European Journal of Epidemiology

, Volume 16, Issue 5, pp 483–488 | Cite as

A statistical analysis of the seasonality in pulmonary tuberculosis

  • M. Ríos
  • J.M. García
  • J.A. Sánchez
  • D. Pérez


The present study examines whether pulmonary tuberculosis (PTB) has an annual seasonal pattern. A mathematical model is also obtained to forecast the pattern of incidence. The data for the study are the cases of PTB reported throughout Spain, published in the Epidemiology Bulletin by the Carlos III Health Center of the Spanish Ministry of Health in a 26-year period, 1971–1996. The analytical results show that the low rates in tuberculosis notifications over the period 1971–1981 have changed, halting in 1982 and reversing with high incidence from 1983 onwards. An annual seasonal pattern was also shown with higher incidence during summer and autumn. With the mathematical model we predicted the disease behaviour in 1997 and the results were compared to the reported cases. In Spain, as in several industrialised countries, the reason for this recent increase in the number of reported cases is, mainly, the human immunodeficiency virus (HIV) infection. The seasonal trend, with higher incidence in winter, can be attributed to the increase in indoor activities, much more common than in a warm climate. The tubercle bacilli expelled from infected persons in a room with closed windows may remain infectious for a long time, increasing the risk of exposure of healthy persons to the bacilli. As the preclinical period, from exposure to clinical onset, may be of several weeks, the high incidence in spring would be explained. Moreover, in winter and spring the infections of viral aetiology, like flu, are more frequent and cause immunological deficiency which is another reason for the seasonal trend observed. An incidence greater than that foreseen by the mathematical model would express a failure in epidemiologic surveillance, and thus the results of this study may be used to assess a quality of the preventive measures.

Epidemiology Pulmonary tuberculosis (PTB) Seasonality Time series Tuberculosis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Raviglione MC, Sudre P, Rieder HL, Spinaci S, Kochi A. Secular trends of tuberculosis in western Europe. Bull WHO 1993; 71: 297-306.Google Scholar
  2. 2.
    Rieder HL. Misbehaviour of a dying epidemic: A call for less speculation and better surveillance. Tubercle and Lung Disease 1992; 73: 181-183.Google Scholar
  3. 3.
    Narain JP, Raviglione MC, Kochi A. HIV-associated tuberculosis in developing countries: Epidemiology and strategies for prevention. Tubercle and Lung Disease 1992; 73: 311-321.Google Scholar
  4. 4.
    Snider DE Jr, Roper WI. The new tuberculosis. New Eng J Med 1992; 326: 703-705.Google Scholar
  5. 5.
    Brudney K, Dobkins J. Resurgent tuberculosis in New York City. Human immunodeficiency virus, homeless, and the decline of tuberculosis control program. Am Rev Resp Disease 1991; 144: 745-749.Google Scholar
  6. 6.
    Raviglione MC, Snider DE, Kochi A. Global epidemiology of tuberculosis. Morbidity and mortality of a worldwide epidemic. JAMA 1995; 273: 220-226.Google Scholar
  7. 7.
    Ministerio de Sanidad y Consumo. Informe epidemiológico 1992. Boletín Epidemiolóco y Microbiológico 1993; 1(Suppl. 1).Google Scholar
  8. 8.
    March P. Situación actual de la tuberculosis en españa. Med Clin (Barc) 1991; 97: 463-472.Google Scholar
  9. 9.
    Box G, Jenkins G. Time series analysis forecasting and control. San Francisco: Holden Day, 1976.Google Scholar
  10. 10.
    Helfenstein U. Box-Jenkins modelling of some viral infections diseases. Statist In Med 1986; 5: 37-47.Google Scholar
  11. 11.
    Zaidi A, Schnell D, Reynolds G. Time series analysis of syphilis surveillance data. Statist In Med 1989; 8: 353-362.Google Scholar
  12. 12.
    Schnell D, Zaidi A, Reynolds G. A time series analysis of gonorrhoea surveillance data. Statist In Med 1989; 8: 343-352.Google Scholar
  13. 13.
    Ríos M, García JM, Cubedo M, Pérez D. Análisis de Series temporales en la epidemiología de la fiebre ti-foidea en españa. Med Clín (Barc) 1996; 106: 686-689.Google Scholar
  14. 14.
    Fuller WA. Introduction to statistical time series. New York: John Wiley, 1976.Google Scholar
  15. 15.
    Diggle PJ. Time series, a biostatistical introduction. Oxford: Clarendon Press, 1990.Google Scholar
  16. 16.
    Cryer JD. Time series analysis. Boston: Duxbury Press, 1985.Google Scholar
  17. 17.
    Catalano R, Serxner S. Time series designs of potential interest to epidemiologist. Am J Epidemiol 1987; 126: 724-731.Google Scholar
  18. 18.
    Crabtree B, Ray S, Schmidt P, O'Connor P, Schmidt D. The individual over time: Time series applications in health care research. J Clin Epidemiol 1990; 43: 241-260.Google Scholar
  19. 19.
    Ministerio de Sanidad y Consumo. Bol Epidemiol Semanal, Vol 6. 1998; 1: 3-4.Google Scholar
  20. 20.
    Mateo S, Cano R, Garcia C. Changing epidemiology of meningococcal disease in Spain 1989-1997. Eurosur veillance 1997; 2: 71-74.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • M. Ríos
    • 1
  • J.M. García
    • 2
  • J.A. Sánchez
    • 1
  • D. Pérez
    • 2
  1. 1.Statistical DepartmentUniversity of BarcelonaSpain
  2. 2.Faculty of MedicineUniversity of MurciaSpain

Personalised recommendations