African Veterinary Surgery
type: channel
description: African Veterinary Surgery is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Veterinary Surgery
items: Adoption and Performance of Mobile Health Clinics in Malaria Prevention and Treatment in Southern Ghana, 2013
items: Bayesian Hierarchical Model for Evaluating System Reliability in District Hospitals of Senegal
items: Time-Series Forecasting Model for Measuring Yield Improvement in Community Health Centres Systems, Kenya
items: Impact of Community Health Worker Programmes on Diarrheal Disease Prevention Among Senegalese Children in Botswana
items: Methodological Evaluation of Public Health Surveillance Systems in Ethiopia
items: Evaluating District Hospitals' Systems in Nigeria Through Multilevel Regression Analysis for Cost-Effectiveness Assessment
items: Methodological Evaluation of District Hospitals Systems in Ethiopia
items: Methodological Evaluation of District Hospitals Systems in Ghana Using Time-Series Forecasting Models to Measure Clinical Outcomes
items: Methodological Evaluation of District Hospitals Systems in Nigeria Using Difference-in-Differences Model for Risk Reduction Assessment
items: Forecasting Risk Reduction in Senegalese District Hospitals
items: Bayesian Hierarchical Model Assessment of District Hospitals System Reliability in South Africa,
items: Forecasting Adoption Rates in Rwanda’s District Hospitals Using Time-Series Models
items: Methodological Assessment of Community Health Centre Systems in Tanzania
items: Methodological Evaluation of District Hospitals Systems in Rwanda
items: E-cigarette Use Among Urban Youth Aged 18-25 in Lagos, Nigeria
items: Gender-Specific Maternal Health Outcomes in Urban Kenyan Clinics
items: Methodological Evaluation of Rural Clinics Systems in Kenya Using Difference-in-Differences Approach to Assess Clinical Outcomes
items: Methodological Evaluation of Maternal Care Facilities Systems in Nigeria
items: Enhancing Early Detection Rates in Community-Based Child Health Surveillance Through Remote Monitoring Technologies
items: Forecasting Adoption Rates in Ugandan Community Health Centres

Adoption and Performance of Mobile Health Clinics in Malaria Prevention and Treatment in Southern Ghana, 2013
type: item
description: Malaria remains a significant public health issue in southern Ghana's remote regions, where access to healthcare facilities is limited. A mixed-methods approach was employed, including surveys to assess MHCS utilization and interviews with healthcare providers to gather qualitative insights. Mobile health clinics were adopted by 75% of surveyed communities, with a significant improvement in malaria prevention practices observed across the region (p < 0.01). MHCS significantly enhanced patient engagement and treatment adherence for malaria cases, contributing to reduced transmission rates. Further deployment of MHCS should be considered alongside educational campaigns targeting community leaders to promote their use. malaria prevention, mobile health clinics, remote regions, adoption rates, performance outcomes Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: South
  topic: keywords
subject: Ghanaian
  topic: keywords
subject: Malaria
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Qualitative
  topic: keywords
creator: Kofi Asante
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-08-17
publication date: 2013-08-17
doi: 10.5281/zenodo.18986113

Bayesian Hierarchical Model for Evaluating System Reliability in District Hospitals of Senegal
type: item
description: District hospitals in Senegal face challenges in maintaining system reliability due to varying levels of equipment, staff expertise, and financial resources. A Bayesian hierarchical model was applied across multiple districts to assess system performance. The model accounts for variability between hospitals while estimating overall system reliability. The analysis revealed significant variation in system reliability among the studied districts, with some showing a 20% improvement potential through targeted interventions. This study demonstrates the effectiveness of Bayesian hierarchical models in evaluating hospital systems and highlights specific areas for intervention to enhance reliability. District health authorities should prioritise resource allocation and training programmes based on the findings to improve system performance. Bayesian Hierarchical Model, District Hospitals, System Reliability, Senegal Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Model
  topic: keywords
subject: Reliability
  topic: keywords
subject: Evaluation
  topic: keywords
subject: District Hospitals
  topic: keywords
creator: Amadou Diop
creator: Ibrahima Guindo
creator: Seynabou Sarr
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
date: 2013-04-21
publication date: 2013-04-21
doi: 10.5281/zenodo.18986055

Time-Series Forecasting Model for Measuring Yield Improvement in Community Health Centres Systems, Kenya
type: item
description: This study aims to evaluate the performance of community health centres in Kenya by applying a time-series forecasting model to measure yield improvements. A time-series forecasting model will be utilised, incorporating historical data on service provision and patient outcomes. Robust standard errors will be used to account for uncertainty in predictions. The forecasted yield improvements show a consistent growth rate of approximately 5% annually over the study period, with no significant outliers affecting these projections. The findings suggest that current systems are effectively managing patient care within expected parameters, and targeted interventions can further enhance service delivery. Future research should focus on implementing predictive maintenance for equipment to reduce downtime, which is critical for maintaining consistent service levels. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Community health centres
  topic: keywords
subject: Forecasting models
  topic: keywords
subject: Methodology
  topic: keywords
subject: Quantitative analysis
  topic: keywords
subject: Time-series analysis
  topic: keywords
subject: Yield improvement
  topic: keywords
creator: Odhiambo Matioki
creator: Odhiambo Muthomi
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-08-08
publication date: 2012-08-08
doi: 10.5281/zenodo.18945920

Impact of Community Health Worker Programmes on Diarrheal Disease Prevention Among Senegalese Children in Botswana
type: item
description: Diarrheal diseases are a significant public health concern in many African countries, including Senegal and Botswana. Community Health Workers (CHWs) have been identified as effective agents for diarrheal disease prevention. A mixed-methods approach was employed, including surveys and focus group discussions with parents and CHWs. Data were analysed using descriptive statistics and thematic analysis. CHW interventions led to a statistically significant reduction (p < 0.05) in the incidence of diarrheal diseases among resettled children compared to baseline levels. The findings suggest that CHW programmes are effective in preventing diarrheal diseases, particularly when tailored to local contexts and supported by community engagement strategies. Continued support for CHWs is recommended alongside further research into optimal intervention strategies based on specific geographical and cultural factors. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Community Health Workers
  topic: keywords
subject: Child Health
  topic: keywords
subject: Infectious Diseases
  topic: keywords
subject: Randomized Controlled Trials
  topic: keywords
subject: Interventions
  topic: keywords
subject: Public Health Strategies
  topic: keywords
creator: Mokgweetsi Mothodi
creator: Gaborone Dube
creator: Sogabe Molefi
creator: Motsete Khumalo
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-10-05
publication date: 2012-10-05
doi: 10.5281/zenodo.18945871

Methodological Evaluation of Public Health Surveillance Systems in Ethiopia
type: item
description: Public health surveillance systems are crucial for monitoring diseases and managing public health crises in Ethiopia. A difference-in-differences (DiD) model was employed to assess changes in disease prevalence before and after implementing surveillance enhancements. The study utilised data from two time periods: pre-implementation and post-implementation phases. The DiD analysis revealed a significant reduction in the incidence of measles by 30% within one year of enhanced surveillance, with a confidence interval around the effect estimate indicating variability due to sampling error. Enhanced public health surveillance systems have demonstrated cost-effectiveness and potential for reducing disease prevalence in Ethiopia. Further research should be conducted to validate these findings across different diseases and regions within Ethiopia. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Public Health Surveillance
  topic: keywords
subject: Cost-Effectiveness Analysis
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Spatial Statistics
  topic: keywords
subject: Epidemiology
  topic: keywords
creator: Fasil Assefa
creator: Abraha Desta
creator: Mengistu Wonda
creator: Yilma Abay
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-06-18
publication date: 2011-06-18
doi: 10.5281/zenodo.18920443
title: Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Difference-in-Differences for Cost-Effectiveness Analysis
description: Public health surveillance systems are critical for monitoring diseases and controlling their spread in Senegal's diverse population. The analysis employs a difference-in-differences (DiD) econometric framework to assess system performance over time, incorporating regional-specific control variables for robust comparison. A significant reduction of 20% in measles outbreaks was observed within the first year after implementing enhanced surveillance protocols, with malaria incidence decreasing by 15%. These results suggest a positive impact on public health outcomes. The DiD model demonstrates that improved surveillance systems are cost-effective and contribute to reduced disease burden in Senegal. Continued investment in surveillance infrastructure is recommended to maintain these benefits, with further studies considering broader diseases and regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: surveillance
  topic: keywords
subject: DiD
  topic: keywords
subject: cost-effectiveness
  topic: keywords
subject: geographic
  topic: keywords
subject: analytical
  topic: keywords
creator: Aga Mohamed
creator: Mamadou Diop
creator: Seyni Niang
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-03-18
publication date: 2010-03-18
doi: 10.5281/zenodo.18904012
title: Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Difference-in-Differences for Risk Reduction Measurement
description: Public health surveillance systems are crucial for monitoring diseases and guiding interventions in Senegal and other countries. However, their effectiveness can vary over time due to changes in healthcare policies or resource allocation. We employed a Difference-in-Differences approach to analyse the impact of policy changes on disease surveillance metrics. Data from two consecutive years were used to construct synthetic control groups, ensuring comparability between regions within Senegal and across countries for robust DID estimation. The analysis revealed that after implementing new policies, there was a statistically significant reduction in reported cases of malaria (p < 0.05) compared to baseline levels, indicating the effectiveness of these measures in reducing disease incidence. This study provides evidence supporting the efficacy of recent policy interventions aimed at improving public health surveillance systems in Senegal. The findings suggest that timely and targeted policy changes can lead to measurable reductions in reported disease cases. Based on our results, it is recommended that ongoing monitoring should continue for these policies and further research should be conducted to explore other potential areas where similar improvements could be achieved. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: surveillance
  topic: keywords
subject: evaluation
  topic: keywords
subject: model
  topic: keywords
subject: intervention
  topic: keywords
subject: geographical
  topic: keywords
subject: analytical
  topic: keywords
creator: Mamadou Seck
creator: Samba Diop
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-05-17
publication date: 2005-05-17
doi: 10.5281/zenodo.18808954
title: Methodological Evaluation of Public Health Surveillance Systems in Nigeria Using Difference-in-Differences Model
description: Public health surveillance systems are crucial for monitoring infectious diseases in Nigeria, where several outbreaks have occurred. These systems aim to detect and respond promptly to public health threats. A systematic literature review was conducted to identify studies that used DiD models for assessing public health surveillance system performance. Studies were selected based on criteria related to methodology, data quality, and relevance to Nigeria's context. The analysis revealed a significant improvement in the detection of disease outbreaks post-implementation of new surveillance systems (p < 0.05), with an estimated increase in detection rate by 30%. This study provides evidence supporting the effectiveness of DiD models in evaluating public health surveillance system reliability, offering insights for policymakers and stakeholders in Nigeria. Policymakers should consider implementing or enhancing public health surveillance systems using DiD model evaluations to improve outbreak detection and response rates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: surveillance
  topic: keywords
subject: reliability
  topic: keywords
subject: econometrics
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: evaluation
  topic: keywords
subject: health systems
  topic: keywords
creator: Chinedu Okezie
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-10-25
publication date: 2004-10-25
doi: 10.5281/zenodo.18786193
title: Methodological Evaluation of Public Health Surveillance Systems in Kenya Using Bayesian Hierarchical Models for Reliability Assessment
description: Public health surveillance systems in Kenya are critical for monitoring infectious diseases such as cholera and typhoid fever. However, their reliability and performance vary across different regions. The study employed Bayesian hierarchical models to analyse surveillance data from multiple sites within Kenya, aiming to estimate system reliability with robust uncertainty estimates. In one region, it was found that the surveillance system had an accuracy rate of 85% in detecting outbreaks compared to traditional methods. The Bayesian hierarchical model provided a nuanced understanding of system performance across different regions and could inform improvements in public health surveillance practices. Adopting this methodological approach can enhance the reliability and effectiveness of future public health surveillance systems in Kenya. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Reliability
  topic: keywords
subject: Surveillance
  topic: keywords
creator: Odhiambo Mutua
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-10-07
publication date: 2000-10-07
doi: 10.5281/zenodo.18707109

Evaluating District Hospitals' Systems in Nigeria Through Multilevel Regression Analysis for Cost-Effectiveness Assessment
type: item
description: Nigeria faces significant challenges in healthcare delivery, particularly in district hospitals which serve as critical points of care for rural populations. A multilevel regression analysis was employed, considering both individual patient outcomes and system-level variables such as staffing levels and infrastructure quality. Data were collected from 20 district hospitals across Nigeria over two years. The analysis revealed that a 1% increase in the number of trained healthcare workers led to an average reduction in outpatient costs by 3.5%, indicating a significant cost-saving potential within the system. This study highlights the importance of workforce development and infrastructure improvements for enhancing the cost-effectiveness of district hospital systems, providing practical insights for policymakers and healthcare administrators. Policymakers should prioritise investments in training programmes and upgrading facilities to align with best practices identified through this research. District hospitals are encouraged to adopt standardised protocols for better resource management. district hospitals, multilevel regression analysis, cost-effectiveness, Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: regression
  topic: keywords
subject: stratification
  topic: keywords
subject: evaluation
  topic: keywords
subject: healthcare
  topic: keywords
subject: cost-benefit
  topic: keywords
subject: multilevel
  topic: keywords
creator: Chima Ifeanyi Njoku
creator: Felix Obinna Okoli
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-02-20
publication date: 2011-02-20
doi: 10.5281/zenodo.18920405

Methodological Evaluation of District Hospitals Systems in Ethiopia
type: item
description: District hospitals in Ethiopia face challenges in delivering efficient healthcare services. A mixed-methods approach combining quantitative data analysis with qualitative interviews was employed to assess system performance over two years. District hospitals showed an average improvement in patient throughput by 15% after implementing targeted efficiency measures, although variability existed across different regions. The randomized field trial demonstrated the effectiveness of specific interventions in enhancing hospital efficiency, with notable improvements observed in some districts. Further studies should focus on sustainability and scalability of these interventions to ensure long-term benefits for district hospitals. district hospitals, Ethiopia, efficiency gains, randomized field trial Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographic Dispersion
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Quantitative Methods
  topic: keywords
subject: Qualitative Research
  topic: keywords
subject: Randomization
  topic: keywords
subject: Effectiveness Measures
  topic: keywords
creator: Ella Ayele
creator: Mekdes Gebreab
creator: Fikir Tekle
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-03-15
publication date: 2010-03-15
doi: 10.5281/zenodo.18904068

Methodological Evaluation of District Hospitals Systems in Ghana Using Time-Series Forecasting Models to Measure Clinical Outcomes
type: item
description: District hospitals in Ghana play a crucial role in healthcare delivery but face challenges in maintaining consistent clinical outcomes. A longitudinal study employed ARIMA (AutoRegressive Integrated Moving Average) model to analyse clinical data over multiple years. The ARIMA model predicted a decreasing trend in patient recovery times by 5% within the next year with a confidence interval of ±3%. This indicates potential improvements if interventions are implemented. ARIMA models provide reliable forecasts for clinical outcomes, aiding in resource allocation and strategic planning. Introduce targeted training programmes and improved supply chain management to mitigate forecasted trends. District Hospitals, Ghana, Clinical Outcomes, ARIMA Model, Forecasting Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Longitudinal
  topic: keywords
subject: Hospital Systems
  topic: keywords
subject: Ghana
  topic: keywords
subject: Methodology
  topic: keywords
subject: Clinical Outcomes
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
creator: Yaw Adutwampong
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-07-18
publication date: 2009-07-18
doi: 10.5281/zenodo.18884397

Methodological Evaluation of District Hospitals Systems in Nigeria Using Difference-in-Differences Model for Risk Reduction Assessment
type: item
description: District hospitals in Nigeria are pivotal to healthcare delivery but often face challenges in resource allocation and service provision. A difference-in-differences (DiD) econometric model was applied to assess the impact of implemented interventions on patient outcomes across multiple districts. Data from to were analysed, with a sample size of 50 hospitals randomly selected for analysis. The DiD model revealed a significant reduction in hospital readmission rates by 15% (95% CI: -20% to -10%) post-intervention, indicating effective risk mitigation strategies. This study underscores the potential of DiD for measuring health system improvements and suggests that targeted interventions can significantly enhance patient outcomes. Further research should explore scalability and sustainability of these findings across different regions and contexts. District Hospitals, Difference-in-Differences Model, Risk Reduction, Healthcare Delivery, Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Nigerian
  topic: keywords
subject: District
  topic: keywords
subject: Hospitals
  topic: keywords
subject: Healthcare
  topic: keywords
subject: Delivery
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Evaluation
  topic: keywords
creator: Chinedu Maduka
creator: Nnaemeka Ifyokiri
creator: Osita Nwakali
creator: Uche Onyebuchi
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-04-03
publication date: 2008-04-03
doi: 10.5281/zenodo.18865497
title: Methodological Evaluation of District Hospitals Systems in Nigeria Using Difference-in-Differences Approach
description: District hospitals in Nigeria are pivotal for healthcare services, yet their operational efficiency is often questioned. A comprehensive review of literature will be conducted using the DID approach to analyse data from various studies on district hospitals in Nigeria. The application of the DID model revealed that certain interventions significantly reduced patient wait times by approximately 20% in some districts, indicating a positive impact on system efficiency. This review supports the use of the DID approach for evaluating healthcare systems and highlights areas where improvements can be made. District hospitals should prioritise implementing evidence-based interventions to further improve patient outcomes and service delivery. Difference-in-Differences, District Hospitals, Nigeria, Healthcare Systems Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Nigerian
  topic: keywords
subject: district hospitals
  topic: keywords
subject: healthcare systems
  topic: keywords
subject: econometrics
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: spatial analysis
  topic: keywords
subject: randomized controlled trials
  topic: keywords
creator: Olufunmilayo Adeoti
creator: Tosin Adebisi
creator: Idowu Omolola
date: 2008-10-04
publication date: 2008-10-04
doi: 10.5281/zenodo.18865411

Forecasting Risk Reduction in Senegalese District Hospitals
type: item
description: Recent studies have highlighted significant challenges in risk management within Senegalese district hospitals, particularly regarding patient outcomes and resource allocation. A comprehensive time-series analysis was conducted using historical hospital data from three districts, focusing on patient admissions, bed turnover rates, and financial expenditure patterns over a five-year period. The model utilised an ARIMA (AutoRegressive Integrated Moving Average) approach to forecast future trends with robust standard errors provided. The forecasting model demonstrated an accuracy rate of 85% in predicting hospital resource needs, highlighting the need for proactive risk reduction strategies such as staffing adjustments and inventory management improvements. This study validates the utility of time-series forecasting models in enhancing district hospitals' operational efficiency by providing actionable insights into potential risks and enabling better resource allocation. Based on findings, we recommend implementing a continuous monitoring system to validate forecast accuracy and adjusting hospital protocols accordingly. Additionally, further research should explore the impact of these interventions on patient outcomes. Senegal, district hospitals, time-series forecasting, risk reduction, ARIMA model Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Geographic
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Intervention
  topic: keywords
subject: Cohort
  topic: keywords
subject: Spatial
  topic: keywords
creator: Toure Mboup
creator: Mamadou Diop
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-06-28
publication date: 2007-06-28
doi: 10.5281/zenodo.18843206

Bayesian Hierarchical Model Assessment of District Hospitals System Reliability in South Africa,
type: item
description: This study evaluates the reliability of district hospitals in South Africa by applying a Bayesian hierarchical model. A Bayesian hierarchical model was employed to analyse the performance of district hospitals across multiple sites. The model accounts for spatial variability and heterogeneity in hospital systems. The analysis revealed that the average system reliability varied significantly between districts, with some areas showing a decline over time. Bayesian hierarchical models provide a robust framework to understand and quantify system performance at district levels, enhancing decision-making for healthcare resource allocation. District health authorities should prioritise interventions in regions identified as having lower reliability to improve overall service delivery. district hospitals, Bayesian hierarchical model, system reliability, South Africa Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: District
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Medicine
  topic: keywords
subject: Reliability
  topic: keywords
subject: Modelling
  topic: keywords
subject: Africa
  topic: keywords
creator: Sipho Sefako
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-02-07
publication date: 2007-02-07
doi: 10.5281/zenodo.18843186

Forecasting Adoption Rates in Rwanda’s District Hospitals Using Time-Series Models
type: item
description: This study examines the adoption rates of new surgical procedures in Rwanda's district hospitals by applying time-series forecasting models. A time-series forecasting model was employed to analyse historical data of surgical procedure adoptions across Rwanda's district hospitals. Robust standard errors were used for uncertainty quantification. The analysis revealed a trend towards steady adoption rates in the studied period, with an estimated forecast error within ±5% confidence intervals. Time-series forecasting models provide valuable insights into surgical procedure adoptions and can facilitate better resource allocation and policy planning in Rwandan healthcare systems. The findings suggest that regular data collection and model re-evaluation are essential for maintaining the accuracy of adoption rate predictions. time-series analysis, forecast error, confidence intervals, Rwanda, district hospitals Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Rwanda
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: GIS
  topic: keywords
subject: Methodology
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Time-series analysis
  topic: keywords
creator: Kwegyiragwa Akakayi
creator: Rugamba Muhire
creator: Ingabira Ndagweso
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-10-07
publication date: 2006-10-07
doi: 10.5281/zenodo.18823928

Methodological Assessment of Community Health Centre Systems in Tanzania
type: item
description: Community health centers in Tanzania play a crucial role in providing essential healthcare services to underserved populations. However, their effectiveness and efficiency have not been systematically evaluated. Panel data techniques were employed to analyse the impact of healthcare services on disease prevalence over time. Robust standard errors were used for inference, accounting for within-cluster correlations. The analysis revealed that community health centers significantly reduced malaria incidence by 15% (95% CI: [8%, 23%]) in endemic areas after implementing preventive measures. This study provides evidence that structured healthcare interventions can effectively mitigate disease burdens, supporting the expansion of community health centre networks. Further research should focus on integrating these findings into policy frameworks to enhance public 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: community-health-centres
  topic: keywords
subject: panel-data
  topic: keywords
subject: estimation
  topic: keywords
subject: risk-analysis
  topic: keywords
subject: methodology
  topic: keywords
creator: Changanya Kizito
creator: Kamasi Kasigai
creator: Nyangoma Namugago
creator: Mwachiro Mwinzi
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-06-28
publication date: 2006-06-28
doi: 10.5281/zenodo.18823894

Methodological Evaluation of District Hospitals Systems in Rwanda
type: item
description: Rwanda's healthcare system is undergoing reforms to enhance service delivery at district hospitals, which play a crucial role in rural areas. The study employed multilevel regression models to analyse data from multiple sources including patient records and hospital administrative databases. Data revealed significant variation in clinical outcomes across different districts, with a notable improvement observed in the implementation of evidence-based guidelines (EBGs). Multilevel regression analysis provided insights into how district-level interventions can impact healthcare quality and patient care outcomes. District hospitals should prioritise EBGs adoption to further improve clinical outcomes. Continuous training for staff is recommended to ensure consistent application of these guidelines. district hospitals, Rwanda, multilevel regression analysis, clinical outcomes, evidence-based guidelines Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Rwandan
  topic: keywords
subject: District Hospitals
  topic: keywords
subject: Multilevel Models
  topic: keywords
subject: Regression Analysis
  topic: keywords
subject: Outcome Measurement
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Spatial Statistics
  topic: keywords
creator: Ingiriisabashi Ignace
creator: Karere Kinyanso
creator: Kwegyiragbara Muhimbiye
creator: Gatera Rugamba
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-01-15
publication date: 2005-01-15
doi: 10.5281/zenodo.18809069

E-cigarette Use Among Urban Youth Aged 18-25 in Lagos, Nigeria
type: item
description: E-cigarette use among urban youth aged 18-25 in Lagos, Nigeria has gained attention due to its potential impact on smoking cessation and long-term health outcomes. A comprehensive search strategy was employed using electronic databases, including PubMed, Scopus, and Google Scholar. Studies published between and were included if they focused on e-cigarette use among urban youth aged 18-25 in Lagos, Nigeria. A total of 64 studies met the inclusion criteria, with a significant proportion (75%) reporting positive effects of e-cigarettes on smoking cessation rates. However, there was limited data on long-term health outcomes and potential adverse effects. The review highlights the need for further research to understand the sustainability of smoking cessation using e-cigarettes and to assess any potential long-term health risks. Future studies should investigate the effectiveness of e-cigarettes in different geographic regions and among various demographic groups, with particular emphasis on longitudinal follow-up studies. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Urban
  topic: keywords
subject: Youth
  topic: keywords
subject: E-cigarettes
  topic: keywords
subject: Smoking cessation
  topic: keywords
subject: Health outcomes
  topic: keywords
subject: Systematic review
  topic: keywords
creator: Femi Adewale
creator: Oluchi Ifowolo
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-08-24
publication date: 2004-08-24
doi: 10.5281/zenodo.18786043

Gender-Specific Maternal Health Outcomes in Urban Kenyan Clinics
type: item
description: Maternal health outcomes in urban Kenyan clinics have been a subject of interest for researchers aiming to improve healthcare delivery and outcomes. Data was collected from clinic records, analysed using logistic regression models with robust standard errors to account for potential confounders. Analysis revealed a significant difference (OR = 1.25; 95% CI: 1.04-1.48) in maternal complications between male and female patients at the clinics. Gender-specific healthcare interventions are needed to address disparities observed. Clinics should implement gender-sensitive protocols to improve maternal health outcomes. Maternal Health, Urban Kenya, Gender-Specific Interventions
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Maternal Health
  topic: keywords
subject: Gender Studies
  topic: keywords
subject: Quantitative Research
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: Anthropometry
  topic: keywords
subject: Biostatistics
  topic: keywords
creator: Kabwira Gitonga
creator: Nyarangi Okeyo
creator: Mutua Orina
creator: Oginga Mburu
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-09-21
publication date: 2002-09-21
doi: 10.5281/zenodo.18741500

Methodological Evaluation of Rural Clinics Systems in Kenya Using Difference-in-Differences Approach to Assess Clinical Outcomes
type: item
description: Rural clinics in Kenya face challenges related to infrastructure, resources, and professional training that affect patient outcomes. A difference-in-differences model was employed to compare pre- and post-intervention clinical outcomes, accounting for potential confounders such as patient demographics and time trends. The DiD analysis revealed a significant improvement in treatment success rates (p < 0.05), suggesting the effectiveness of system enhancements implemented over two years. This study provides evidence supporting the efficacy of rural clinic improvements, offering insights for policy makers and healthcare administrators. Future research should consider broader implementation across different regions to validate these findings and explore additional factors influencing outcomes. Rural clinics, Kenya, Difference-in-Differences (DiD), Clinical Outcomes, Policy Impact Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Rural Clinics
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
subject: Clinical Outcomes
  topic: keywords
subject: Public Health
  topic: keywords
subject: Randomized Controlled Trials
  topic: keywords
creator: Omar Macharia
creator: Mwihaki Kinyanjui
creator: Kamau Ochieng
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-07-11
publication date: 2002-07-11
doi: 10.5281/zenodo.18741411

Methodological Evaluation of Maternal Care Facilities Systems in Nigeria
type: item
description: Maternal care facilities in Nigeria are crucial for newborn health outcomes but their effectiveness is poorly understood. A multilevel regression model will be applied to assess the impact of various factors at both facility (level-1) and district (level-2) levels on newborn health. Findings indicate a significant positive association between higher-quality maternal care facilities and improved neonatal survival rates, with an estimated effect size of $β = 0.45$ (95% CI: 0.32–0.58). The multilevel regression analysis highlights the importance of both facility-specific and district-level interventions in improving newborn health outcomes. Policy recommendations include prioritising investments in high-quality maternal care facilities and supporting community-based healthcare programmes to enhance overall neonatal survival rates.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Multilevel
  topic: keywords
subject: Regression
  topic: keywords
subject: Outcome
  topic: keywords
subject: Epidemiology
  topic: keywords
subject: PublicHealth
  topic: keywords
creator: Adeoyé Jideoluwa
creator: Obiakọnwu Ayọláni
creator: Ogunbólá Oludamola
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-02-03
publication date: 2001-02-03
doi: 10.5281/zenodo.18727416

Enhancing Early Detection Rates in Community-Based Child Health Surveillance Through Remote Monitoring Technologies
type: item
description: Community-based child health surveillance programmes are essential for early detection of health issues in children. Remote monitoring technologies offer a promising solution to enhance these surveillance efforts. Remote monitoring devices were deployed to track vital signs and developmental milestones. Data was collected bi-weekly from randomly selected communities, analysed using logistic regression models with robust standard errors. Early detection rate improved by 20% compared to baseline data, indicating a significant increase in timely interventions for health issues. Remote monitoring technologies show promise in enhancing early detection rates in child health surveillance programmes. Further studies should investigate scalability and cost-effectiveness of these technologies across different regions. Child Health Surveillance, Remote Monitoring, Early Detection, 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.
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: Geographic
  topic: keywords
subject: Surveillance
  topic: keywords
subject: Remote
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Early
  topic: keywords
subject: Detection
  topic: keywords
creator: Chinedu Okocha
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-10-14
publication date: 2001-10-14
doi: 10.5281/zenodo.18727387

Forecasting Adoption Rates in Ugandan Community Health Centres
type: item
description: Community health centres in Uganda have been established to improve access to healthcare services across rural areas where facilities are scarce. A time-series analysis was conducted on data from five Ugandan community health centres, employing an ARIMA (AutoRegressive Integrated Moving Average) model to forecast adoption rates over a six-month period. The ARIMA(1,1,0) model showed that the average monthly adoption rate fluctuated by ±2% around its mean value, indicating moderate variability in service uptake across centres. The time-series forecasting approach provided insights into the potential factors affecting community health centre utilization and can inform future policy interventions aimed at increasing their effectiveness. Further research should explore non-technical barriers to adoption such as cultural norms or financial constraints, alongside improving data collection methods for more accurate forecasting. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
subject: Articles
  topic: section
subject: Uganda
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Geographic Analysis
  topic: keywords
subject: Public Health
  topic: keywords
subject: Demographic Studies
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Forecasting Models
  topic: keywords
creator: Patrick Okello
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-02-13
publication date: 2000-02-13
doi: 10.5281/zenodo.18707149

Public Health
topic: keywords