Assessing the impact of Enhanced-Case-Finding on tuberculosis incidence and transmission in The Gambia using epidemiological and phylodynamic approaches
Gehre, F.; Oko, F.; Ofori-Anyinam, B.; Meehan, C. J.; Windels, E. M.; Joof, K.; Faal, T.; Mendy, F.; Jobarteh, T.; Gitteh, E.; Riley, A. J.; Sarr-Kuyateh, B.; Okoi, C.; Demba, E.; Del-Alorse, W.; Mlaga, K.; Sambou, B.; Kanuteh, F.; Lette, K.; Muhammad, A. K.; Agbla, S.; Mulders, W.; Donkor, S.; Jeffries, D.; Roca, A.; DAlessandro, U.; Antonio, M.; Adetifa, I.; de Jong, B. C.
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BackgroundMost tuberculosis (TB) cases in The Gambia are notified in the Greater Banjul Area (GBA). We conducted an Enhanced-Case-Finding (ECF) intervention in the GBA and determined its effect on TB case notifications and ongoing TB transmission. MethodsThis was a cluster randomized trial in which randomly assigned intervention areas of grouped settlements received three rounds of an ECF strategy consisting of sensitization followed by auramine microscopy, whereas people with TB in control areas continued to be identified through passive case finding. People with TB were recruited at the TB diagnostic and treatment centers serving both the intervention- and control areas. The primary outcome was TB case notification rate. To exclude that an increase in notified cases, followed by a decrease in notified cases, would hide the future impact of the intervention, we tested for changes in transmission dynamics using both genetic clustering and phylodynamic methods. Results3,047 people living with TB were recruited in the study, evenly split between intervention and control regions. No significant difference in TB case notification rates, transmission clustering or effective reproductive number was detected between intervention and control areas using either a case notification rate or phylodynamic approach. ConclusionAlthough we did not find evidence for decreased TB case notification nor TB transmission through the ECF strategy used, this approach is an examplar of how both classical epidemiology and genomic phylodynamics approaches can be integrated to better assess public health intervention outcomes.
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