Figure 1.

Individual-level model framework of progression and recovery in tuberculosis. A, Each patient’s disease is modeled through time as a sequence of transitions between disease progression and disease recovery. B, A patient may take her rate of progression and her rate of recovery from a range of plausible rates, represented by probability densities across possible values of progression (black density) and recovery (gray density). The shape of these densities is determined by the specific value of the rate mode parameters. Within each cohort, a value from each of these densities (depicted by vertical lines in the plot) is stochastically sampled to characterize each patient’s infection. C, In the case of an arbitrary simulated Patient A, disease development begins in the progression phase, during which growth is characterized by the patient’s sampled rate of progression. At any time (with a given weekly probability), the infection may transition to recovery, during which growth/decay is characterized by the patient’s sampled rate of recovery. Similarly, at any subsequent time, the infection may transition from recovery to the progression phase, with the same rate of progression as sampled previously. The concomitant changes in Patient A’s disease burden are represented in Figure 2.