  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
