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A larger difference arises when we consider the probability of progressing from latency to active disease in each of the models.
In a model with exponential lifespans, the probability of progressing from latency to active disease is up to twice as likely (Fig. 2A).
For children under five years of age from medium/high transmission areas, all but 4 panellists estimated that the probability of progressing to severe malaria was 30% or less; however, one panellist estimated the risk to be 80%.
With constant lifetimes, the number of recent infections is greater due to the larger pool of susceptible individuals and the number of cases due to reactivation or reinfection is also greater due to the increased probability of progressing from latency to disease.
Cells with damaged DNA frequently arrest, which reduces the probability of progressing to malignancy.
A large majority of nevi have oncogenic BRAF mutations, but have a low probability of progressing to melanoma.
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We assumed that preexposure vaccines could reduce the risk for infection in the uninfected (mechanism 1), allow infection but reduce the probability of rapidly progressing to disease (mechanism 2), and allow infection but reduce the rate of progression of latently infections to disease (mechanism 3).
Recently, we have also proposed a formally rigorous incidence paradigm [8], which accounts for assay non-progression using fewer assumptions than are made by McDougal et al. The parameters that emerge naturally in our estimator are a mean window period and a probability of not progressing on the assay (which can also be expressed as a long-term specificity).
The Kalman filter model performs at higher specificity and sensitivities for significant disease progression classification due to the greater difference in mean fitted values (i.e. average estimated probability of progression) between progressing and nonprogressing instances.
The probabilities of progressing through the states of anthrax illness were taken from a comprehensive review of anthrax illness [ 8].
In contrast, models of infection are based on population-level probabilities of progressing from exposure to infected, infectious, or immune/susceptible states.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com