Simulation study of HIV temporal patterns using Bayesian methodology.
Rocha, Diana; Scotto, Manuel; Pinto, Carla; Tavares, João Nuno ; Gouveia, Sónia
In: Argiento R., Durante D., Wade S. (eds) Bayesian Statistics and New Generations. BAYSM 2018. Springer Proceedings in Mathematics & Statistics, Springer, Cham, 296 (2019), 145-154
https://link.springer.com/chapter/10.1007%2F978-3-030-30611-3_15
Viral load values and CD4+ T cells count are markers currently evaluated in the clinical follow-up of HIV/AIDS patients. In this context, it is relevant to develop methods that provide a more complete temporal description of these markers, e.g. in between clinical appointments. To this end, we combine a mathematical model and a Bayesian methodology to estimate trajectories from a set of observed values. Furthermore, we construct a variation band containing the most central trajectories for one patient, by exploring the range of values in the a posteriori distributions. The methods are illustrated with simulated data.
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