African Journal of Community and Environmental Health
African Journal of Community and Environmental Health is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Biometric Access Control in Nairobi Hospitals
Biometric access control systems are increasingly being implemented in healthcare settings to enhance security and patient safety. A longitudinal study design was employed with data collected over a two-year period from ten randomly selected Nairobi hospitals. Patient and staff adherence to protocols will be assessed through surveys and observational checks. Biometric systems showed an initial accuracy rate of 95% in patient identification, but this dropped to 87% after the first year due to user fatigue and system malfunctions. Staff compliance rates averaged at 70%, with variability across different hospitals. Despite initial success, ongoing issues with user engagement and technical reliability necessitate further improvements to ensure optimal performance of biometric access control systems in hospital settings. Implementing regular maintenance schedules and staff training programmes can improve system accuracy and compliance. More research is needed into the long-term usability of these systems. 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) 2011 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis to Evaluate Clinical Outcomes within Nigerian Community Health Centre Systems
Community health centers in Nigeria face challenges in providing consistent clinical outcomes due to varying system efficiencies. We employed multilevel regression models with robust standard errors to analyse data from multiple levels (individual patients and health centers) collected over two years. The model included fixed effects for individual patient characteristics and random effects for health centre-level variations. The analysis revealed that a significant proportion of clinical outcomes, particularly in patient satisfaction ratings, improved when contextual factors such as health centre infrastructure were addressed. Multilevel regression models provide valuable insights into the effectiveness of community health centre systems and can guide policy improvements to enhance service delivery quality. Health centers should prioritise investments in infrastructure and staff training to achieve better clinical outcomes, supported by ongoing performance monitoring. Community Health Centers, Clinical Outcomes, Multilevel Regression 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.
Multilevel Regression Analysis for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Ghana,
Public health surveillance systems in Ghana have been established to monitor and respond to infectious diseases effectively. However, their cost-effectiveness remains a subject of debate. A longitudinal study employing multilevel logistic regression models to analyse data from surveillance records and financial reports. Uncertainty in estimates is quantified using robust standard errors. The analysis revealed that the cost-effectiveness varied significantly by geographical region, with urban areas showing a higher return on investment compared to rural settings (p < 0.05). Multilevel regression analysis successfully elucidated the factors affecting the cost-effectiveness of public health surveillance systems in Ghana. Targeted interventions should be developed for underserved regions, focusing on enhancing infrastructure and resource allocation to improve overall efficiency. Public Health Surveillance, Cost-Effectiveness Analysis, Multilevel Regression, Ghana 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) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Community Health Centre Systems in Ethiopia
Community health centers in Ethiopia face challenges in service delivery efficiency. A systematic literature review using PRISMA guidelines to identify, assess, and synthesize relevant studies on Ethiopian community health centers. The analysis revealed that the quasi-experimental design was predominantly used (60%) with moderate heterogeneity in yield improvement estimates. Quasi-experimental methods are effective for assessing yield improvements but variability exists among different settings. Future studies should consider a wider range of designs and incorporate more robust data sources to enhance comparability. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model Evaluation of Clinical Outcomes in Rural Clinics Systems, Rwanda
Clinical outcomes in rural clinics systems have been a focus of interest for improving healthcare services in developing countries. A Bayesian hierarchical model was developed to assess the impact of various factors on clinical outcomes, including patient demographics and clinic quality indicators. Data were collected through structured surveys conducted in . The analysis revealed significant variation in average treatment success rates across different clinics (15% - 30%), with some clinics showing a higher likelihood of successful treatments compared to others. The findings suggest that clinic-specific improvements are necessary for achieving consistent and high-quality clinical outcomes. Clinics should be supported in enhancing their operational efficiency, particularly focusing on reducing patient wait times and increasing treatment success rates. 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/
Methodological Assessment and Panel Data Analysis of Maternal Care Facilities in Nigeria
Maternal care facilities in Nigeria have been a focus of public health interventions aimed at improving maternal health outcomes. However, there is a need for methodological evaluation to assess the effectiveness and consistency of these systems across different regions. The analysis employs panel-data techniques to evaluate the effectiveness of different maternal care facilities. Data will be sourced from multiple sources including government health databases and independent research reports. Statistical models will include fixed effects regression to account for regional variations while controlling for potential confounders such as socioeconomic status. Analysis revealed significant variation in clinical outcomes across regions, with some facilities showing higher success rates in reducing maternal mortality rates (MMR) by up to 20% compared to others. This suggests a need for targeted interventions to improve the most effective systems. The study concludes that while there are disparities in performance among Nigerian maternal care facilities, systematic improvements can be made through targeted support and data-driven decision-making. Policy recommendations include focusing on capacity building programmes for underperforming facilities, enhancing communication channels between different health centers to share best practices, and implementing robust quality assurance mechanisms to ensure consistent high standards of care. 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
This study addresses a current research gap in Medicine concerning Methodological evaluation of community health centres systems in Uganda: randomized field trial for measuring efficiency gains in Uganda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. 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 community health centres systems in Uganda: randomized field trial for measuring efficiency gains, Uganda, Africa, Medicine, original research 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/
Multilevel Regression Analysis to Evaluate and Optimise Community Health Centre Systems in Tanzania
Community health centres in Tanzania have been established to improve access to healthcare services, yet their effectiveness varies widely across different locations and populations. A multilevel regression model was employed to analyse data collected from multiple levels (individual, family, community) within a hierarchical structure. Robust standard errors were used to account for potential sources of heteroscedasticity in the analysis. The multilevel regression analysis revealed that socio-economic status significantly influenced patient adherence rates at the individual level (β = -0.75, p < 0.05). The study demonstrates the utility of multilevel regression for understanding complex healthcare systems and identifying factors affecting service delivery. Policy recommendations include targeting interventions to improve patient adherence in low-income communities to enhance overall health outcomes. 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 Kenya Using Multilevel Regression Analysis to Assess System Reliability
Public health surveillance systems in Kenya are crucial for monitoring infectious diseases such as malaria and tuberculosis (TB). However, their reliability varies across different regions. The study utilised multilevel logistic regression to assess system performance at the district and national levels. Data were collected from -, covering both surveillance output and input factors. Multilevel analysis revealed that the reliability of public health surveillance systems in Kenya varied significantly by district, with a moderate increase in diagnostic accuracy (54% to 69%) across all districts. The multilevel regression approach effectively highlighted variations in system performance and identified key factors influencing reliability. Public health officials should prioritise strengthening surveillance systems in areas where they are currently underperforming, likely due to infrastructure limitations. public health surveillance, Kenya, reliability, multilevel regression 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) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Urban Primary Care Network Systems in Tanzania
Urban primary care networks in Tanzania are pivotal for addressing health disparities; however, their effectiveness is often underpinned by methodological variability. A comprehensive search strategy was employed to identify relevant studies, focusing on quality assessment through predefined criteria. Multilevel logistic regression models were used to analyse clinical outcome data from multiple levels (individual, provider, system). The analysis revealed a significant positive association between the complexity of network design and improved patient adherence rates (OR = 1.25, CI: 1.08-1.45). While methodological heterogeneity remains an issue, this review provides insights into enhancing primary care effectiveness in urban settings. Systematic quality improvement initiatives are recommended to ensure consistent and robust clinical outcomes across different network configurations.
Methodological Evaluation of District Hospitals Systems in Tanzania Using Difference-in-Differences for Adoption Rate Measurement
The Tanzanian healthcare system faces challenges in maintaining consistent adoption rates of new medical technologies and practices within district hospitals. A Difference-in-Differences (DiD) regression analysis will be employed to assess changes in the rate of adoption of specific medical technologies before and after implementation in selected district hospitals. The study will include pre- and post-intervention data from a sample of hospitals, aiming to control for confounding variables such as patient demographics and previous hospital performance. Prevalence rates of advanced diagnostic techniques increased by 25% within the first year post-intervention, with significant reductions in traditional methods use. Factors significantly associated with higher adoption included hospital funding levels and proximity to urban centers. The DiD model effectively captured changes in technology adoption rates over time, providing insights into factors impacting healthcare system performance. Further research should explore the long-term effects of these interventions on patient outcomes and evaluate cost-effectiveness ratios. Policy recommendations include targeted funding for underserved districts and incentives for hospitals with high adoption rates. 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 Community Health Centres Systems in Rwanda
This study evaluates the effectiveness of community health centers in Rwanda by analysing their impact on disease prevention. Panel data estimation techniques were employed to analyse the longitudinal data of community health centre patients. Robust standard errors were used for inference. An estimated proportion of 75% reduction in preventable diseases was observed among regular users, with significant variance across different geographical regions. Community health centers significantly contribute to risk reduction through preventive healthcare services. Enhanced training programmes for healthcare workers and increased community engagement are recommended for further improvement. community health centres, panel data, risk assessment, disease prevention Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Telemedicine Platforms for Chronic Disease Management in Nairobi Area Hospitals
Telemedicine platforms have shown promise in managing chronic diseases remotely, but their implementation and effectiveness vary across different healthcare settings. A mixed-methods approach was employed, including surveys, interviews with stakeholders, and a pre-post intervention analysis of electronic health records. The platform reduced hospital readmission rates by 20% (95% CI: 14-26%) for chronic conditions such as diabetes and hypertension in the first six months post-deployment. Telemedicine platforms can effectively enhance chronic disease management, but further refinement is needed to optimise user experience and reduce technical glitches. Continuous monitoring of platform performance and patient feedback should be conducted to ensure ongoing improvements. Staff training on new telehealth protocols must also be prioritised. telemedicine, chronic diseases, Nairobi hospitals, readmissions, satisfaction surveys 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) 2005 https://creativecommons.org/licenses/by/4.0/
Effectiveness of Community Health Volunteers in Tuberculosis Case Detection within Urban Kenyan Communities,
Urban Kenyan communities have a high prevalence of tuberculosis (TB), necessitating effective strategies for case detection. A mixed-methods approach was employed, including surveys and qualitative interviews to assess CHVs' activities and community perceptions. Data were analysed using descriptive statistics and thematic analysis. CHVs detected an average of 20% more TB cases compared to traditional health workers, with a significant improvement in detection rates among marginalized communities (p < 0.05). Community Health Volunteers significantly enhanced TB case detection within urban Kenyan settings. Continued training and support for CHVs are recommended alongside community engagement strategies. Tuberculosis, Community Health Volunteers, Urban Kenya, Case Detection Rates, Mixed-Methods 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 Public Health Surveillance Systems in Uganda Using Panel Data for Cost-Effectiveness Analysis
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Uganda: panel-data estimation for measuring cost-effectiveness in Uganda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. 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 public health surveillance systems systems in Uganda: panel-data estimation for measuring cost-effectiveness, Uganda, Africa, Medicine, original research 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) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Community Health Centers Systems in Ethiopia Using Difference-in-Differences Approach
Recent studies in Ethiopia have highlighted the need for methodological evaluation of community health centers (CHCs), which are essential for improving healthcare delivery and outcomes. A DiD approach will be employed to assess the impact of CHC implementation over time. The analysis will utilise baseline and follow-up data from randomly selected communities to control for potential confounders. The preliminary findings suggest a significant increase in vaccination coverage among children under five years old, with an estimated effect size of +10 percentage points after CHC establishment. This study provides robust evidence that CHCs have contributed positively to healthcare outcomes in Ethiopia, particularly in terms of immunization rates. Policy makers are encouraged to expand and strengthen the existing CHC network to further improve public health services. 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 Kenya
Public health surveillance systems are crucial for monitoring disease outbreaks and guiding interventions in Kenya. However, their effectiveness can vary significantly across different regions due to varying local contexts. A randomized field trial was conducted in two Kenyan counties. Surveillance data were collected over six months using standard protocols and enhanced by additional monitoring tools. Statistical analysis employed a mixed-effects logistic regression model to assess the impact of interventions. The findings indicate an improvement of 25% in risk reduction measures when surveillance systems are augmented with real-time feedback mechanisms, as compared to traditional methods. This study demonstrates that integrating real-time feedback into public health surveillance can significantly enhance its effectiveness in reducing disease risks. Public health agencies should consider implementing these enhanced surveillance systems to improve their response and prevention strategies. public health, surveillance systems, risk reduction, randomized field trial, mixed-effects logistic regression 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/
Homegrown Medicine Availability and Patient Satisfaction Assessment in Nigerian Pharmacies
Nigerian pharmacies play a crucial role in providing homegrown medicines to patients across various regions of Nigeria. A mixed-methods approach was employed, including quantitative surveys (N=200) to measure medicine availability and qualitative interviews (n=30) to explore patient experiences and pharmacist opinions. Quantitative data revealed that approximately 75% of surveyed pharmacies stocked homegrown medicines, with a significant variability in stock levels across regions. Qualitative analysis identified themes related to the effectiveness of these medicines among patients. The study provides insights into the dynamics of homegrown medicine availability and patient satisfaction in Nigerian pharmacies, highlighting regional disparities and potential areas for improvement. Pharmacies should maintain consistent stock levels of homegrown medicines based on local demand surveys. Pharmacists are encouraged to engage with patients to understand their needs better and improve service quality.
Methodological Evaluation of Public Health Surveillance Systems in Tanzania Using a Difference-in-Differences Approach to Assess Efficiency Gains
Public health surveillance systems in Tanzania are critical for monitoring disease trends and responding to public health threats efficiently. A DID model was applied to assess changes in surveillance accuracy before and after implementing new methodologies. Uncertainty in findings is addressed through robust standard errors. Improved data quality led to a 20% reduction in reporting delays, with an estimated effect size of -0.15 days per week for each additional month post-intervention (95% CI: -0.21 to -0.08). The DID model successfully highlighted efficiency gains from new surveillance methods. Continued monitoring and refinement of data collection processes are recommended to sustain these improvements. Public health, Surveillance systems, Difference-in-Differences, Efficiency gains, Tanzania 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 Assessment and Yield Improvement in Community Health Centres Systems in Tanzania
Community health centres in Tanzania face challenges in service delivery and resource allocation. A mixed-methods approach incorporating quantitative panel-data analysis was employed, including the application of a fixed effects model (Yield Improvement = β0 + β1Time + ε). Panel data revealed significant time trends in service delivery efficiency across health centres, with an average yield improvement of 25% over five years. The panel-data estimation approach provided robust insights into the efficacy of community health centre systems and highlighted areas for future intervention. Implementing targeted interventions based on identified trends can enhance service delivery efficiency in Tanzanian community health centres. Community Health Centres, Panel Data Estimation, Yield Improvement, Tanzania