Know your epidemic : disease surveillance for targeting efforts to end TB
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Know your epidemic : disease surveillance for targeting efforts to end TB

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      Strong laboratory networks, robust treatment programs, and tuberculosis (TB) disease surveillance systems form the core of effective national TB programs. At the local, national, and global levels, surveillance systems – the collection, analysis, and interpretation of public health-related data – are critical to monitor progress toward elimination of any disease, including TB. Disease surveillance is an indispensable source of information that can improve the effectiveness of TB prevention and control programs when data are used to target the most effective interventions to the right populations in the right places. Surveillance can also be used for monitoring the impact of those interventions.

      Strong TB disease surveillance helps identify gaps in health systems, and by doing so, saves lives. For example, disease surveillance can identify if there is a substantial gap between people who are diagnosed with TB and those who are started on treatment. Such information can enable outreach to individual patients, but also trigger an assessment of the linkage to care between diagnosis and treatment and change policies or practices that can contribute to this gap.

      However, surveillance systems can be difficult to implement effectively, as there are challenges to ensuring accurate, timely, and complete information is captured and can be used at all levels of the health system. To compare data about TB over time and from country to country, there must be a common methodology for the indicators and the methods of collection and reporting. In addition, as new evidence, tools, and strategies emerge to address TB, global strategies continue to evolve. Disease surveillance systems and the data they collect must shift to capture such information; such global shifts in disease surveillance systems take time. Even when good surveillance systems are in place, data are not always used to guide program priorities and interventions if those accessing the data are not trained on how to access, analyze, and interpret the data.


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