[Analysis and prediction of thyroid cancer morbidity and mortality trends in China].

Objective: To analyze the morbidity and mortality trends of thyroid cancer in China from 1990 to 2019, explore the causes of the trends, and predict morbidity and mortality in the future. Methods: The morbidity and mortality data of thyroid cancer in China from 1990 to 2019 were collected from the 2019 Global Burden of Disease database. The Joinpoint regression model was used to describe the change trends. Based on the morbidity and mortality data from 2012 to 2019, a grey model GM (1,1) was constructed to predict the trends in the next ten years. The model was tested by the posterior error method and residual test method. Results: In all populations, men and women, the AAPC values of the crude morbidity rates were 4.15% (95%CI: 3.86%-4.44%, P<0.001), 5.98% (95%CI: 5.65%-6.31%, P<0.001) and 3.23% (95%CI: 2.94%-3.53%, P<0.001) respectively, the AAPC values of age-standardized morbidity rates were 2.47% (95%CI: 2.12%-2.83%, P<0.001), 3.98% (95%CI: 3.68%-4.29%, P<0.001), 1.65% (95%CI: 1.38%-1.93%, P<0.001), the AAPC values of crude mortality rates were 2.09% (95%CI: 1.92%-2.25%, P<0.001), 3.68% (95%CI: 3.45%-3.90%, P<0.001), 0.60% (95%CI: 0.50%-0.71%, P<0.001). The age-standardized mortality rates in men showed a fluctuating trend of first decrease (1990-1994), then increase (1994-2012), and then decrease (2012-2019) (AAPC=1.35%, 95%CI: 1.16%-1.53%, P<0.001). The age-standardized mortality rate in women continuously decreased (AAPC=-1.70%, 95%CI: -1.82%- -1.58%, P<0.001). The GM (1,1) models can be used for medium and long-term predictions. The results of the residual test show that the average relative error values of all models are less than 10.00%, the prediction accuracy values are more than 80.00%, and the prediction effects are good. The results of the posterior error method show that all the prediction results are good except the qualified prediction of the age-standardized morbidity rate in men. In 2029, the crude morbidity rates would increase to 3.57/100 000, 2.78/100 000, and 4.40/100 000, respectively, and the age-standardized incidence rates would increase to 2.38/100 000, 1.89/100 000, and 2.88/100 000, respectively, the crude mortality rates would increase to 0.57/100 000, 0.62/100 000 and 0.53/100 000, and the age-standardized mortality rates would decrease to 0.33/100 000, 0.42/100 000 and 0.27/100 000 in all population, men and women in China. Conclusions: The overall, gender- specific age-standardized mortality rates showed downward trends in the last decade or so, and the prediction results showed that it might further decline. However, the crude morbidity rates, age-standardized and crude mortality rates have been on the rise, and the population aging is becoming increasingly serious in China, which requires close attention and targeted prevention and control measures.

[Application of ARIMA model in predicting the incidence of tuberculosis in China from 2018 to 2019].

Objective: Autoregressive integrated moving average (ARIMA) model was used to predict the incidence of tuberculosis in China from 2018 to 2019, providing references for the prevention and control of pulmonary tuberculosis. Methods: The monthly incidence data of tuberculosis in China were collected from January 2005 to December 2017. R 3.4.4 software was used to establish the ARIMA model, based on the monthly incidence data of tuberculosis from January 2005 to June 2017. Both predicted and actual data from July to December 2017 were compared to verify the effectiveness of this model, and the number of tuberculosis cases in 2018-2019 also predicted. Results: From 2005 to 2017, a total of 13 022 675 cases of tuberculosis were reported, the number of pulmonary tuberculosis patients in 2017 was 33.68% lower than that in 2005, and the seasonal character was obvious, with the incidence in winter and spring was higher than that in other seasons. According to the incidence data from 2005 to 2017, we established the model of ARIMA (0,1,2)(0,1,0)(12). The relative error between the predicted and actual values of July to December 2017 fitted by the model ranged from 1.67% to 6.80%, and the predicted number of patients in 2018 and 2019 were 789 509 and 760 165 respectively. Conclusion: The ARIMA (0, 1, 2)(0, 1, 0)(12) model well predicted the incidence of tuberculosis, thus can be used for short-term prediction and dynamic analysis of tuberculosis in China, with good application value.