Impact of COVID-19 pandemic in the Brazilian maternal mortality ratio: A comparative analysis of Neural Networks Autoregression, Holt-Winters exponential smoothing, and Autoregressive Integrated Moving Average models.

Mayara Carolina CañedoThiago Inácio Barros LopesLuana RossatoIsadora Batista NunesIzadora Dillis FaccinTúlio Máximo SaloméSimone Simionatto

Published in: PloS one (2024)

Our study revealed an increase in BMMR and its temporal correlation with COVID-19 incidence. Additionally, it showed that Holt-Winter and ARIMA models can be employed for BMMR forecasting with lower errors. This information can assist governments and public health agencies in making timely and informed decisions.

Keyphrases

neural network
public health
coronavirus disease
risk factors
sars cov
cardiovascular events
birth weight
emergency department
type diabetes
single cell
healthcare
coronary artery disease
cardiovascular disease
pregnancy outcomes
adverse drug
respiratory syndrome coronavirus