Towards a Big Data Framework for the Prevention and Control of HIV/AIDS, TB and Silicosis in the Mining Industry

This paper proposes a big data integrated framework to assist with prevention and control of HIV/AIDS, TB and silicosis (HATS) in the mining industry. The linkage between HATS presents a major challenge to the mining industry globally. When the immune system is compromised by HIV/AIDS and silicosis, it makes it easier for tuberculosis to infect the body. In addition, the silica dust which affects the lungs may also cause silicosis and tuberculosis. The objective of this paper is to posit a big data integrated framework to assist in the prevention and control of HATS in the mining industry. Literature was reviewed in order to build a conceptual framework. Although this study is not the first to apply big data in healthcare, to the researcher's knowledge, it is the first to apply big data in understanding the linkage between HATS in the mining industry. The literature review indicates only a few studies using big data in healthcare with no research found on big data and HATS. It therefore makes a contribution to existing body of literature on the control of HATS. The proposed big data framework has the potential of addressing the needs of predictive epidemiology which is important in forecasting and disease control in the mining industry. The paper therefore lays a foundation for the use of viable systems model and big data to address the challenges of HATS in the mining industry. As part of future work, the framework will be validated using sequential explanatory mixed methods case study approach in mining organizations.