In various institutions, talent management can be seen as a response to changes affecting the workplace such as the industrial revolution, the rise of labour unions, globalisation and competitiveness. Health care institutions need to and are interested in managing talented people to ensure high quality care, long term competitiveness, sustainable prosperity and continuous development. This is to achieve the goal of health care which is, delivering safe, effective, efficient, timeous and equitable health care. The purpose of this article was to identify antecedents that influence effective talent management in public health institutions in Uganda. The research findings reveal that an enabling work environment, a stable working environment and career development highly influence effective talent management than organisational support and employee satisfaction. Even though job autonomy and personal value effectively influence talent management, management in public health institutions need to realise the importance of nurturing and monitoring job autonomy and acknowledge personal values to effectively enhance talent management.

Purpose The purpose of this study is to examine the relationship between entrepreneurial alertness, personal initiative and social entrepreneurial venture creation and to examine the mediating role of personal initiative in the relationship between entrepreneurial alertness and social entrepreneurial venture creation among social ventures in Uganda. Design/methodology/approach The study adopts a quantitative approach where hypotheses were statistically tested using structural equation modeling based on survey data (n = 243) from community-based organization owner-managers in Uganda. Findings Results show that both entrepreneurial alertness and social personal initiative are positively and significantly associated with social entrepreneurial venture creation. Results further indicate that personal initiative partially mediates the relationship between entrepreneurial alertness and social entrepreneurial venture creation. Originality/value To the authors’ knowledge, this study provides a shred of initial empirical evidence on the relationship between entrepreneurial alertness, entrepreneurial personal initiative and social entrepreneurial venture creation using evidence from Uganda, a developing country. Mostly, this study provides initial evidence of the mediating role of personal initiative in the relationship between entrepreneurial alertness and social entrepreneurial venture creation in an under-researched developing country – Uganda.

Background Malaria risk factors at household level are known to be complex, uncertain, stochastic, nonlinear, and multidimensional. The interplay among these factors, makes targeted interventions, and resource allocation for malaria control challenging. However, few studies have demonstrated malaria’s transmission complexity, control, and integrated modeling, with no available evidence on Uganda’s refugee settlements. Using the 2018–2019 Uganda’s Malaria Indicator Survey (UMIS) data, an alternative Bayesian belief network (BBN) modelling approach was used to analyse, predict, rank and illustrate the conceptual reasoning, and complex causal relationships among the risk factors for malaria infections among children under-five in refugee settlements of Uganda. Methods In the UMIS, household level information was obtained using standardized questionnaires, and a total of 675 children under 5 years were tested for malaria. From the dataset, we created a casefile containing malaria test results, demographic, social-economic and environmental information. The casefile was divided into a training (80%, n = 540) and testing (20%, n = 135) datasets. The training dataset was used to develop the BBN model following well established guidelines. The testing dataset was used to evaluate model performance. Results Model accuracy was 91.11% with an area under the receiver-operating characteristic curve of 0.95. The model's spherical payoff was 0.91, with the logarithmic, and quadratic losses of 0.36, and 0.16 respectively, indicating a strong predictive, and classification ability of the model. The probability of refugee children testing positive, and negative for malaria was 48.1% and 51.9% respectively. The top ranked malaria risk factors based on the sensitivity analysis included: (1) age of child; (2)roof materials (i.e., thatch roofs); (3)wall materials (i.e., poles with mud and thatch walls); (4)whether children sleep under insecticide-treated nets; 5)type of toilet facility used (i.e., no toilet facility, &pit latrines with slabs); (6)walk time distance to water sources, (between 0–10minutes); (7)drinking water sources (i.e., open water sources, and piped water on premises). Conclusion Ranking, rather than the statistical significance of the malaria risk factors, is crucial as an approach to applied research, as it helps stakeholders determine how to allocate resources for targeted malaria interventions within the constraints of limited funding in the refugee settlements.

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