title: Trends, seasonality and forecasts of pulmonary tuberculosis in Portugal.
abstract: METHODS
  Tuberculosis (TB) is a global public health concern. Surveillance programmes present invaluable epidemiological information regarding its temporal evolution, particularly for pulmonary tuberculosis (PTB), the most common form of TB and the one that presents the greatest challenge in public health.
  
  
  OBJECTIVE
  To characterise, model and predict monthly incidence rates for PTB in Portugal disaggregated by high/low-incidence areas, sex and age groups.
  
  
  METHODS
  PTB monthly incidence rates were estimated based on PTB cases diagnosed in 2000-2010, disaggregated by population and geographic characteristics. Seasonal-trend LOESS (STL) decomposition was employed to model trend and seasonality. Seasonal autoregressive integrated moving average (SARIMA) models were fit to characterise series behaviour and forecast PTB monthly incidence rates.
  
  
  RESULTS
  Overall, the time series showed a downward trend in and seasonality of PTB diagnosis, with a peak in March and a trough in December. The mean seasonal amplitude was consistently higher in high-incidence areas, in males and in adults aged 25-54 years. SARIMA models were found to adequately fit and forecast the time series, thus predicting trend and seasonal persistence.
  
  
  CONCLUSIONS
  STL and SARIMA findings concurred and were accurate. Endemic PTB seems to be slowly declining and case diagnosis is likely seasonal, which can be expected to persist if past conditions continue.
authors.affiliation: Faculty of Veterinary Medicine, University of Calgary, Production Animal Health, Calgary, Alberta, Canada.
authors.forename: A L
authors.initials: AL
authors.lastname: Bras
authors.affiliation: School of Science and Technology, University of Evora, Centro de Investigação em Matemática e Aplicações, Universidade de Évora, Evora, Portugal.
authors.forename: D
authors.initials: D
authors.lastname: Gomes
authors.affiliation: School of Science and Technology, University of Evora, Centro de Investigação em Matemática e Aplicações, Universidade de Évora, Evora, Portugal.
authors.forename: P A
authors.initials: PA
authors.lastname: Filipe
authors.affiliation: Faculty of Psychology and Education Sciences, University of Coimbra, Cognitive and Behavioural Center for Research and Intervention, Coimbra, Portugal.
authors.forename: B
authors.initials: B
authors.lastname: de Sousa
authors.affiliation: National School of Public Health, Nova University of Lisbon, Lisbon, Portugal.
authors.forename: C
authors.initials: C
authors.lastname: Nunes
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D002675:Child, Preschool; D005260:Female; D005544:Forecasting; D006801:Humans; D015994:Incidence; D007223:Infant; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011174:Portugal / Q000453:epidemiology; D012621:Seasons; D014397:Tuberculosis, Pulmonary / Q000175:diagnosis* / Q000453:epidemiology*; D055815:Young Adult