巴西的结核病发病率:2001 年至 2021 年的时间序列分析和 2030 年前的预测。

Marcus Tolentino Silva, Taís Freire Galvão
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引用次数: 0

摘要

目的评估 2001 年至 2022 年期间巴西的结核病发病率,并对 2030 年之前的每月发病率进行预测:这是一项时间序列研究,基于应报告疾病信息系统的每月结核病记录和巴西人口的官方预测。使用分段线性回归对 2001 年至 2022 年的结核病月发病率进行评估,以确定趋势断点。使用季节性自回归综合移动平均数(Sarima)预测了 2023 年至 2030 年(实现可持续发展目标(SDGs)的最后期限)的月发病率:结果:2001 年 1 月至 2014 年 12 月期间,发病率有所下降(4.60 例-月/10 万居民降至 3.19 例-月/10 万居民;β=-0.005;p 结论:肺结核发病率呈下降趋势:肺结核病例的下降趋势从 2015 年起出现逆转,当时正值经济危机时期,而且还受到大流行病的影响,记录有所减少。萨里玛模型可作为流行病监测的有用预测工具。根据可持续发展目标,需要加大对预防和控制的投资,以减少结核病的发生。
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Tuberculosis incidence in Brazil: time series analysis between 2001 and 2021 and projection until 2030.

Objective: To assess the incidence of tuberculosis in Brazil between 2001 and 2022 and estimate the monthly incidence forecast until 2030.

Methods: This is a time-series study based on monthly tuberculosis records from the Notifiable Diseases Information System and official projections of the Brazilian population. The monthly incidence of tuberculosis from 2001 to 2022 was evaluated using segmented linear regression to identify trend breaks. Seasonal autoregressive integrated moving average (Sarima) was used to predict the monthly incidence from 2023 to 2030, deadline for achieving the sustainable development goals (SDGs).

Results: There was a decrease in incidence between January/2001 and December/2014 (4.60 to 3.19 cases-month/100,000 inhabitants; β=-0.005; p<0.001), followed by an increase between January/2015 and March /2020 (β=0.013; p<0.001). There was a sharp drop in cases in April/2020, with the onset of the pandemic, and acceleration of the increase in cases since then (β=0.025; p<0.001). A projection of 124,245 cases in 2030 was made, with an estimated incidence of 4.64 cases-month/100,000 inhabitants, levels similar to those in the 2000s. The Sarima model proved to be robust, with error of 4.1% when removing the pandemic period.

Conclusion: The decreasing trend in tuberculosis cases was reversed from 2015 onwards, a period of economic crisis, and was also impacted by the pandemic when there was a reduction in records. The Sarima model can be a useful forecasting tool for epidemiological surveillance. Greater investments in prevention and control need to be made to reduce the occurrence of tuberculosis, in line with the SDGs.

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