School of Public Health (Public-Health) Collections

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    Assessment of health risks associated with microbial contamination of springs among slum residents in Kinawataka, Nakawa Division, Kampala, Uganda
    (Makerere University, 2025) Mwanja, Herman
    Springs, the most utilised source of water in informal settlements, are at high risk of contamination from poor sanitation and waste disposal, threatening residents' health. However, there is limited evidence quantifying health risks from contaminated spring water in Uganda. This study aimed to assess human health risks associated with the microbiological contamination of springs in the Kinawataka slum in Kampala. A cross-sectional study design was employed involving quantitative data collection through sanitary inspections, water quality analyses and the quantitative microbiological risk assessment (QMRA) across 7 springs and 287 households. Water samples from the households and springs were collected and analysed from the National Water Quality Reference Laboratory. Microsoft Excel and Stata 14 statistical software were utilised for data management and analysis. The significance of the associations employed appropriate tests such as Fisher’s Exact and the Wilcoxon rank-sum tests. Sanitary conditions around the springs were poor, with six of the seven classified as high-risk due to inadequate fencing and proximity to pollution sources. The microbial water quality analyses indicated that five of the seven springs posed a risk due to contamination with E. coli. A high proportion, 84.32% (242/287) of the respondents utilised spring water for drinking. Despite 62.72% (180/287) of the residents treating their water, 71.43% (205/287) of drinking water samples collected from households were contaminated with Escherichia coli. A daily infection risk of 0.148, translating to a daily risk of illness of 0.037 and an annual risk of infection approximating 1.00 (0.993) were estimated from the QMRA, indicating a high risk of waterborne diseases among the residents of Kinawataka slum. This study highlighted that contaminated water sources, particularly in the Kinawataka slum, pose a significant public health risk. This calls for targeted interventions to enhance water safety in these communities. Keywords: Microbial contamination, Slum residents, Kinawataka, Nakawa Division
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    Prevalence and factors associated with timely initiation of breastfeeding among mothers who deliver by cesarean section at Kawempe National Referral Hospital, Uganda
    (Makerere University, 2025) Nanyombi, Grace
    Breastfeeding is essential in reducing infant mortality and promoting growth and development. The World Health Organization recommends the timely initiation of breastfeeding to prevent neonatal mortality and provide babies with colostrum. Despite its benefits, many mothers who deliver by cesarean section do not timely breastfeed due to postoperative challenges and experiences, inadequate health care support, and socio-economic factors. The study aimed to determine the prevalence and factors associated with the timely initiation of breastfeeding among mothers who delivered by cesarean section at Kawempe Hospital in Uganda. A cross-sectional convergent mixed methods study design was employed. A total of 385 postnatal mothers who delivered by cesarean section were consecutively selected and interviewed using a structured questionnaire and review of medical records while seven in-depth interviews and four Key Informant interviews were purposively conducted. Data entry and analysis was done using STATA v14. Descriptive statistics was used to summarize the data. The modified Poisson model was used to determine the factors associated with the timely initiation of breastfeeding using the adjusted prevalence ratios at 95% confidence interval. Qualitative data was analyzed using Atlas.ti version 9. The prevalence of timely initiation of breastfeeding among mothers who delivered by cesarean section was 33.5%. Factors significantly associated with the timely initiation of breastfeeding included maternal knowledge, prenatal counselling, birthweight, emergency cesarean section, baby-mother separation, and health worker support. Postoperative pain, fear of breast milk inadequacy, prelacteal feeding negatively influenced maternal attitude to timely initiate breastfeeding. Timely initiation of breastfeeding remains low among mothers who deliver by cesarean section at Kawempe hospital. This was attributed to emergency cesarean sections, mother-baby separation, lack of prenatal counselling, limited maternal knowledge, and inadequate health worker support. Therefore, integrating breastfeeding messages in prenatal and antenatal health education, adequate health worker support and re-enforcing the Baby-Friendly Health Initiatives that encourage skin -to-skin contact and rooming-in may improve timely initiation of breastfeeding among mothers who deliver by cesarean section.
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    Incidence and factors associated with tuberculosis disease among people living with HIV who completed tuberculosis preventive treatment: a retrospective comparative cohort study at Baylor-Uganda HIV Clinic
    (Makerere University, 2025) Amuge, Pauline Mary
    The life-time risk of tuberculosis disease (TB) is higher among people living with HIV (PLHIV) compared to the general population. This study aimed to determine the incidence and factors associated with TB disease among PLHIV after completion of at least one course of TB preventive treatment (TPT). This was a retrospective comparative cohort study among PLHIV of all ages, who initiated and completed TPT, in comparison with PLHIV who did not receive TPT at Baylor-Uganda HIV clinic for the period Jan 2016 to Dec 2021. The incidence of TB disease was reported as the number of new TB cases per 1000person years of follow-up. A multivariable Poisson regression model was used to assess for significant factors associated with TB disease after completion of TPT, adjusting for potential confounders. Of the 9505 PLHIV in care, 6014 (79.2%) initiated and completed TPT, and 1907 (20.0%) did not initiate TPT. Majority of PLHIV were female (61%). The TB incidence among PLHIV who completed TPT reduced over the study period, from 4.34 in 2016 to 1.71 TB cases per 1000person years in 2020, and increased slightly in 2021. Among PLHIV who completed TPT, unsuppressed viral load (≥1000 copies/mL) significantly increased TB risk (aIRR: 6.19; 95% CI: 2.80–13.69, p<0.001). The overall median survival time to TB disease after completing TPT PLHIV was 2.5 years (IQR: 2.3–2.8 years). The TB incidence is low among PLHIV who complete TPT compared to PLHIV who do not receive TPT. After completing TPT, HIV viral non-suppression increases risk of TB disease by six times. Therefore, TB screening and treatment adherence support should continue after completing TPT. The risk of TB disease after receiving TPT increases after 2.5 years. This calls for research on the need of repeat TPT doses in high-risk groups.
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    Food security and associated factors among urban refugee households: A case study of refugees in Makindye Division, Kampala-Uganda
    (Makerere University, 2025) Otim, Bernard
    Food security is one of the most important foundations of not only health but sustainable development in its entirety. However, currently, the world has about 828 million people who are not certain of whether they will eat the next day and almost a million people are chronically food insecure at any one time. Among those affected are refugees, who currently number at over 43.7 million globally, with their number of expected to escalate over the years. Of concern, refugees are among the most food insecure persons in the world, and in Uganda out of the 1.8 million, the United Nations High Commissioner for Refugees noted that 44% of them had borderline food consumption. In addition, refugees in Uganda, including urban ones post more cases of child acute malnutrition than host communities, despite the reception of food and cash aid. The purpose of this study was to assess the factors associated with food security among refugee households in Makindye division, in Kampala, Uganda and its influence on the nutritional status of children under five years. An explanatory sequential mixed method design was used to study refugee household heads in Makindye division. Parishes were purposively sampled, and systematic random sampling used to conduct a household survey, following which the household head were purposively sampled and engaged in structured and in-depth interviews. Data was captured using structured questionnaires and in-depth interview guides, with quantitative data analyzed using a log-binomial model, and qualitative data, thematically. The proportion of selected refugee households in Makindye division that are food secure is 90% (n = 334), with 74.5% of those being highly food secure. Female-headed household, and those with three to four members, were more likely to be food secure. Household head education to primary level, household head being employed, inability to speak the local language, local integration, being in a host community that can speak the local language as refugees reduced odds of food security. However, easy access to transport means in the community, increased food security odds. Children in food secure households had 86% less odds of being malnourished. The prevalence of food security among urban refugees in Makindye division is high; 9 in every 10 of them have high availability and access to food, which leaves only 1 in every 10 that are food insecure. However, while that level of food security is laudable, about three quarters of those that are food secure are truly secure (high security), which implies that 25% of the secure households are at a risk of slumping in to insecurity. Both intrahousehold and societal characteristics influence food security among those urban refugee households, almost in equal measure, and food security is significantly associated with child malnutrition in those households.
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    Development of a predictive model for weekly severe pneumonia cases among children under 5 years of age in Kampala using machine learning and ARIMA models
    (Makerere University, 2025) Nebyeye, Gift
    Background: Pneumonia remains a significant public health concern, particularly among children under five in Kampala. Predicting severe pneumonia cases using climate and environmental factors can enhance early interventions and resource allocation. Objective: This study aimed to develop a predictive model for weekly severe pneumonia cases among children under five years old in Kampala, Uganda, utilizing machine learning approaches (Random Forest and extreme gradient boosting-XGBoost) and statistical modeling (Auto-Regressive Integrated Moving Average Exogenous -ARIMAX). Methods: A time series dataset incorporating severe pneumonia cases and climate variables such as temperature, rainfall, and humidity was used. The ARIMAX model was initially developed to capture temporal dependencies, while machine learning models (Random Forest and XGBoost) were applied for further predictive analysis. Model evaluation was performed using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Squared Error (MSE), with RMSE being the primary metric for model selection. The best-performing model was deployed as a web-based application using Flask for real-time predictions. Results: The XGBoost model achieved the lowest RMSE of 85.2 cases, indicating the highest predictive accuracy, followed by the Random Forest model (RMSE = 92.7), while the ARIMAX model recorded an RMSE of 105.4. An ensemble combining XGBoost and ARIMAX further improved performance, achieving an RMSE of 80.3 cases. From the statistical modeling perspective, ARIMAX analysis revealed that climatic factors such as high humidity and rainfall significantly influenced weekly severe pneumonia cases (p < 0.05). These findings demonstrate that integrating environmental data enhances disease forecasting accuracy and provides critical insights for early public health interventions. Conclusion: This study demonstrates the potential of machine learning in forecasting severe weekly pneumonia cases based on climate variables as well as ARIMAX models that effectively capture temporal patterns, highlighting key climatic drivers. The deployment of a Flask-based web application ensures accessibility for healthcare professionals, allowing real-time predictions for better planning and response. Future research should integrate additional air quality factors and explore deep learning techniques for improved prediction accuracy.