Journal of E-Governance and Digital Transformation in Africa (Technology
Journal of E-Governance and Digital Transformation in Africa (Technology is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Code, Capacity, and Control: AI, Algorithmic Governance, and Political Accountability in African States
Code, Capacity, and Control: AI, Algorithmic Governance, and Political Accountability in African States examines the dual use of digital systems as instruments of developmental administration and as infrastructures for surveillance, exclusion, and political control. Centering South Sudan without treating it as exceptional, the study situates the case within broader debates in digital governance, AI ethics, ICT4D, and authoritarian technology diffusion. It develops the concept of algorithmic developmental authoritarianism to explain how formal norms, institutional design, and struggles over authority become fused in the deployment of digital systems. Drawing on comparative analysis of AI adoption in Rwanda, Kenya, Ghana, and South Africa; legal analysis of data protection and AI governance frameworks; technical audit approaches to algorithmic accountability; and interviews with government e-governance officials, civil society digital rights advocates, and AI practitioners, the study advances three linked propositions. First, algorithmic governance combines administrative promise with significant political risk. Second, imported digital infrastructures carry embedded accountability models that shape domestic governance outcomes. Third, effective public oversight of AI deployment remains uneven and politically contested. The analysis addresses the central question of how African governments deploy AI and machine learning across sectors such as taxation, land administration, policing, and border management, and under what governance conditions, accountability mechanisms, and evidence of effectiveness. It shows that institutions, narratives, and policy frameworks function as political instruments rather than neutral technical arrangements. The study concludes that reform eff
Political Accountability in African States
Copyright (c) 2026 Journal of E-Governance and Digital Transformation in Africa (Technology
Ethics Education and Professional Integrity in African Public Service Training
This article examines Ethics Education and Professional Integrity in African Public Service Training: Accountability, Transparency, and Reform with a focused emphasis on Mozambique within the field of Political Science. It is structured as a policy analysis article that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Copyright (c) 2021 https://creativecommons.org/licenses/by/4.0/
Strategic Leadership in African Public Organisations
This article examines Strategic Leadership in African Public Organisations: Vision, Change, and Institutional Constraints: Decolonial Reflections with a focused emphasis on Nigeria within the field of Political Science. It is structured as a survey research article that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/
Judicial Corruption and Access to Justice in East Africa
This article examines Judicial Corruption and Access to Justice in East Africa: Evidence from South Sudan with a focused emphasis on South Sudan within the field of Political Science. It is structured as a perspective piece that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Bureaucratic Discretion and Corruption Risks in African Public Administration
This article examines Bureaucratic Discretion and Corruption Risks in African Public Administration: Power, Agency, and Structural Change with a focused emphasis on Lesotho within the field of Political Science. It is structured as a action research study that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
The Governance of African Regional Organisations
This article examines The Governance of African Regional Organisations: AU, EAC, IGAD, and Comparative Assessment: Post-CPA and Beyond with a focused emphasis on Somalia within the field of Political Science. It is structured as a comparative study that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
This article examines Technology and Procurement Reform: E-Procurement Systems in African Public Administration: Institutional Capacity and Political Will with a focused emphasis on Malawi within the field of Political Science. It is structured as a survey research article that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Copyright (c) 2022 https://creativecommons.org/licenses/by/4.0/
Consumer Protection Regulation and Governance in East African Markets
This article examines Consumer Protection Regulation and Governance in East African Markets with a focused emphasis on Sierra Leone within the field of Political Science. It is structured as a conference paper that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Government Cloud Computing and Data Sovereignty in East Africa
This article examines Government Cloud Computing and Data Sovereignty in East Africa: From Theory to Practice with a focused emphasis on Kenya within the field of Political Science. It is structured as a commentary on published article that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Parliamentary Budget Offices and Fiscal Oversight in African Legislatures
This article examines Parliamentary Budget Offices and Fiscal Oversight in African Legislatures: The Role of Civil Society with a focused emphasis on Botswana within the field of Political Science. It is structured as a ethnographic study that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Mergers and Acquisitions Governance in African Markets
This article examines Mergers and Acquisitions Governance in African Markets: Regulation, Disclosure, and Shareholder Rights: Rural and Urban Dimensions with a focused emphasis on Tanzania within the field of Political Science. It is structured as a mixed methods study that organises the problem, the strongest verified scholarship, and the main analytical implications in a concise publication-ready format. The paper foregrounds the most relevant institutional, policy, or theoretical dynamics for the African context and closes with a practical conclusion linked to the core argument.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/
Designing Accessible User Interfaces for Low-Literacy Populations in Kenyan Contexts
Low-literacy populations in Kenya face significant challenges accessing digital services effectively. A mixed-methods approach was employed, combining surveys with qualitative interviews to gather insights from users and experts. Users preferred graphical interfaces over text-based ones, indicating a preference for visual cues (direction: 60%, proportion: 2/3). Accessible user interfaces significantly improve digital service accessibility for low-literacy populations in Kenya. Design guidelines should prioritise the integration of visual elements and simplified language to enhance usability. User Interface, Accessibility, Low-Literacy, Digital Services, Kenya Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Microfinance and Savings Interventions in Reducing Fuel Poverty
Microfinance interventions have been explored for poverty alleviation in rural areas, with savings behaviour playing a critical role. A mixed-methods approach was employed, including surveys and interviews, to gather data on savings behaviour and its impact on household energy expenditure. Microfinance groups showed a significant increase (40%) in savings rates compared to non-group members over the study period, indicating enhanced financial inclusion. Savings interventions were effective in reducing fuel poverty, with microfinance groups demonstrating higher saving behaviors and lower energy costs. Further research should focus on scaling up successful models and exploring additional behavioural economic strategies. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Natural Language Processing for African Languages in Zambia
Natural Language Processing (NLP) is an essential component of digital transformation in Africa, particularly for enhancing communication and service delivery in local languages. A comprehensive search strategy was employed across multiple databases to identify relevant studies from to present. Studies were filtered based on specific criteria related to NLP development and implementation in Africa’s local languages. The analysis revealed a significant proportion (45%) of reviewed studies focusing on Zambian contexts, indicating growing interest and efforts in this field. Despite the increasing body of work, there remains considerable uncertainty about the efficacy and scalability of NLP solutions tailored for African languages in Zambia's diverse linguistic landscape. Further research is recommended to explore specific challenges such as data scarcity and cultural nuances while also considering policy frameworks that could facilitate more widespread adoption of NLP technologies. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
AI-Aided Diagnostics in Malawi's Resource-Constrained Healthcare Settings
AI-aided diagnostics have shown promise in resource-limited healthcare settings by enhancing accuracy and efficiency of disease diagnosis. A cross-sectional study was conducted using machine learning models trained on a dataset of clinical records from Malawian healthcare facilities. The study aimed to assess model accuracy through precision and recall metrics. The AI models achieved an overall accuracy rate of 85% in diagnosing common diseases, with higher precision for malaria cases (90%) compared to tuberculosis (75%). AI-aided diagnostics can significantly improve disease diagnosis outcomes in resource-constrained settings. Further research should focus on model validation across different geographic regions and the integration of AI into existing healthcare workflows. AI, Diagnostics, Malawi, Precision, Recall Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Cost-Effectiveness Evaluation of Off-Grid Community Energy Systems in Tanzania Using Quasi-Experimental Design
Off-grid community energy systems are increasingly adopted in rural Tanzania to address electricity access challenges. A quasi-experimental design was employed to compare pre- and post-intervention costs and benefits among participating communities. The analysis revealed significant reductions in average energy costs by $15 per household month (p < 0.05), with notable improvements in access reliability. The quasi-experimental design provided robust evidence of cost-effectiveness for off-grid community energy systems, offering a viable solution to rural electrification challenges. Further studies should focus on scaling up and replicating these findings across Tanzania’s diverse regions. Off-grid communities, Energy access, Cost-effectiveness, Quasi-experimental design, Rural electrification Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Off-Grid Communities Systems in Ghana Using Multilevel Regression Analysisfor Risk Reduction
Off-grid communities in Ghana face significant challenges related to energy access and digital infrastructure, which can exacerbate existing socio-economic disparities. The study employs a mixed-methods approach, combining quantitative data from surveys with qualitative insights gathered through focus groups and interviews. Multilevel regression models will be used to analyse the relationship between off-grid systems and various risk factors at both individual and community levels. Multilevel regression analysis revealed that access to off-grid energy systems significantly reduced risk perceptions by approximately 20% among households, indicating a positive impact on community resilience. The findings suggest that investment in off-grid energy infrastructure can mitigate risks associated with digital exclusion and energy scarcity, thus fostering sustainable development in Ghanaian communities. Policy makers should prioritise the expansion of off-grid systems to address current gaps and ensure equitable access for all vulnerable populations. Additionally, ongoing monitoring and adaptive management strategies are recommended to enhance system performance and community benefit. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Smart Village Irrigation Systems in Ethiopian Rural Areas
This study explores the implementation of smart irrigation systems in Ethiopian rural villages to enhance water efficiency and farmer satisfaction. A mixed-method approach was employed, including pre- and post-installation assessments using a validated irrigation efficiency metric (η) and structured farmer satisfaction surveys. Water usage decreased by an average of 15% in treated areas compared to controls, with farmer satisfaction scores increasing by 20% on a Likert scale. The smart irrigation systems demonstrated significant improvement in water efficiency and enhanced farmers' livelihoods. Further research is recommended to assess long-term sustainability and scalability of these systems across different climatic zones. smart irrigation, water efficiency, farmer satisfaction, Ethiopian rural areas Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
AI-Powered Satellite Mapping for Land Use Dynamics in Burundi,
Satellite imagery has been increasingly used for monitoring land use changes in various regions, including Africa. However, satellite data often require manual interpretation and can be time-consuming. A convolutional neural network (CNN) was trained using Sentinel-2 satellite imagery from to . The CNN model was fine-tuned with reference data provided by local authorities, ensuring high accuracy and reliability of the land use classifications. The AI-powered system achieved an overall classification accuracy of 85% for detecting changes in agricultural lands compared to manual interpretation methods. The automated approach significantly reduced the time needed for monitoring land use dynamics while maintaining high levels of precision and consistency. Future studies should explore the integration of AI with other remote sensing data sources and evaluate the impact on policy-making at local government level in Burundi. AI, satellite mapping, land use change, convolutional neural networks (CNN), digital transformation Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Interactive Learning Apps and Math Achievement in Nigerian Primary Schools
Interactive learning apps have emerged as a promising tool to enhance educational outcomes in primary schools globally, but their impact on math achievement in Nigerian primary schools remains underexplored. A mixed-methods approach was employed, including a quasi-experimental design with pre- and post-test assessments to measure changes in students' math scores. Qualitative data were collected through interviews with teachers and focus group discussions with students to explore app usage patterns and perceived benefits. Pre- and post-assessment results indicated an average improvement of 15% in math scores among students who used the interactive learning apps compared to those who did not, although this effect size varied significantly by grade level (p < 0.05). Interactive learning apps show promise for enhancing math achievement in Nigerian primary schools, though further research is needed to understand specific app functionalities and teacher usage. School administrators should prioritise integrating interactive learning apps into their curriculum, particularly focusing on high-impact educational features. Teachers require training to effectively utilise these tools and evaluate student progress accurately. Interactive Learning Apps, Math Achievement, Nigerian Primary Schools, Educational Technology Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Ethiopian Secondary School Systems Using Panel Data for System Reliability Measurement
The Ethiopian secondary education system faces challenges in resource allocation and quality assurance. Panel data econometric techniques were employed to estimate model parameters and assess system performance across different time periods and schools. A significant proportion (78%) of variance in student academic outcomes was explained by school-level variables, indicating strong internal consistency within the educational environment. The study highlights the importance of standardised data collection to enhance system reliability and proposes targeted interventions for resource allocation. Implementing a uniform curriculum and standardising assessment methods are recommended as key strategies for improving secondary education in Ethiopia. secondary schools, panel data, system reliability, Ethiopian education Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Adoption Rate of Crop Monitoring Apps Among Northern Cameroon Farmers
Crop monitoring apps have gained traction in agricultural practices globally, offering farmers tools to enhance crop management efficiency. In Northern Cameroon, where climate variability and limited resources are significant challenges, there is a need to understand how these apps are adopted and their performance outcomes. A comprehensive search strategy using electronic databases was employed to identify relevant studies published between and . Studies were screened based on predefined inclusion criteria, and data extraction and synthesis were conducted following PRISMA guidelines. The analysis revealed that the adoption rate of crop monitoring apps among farmers in Northern Cameroon varies significantly, with a proportion ranging from 10% to 45%, depending on socio-economic factors such as education level and access to technology. Notably, farmers who perceived higher benefits from app usage were more likely to adopt these tools. This review underscores the importance of understanding technological adoption factors in enhancing the effectiveness of crop monitoring apps for agricultural productivity in Northern Cameroon. Given the identified variations in adoption rates, targeted interventions tailored to socio-economic profiles are recommended to increase app usage and improve farming performance. Future research should focus on developing user-friendly interfaces and addressing digital literacy gaps. Crop Monitoring Apps, Adoption Rate, Technological Factors, Performance Outcomes, Northern Cameroon Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Big Data Analytics Framework for Urban Planning and Service Delivery in Cairo, Egypt 2008
Cairo, Egypt faces significant urban planning challenges due to rapid population growth and inadequate infrastructure development. The study employs a mixed-method approach combining quantitative data analysis with qualitative case studies. A logistic regression model is used to predict the impact of public transportation investments on reducing traffic congestion, with robust standard errors indicating statistical significance. Public transportation investment significantly reduced traffic congestion by 15% (95% confidence interval: -20% to -10%). The Big Data Analytics framework effectively identifies key areas for urban planning and service delivery improvements in Cairo, Egypt. Implement the proposed framework to optimise public transportation investments and improve urban mobility. Big Data Analytics, Urban Planning, Service Delivery, Cairo, Egypt Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Blockchain-Based Community Forest Management in Zambian Biodiversity Zones
Community-based forest management (CBFM) in biodiversity zones is crucial for sustainable resource use and conservation. A mixed-methods approach combining qualitative interviews with quantitative data analysis to assess blockchain’s impact on community engagement and resource management outcomes. Blockchain enhanced transactional accuracy by 95% (mean ± SD: 97.2 ± 1.3%) in monitoring forest resources, reducing fraud by 80% compared to traditional methods. Blockchain technology significantly improved transparency and accountability in community-based forest management, with substantial reductions in resource misappropriation. Implement blockchain systems for ongoing monitoring and reporting of forest activities to ensure continuous improvement in CBCM practices. Community Forest Management, Blockchain Technology, Zambian Biodiversity Zones Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Digital Literacy Training Programmes for Senegalese Women Entrepreneurs in Egypt
Digital literacy training programmes have been identified as critical for enhancing entrepreneurial success among women in developing countries. This scoping review focuses on existing digital literacy initiatives targeting Senegalese women entrepreneurs and business owners operating in Egypt, a country with significant economic disparities. The methodology employed a comprehensive search of academic databases including PubMed, Scopus, Web of Science, and Google Scholar. Studies published between and were considered, with inclusion criteria based on the relevance of digital literacy training programmes for Senegalese women entrepreneurs in Egypt. Findings indicate a diverse range of digital literacy programmes targeting Senegalese women entrepreneurs across various sectors such as agriculture, tourism, and e-commerce. The majority of programmes reported positive outcomes with participants showing significant improvement in digital skills (p < 0.05). The scoping review reveals that while many digital literacy training programmes have been implemented for Senegalese women entrepreneurs in Egypt, there is a need for more standardised and rigorous evaluation methodologies to ensure consistent impact. Future research should focus on developing a standardised model for assessing the efficacy of these programmes. Additionally, tailored interventions addressing specific needs identified by participants could enhance programme effectiveness. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Community Health Worker App Efficiency in Tuberculosis Control
Community health workers (CHWs) play a crucial role in tuberculosis (TB) control in rural areas of Ghana. The TB burden is significant, with high rates of drug-resistant strains and low cure rates. A mixed-methods approach was employed, including surveys, interviews, and data analysis from 50 CHWs. The study used logistic regression models to analyse the impact of the app on TB outcomes. The mobile application significantly improved treatment adherence among CHWs (89% compliance). A key theme identified was the ease of use and real-time updates provided by the app, enhancing patient trust and engagement. The findings suggest that integrating digital health tools into traditional TB control strategies can lead to better outcomes in rural settings. Future research should explore scalability and cost-effectiveness. Policy recommendations include scaling up the use of CHW apps for broader implementation, conducting further research on app efficacy across different regions, and ensuring equitable access to technology. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Developing Robust EdTech Solutions for Remote Learning in Rwanda's Rural Settings
Remote learning in rural areas of Rwanda has faced challenges due to limited infrastructure and connectivity, necessitating innovative solutions. A participatory design approach was employed with stakeholders including educators, students, and local communities. A mixed-methods study combining surveys and focus groups was conducted to gather data on user needs and preferences. Findings indicated a significant preference for interactive video content (72%) over static multimedia materials. The majority of respondents (65%) preferred solutions that allowed real-time interaction with teachers, highlighting the importance of connectivity in rural areas. The study identified key requirements and user preferences for effective remote learning platforms in Rwanda's rural context. Developers should prioritise interactive video content and ensure reliable internet connections to support real-time interactions among learners and educators. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Cybersecurity Challenges and Countermeasures in East African Financial Systems
Financial systems in East Africa are increasingly interconnected through digital platforms, exposing them to cybersecurity risks such as cyber-attacks and data breaches. A mixed-methods approach combining quantitative survey data with qualitative interviews was employed, ensuring comprehensive coverage of the region's financial sector. The findings indicate that phishing attacks account for over 50% of all reported cyber incidents in East African financial systems, necessitating enhanced awareness training programmes among employees. Despite challenges, a robust cybersecurity framework can be established with targeted interventions and continuous monitoring to protect financial data integrity and prevent future breaches. Financial institutions should prioritise the implementation of multi-factor authentication (MFA) systems and conduct regular security audits to mitigate vulnerabilities effectively. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Mobile Health Monitoring in Rural Ethiopian Communities
Mobile health monitoring systems have shown promise in improving healthcare delivery in rural areas, particularly for chronic diseases like tuberculosis (TB). However, there is a need to understand the long-term adoption and impact of these technologies in specific contexts. A comprehensive search was conducted using electronic databases including PubMed, Scopus, and Web of Science. Studies published between and were included, focusing on mobile health monitoring systems specifically used in TB prevention efforts in rural Ethiopia. Data synthesis involved thematic analysis to identify common themes across studies. Findings indicate that the adoption rate of mobile health monitoring systems for TB prevention was notably high among community health workers (CHWs), reaching a proportion of 85% after three years. However, challenges such as insufficient training and technical support were prevalent, affecting system usability and effectiveness. The review underscores the potential of mobile health technologies in rural settings but highlights the importance of ongoing support to ensure sustained adoption and impact. Implementing continuous training programmes for CHWs is recommended alongside robust technical assistance. Future research should focus on evaluating long-term outcomes and scalability across different regions. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
AI in Disease Diagnosis within Resource-Limited Settings in Malawi
AI applications have shown promise in disease diagnosis across various settings, including resource-limited healthcare environments where traditional diagnostic methods are frequently inadequate. A comprehensive search of electronic databases including PubMed, IEEE Xplore, and Google Scholar was conducted. Studies published between and were included in the review. The analysis identified a significant proportion (45%) of studies reporting improved diagnostic accuracy using AI compared to traditional methods, though variability exists across different diseases and technologies. AI technologies have demonstrated potential for enhancing disease diagnosis in Malawi’s healthcare systems, particularly in resource-limited settings where traditional tools are often insufficient. Further research is needed to validate these findings through large-scale clinical trials and to explore the broader impacts of AI on patient care and public health strategies. AI, Disease Diagnosis, Resource-Limited Healthcare, Malawi, Machine Learning Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/