A modelling framework to support the selection and implementation of new TB diagnostic tools

Lin, H.H., Langley, I., Mwenda, R., Doulla, B., Egwaga, S., Millington, K.A., Mann, G.H., Murray, M., Squire, S.B. and Cohen, T., 2011. A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools. The International journal of tuberculosis and lung disease, 15(8), pp.996-1004.

· Different diagnostic strategies may be more effective in regions with varying levels of HIV-associated or drug-resistant TB and differing healthcare infrastructure.

· Tests that don't require multiple visits can reduce patient costs and minimize follow-up losses.

· Early detection of TB may lead to better treatment outcomes for patients.

· New diagnostic tools might reduce delays in the lab but could create new bottlenecks in other parts of the healthcare system.

· Changes in diagnostic patterns can shift demand in other areas of the health system.

· While accurate diagnostic tools are important, they alone won't guarantee better TB control.

· The impact of these tools depends on whether they speed up the administration of effective treatment.

· Evaluating the epidemiological impact of new tools is challenging due to TB's slow progression.

· Operational and dynamic epidemiological models can help assess the overall effects of different diagnostic strategies.

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