Universidade de Brasília, Brasília, DF, Brasil.
Universidad Autónoma de Barcelona, Spain.
Rev Soc Bras Med Trop. 2020 Sep 14;53:e20200528. doi: 10.1590/0037-8682-0528-2020. eCollection 2020.
The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths.
The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics.
Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases.
The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical & epidemiological characteristics.
冠状病毒病（COVID-19）的爆发使严重急性呼吸道感染（SARI）监测工作不堪重负，其中包括实验室网络。本研究旨在纠正报告的 SARI 死亡病例中缺乏实验室结果的问题。
应用临床流行病学特征对无实验室信息的 SARI 死亡病例进行缺失值插补。
在 84449 例 SARI 死亡病例中，51%的病例确诊为 COVID-19，3%的病例确诊为其他病毒性呼吸道疾病。经过插补方法后，95%的死亡病例重新分类为 COVID-19，5%的死亡病例重新分类为其他病毒性呼吸道疾病。
该插补方法是一种有用且稳健的解决方案（通过临床和流行病学特征，缺失值的灵敏度和阳性预测值为 98%）。
