design, maintenance, and rehabilitation strategies should be enhanced by dynamic approaches that help minimize the impacts of potential degradation due to climate change, natural hazards and aging of port infrastructure. Introducing Structural Health Monitoring (SHM) practices to asset management frameworks can improve port sustainability and resilience. Recently, new aspects for assisting SHM approaches with Unmanned Aerial Vehicle (UAV) applications have emerged. Therefore, the present research is focused on investigating the capabilities of an Unmanned Aerial Vehicle (UAV) monitoring program to advance current SHM practices for port infrastructure. For this purpose, four in-situ inspections were conducted by the Laboratory of Harbour Works (LHW) of the National Technical University of Athens (NTUA) at a Greek port in central-eastern Greece, namely Lavrio port. Data analysis was performed with Close Range Photogrammetry (CRP) methods and Geographic Information System (GIS) tools. The overall research showed that the UAV-driven SHM supports the condition assessment of port infrastructure, thus assisting practices for smart maintenance.

A multi-objective comparison of CNN architectures in Arctic human-built infrastructure mapping from sub-meter resolution satellite imagery

ABSTRACTRisk assessment of infrastructure exposed to ice-rich permafrost hazards is essential for climate change adaptation in the Arctic. As this process requires up-to-date, comprehensive, high-resolution maps of human-built infrastructure, gaps in such geospatial information and knowledge of the applications required to produce it must be addressed. Therefore, this study highlights the ongoing development of a deep learning approach to efficiently map the Arctic built environment by detecting nine different types of structures (detached houses, row houses, multi-story blocks, non-residential buildings, roads, runways, gravel pads, pipelines, and storage tanks) from recently-acquired Maxar commercial satellite imagery (<1 m resolution). We conducted a multi-objective comparison, focusing on generalization performance and computational cost, of nine different semantic segmentation architectures. K-fold cross validation was used to estimate the average F1-score of each architecture and the Friedman Aligned Ranks test with the Bergmann-Hommel post-hoc procedure was applied to test for significant differences in generalization performance. ResNet-50-UNet++ performs significantly better than five out of the other eight candidate architectures; no significant difference was found in the pairwise comparisons of ResNet-50-UNet++ to ResNet-50-MANet, ResNet-101-MANet, and ResNet-101-UNet++. We then conducted a high-performance computing scaling experiment to compare the number of service units and runtime required for model inferencing on a hypothetical pan-Arctic scale dataset. We found that the ResNet-50-UNet++ model could save up to ~ 54% on service unit expenditure, or ~ 18% on runtime, when considering operational deployment of our mapping approach. Our results suggest that ResNet-50-UNet++ could be the most suitable architecture (out of the nine that were examined) for deep learning-enabled Arctic infrastructure mapping efforts. Overall, our findings regarding the differences between the examined CNN architectures and our methodological framework for multi-objective architecture comparison can provide a foundation that may propel future pan-Arctic GeoAI mapping efforts of infrastructure.

Rainfall-induced transportation embankment failure: A review

Abstract Rainfall is one of the leading causes of transportation embankment failure. Similarly, the fill material properties and the loading conditions of the embankment serve as principals for assessing the mechanisms of potential failures that are derived from rainfall-related events. These events affect the hydro-mechanical behaviors of embankment fills and cast doubt on the construction and service life of most transportation-infrastructure. This article presents a review, of existing available records to critically examine rainfall-induced transportation embankment failures, causes, mechanisms, existing measures, and prevention techniques. Consequently, a review of the susceptibility assessment of infrastructures due to rainfall-induced failures, particularly in China, and embankment characteristics and their effects on the duration, magnitude, and safety of the infrastructures was carried out. The study was able to classify rainfall conditions as they influence embankment stability. We suggest the development of local and global rainfall-embankment fill material relationships that will give unique information on how rainfall-events change the behavior of fill material and to what extent they trigger failures. A summary of some of the active processes leading to transportation embankment failures is presented. Finally, we concluded by identifying future and prospective rainfall-induced transportation embankment failures that will enhance monitoring and mitigation of instability in embankments.

Seismic excitation model in probabilistic risk assessment of civil infrastructure

AbstractRealistic risk assessment of civil infrastructure subjected to catastrophic events plays a crucial role in strategic asset management. In this process, visualization of the asset and its environment always possesses some epistemic uncertainty associated with the modeler's simplification/abstraction. The present paper aims at providing a critical perspective into the characterization of the seismic excitation model for risk assessment of civil infrastructures and identifying gaps in the present knowledge. For this purpose, the main factors that influence the development of a comprehensive framework for the simulation of seismic excitation are highlighted. The coupling effect of the spatial variability of ground motions and the substructure's footprint on the realization of the seismic excitation model is illustrated. Finally, the necessity of direct incorporation of the load analysis subtask in the probabilistic seismic risk assessment of civil infrastructures is discussed. In addition, simplified probability density functions are proposed for the simulation of the seismic excitation model.

Application of artificial intelligence in road network inventory and network-wide road safety assessment

This research paper examines the application of artificial intelligence (AI) in road network inventory and network-wide road safety assessment. An overview of current research related to this field is presented and various aspects of the use of AI in road infrastructure and safety assessment are analysed. In today’s world, where the road network continues to develop and grow, the use of AI can offer significant advantages in the inventory and assessment of road infrastructure and safety. AI can be used to process large volumes of data collected from various sources such as geographic data, photos, documentation and more. One of the main aspects that the article looks at is the use of AI to automatically process data and create a digital inventory of the road network. AI systems can analyse geographic data and photos to identify and classify roads, road signs, markings, and other elements of road infrastructure. This can facilitate engineers and competent authorities in the process of road inventory and maintenance. Another important aspect discussed in the paper is the use of AI for the general assessment of road safety. AI models can analyse road infrastructure inventory data, as well as traffic data, crashes, and other factors, to provide a comprehensive assessment of road network safety. This allows the competent authorities to identify vulnerable places, carry out preventive measures and plan appropriate interventions aimed at improving road safety. In conclusion, the paper highlights the possibilities and advantages of using artificial intelligence in road network inventory and network-wide road safety assessment. Such an approach can contribute to more efficient management of road infrastructure and improvement of road safety.

Geospatial approach for Landslides Vulnerability Assessment of Physical Infrastructures in Sireh Park, Johor Bahru

Geospatial approach for Landslides Vulnerability Assessment of Physical Infrastructures in Sireh Park, Johor Bahru

Analysis and Optimization Strategies of Pedestrian Environment around TOD Rail Transit Stations in Guangzhou

This study extensively examines the urban dynamics of Guangzhou, a city that has notably embraced and incorporated the concept of Transit-Oriented Development (TOD) into its urban structure. Through a comprehensive and meticulously designed questionnaire survey, the research aims to understand different demographic groups' diverse preferences and needs. The main focus is comprehending individuals' views and experiences regarding the pedestrian environment near Transit-Oriented Development (TOD) stations. The study findings reveal a wide range of outcomes, indicating significant variations in walking distance tolerance and environmental satisfaction among different populations. Notably, walking distance emerged as a crucial factor, as a positive correlation was found between shorter perceived distances and higher levels of enjoyment. Evaluating pedestrian amenities reveals their insufficiency and emphasizes the need for improved pedestrian comfort and infrastructure. Various factors influence individuals' satisfaction with the walking environment. The assessment of pedestrian infrastructure in Guangzhou's Transit-Oriented Development (TOD) areas generally shows positive feedback, but there is still room for improvement. This study analyzes the current shortcomings in pedestrian infrastructure and proposes practical recommendations for enhancement. Its purpose is to provide a basis for policy formulation and future renovations to enhance pedestrian mobility near TOD train stations in Guangzhou.

Assessment of neonatal referral infrastructure and clinical characteristics of referred neonates in three first referral hospitals in Nairobi County, Kenya.

One in five newborns in Nairobi County, Kenya, may require inpatient neonatal care. We sought to examine referrals to and from three busy first-level referral public hospitals in Nairobi and what infrastructure and systems are available to support neonatal transport from these first-referral level hospitals to the main tertiary care center. Patient-level data of newborns over 12 months were retrospectively extracted from routinely collected patient data and examined to characterize those referred into and out of three newborn units in the study hospitals. Structural assessments using a checklist completed during hospital visits were used to describe hospitals' readiness to support newborn referral and transport. Five percent (398/7720) of the cohort studied were either referrals into study hospitals (68%, 272/398) or referrals out (32%, 126/398). Among 397 (99%) and 268 (67%) with sex and gestation documented respectively, 63% (251) were male and 44% (118) were preterm infants (<37 weeks). Among those referred in, 26% (69/272) died and 2.6% (7/272) were further referred to a tertiary-care newborn unit. Prematurity (39%) and birth asphyxia (29%) were the main in-referral reasons from 38 different health facilities, with specialist reviews (34%) predominant for out-referrals to a tertiary center. Diverse transport methods were used for referrals to study hospitals including private and public ambulances, vehicles, and guardian's arms while onward referrals to the tertiary center were done by hospital ambulances. Drugs and medical supplies required for stabilization were well available at the study sites, however, only oxygen nasal cannula, nasal prongs, and face masks were available in ambulance of hospital 3. There is a need to develop, equip and maintain a high-quality referral and newborn transport system that can support the continuum of newborn care across referral care pathways into and from first-referral level hospitals.