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• Research Papers

  Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators

  Malnutrition is a leading cause of morbidity and mortality for children under-5 globally. Low- and middle-income countries, such as Kenya, bear the greatest burden of malnutrition. The Kenyan government has been collecting clinical indicators, including on malnutrition, using District Health Information Software-2 (DHIS2) for over a decade. We aim to address the existing gap in decision-makers’ ability to develop and utilize malnutrition forecasting capabilities for timely interventions. Read More >>

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• Research Papers

  Fintechs’ Future in Kenya: Does Social Influence Matter?

  This study explores how social influence affects the continued use of Fintech mobile money lending apps in Kenya. Analyzing data from 342 users through structural equation modeling, it finds that social influence significantly impacts perceived security, satisfaction, and ongoing usage. It also enhances the positive effects of perceived security and usefulness on satisfaction and continued use. Ultimately, users are likely to keep using these apps if they find them secure, useful, and satisfying.   Read Mor

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• Research Papers

  Analysing 3429 digital supervisory interactions between Community Health Workers in Uganda and Kenya: the development, testing and validation of an open access predictive machine learning web app

  This study explored the use of artificial intelligence to support supervision of Community Health Workers (CHWs) through a machine learning web application called CHW supervisor, which was designed to automatically code instant messages exchanged between CHWs and their supervisors. Developed using 2,187 messages from Uganda and validated on 1,242 messages from Kenya, the app’s performance was compared to human coders. While human coders showed high agreement (88–95%, Cohen’s kappa 0.7–0.91), the app achieved moderate accuracy (73–78%, kappa 0.51–0.56). The findings highlight that

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• Research Papers

  Perceptions of eLearning Innovative Training Approaches among Nurses, Midwives, and Tutors: A Descriptive Cross-Sectional Study from Nurse-Midwifery Colleges in Tanzania

  Africa carries 24% of the global disease burden but has only 3% of the world’s health workforce, with a critical shortage among frontline workers like nurses and midwives. This imbalance contributed to the continent’s failure to meet the Millennium Development Goals by 2015. eLearning has emerged as a flexible and scalable solution for training in-service health workers. This study investigates how nurses, midwives, and tutors in Tanzania perceive eLearning as an innovative training method.   Read More >>><

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