Use of big data on the social determinants of TB to find the “missing millions”

The WHO and the United Nations Sustainable Development Goals (SDGs) aim to end TB disease by 2030, highlighting the need for active case-finding as part of an integrated approach to finding the ‘missing millions’. The data sources that are typically used to identify people with TB (e.g., survey data from demographic and health surveys) are limited in their capacity to identify areas of high risk, and therefore in their ability to have precisely targeted interventions. Understanding the social determinants of TB through the use of new data sources, including ‘big data’ (characterised by high volume, velocity and variety), could help to reveal uncounted vulnerable populations and allow better targeted TB interventions.4 For example, better targeting could enhance the accuracy and yield of active casefinding strategies, help identify communities where standard TB health service delivery is of low quality, educate people about TB and reduce stigma. It could also inform efforts for TB prevention (e.g. the provision of TB preventive therapy), or the delivery of holistic support packages with broader health and socio-economic benefits.

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