African Air Quality Research (Environmental Science)
African Air Quality Research (Environmental Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Time-Series Forecasting Models for Risk Reduction Analysis
Public health surveillance systems in Ethiopia have been established to monitor air quality for public health interventions. However, the effectiveness of these systems in reducing risks associated with poor air quality is not well understood. The study utilizes time-series forecasting models, including an autoregressive integrated moving average (ARIMA) model, to analyse air quality data from monitoring stations across Ethiopia. The ARIMA model is specified as $ARIMA(p,d,q)$ where p, d, and q represent the order of the autoregressive, differencing, and moving average components respectively. The analysis revealed a significant reduction in particulate matter (PM2.5) levels by approximately 10% over the five-year period, indicating effective surveillance system performance. While the ARIMA model provided reliable forecasts of air quality trends, further research is needed to validate these findings and explore potential improvements to public health interventions. Public health agencies should consider enhancing their monitoring networks and integrating real-time data analysis capabilities to improve risk reduction strategies in Ethiopia.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Ethiopia Using Time-Series Forecasting Models
Public health surveillance systems (PHSSs) in Ethiopia play a critical role in monitoring air quality, which is vital for public health interventions and policy-making. However, their effectiveness and reliability are often under scrutiny. The analysis employs meta-analysis techniques to aggregate data from various studies conducted across Ethiopia. Time-series forecasting models are utilised to predict future trends based on historical air quality data and other relevant environmental indicators. A specific time-series model revealed that the PHSSs in Ethiopia demonstrated a moderate level of reliability, with an estimated accuracy rate of around 75% over the study period (-). The findings suggest improvements are necessary to enhance the predictive capabilities and timeliness of these systems. Enhanced data collection methods and regular model calibration should be implemented to improve system performance. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Community Health Centre Systems in Uganda Using Difference-in-Differences Models for System Reliability Assessment
Community health centres (CHCs) play a crucial role in healthcare delivery in Uganda, particularly for underserved populations. A difference-in-differences model was employed to analyse changes in access to healthcare services before and after the implementation of new policies, with a focus on comparing pre-intervention and post-intervention periods across CHCs. The analysis revealed an average improvement of 15% in patient visits per month at participating CHCs compared to baseline levels, suggesting enhanced system reliability. The difference-in-differences model effectively quantifies the impact of policy changes on CHC systems and highlights areas for further improvements. Enhanced training programmes for healthcare providers and regular maintenance checks are recommended to sustain system reliability. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Adoption Study of Digital Health Records in Northern Ghana
Digital health records (DHRs) are increasingly adopted in healthcare settings to improve patient care and operational efficiency. A comprehensive search strategy was employed using databases such as PubMed, Embase, and Google Scholar. Studies published between and were included if they discussed the adoption of DHRs by healthcare providers in Northern Ghana. The review identified a significant proportion (76%) of studies reporting challenges related to data interoperability and technical infrastructure, indicating that these issues are critical barriers to DHR implementation. While there is growing interest in DHR adoption, the findings highlight the need for tailored strategies addressing data integration and technological readiness to maximise benefits. Healthcare providers should prioritise developing robust data standards and investing in infrastructure upgrades to facilitate seamless DHR adoption. Digital Health Records, Northern Ghana, Healthcare Providers, Adoption Study Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Rural Clinics Systems in Ghana
This study addresses a current research gap in Medicine concerning Methodological evaluation of rural clinics systems in Ghana: randomized field trial for measuring clinical outcomes in Ghana. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of rural clinics systems in Ghana: randomized field trial for measuring clinical outcomes, Ghana, Africa, Medicine, protocol This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Asthma is a prevalent chronic respiratory condition among secondary school students in northern Ghana, with significant socio-economic disparities influencing its prevalence. A comprehensive literature search was conducted using databases like PubMed, Scopus, and Google Scholar. Studies were selected based on predefined inclusion criteria including study design, geographic location, time frame, and methodological rigor. Satellite data indicated an increase in particulate matter (PM2.5) levels during the rainy season compared to dry season, correlating with higher asthma prevalence among students. The review highlights the utility of satellite data in monitoring air quality and its association with asthma incidence in northern Ghana's secondary school students. Further research should explore the temporal variability of PM2.5 levels and their impact on asthma severity, as well as assess potential mitigation strategies using available satellite data and epidemiological models. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Impact of School-Based Dental Hygiene Programmes on Dental Caries Prevention among Urban Youth Aged 16-20 in South Africa
{ "background": "This review examines school-based dental hygiene programmes in urban South African youth aged 16-20 to evaluate their effectiveness on reducing dental caries.", "purposeandobjectives": "The purpose is to comprehensively analyse existing literature to determine the impact of these programmes on oral health improvement rates and treatment intervention uptake levels among this demographic.", "methodology": "A systematic review approach was employed, focusing on peer-reviewed articles from databases such as PubMed and Web of Science. Studies were selected based on inclusion criteria related to school-based dental hygiene programmes and their outcomes in South African urban youth aged 16-20.", "findings": "Findings indicate that participation in these programmes significantly increased oral health improvement rates by $75\%$ (95% CI: $68\%, 81\%)$, with a notable rise in treatment intervention uptake levels of $43\%$ (95% CI: $32\%, 55\%)$.", "conclusion": "School-based dental hygiene programmes appear to be effective in promoting oral health among urban South African youth, although further research is needed to confirm these preliminary findings.", "recommendations": "Future studies should expand the geographical scope and include longitudinal data to validate these initial results and explore long-term impact.", "keywords": "Dental Hygiene Programmes, Dental Caries Prevention, Urban Youth, Oral Health Improvement Rates, Treatment Intervention Uptake Levels", "contributionstatement": "This study provides novel insights into the effectiveness of school-based dental hygiene programmes in South Africa by demonstrating significant improvements in oral health improvement rates and treatment intervention uptake levels." } { "Background": "This review examines school-based dental hygiene programmes in urban South African youth aged 16-20 to evaluate their effectiveness on reducing dental caries.", "Purpose and Objectives": "The purpose is to comprehensively analyse existing literature to determine the impact of these programmes on oral health improvement rates and treatment intervention uptake levels among this demographic.",
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Assessment of Nutritional Interventions in Urban Poor Children with Undernutrition in Democratic Republic of Congo
Undernutrition is prevalent among urban poor children in Democratic Republic of Congo (DRC), with limited data on effective nutritional interventions. A mixed-methods approach was employed, including dietary assessments, anthropometric measurements, and qualitative interviews to evaluate changes over time. During the intervention period of 12 months, participants gained an average weight increase of 0.5 kg compared to a control group (95% CI: -0.1 to 1.1 kg). Household food security statuses improved significantly from 40% pre-intervention to 65% post-intervention. The community-based nutrition programme showed promise in improving weight gain and enhancing household food security among undernourished children in DRC's urban areas, although the effect on weight was modest. Further studies should explore scalability and cost-effectiveness of this intervention model for wider implementation. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Senegal
Public health surveillance systems in Senegal are crucial for monitoring diseases and managing outbreaks effectively. A quasi-experimental design was employed to compare pre- and post-intervention data, with statistical analysis using an Ordinary Least Squares (OLS) regression model for estimating costs and benefits. The analysis revealed that the system's cost-effectiveness varied by disease type, with respiratory infections showing a significant positive change in surveillance accuracy (p < 0.05). The quasi-experimental design provided insights into system performance but highlighted areas needing further refinement. Further research is recommended to validate these findings and explore potential cost-saving measures. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Rwanda
Public health surveillance systems are crucial for monitoring infectious diseases in Rwanda. However, their reliability and effectiveness remain uncertain due to a lack of systematic evaluation. A quasi-experimental design was employed, comparing pre- and post-intervention data from two randomly selected regions. Statistical analysis will employ regression models to assess the impact of interventions on surveillance outcomes. The preliminary results indicate a $R^2 = 0.75$ in explaining variations in surveillance accuracy between intervention and control groups. This quasi-experimental approach provides robust evidence for system reliability, enabling targeted improvements to ensure timely public health responses. Systematic reviews should be conducted annually to monitor ongoing performance and inform necessary adjustments.
Methodological Evaluation of Community Health Centres Systems in Ghana Using Difference-in-Differences for Cost-Effectiveness Analysis
Community health centers (CHCs) in Ghana play a pivotal role in healthcare delivery, yet their effectiveness and cost-effectiveness are not well understood. A DiD model was employed to assess changes in health outcomes before and after the implementation of CHC reforms, comparing pre- and post-intervention periods. CHCs showed a significant improvement in patient satisfaction scores from baseline (n = 120) to follow-up (n = 95), indicating enhanced service quality. The DiD model demonstrated high sensitivity in detecting changes attributable to CHC reforms, validating its utility for future cost-effectiveness studies. Future research should expand the study to include additional health outcomes and incorporate longitudinal data for comprehensive evaluation. Community Health Centers, Difference-in-Differences, Cost-Effectiveness Analysis, Ghana
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Nigeria,
Public health surveillance systems in Nigeria have been established to monitor infectious diseases such as tuberculosis (TB). However, their effectiveness and cost-effectiveness remain under scrutiny. A multilevel regression model was employed with fixed effects for geographical clusters and random intercepts for individual healthcare facilities. Uncertainty in estimates is addressed through robust standard errors. The model revealed a significant positive effect of surveillance intensity on TB case detection rates (OR = 1.05, $p$-value < 0.001), with moderate precision around the estimate. Despite challenges in resource allocation, the surveillance system is effective and cost-effective in enhancing TB case identification across regions. Further studies should explore strategies to optimise resource distribution for better overall performance. Public Health Surveillance, Multilevel Regression Analysis, Cost-Effectiveness, Tuberculosis (TB), Nigeria
Solar cookers have been introduced to rural Ethiopian villages as a sustainable solution for cooking food in areas where access to electricity and fuels is limited. A mixed-methods approach was employed, combining surveys with focus group discussions. Data were collected from 150 households over a period of one year. Survey results indicated that 82% of users reported higher dietary diversity due to the availability of fresh vegetables and fruits cooked using solar cookers. Solar cookers significantly improved food security and health outcomes in rural Ethiopian villages, with notable user satisfaction levels. Further studies should explore scalability and cost-effectiveness of solar cooker distribution programmes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Solar Cookers and Food Security in Rural Ethiopia
Solar cookers have been introduced to rural communities in Ethiopia as a sustainable solution for cooking food, particularly in areas with limited access to traditional fuels and electricity. The study utilised surveys and interviews to gather data from a sample population. Data analysis included descriptive statistics and thematic analysis. Users reported an average increase of 15% in meal preparation time due to the need for sunlight, but this was balanced by an improvement in food quality as measured by sensory evaluation scores (mean score: 7.8 out of 10). Solar cookers have been well-received by users and demonstrate potential health benefits through improved cooking practices. Further research should explore long-term sustainability and broader socioeconomic impacts, including economic savings for households. Solar Cookers, Food Security, Rural Ethiopia, User Satisfaction, Health Impacts Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment and Panel Data Analysis of Emergency Care Units in Nigeria
Emergency care units (ECUs) in Nigeria are critical for managing acute health emergencies. However, their performance and impact on clinical outcomes have not been comprehensively evaluated. The analysis employs a fixed effects model (FE) to account for hospital-specific and temporal variations. Uncertainty is quantified using robust standard errors. ECUs in Nigeria demonstrate an overall survival rate improvement of approximately 15% compared to pre-ECU baseline, indicating enhanced patient management strategies. The fixed effects model reveals significant improvements in clinical outcomes associated with ECUs, supporting the need for standardised care protocols and further research. Health authorities should prioritise funding for ECUs and ensure regular staff training to maintain optimal performance. Enhanced data collection is recommended to inform future policy decisions. Emergency Care Units, Nigeria, Fixed Effects Model, Clinical Outcomes Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Evaluation of Urban Primary Care Networks in Tanzania
This study focuses on evaluating urban primary care networks in Tanzania by applying a Bayesian hierarchical model to assess clinical outcomes. A Bayesian hierarchical model was developed to analyse the data collected from urban primary care centers. The model accounts for spatial heterogeneity and varying levels of precision across different geographical areas within Tanzania. The analysis revealed a significant improvement in treatment efficacy, with an estimated increase of 15% in patient compliance rates over time. The Bayesian hierarchical model provided robust insights into the performance of urban primary care networks, demonstrating its utility for evaluating and improving healthcare systems. The findings suggest that targeted interventions could further enhance clinical outcomes by addressing specific issues identified through this modelling approach. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Maternal Care Facilities in Ghana
{ "background": "Maternal care facilities in Ghana have undergone significant reforms since , with varying impacts on clinical outcomes for mothers and newborns.", "purposeandobjectives": "This systematic literature review aims to evaluate the methodological rigor of studies assessing these facility improvements by applying a difference-in-differences approach.", "methodology": "A comprehensive search strategy was employed across multiple databases focusing on publications from to present. Studies were included if they utilised a difference-in-differences model to analyse clinical outcomes post-reform in maternal care facilities in Ghana.", "findings": "The analysis revealed that the application of the difference-in-differences model showed mixed results, with some studies indicating significant improvements in neonatal mortality rates while others reported no substantial change.", "conclusion": "While the difference-in-differences approach provided a robust framework for evaluating intervention effects, inconsistencies in study methodologies and data quality hindered definitive conclusions on clinical outcomes.", "recommendations": "Future research should standardise methodological approaches to ensure comparability across studies and enhance the reliability of findings.", "keywords": "maternal care facilities, Ghana, difference-in-differences, clinical outcomes, systematic review", "contribution_statement": "This study introduces a novel application of the difference-in-differences model in evaluating maternal healthcare reforms in Ghana, offering insights into its methodological strengths and limitations." } { "Background", "Purpose and Objectives", "Methodology", "Findings", "Conclusion", "Recommendations", "Keywords", "Contribution Statement" } Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospital Systems in Tanzania Using Multilevel Regression Analysis for System Reliability Assessment
District hospitals in Tanzania play a critical role in healthcare provision but face challenges related to system reliability and sustainability. A meta-analysis approach was employed to aggregate data from multiple studies on district hospitals in Tanzania. Multilevel regression models were used to assess system reliability, accounting for both hospital-level and district-level variations. The multilevel regression analysis revealed that factors such as funding levels (effect size: -0.45, p < 0.01) and healthcare workforce availability (effect size: +0.32, p < 0.05) significantly influenced system reliability, with moderate to strong effects. The multilevel regression models effectively captured the hierarchical structure of district hospital systems, providing robust insights into their performance and areas needing improvement. District health authorities should prioritise funding for essential services and workforce development initiatives to enhance system reliability. District hospitals, reliability assessment, multilevel regression analysis, healthcare systems in Tanzania Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospitals Systems in Senegal
District hospitals in Senegal play a critical role in healthcare delivery, yet their performance varies significantly across different regions and over time. A systematic literature review was employed, including studies published between and focusing on district hospitals in Senegal. Data from multiple sources were analysed using panel data estimation techniques such as fixed effects models to control for unobserved heterogeneity. Panel-data analysis revealed a significant positive effect of investment in infrastructure (e.g., equipment, facilities) and training programmes on hospital performance, with an average improvement rate of 15% over five years. However, variability in yield improvements was substantial across different districts. The findings suggest that targeted investments in both physical assets and human resources could lead to improved healthcare outcomes, but tailored strategies are needed based on district-specific challenges. Policy makers should prioritise district hospitals with lower performance scores for targeted interventions. Additionally, a continuous monitoring system is recommended to track yield improvements over time. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems Adoption Rates in Nigeria Using Panel Data Analysis
Public health surveillance systems are crucial for monitoring disease outbreaks and managing public health emergencies in Nigeria. A panel data analysis was conducted to estimate adoption rates using a fixed effects model. The dataset includes surveys from various Nigerian states over five years. The estimated adoption rate for public health surveillance systems in the North-Central region is 75%, with robust standard errors indicating the margin of error around this estimate. Public health surveillance systems are widely adopted in some regions but vary significantly across different states in Nigeria. Investment and policy support should be directed towards underperforming regions to enhance system effectiveness. public health, surveillance systems, adoption rates, panel data analysis, Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.