Graduate Program in Intellectual Property and Information Technology Transfer - PROFNIT, Federal University of Tocantins, Palmas 77001-090, TO, Brazil.
Medicine Course, State University of Tocantins, Palmas 77020-122, TO, Brazil.
Int J Environ Res Public Health. 2021 Dec 31;19(1):415. doi: 10.3390/ijerph19010415.
This work aimed to apply the ARIMA model to predict the under-reporting of new Hansen's disease cases during the COVID-19 pandemic in Palmas, Tocantins, Brazil. This is an ecological time series study of Hansen's disease indicators in the city of Palmas between 2001 and 2020 using the autoregressive integrated moving averages method. Data from the Notifiable Injuries Information System and population estimates from the Brazilian Institute of Geography and Statistics were collected. A total of 7035 new reported cases of Hansen's disease were analyzed. The ARIMA model (4,0,3) presented the lowest values for the two tested information criteria and was the one that best fit the data, as AIC = 431.30 and BIC = 462.28, using a statistical significance level of 0.05 and showing the differences between the predicted values and those recorded in the notifications, indicating a large number of under-reporting of Hansen's disease new cases during the period from April to December 2020. The ARIMA model reported that 177% of new cases of Hansen's disease were not reported in Palmas during the period of the COVID-19 pandemic in 2020. This study shows the need for the municipal control program to undertake immediate actions in terms of actively searching for cases and reducing their hidden prevalence.
本研究旨在应用 ARIMA 模型预测巴西托坎廷斯州帕尔马斯市在 COVID-19 大流行期间新发现的麻风病例漏报情况。这是一项关于 2001 年至 2020 年期间帕尔马斯市麻风病指标的生态时间序列研究，使用自回归综合移动平均法。收集了来自可报告伤害信息系统的数据和来自巴西地理与统计研究所的人口估计数据。共分析了 7035 例新报告的麻风病病例。ARIMA 模型（4,0,3）在两个测试信息标准中表现出最低值，并且是最适合数据的模型，AIC = 431.30 和 BIC = 462.28，使用的统计显着性水平为 0.05，并显示了预测值与通知中记录的值之间的差异，表明 2020 年 4 月至 12 月期间麻风病新病例的漏报数量较多。ARIMA 模型报告称，2020 年 COVID-19 大流行期间，帕尔马斯市有 177%的新麻风病例未报告。本研究表明，市控制计划需要立即采取行动，积极寻找病例并降低其隐性流行率。
