ArticleInfectious Disease Modelling2022
Mathematical modelling of the progression of active tuberculosis: Insights from fluorography data.
Article in Infectious Disease Modelling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Opening Pandora's box: caveats with using toolbox-based approaches in mathematical modeling in biology.Frontiers in applied mathematics and statistics · 2024Article
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4 authors.
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Abstract
Little is known about the dynamics of the early stages of untreated active pulmonary tuberculosis: unknown are both the rates of progression and the model "scheme". The "parallel" scheme assumes that infectiousness of tuberculosis cases is effectively predefined at the onset of the disease, and the "serial" scheme considers all cases to be non-infectious at the onset, with some of them later becoming infectious. Our aim was to estimate the progression of the early stages of pulmonary tuberculosis using data from a present-day population. We used the routine notification data from Moscow, Russia, 2013-2018 that contained the results and time of the last fluorographic screening preceding the detection of tuberculosis cases. This provided time limits on the duration of untreated tuberculosis. Parameters of TB progression under both models were estimated. By the goodness of fit to the data, we could prefer neither the "parallel", nor the "serial" model, although the latter had a bit worse fit. On the other hand, the observed rise in the fraction of infectious tuberculosis cases with the time since the last screening was explained by the "serial" model in a more plausible way - as gradual progression of some cases to infectiousness. The "parallel" model explained it through less realistic quick removal of non-infectious cases and accumulation of the infectious ones. The results demonstrate the potential of using such detection data enriched with reassessments of the previous screenings.
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