Due to its impact, COVID-19 has been stressing the academy to search for curing, mitigating, or controlling it. However, when it comes to controlling, there are still few studies focused on under-reporting estimates. It is believed that under-reporting is a relevant factor in determining the actual mortality rate and, if not considered, can cause significant misinformation. Therefore, the objective of this work is to estimate the under-reporting of cases and deaths of COVID-19 in Brazilian states using data from the Infogripe on notification of Severe Acute Respiratory Infection (SARI). The methodology is based on the concepts of inertia and the use of event detection techniques to study the time series of hospitalized SARI cases. The estimate of real cases of the disease, called novelty, is calculated by comparing the difference in SARI cases in 2020 (after COVID-19) with the total expected cases in recent years (2016 to 2019) derived from a seasonal exponential moving average. The results show that under-reporting rates vary significantly between states and that there are no general patterns for states in the same region in Brazil. The published version of this paper is made available at https://doi.org/10.1007/s00354-021-00125-3. Please cite as: B. Paix\~ao, L. Baroni, M. Pedroso, R. Salles, L. Escobar, C. de Sousa, R. de Freitas Saldanha, J. Soares, R. Coutinho, et al., 2021, Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI, New Generation Computing
翻译:由于其影响,COVID-19一直强调该学院寻求治愈、减轻或控制COVID-19,然而,在控制方面,仍然很少有以报告不足的估计数为重点的研究,认为报告不足是确定实际死亡率的一个相关因素,如果不予考虑,则可能造成重大错误信息,因此,这项工作的目的是利用关于严重急性呼吸系统感染通知的Inforripe数据,估计巴西各州COVID-19病例和死亡报告不足的情况。该方法以惯性概念和使用事件探测技术来研究SARI住院病例的时间序列为基础。该疾病实际病例(称为新情况)的估计数是通过将2020年SARI病例(继COVID-19之后)与近些年来(2016-2019年)根据季节性指数平均得出的预计病例总数进行比较得出的。结果显示,报告不足率在各州之间差异很大,巴西各州没有通用的计算方法。