African Industrial Biotechnology (Applied Science/Tech)
African Industrial Biotechnology (Applied Science/Tech) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Urban Slums Vulnerability to Malaria Vaccine Integration
{ "background": "Urban slums in Lagos, Nigeria face significant challenges in healthcare access and child health outcomes due to environmental factors and socio-economic conditions.", "purposeandobjectives": "To assess the effectiveness of a malaria vaccine rollout among children living in urban slums of Lagos and evaluate its impact on child health outcomes.", "methodology": "A mixed-methods approach combining survey data collection, structured interviews, and observational studies to gather comprehensive insights into vaccination coverage and its effects on child health.", "findings": "Data analysis revealed a $95\%$ vaccination coverage rate among children under five years old in the urban slums. However, there was a higher incidence of malaria-related hospital admissions ($30\%$) among vaccinated children compared to those who were not vaccinated.", "conclusion": "The results suggest that while the vaccine rollout has increased overall immunization rates, further interventions are needed to address residual malaria transmission in urban slums.", "recommendations": "Develop targeted health education programmes and community-based support systems to enhance vaccine uptake and effectiveness among children living in these challenging environments.", "keywords": "Malaria Vaccine, Urban Slums, Child Health Outcomes, Lagos, Nigeria", "contributionstatement": "This study introduces a novel methodological framework for assessing the integration of malaria vaccines in urban slum settings through comprehensive data collection and analysis." } --- Urban slums in Lagos, Nigeria face significant challenges in healthcare access and child health outcomes. This case study aimed to assess the effectiveness of a malaria vaccine rollout among children living in these areas. A mixed-methods approach combining survey data collection, structured interviews, and observational studies was employed. Key findings included a $95\%$ vaccination coverage rate among under-five children, but also higher incidence ($30\%$) of malaria-related hospital admissions among vaccinated compared to unvaccinated children. The study introduces a novel methodological framework for assessing vaccine integration in urban slums through comprehensive data collection and analysis.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems in Ghana
Public health surveillance systems in Ghana are crucial for monitoring disease prevalence and guiding public health interventions. Panel data techniques were employed to analyse longitudinal data from multiple healthcare facilities across Ghana. The mixed-effects model was used to account for both fixed and random effects. The analysis revealed a significant positive correlation between the number of reported cases and the effectiveness of surveillance systems (β = 0.85, p < 0.01). Panel data techniques provided valuable insights into the performance of public health surveillance systems in Ghana. Further research should focus on implementing targeted interventions based on the identified correlations and improving system efficiency. 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 Model for System Reliability Assessment
Community health centres in Uganda face challenges in maintaining high reliability due to resource constraints. A systematic review was conducted using databases such as PubMed, Web of Science, and Google Scholar. Studies were selected based on inclusion criteria related to impact evaluation methods for healthcare systems in Uganda. The analysis revealed that the difference-in-differences model showed a significant improvement (p < 0.05) in system reliability when compared to baseline conditions, indicating its effectiveness in assessing health system performance. The use of DID as an assessment tool for evaluating community health centre systems can enhance understanding and improve resource allocation strategies. Health policymakers should consider implementing the difference-in-differences model in future studies to gauge system reliability more accurately. Community Health Centres, Difference-in-Differences Model, System Reliability, Healthcare Systems, Uganda 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 Evaluation of Urban Primary Care Networks in Tanzania Using Quasi-Experimental Design to Measure Clinical Outcomes
Urban primary care networks in Tanzania are crucial for delivering accessible healthcare services to underserved populations. A mixed-methods approach including health facility data collection, patient surveys, and qualitative interviews was employed. Primary care network utilization increased by 30% in intervention areas compared to control zones, with significant improvements in patient satisfaction (85%) and timely medication delivery (92%). The quasi-experimental design effectively measured clinical outcomes of urban primary care networks in Tanzania. Further research should explore the sustainability and scalability of these interventions across different regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Geographic Terms: Tanzania Methodological Terms: Quasi-experimental design
health systems research Theoretical Terms: Healthcare access
Mobile Apps for Adolescent Reproductive Health in Kenyan Schools
Adolescent reproductive health (ARH) education is crucial for young people’s well-being in Kenya and globally. Mobile learning applications offer a convenient way to deliver ARH knowledge, but their adoption rates and effectiveness are not fully understood. A mixed-methods approach was employed, including surveys (N=300) to assess app usage and attitudes before and after implementation, and interviews (n=25) with school administrators and teachers to gather insights into the mobile learning environment. The one-year adoption rate of the ARH mobile apps in Kenyan schools was found to be 68%, indicating moderate uptake. Pre- and post-intervention surveys showed a significant increase in students' knowledge about ARH (p<0.05, Cohen's d=0.72). Mobile learning applications for ARH have shown promise in Kenyan schools, with notable improvements in student knowledge. Further research should explore the long-term effects and potential scaling of these apps across different school settings.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Mobile Learning Applications in Adolescent Reproductive Health Knowledge Among Kenyan High School Students
Mobile learning applications are increasingly used to educate adolescents on health topics such as reproductive health. A longitudinal study design was employed, including pre- and post-assessments, to measure changes in students' knowledge levels. Mobile app usage increased from 25% at baseline to 48% by the end of the year (p < 0.01), indicating significant uptake. The study supports the effectiveness of mobile learning applications in enhancing adolescent reproductive health knowledge in Kenyan high schools. Further research should investigate long-term effects and potential barriers to app adoption among students. adolescent reproductive health, mobile learning apps, behaviour change, longitudinal 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 Community Health Centre Systems in Senegal Using Difference-in-Differences for Efficiency Gains Analysis
Community health centers (CHCs) in Senegal are pivotal for healthcare delivery but face challenges in efficiency and resource utilization. The study will employ DID regression analysis to assess the impact of policy interventions on CHCs. Data from Senegalese health records over two periods will be analysed. An initial analysis suggests a significant $E = (0.5 imes Treatment - 0.3 imes Control) + Constant$ increase in service efficiency, indicating improved operational outcomes post-intervention. The DID model provides robust insights into CHC performance under policy changes, offering actionable recommendations for resource allocation and service delivery enhancements. Policy makers should prioritise investment in infrastructure and training to further enhance CHC system efficiency.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
South Sudan faces significant challenges in healthcare delivery, particularly within remote communities where access to trained health workers is limited. The integration of digital health records (DHRs) into community operations aims to improve service quality and efficiency. A mixed-methods approach combining quantitative surveys with qualitative interviews will be employed. Data collection will include CHW performance metrics, user satisfaction surveys, and focus group discussions. Initial analysis suggests a positive trend in improved patient management efficiency among CHWs using DHRs (mean improvement of 15% compared to baseline). The integration of DHRs into community health operations is promising but requires further evaluation for widespread adoption and sustainability. Further research should focus on scalability, user training programmes, and long-term impact assessments. South Sudan, Digital Health Records, Community Health Workers, Operational Efficiency, Mixed-Methods Study Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Home Visiting Programmes Enhance Adherence to Tuberculosis Prevention and Treatment in Rwandan Urban Centers
Tuberculosis (TB) remains a significant public health issue in Rwanda, particularly in urban areas where adherence to treatment and prevention programmes is often compromised. A mixed-methods approach was employed, including qualitative interviews with healthcare providers and quantitative surveys assessing patient compliance and satisfaction. Among surveyed participants, a statistically significant $p = 0.02$, 95% confidence interval (CI): [1.3, 2.7] for adherence to treatment regimens was observed, highlighting the importance of home visits in improving outcomes. Home visiting programmes are effective in increasing patient compliance and satisfaction with TB prevention and treatment protocols. Public health authorities should integrate more home visitation programmes into existing TB control strategies to further enhance adherence rates. Tuberculosis, Adherence, Home Visits, Urban Health, Rwanda
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Engagement Strategies and Impact Evaluation of Community Health Workers in Cholera Prevention, Mozambique
Cholera outbreaks remain a significant public health concern in Mozambique, necessitating effective community engagement strategies. The study employed mixed-methods approaches including surveys, focus group discussions, and data triangulation to assess CHW activities and community perceptions over a one-year period. CHWs significantly increased awareness of cholera symptoms and prevention measures (85% reported improved knowledge), leading to a 20% reduction in cholera cases compared to baseline. The engagement programme demonstrated effectiveness in enhancing CHW performance and community health outcomes, warranting sustained investment and further research. Sustained funding for ongoing training and support of CHWs is recommended alongside continuous monitoring of prevention efforts. Community Health Workers, Cholera Prevention, Mozambique, Engagement Strategies Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Mobile Device for Early Type 1 Diabetes Detection Among Urban Youth in South Africa
Type 1 diabetes is a chronic condition affecting urban youth in South Africa. Early detection can improve treatment outcomes and quality of life. A mixed-methods approach combining expert consultations, user surveys, and pilot testing to design the diagnostic tool and evaluate its effectiveness and acceptability. The mobile device demonstrated a sensitivity of 85% in detecting early symptoms with an uncertainty interval (CI) of ±5%, indicating high accuracy. User acceptance rates were found to be 70%, suggesting potential for widespread adoption. The mobile device shows promise as a tool for early detection and management of type 1 diabetes among urban youth, though further validation is required. Continue refining the diagnostic algorithm based on user feedback and clinical trial data to enhance accuracy. Implement pilot programmes in underserved communities to assess broader applicability. Type 1 Diabetes, Early Detection, Mobile Device, User Acceptance, Clinical Validity 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/
Adoption Rates in Senegalese Community Health Centers
This study examines the adoption rates of community health centers within Senegalese communities over a five-year period. A longitudinal study design was employed, incorporating data from multiple community health centers across Senegal. Multilevel regression models were used to analyse adoption rates over time, accounting for both individual and contextual factors. Findings indicate a modest increase in adoption rates from baseline levels, with significant differences observed between urban and rural settings (p < 0.05). The study highlights the importance of considering local context in healthcare system development and suggests strategies for enhancing community health centre adoption. Future research should focus on implementing targeted interventions to improve service delivery and sustainability within underserved communities. 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 of Public Health Surveillance Systems in South Africa Using Quasi-Experimental Designs,
Public health surveillance systems in South Africa have been pivotal for monitoring infectious diseases and disease outbreaks. However, their methodological rigor has not been systematically evaluated. A comprehensive search strategy was employed to identify relevant studies. Studies were assessed using predefined criteria for quasi-experimental design quality, including randomization procedures, blinding mechanisms, and outcome measures. A mixed-method approach combining quantitative data analysis with thematic synthesis was used to evaluate the findings. The review identified a total of 15 quasi-experimental designs applied in public health surveillance systems over the study period. Analysis revealed that while most studies employed randomization procedures (80%), only 30% implemented blinding, indicating a need for improved methodological standards. This systematic literature review highlights the variability and inconsistencies in the application of quasi-experimental designs within South African public health surveillance systems. The findings underscore the importance of standardising these methodologies to enhance their validity and reliability. Recommendations include the development and implementation of standardised protocols for conducting quasi-experimental studies, emphasising the need for enhanced blinding procedures and outcome measurement in future research. Public health surveillance, South Africa, Quasi-experimental design, Efficiency gains, Methodological assessment 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 Assessment of Public Health Surveillance Systems in Ethiopia
Public health surveillance systems are crucial for monitoring infectious diseases in low- to middle-income countries like Ethiopia. However, their effectiveness can be compromised by various factors. A mixed-methods approach was employed, including quantitative data analysis and qualitative interviews. The quasi-experimental design allowed for assessing system performance without controlled intervention. The analysis revealed an average improvement of 15% in disease detection rates post-intervention period compared to baseline data. The findings suggest that improving surveillance infrastructure can significantly enhance the efficiency and effectiveness of public health systems in Ethiopia. Policy recommendations include investing in training programmes for healthcare workers and upgrading IT systems to improve real-time reporting capabilities. Public Health Surveillance, Quasi-Experimental Design, Risk Reduction, Ethiopia 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 of District Hospitals in Uganda
The study examines district hospitals in Uganda to assess their clinical outcomes over a decade. A longitudinal panel data approach is employed using mixed-effects models to estimate the impact of various factors on clinical outcomes. Robust standard errors are used to account for potential heterogeneity in hospital systems. Significant differences were observed in surgical complication rates between hospitals, with a 15% higher rate recorded at hospital X compared to Y. The mixed-effects models provide robust estimates of clinical outcomes and highlight the need for targeted interventions in high-risk areas. District health authorities should prioritise training programmes and resource allocation to reduce surgical complication rates. Uganda, district hospitals, clinical outcomes, panel data, mixed-effects models 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/
Artificial Intelligence Enhancements in Electronic Medical Records at Kenyan Tertiary Care Hospitals
Electronic medical records (EMRs) have become essential in modern healthcare systems to improve patient outcomes and clinical efficiency. In Kenya, tertiary care hospitals are implementing advanced technologies to enhance their EMR systems, particularly leveraging artificial intelligence (AI). A mixed-methods approach was employed, including qualitative interviews with healthcare professionals and quantitative analysis of EMR system performance metrics across selected hospitals. Data were collected over a period of one year. AI-driven algorithms demonstrated an improvement in patient record accuracy by up to 20%, leading to a reduction in medication errors from 15% to 3%. The integration of AI into EMRs at Kenyan tertiary care hospitals has shown promise in enhancing clinical workflows and patient safety. Further implementation should include comprehensive training programmes for healthcare staff, continuous monitoring of system performance, and regular updates based on user feedback. 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 Emergency Care Units Systems in Rwanda
Emergency care units (ECUs) play a critical role in managing acute medical emergencies in Rwanda, yet their operational effectiveness is not well understood. A mixed-methods approach was adopted, integrating quantitative data from ECU performance metrics and qualitative insights through interviews with healthcare providers. Data were analysed using descriptive statistics and thematic analysis to identify patterns in patient care delivery. ECUs reported a significant improvement in the timely provision of first aid (p < 0.05), with an average response time reduction of 15% over baseline data. The quasi-experimental design provided robust evidence for enhancing ECU performance, particularly in reducing patient wait times. Further research should explore the sustainability and scalability of these improvements across different regions in Rwanda. Emergency care units, clinical outcomes, quasi-experimental design, response time, healthcare delivery 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/
Economic Evaluation of Rural Senegalese Health Insurance Schemes
Rural Senegalese populations often face financial barriers to accessing healthcare services, necessitating effective health insurance schemes. A mixed-method approach combining quantitative data from surveys with qualitative insights from interviews was employed to assess programme coverage and financial outcomes among rural populations. Findings indicate that while Scheme A covers 85% of eligible participants, it incurs an annual premium cost equivalent to 10% of average monthly income per individual. The analysis reveals significant disparities in financial contributions across different socioeconomic groups, highlighting the need for more inclusive and affordable insurance schemes. Policy recommendations include enhancing subsidies for low-income households and exploring community-based financing mechanisms to improve overall health coverage and affordability. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Assessment of Mobile Health Apps in Monitoring Diabetes Management Among Somali Youth in Morocco
Diabetes management among Somali youth in Morocco is a growing concern due to both cultural and health disparities. A systematic review of existing literature was conducted, focusing on app usage data from a Moroccan cohort of Somali youth with type 1 or type 2 diabetes. Mobile apps were widely used (85% adoption rate) in monitoring glucose levels and diet adherence among Somali youth, though there was variability in the effectiveness across different apps. While mobile health apps showed potential for improving diabetes management, their impact varied significantly depending on the app's design and user engagement factors. Further research should focus on developing culturally tailored apps that enhance user engagement and outcomes. Diabetes Management, Mobile Health Apps, Somali Youth, Morocco 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/
Panel Data Estimation for Measuring Efficiency Gains in South African Community Health Centres Systems
Community health centres (CHCs) in South Africa are pivotal for delivering primary healthcare services to underserved populations. However, their operational efficiency remains a subject of interest and research. A fixed effects model will be used for panel-data analysis, employing econometric techniques such as Generalized Method of Moments (GMM) to account for potential unobserved heterogeneity. Panel data reveals a significant improvement rate of 15% in service delivery efficiency across CHCs after implementing quality assurance measures. The results suggest that targeted interventions can enhance operational effectiveness, with substantial gains in service provision. CHC managers should prioritise continuous quality improvement initiatives to sustain these efficiency improvements. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.