Time series analysis of the number of tuberculosis cases in tangshan area

ABSTRACT

Objective The time series analysis model was used to predict and warn the number of tuberculosis (TB) cases in Tangshan area in different time, which provided a reference for scientific prevention and control of TB epidemic in this area. Methods The number of monthly TB cases in Tangshan from January 2005 to December 2021 was collected, and the seasonal autoregressive integrated moving average (SARIMA) model was used to predict the number of TB cases in 2022. Meanwhile, the difference between the predicted number of TB cases and the actual observed number of TB cases in the area was explored during the period of COVID-19 in 2020 by this model and rank test. Results From January 2005 to December 2021, the ARIMA (1, 1, 0) (1, 1, 2)s model was fitted well with the actual observed number of TB cases (AR =-0. 530, ARs =-0.967, MAs = 0. 861, P0. 05;Stationary R2 = 0. 558, R2 = 0. 634, BIC = 7. 887;Ljung-Box Q = 25. 605, P 0. 05), with peaks TB incidence in March, April, and December every year, and the predicted number of TB cases in 2020 was 1 800. From 2005 to 2019, ARIMA (1, 1, 0) (0, 1, 2)s model was fitted well with the actual number of cases (AR =-0. 544, ARs =-0. 840, MAs = 0. 697, P 0. 05;Stationary R2 = 0. 582, R2 = 0. 621, BIC = 7. 939;Ljung-Box Q = 24. 211, P 0. 05), with peaks TB incidence in March, April, and December every year, and the predicted number of TB cases in 2020 was 1 985. The observed and predicted number of TB cases from January 2020 to May 2020 were statistically significant (Z =-2. 023, P0. 05). Conclusion It is necessary to increase the intensity of early warning of TB in March, April, and December every year in Tangshan to prevent the epidemic of TB. At the same time, the coordination of the staff of TB prevention institutions and the emergency system should be strengthened during the epidemic situation of COVID-19, and effectively ensure the registration and medical treatment of TB patients during the epidemic situation. © 2023, Editorial Department of Medical Pest Control. All rights reserved.