Portugal remains the country with the highest tuberculosis (TB) incidence in Western Europe. To identify longitudinal trends in TB incidence in Portugal from 2002 to 2012 and investigate the longitudinal effect of sociodemographic and health-related predictors among the resident population on the TB incidence rate. We used data from the National Tuberculosis Surveillance System and other national institutions. K-means longitudinal clustering algorithm was performed on TB incidence time profiles from districts of Portugal. Three longitudinal profiles for the TB incidence rate of Portugal were identified. In all of them, TB incidence decreased over time. Among all studied sociodemographic and health-related predictors, human immunodeficiency virus (HIV) notification rate and unemployment were shown to have (positive) significant effects on TB incidence. In particular, the greatest effects were found for the HIV notification rate. Our study supports the view that combined TB-HIV strategies and the improvement of social determinants can contribute to decreases in TB incidence.

The Human Immunodeficiency Virus can evolve to severe illness having a major impact on socio-demographic and economic features of the affected countries. Most countries rely on surveillance systems to monitor the status of the epidemic which are based on cases notification by physicians. It can take several months until the diagnosed cases are notified and there are even cases that are not reported at all. The purpose of this paper is to adjust the Portuguese notification data to these main possible biasing problems. For the reporting delay we will use the traditional conditional likelihood estimation for count data assuming a Poisson distribution. For the cases that are not reported at all, we will use a mixture of Poisson distributions, based on natural conjugate prior distributions, and estimate the unknown parameters through maximum likelihood. The Poisson model suggests that approximately 80% of the Portuguese AIDS cases were reported within one year after the diagnosis and that the majority of cases were notified in the first three months. The BB/NBD model suggests that the probability of a new AIDS case being notified gets higher once a large amount of AIDS cases has been notified.