Monitoring Project Research Articles

Dual straight-wing FBG accelerometer for low-frequency vibration measurement

Fiber optic accelerometers have a wide range of applications in low-frequency vibration measurement, such as in earthquake monitoring, disaster early warning, underground resource exploration, and anti-seismic monitoring projects for critical structures like dams and bridges. In response to the current issues of Fiber Bragg Gratings (FBG) accelerometers being insensitive to low-frequency vibration signals and challenging to apply in engineering, a dual straight-wing FBG accelerometer for low-frequency vibration measurement is proposed. Firstly, a sensor model is established and theoretically analyzed. Secondly, the impact of the sensor's main structural parameters on sensitivity and natural frequency is analyzed, and the sensor is simulated using ANSYS. Finally, a prototype of the sensor is developed, and a low-frequency vibration testing system is set up to test the sensor's performance. Experimental results show that the accelerometer has a natural frequency of 39.1 Hz, operates in the 5–22 Hz frequency band, and has a sensitivity of 171.7 p.m./g, a dynamic range of 69.82 dB, and a transverse interference resistance of less than 9.5%. This research provides a new reference for the development of similar sensors.

The Application of Bridge Monitoring Projects Exploiting Time Series Data of Structural Health Monitoring

Since the first attempts of Structural Health Monitoring the Vienna Consulting Engineers (VCE) have been involved to advance the BRIMOS technology which offers a wide range of services to engineers and operators of infrastructure networks. Over the last decade the dynamic behavior of hundreds of structures has been measured and evaluated. However, the current practice in Structural Health Monitoring is still a case to case approach which needs a lot of experience for proper interpretation and assessment of the investigated objects. The integration of new technologies is wanted to support and automate the evaluation process as well as increase the objectivity within the assessment routines. This paper shall indicate the need for innovate methods and tools from a user’s point of view and gives a short insight to the workflow and infrastructure of BRIMOS. The efforts which are undertaken within the BRIMOS infrastructure show the approach towards the application of data mining instruments to benefit for future and also from past monitoring projects. Datamining, Time Series Analysis, Knowledge Base, Structural Health Monitoring

Implementing a citizen science bird monitoring project in the Grampians/Gariwerd National Park, Victoria, Australia

ABSTRACT Global bird populations are threatened by ongoing habitat loss and climate change. Inconsistent and short-term funding of faunal surveys in Australia makes population and distribution changes difficult to detect. To meet this challenge, alternative methods of supplementing regular surveys by professional ornithologists have been proffered, including surveys by trained citizen scientists. Here we outline the development, implementation and assessment of the Great Gariwerd Bird Survey (GGBS), a citizen science (CS) monitoring project designed to address long-term management questions in vulnerable Stringybark Heathy Woodland in Grampians/Gariwerd National Park. Forty volunteers that met appropriate criteria were selected and trained in practical 10-week/40-h courses. We assessed data from 288 2-ha/20-min surveys undertaken in autumn and spring 2021 at 36 sites, ran workshops to improve surveyor skills and data quality and assessed trainee experiences and program content through online anonymous surveys. Concurrent professional field ornithologist surveys enabled cross validation of CS surveys. Overlapping species accumulation curves for professional and citizen scientist surveys reflected very high correlations for site species diversity (r = 0.836) and abundances (r = 0.768). In autumn, the professional surveyor recorded significantly more species and birds than CS surveyors. Additional training in the identification of cryptic birds and challenging calls partially addressed the numerical differences in the following spring survey. This project demonstrates the potential for valuable long-term ecological data collection by well-trained citizen scientists with benefits to community environmental knowledge and participation despite some manageable obstacles. Participant surveys showed highly positive program perceptions, reflected by ongoing involvement in the GGBS.

EXAMINING THE FINANCIAL RISK MANAGEMENT OF DONOR FUNDS: CASE OF MINISTRY OF HEALTH IN ZAMBIA

<p>This study examines the financial risk management of donor funds using the Ministry of Health (MOH) in Zambia as a case study. The study employs an exploratory case study methodology on a sample of 224 MOH employees. Zambia, being a developing country, significantly relies on donor funds to support its healthcare sector. Prudent management of donor funds is crucial for the sustained delivery of quality healthcare services. However, there has been concerns regarding the financial risk management practices at the MOH in the efficient utilization and accountability of donor funds. From the literature review, it seems no study has been done regarding the financial risk management of donor funds focusing on the MOH in Zambia. Therefore, this study fills this gap. The study findings seem to show evidence of the misappropriation of donor funds exhibited by misallocation of donor funds to unplanned projects or activities. The misappropriations of donor funds seem to be amplified by a lack of strategic planning, lack of coordination, and the absence of effective monitoring and evaluation systems. Additionally, fraud and corruption posed significant risks to donor funds at MOH. Therefore, to mitigate the risks, the study recommends that robust anti-misappropriation measures, enforcement of due diligence on implementing partners, a thorough review of procurement processes, and regular monitoring and evaluation of donor-funded projects be strengthened at the MOH in Zambia. Whistleblower protection and reporting mechanisms should be promoted to help detect and deter fraudulent activities at this Ministry.</p><p><strong> </strong></p><p><strong>JEL:</strong> H51, I18, O23</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0787/a.php" alt="Hit counter" /></p>

Consideration of Climate Change on Environmental Impact Assessment in Tanzania: Challenges and Prospects.

The potential of the environmental impact assessment (EIA) process to respond to climate change impacts of development projects can only be realized with the support of policies, regulations, and actors' engagement. While considering climate change in EIA has become partly mandatory through the EU revised Directive in Europe, African countries are still lagging. This paper assesses Tanzanian policies, laws, regulations, and EIA reports to uncover consideration of climate change impacts, adaptation, and mitigation measures, drawing from the transformational role of EIA. The methodology integrates content analysis, interpretive policy analysis, and discourse analysis. The analyses draw from environmental policy, three regulatory documents and three EIA reports in Tanzania using a multi-cases study design. The aim was to understand how considering Climate Change issues in EIA has played out in practice. Results reveal less consideration of climate change issues in EIA. The policy, laws, and regulations do not guide when and how the EIA process should consider climate change-related impacts mitigation and adaptation. The practice of EIA in the country is utterly procedural in line with regulations provisions. Consequently, environmental impact statements only profile the climatology of the study area without conducting a deeper analysis of the historical and future climate to enhance the resilience of proposed projects. The weakness exposed in the laws and regulations contributes to the challenges of responding to the impacts of climate change through the EIA process. It is possible to address climate change issues throughout the project life cycle, including design, approval, implementation, monitoring, and auditing, provided the policy and regulations guide how and when the EIA process should consider climate change issues. Additionally, increasing stakeholders' awareness and participation can enhance the EIA process's potential to respond to the impacts of climate change.

Low-Cost Approach to an Instream Water Depth Sensor Construction Using Differential Pressure Sensors and Arduino Microcontrollers.

Accurate hydrological data with high spatial resolution is important for flood risk and water resource management, particularly under the context of climate change. The cost of monitoring networks, as well as the characteristics of the hydrological environment itself, can be a barrier to meeting these data requirements, however. This study covers the design and testing of a low-cost, "build-it-yourself", instream water depth sensor providing an assessment of its potential in future hydrological monitoring projects. The low-cost sensor was built using an Arduino microcontroller, a differential pressure sensor and a thermistor, a real-time clock, and an SD card module. The low-cost logger was deployed in tandem with a factory-calibrated Solinst®LevelLogger® 5 Junior for 6 months in the River Wissey, UK. We found the mean absolute error of the Arduino-based logger relative to the commercial setup to be ±0.69 cm for water depth and ±0.415 °C for water temperature. Economically, the Arduino-based logger offers an advantage, costing a total of £133.35 (USD 168.26 at time of publication) comparative to the industrial comparison's cost of £408 (USD 514.83 at time of publication). This study concludes that the low cost of the Arduino-based logger gives a strong advantage to its incorporation in hydrological data collection, if the trade-offs (i.e., time investment and accuracy) are considered acceptable and appropriate for a project.

UAVs for improving seasonal vegetation assessment in arid environments

In the last few decades, revegetation strategies for ecosystem restoration have received great attention in dryland studies, especially those related to the restoration and revegetation of native desert plants to combat land degradation. Long-term monitoring and assessment are critical for the restoration programs to track the progress of the restoration program goals. The effectiveness and success of monitoring depend on the selected methods with respect to spatial and temporal scales. Traditional methods for vegetation monitoring are time-consuming, expensive, and require considerable labor efforts (manpower) in terms of field measurements, collecting samples, lab analysis, and the difficulty of accessing some study areas. Thus, satellite remote sensing images have been widely used to monitor land degradation and restoration programs using multispectral and hyperspectral sensors and indices such as NDVI, which is the most popular index for vegetation monitoring. However, such techniques showed many limitations when used in arid ecosystems, especially for seasonal vegetation assessments, which could mislead the monitoring and assessment of the restoration projects. This paper discusses lessons learned from previous research work, including the limitations of using satellite remote sensing in arid ecosystems and the use of UAV methods to overcome these issues and challenges to provide more accurate outcomes for seasonal assessment of vegetation in arid landscapes.

ProCoMon: A Web-based Project Procurement Management Plan (PPMP) Consolidation and Monitoring System for Nueva Vizcaya State University

The major purpose of this study is to design and develop a web-based consolidation and monitoring system that can handle the delayed submission of a university's Annual Procurement Plan, which is managed by Nueva Vizcaya State University's Procurement Management Office. As a result of the identification of requirements and specifications, there is a need to design and develop a web-based system wherein research interviews, observations, and user stories are used to identify and analyze the study's methods, issues, and concerns. The Agile Unified Process was used as the research methodology, which managed changing user needs and involved the user in the software development process. AUP includes processes for each of the four phases: inception, elaboration, construction, and transition. As a result, the study lends a better consolidation and monitoring system that is more efficient and accurate in the formulation of an Annual Procurement Plan for the university.

Impact of COVID-19 on People Living With HIV: Data From Five Medical Monitoring Project Sites, 2020-2022.

The COVID-19 pandemic disrupted global economic and healthcare systems. People living with HIV (PLWH) represent a marginalized and stigmatized population who may have been particularly impacted. The purpose of this analysis was to describe the impact of the COVID-19 pandemic on PLWH in the United States. United States. We analyzed surveys of behavioral and clinical characteristics of PLWH residing in 5 states that participated in the Medical Monitoring Project between 2020 and 2022. We described the impact of COVID-19 illness, testing, and diagnoses; receipt of medical care; social service access; employment; and preventive measures by project site and demographic characteristics. Unweighted data from 1715 PLWH were analyzed. A high proportion of PLWH had medical care disrupted by the pandemic; 31% of PLWH missed medical appointments, 26% missed routine laboratory test results, and 7% missed antiretroviral therapy doses. In total, 30% of PLWH reported losing wages and 19% reported difficulty in accessing social services. Overall, 88% reported receiving at least 1 dose of COVID-19 vaccine, but vaccine uptake was low among younger, Black, and Hispanic or Latina/o/x PLWH. This descriptive analysis reinforces previous findings that show that COVID-19 negatively impacted PLWH and their ability to obtain medical care. Additional efforts will be critical to ameliorating the longer-term impacts of COVID-19 on the health of PLWH and supporting PLWH through future pandemics and healthcare system disruptions.

Smarter water quality monitoring in reservoirs using interpretable deep learning models and feature importance analysis

This study utilized datasets from an ongoing monitoring project conducted in Wadi Dayqah Dam, the largest reservoir in Oman. The dataset comprises information on ten water quality variables collected by AAQ-RINKO device for 20 field sampling stations, encompassing different depths within the water columns. First, an in-depth data analysis was conducted to process and characterize variations in key parameters. Then, four deep learning models were developed and evaluated, including the Gated Residual Variable Selection (GRVS), Deep and Cross (DC), Deep and Wide (DW), and Base models for estimating two important water quality parameters, namely dissolved oxygen (DO) and chlorophyll-a (Chl-a). To justify the performance of deep learning methods, they were compared to four traditional machine learning techniques: MLP, SVR, AdaBoost, and LR-Lasso models. The GRVS model emerged as the most effective method, achieving high accuracy with R2 and RMSE values of 0.98 and 0.38 for the DO parameter and 0.84, and 0.45 for the Chl-a parameter, respectively. Finally, two SHapley Additive exPlanations (SHAP) and Softmax layer model interpretation approaches were employed to highlight the influential factors affecting the predictions in the best model. Results from the SHAP analysis identified pH, depth, and temperature as the most significant variables, with mean SHAP values of 1.8, 0.75, and 0.36 for DO and 0.74, 0.37, and 0.3 for Chl-a, respectively. The data-driven framework implemented in this study holds promise for efficiently approximating hard-to-measure water quality indicators in monitoring projects using cost-effective inputs, which is particularly valuable in resource-constrained settings.

Study of solar brightness profiles in the 18–26 GHz frequency range with INAF radio telescopes

Context. The Sun is an extraordinary workbench, on which several fundamental astronomical parameters can be measured with high precision. Among these parameters, the solar radius R⊙ plays an important role in several aspects, for instance, in evolutionary models. Moreover, it conveys information about the structure of the different layers that compose the solar interior and its atmosphere. Despite the efforts to obtain accurate measurements of R⊙, the subject is still debated, and measurements are puzzling and/or lacking in many frequency ranges. Aims. We determine the mean, equatorial, and polar radii of the Sun (Rc, Req, and Rpol) in the frequency range 18.1 − 26.1 GHz. We employed single-dish observations from the newly appointed Medicina Gavril Grueff Radio Telescope and the Sardinia Radio Telescope (SRT) in five years, from 2018 to mid-2023, in the framework of the SunDish project for solar monitoring. Methods. Two methods for calculating the radius at radio frequencies were employed and compared: the half-power, and the inflection point. To assess the quality of our radius determinations, we also analysed the possible degrading effects of the antenna beam pattern on our solar maps using two 2D models (ECB and 2GECB). We carried out a correlation analysis with the evolution of the solar cycle by calculating Pearson’s correlation coefficient ρ in the 13-month running means. Results. We obtained several values for the solar radius, ranging between 959 and 994 arcsec, and ρ, with typical errors of a few arcseconds. These values constrain the correlation between the solar radius and solar activity, and they allow us to estimate the level of solar prolatness in the centimeter frequency range. Conclusions. Our R⊙ measurements are consistent with the values reported in the literature, and they provide refined estimates in the centimeter range. The results suggest a weak prolateness of the solar limb (Req > Rpol), although Req and Rpol are statistically compatible within 3σ errors. The correlation analysis using the solar images from the Grueff Radio Telescope shows (1) a positive correlation between solar activity and the temporal variation in Rc (and Req) at all observing frequencies, and (2) a weak anti-correlation between the temporal variation of Rpol and solar activity at 25.8 GHz.

Decadal vegetation changes in a subarctic‐alpine ecosystem: Can effects of Iceland's largest hydropower reservoir, climate change, and herbivory be detected?

AbstractAimsWhile plot‐based vegetation surveys provide means to precisely track changes in plant species abundance and distribution, ecosystems are continuously influenced by numerous drivers, confounding interpretation of monitoring results. Following the making of Iceland's largest hydropower reservoir in 2006, a decadal vegetation monitoring was set up. Relating our results to those of different types of environmental monitoring associated with the hydropower project, we aimed to gain insights into the forces driving the spatio‐temporal vegetation pattern.LocationSubarctic‐alpine area near Hálslón reservoir, East Iceland.MethodsAt the time of its making, we conducted a baseline plant survey in a total of 72 plots, spread around Hálslón reservoir's vicinity (each containing ten 0.25 m2 subplots). Plots were located in three different habitat types (heathlands, wetlands, poorly vegetated land), at three different sites regarding direction and distance from the reservoir. A decade later, we resurveyed the plots and reviewed the results of other environmental monitoring projects in the area, mostly presented in the gray literature.ResultsTemporal changes in vegetation were mostly inconsistent between and within habitat types, but some general trends were noticed, that is, decreased lichen and fern cover in heathlands. Distance from the reservoir did not significantly affect changes in vegetation cover. The greatest overall changes were detected where great changes in herbivore land usage had been recorded during the study.ConclusionsDirect effects of Hálslón reservoir on vegetation in our study plots were not noticed. Most likely, the reservoir indirectly impacted vegetation in our study through loss of grazing area, affecting herbivore land usage, coupled with an unrelated population growth of two of the area's main wild herbivores before and during the study period. Response to climate change was not detected, potentially concealed by substantial land‐use change and a short study period.

Unmet Needs for HIV Ancillary Services Among Persons With Diagnosed HIV Aged 55 years and Older.

Approximately 2 in 5 persons with HIV (PWH) in the United States are aged 55 years or older. HIV ancillary services, such as case management and transportation services, can help older PWH remain engaged in care. We used data from the Medical Monitoring Project (MMP) to describe the prevalence of unmet needs for ancillary services among persons with diagnosed HIV aged 55 years or older. MMP is an annual cross-sectional study that reports representative estimates on adults with diagnosed HIV in the United States. We used MMP data collected during June 2019-May 2021 to calculate weighted percentages of cisgender men and cisgender women with HIV aged 55 years or older with unmet needs for ancillary services, overall and by selected characteristics (N = 3200). Unmet need was defined as needing but not receiving a given ancillary service. We assessed differences between groups using prevalence ratios (PRs) and 95% confidence intervals with predicted marginal means. Overall, 37.7% of cisgender men and women with HIV aged 55 years or older had ≥1 unmet need for ancillary services. Overall, 16.6% had ≥1 unmet need for HIV support services, 26.9% for non-HIV medical services, and 26.7% for subsistence services. There were no statistically significant differences in unmet needs for services by gender. The prevalence of ≥1 unmet need was higher among non-White persons (PR range: 1.35-1.63), persons who experienced housing instability (PR = 1.70), and those without any private insurance (PR range: 1.49-1.83). A large percentage of older PWH have unmet needs for ancillary services. Given the challenges that older PWH face related to the interaction of HIV and aging-associated factors, deficits in the provision of ancillary services should be addressed.

Accelerating the middle – rise building construction duration using BIM 4D, a case study in central Jakarta

Construction planning involves scheduling and sequencing of project activities for proper execution. Research was conducted to obtain and enhance construction project scheduling, which was good and in accordance with the targets achieved. The results of the project performance analysis in the 9th month using the Earned Value Method resulted in SPI <1 and SV <0, indicating that the project experienced delays. Scheduling using the PDM based on the actual duration of the project shows that the project will be completed in 511 days. The project duration can be accelerated to 429 days by combining overlap and overtime methods. The scheduling results were simulated using BIM 4D to generate a visualization of the scheduling to improve the project monitoring process.

Copula: a decentralized solution for construction project monitoring using blockchain

PurposeThis study aims to introduce and evaluate the COPULA framework, a construction project monitoring solution based on blockchain designed to address the inherent challenges of construction project monitoring and management. This research aims to enhance efficiency, transparency and trust within the dynamic and collaborative environment of the construction industry by leveraging the decentralized, secure and immutable nature of blockchain technology.Design/methodology/approachThis paper employs a comprehensive approach encompassing the formulation of the COPULA model, the development of a digital solution using the ethereum blockchain and extensive testing to assess performance in terms of execution cost, time, integrity, immutability and security. A case analysis is conducted to demonstrate the practical application and benefits of blockchain technology in real-world construction project monitoring scenarios.FindingsThe findings reveal that the COPULA framework effectively addresses critical issues such as centralization, privacy and security vulnerabilities in construction project management. It facilitates seamless data exchange among stakeholders, ensuring real-time transparency and the creation of a tamper-proof communication channel. The framework demonstrates the potential to significantly enhance project efficiency and foster trust among all parties involved.Research limitations/implicationsWhile the study provides promising insights into the application of blockchain technology in construction project monitoring, future research could explore the integration of COPULA with existing project management methodologies to broaden its applicability and impact. Further investigations into the solution’s scalability and adaptation to various construction project types and sizes are also suggested.Originality/valueThis research offers a comprehensive blockchain solution specifically tailored for the construction industry. Unlike prior studies focusing on theoretical aspects, this paper presents a practical, end-to-end solution encompassing model formulation, digital implementation, proof-of-concept testing and validation analysis. The COPULA framework marks a significant advancement in the digital transformation of construction project monitoring, providing a novel approach to overcoming longstanding industry challenges.

A review of drivers and barriers of Digital Twin adoption in building project development processes

Over the past few years, the AECO Industry has undergone a shift toward digital transformation, with a growing trend towards adopting innovative technologies such as Digital Twin (DT). DT offers a wide range of applications throughout the building development process. However, some specific factors impede its widespread adoption in the building industry. This study aims to systematically review the available literature on the building project development process from the perspective of DT, with a particular focus on predictive simulations, i.e., co-sims. The review provides a comprehensive overview of drivers and barriers to DT adoption through an analysis of 147 studies between 2013 and 2023. The research identifies seven external and 41 internal drivers, including efficient project management and monitoring, predictive maintenance, and the collection and visualization of real-time data, all of which contribute to improved decision-making processes and reduced operational expenses. Further, the study identifies nine external and 31 internal barriers that impede the adoption of DT in the building development process. These barriers encompass challenges such as a high initial investment cost, a scarcity of a skilled workforce, difficulties in data interoperability, and resistance to change within the organization. A key outcome of the literature review is having identified the opportunity to exploit technologies developed in the automotive sector that enable a seamless integration of specialized simulator models in building development processes, resulting in collaborative simulations. Thus, we propose the concept of a Building Simulation Identity Card (BSIC) to be pursued in future research that would enable stakeholders to address the challenges of collaboration, cooperation, coordination, and communication by creating a common vocabulary to effectively facilitate the adoption of DT in the building's development process.

Enhancing Students’ Sustainability Understanding Through Air Quality Monitor Project Using Arduino

As an environmental degradation, air pollution is contrary to sustainable development goals (SDGs). Therefore, through education for sustainable development (ESD), there is a need to enhance students’ capability in solving such problem. STEM learning encourages students to work on real-world problem through hands on activity in line with ESD necessity. This research aims to analyze how the ESD-based STEM learning practice through air quality monitor project using Arduino could influence students’ sustainability understanding in solving air pollution. Students’ sustainability understanding towards air pollution which was measured is based on cognitive learning objectives related to SDGs number 3 good health and well-being, SDGs 7 affordable and clean energy, SDGs 12 responsible consumption and production, SDGs 13 Climate action, and SDGs 15 Life on land. The research uses quasi experimental method with pretest-posttest design. This research also developed the instrument to measure sustainability understanding about air pollution. The result of data analysis shows that after the treatment, there is no significant difference between control and experiment class in students’ sustainability understanding. The result implies that the activity of making air quality monitor does not give significant difference in enhancing sustainability understanding. However, the result migh be influenced by some factors which make the implementation of ESD-based STEM learning to be not optimal

Efficient Speech Detection in Environmental Audio Using Acoustic Recognition and Knowledge Distillation.

The ongoing biodiversity crisis, driven by factors such as land-use change and global warming, emphasizes the need for effective ecological monitoring methods. Acoustic monitoring of biodiversity has emerged as an important monitoring tool. Detecting human voices in soundscape monitoring projects is useful both for analyzing human disturbance and for privacy filtering. Despite significant strides in deep learning in recent years, the deployment of large neural networks on compact devices poses challenges due to memory and latency constraints. Our approach focuses on leveraging knowledge distillation techniques to design efficient, lightweight student models for speech detection in bioacoustics. In particular, we employed the MobileNetV3-Small-Pi model to create compact yet effective student architectures to compare against the larger EcoVAD teacher model, a well-regarded voice detection architecture in eco-acoustic monitoring. The comparative analysis included examining various configurations of the MobileNetV3-Small-Pi-derived student models to identify optimal performance. Additionally, a thorough evaluation of different distillation techniques was conducted to ascertain the most effective method for model selection. Our findings revealed that the distilled models exhibited comparable performance to the EcoVAD teacher model, indicating a promising approach to overcoming computational barriers for real-time ecological monitoring.

Improving citizen-based monitoring in South Africa: A social media model

Background: In contemporary public governance, transparent, accountable, and citizen-centric practices are paramount. Citizen-based monitoring (CBM) of government projects is a promising avenue to uphold these principles. However, there is a pressing need for a more effective, structured, and technologically driven approach to CBM.Objectives: This research aims to present a tailored model for the South African government. Utilising social media, the model seeks to transform CBM practices, enhancing governance and ensuring project success. The limitations of current CBM tools necessitate such a model in South Africa.Method: Rooted in rigorous mixed-methodology research, the model’s development and validation involve in-depth interviews with government officials, local media, and civic organisations, along with a citizen survey and literature review. International best practices in CBM and social media analytics inform its design.Results: The study uncovers that current CBM tools have a dual nature, empowering citizens yet facing context-specific challenges like elite capture and inclusivity issues. Social media emerges as a preferred tool among citizens for monitoring government projects, showcasing its transformative potential in fostering transparency and citizen engagement.Conclusion: By leveraging social media’s dynamic capabilities, this model can enhance transparency, accountability, and project success in South Africa’s governance landscape, marking a significant advancement in the digital era.Contribution: This research introduces a novel CBM model for South Africa, tailored to leverage social media’s transformative potential. Addressing existing limitations in CBM tools provides insights into the challenges and opportunities of utilising social media for government project monitoring.

Self-rated health and HIV outcomes among adults with diagnosed HIV - Medical Monitoring Project, United States.

To evaluate associations between self-rated health (SRH) and care outcomes among United States adults with diagnosed HIV infection. We analyzed interview and medical record data collected during June 2020-May 2021 from the Medical Monitoring Project, a complex, nationally representative sample of 3692 people with HIV (PWH). Respondents reported SRH on a 5-point Likert type scale (poor to excellent), which we dichotomized into "good or better" and "poor or fair". We computed weighted percentages with 95% confidence intervals (CIs) and age-adjusted prevalence ratios (aPRs) to investigate associations between SRH and HIV outcomes and demographic, psychosocial, and behavioral characteristics. Nationally, 72% of PWH reported "good or better" SRH. PWH with the following characteristics had a lower prevalence of "good or better" SRH, compared with those without: any missed HIV care appointment in the last 12 months (aPR 0.86, 95% CI: 0.81-0.91), symptoms of moderate or severe depression (aPR 0.51, 95% CI: 0.43-0.59) and anxiety (aPR 0.60, 95% CI: 0.54-0.68), unstable housing or homelessness (aPR 0.77, 95% CI: 0.71-0.82), and hunger or food insecurity (aPR 0.74, 95% CI: 0.69-0.80), as well as having a mean CD4 count <200 cells/mm 3 vs. CD4 + >500 cells/mm 3 (aPR 0.70, 95% CI: 0.57-0.86). Though SRH is a holistic measure reflective of HIV outcomes, integrated approaches addressing needs beyond physical health are necessary to improve SRH among PWH in the United States. Modifiable factors like mental health, unstable housing or homelessness, and food insecurity warrant further study as potential high-yield targets for clinical and policy interventions to improve SRH among PWH.