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.

BACKGROUND AND OBJECTIVES: The acute respiratory infection caused by severe acute respiratory syndrome coronavirus disease (COVID-19) has resulted in increased mortality among pregnant, puerperal, and neonates. Brazil has the highest number of maternal deaths and a distressing fatality rate of 7.2%, more than double the country's current mortality rate of 2.8%. This study investigates the impact of the COVID-19 pandemic on the Brazilian Maternal Mortality Ratio (BMMR) and forecasts the BMMR up to 2025. METHODS: To assess the impact of the COVID-19 pandemic on the BMMR, we employed Holt-Winters, Autoregressive Integrated Moving Average (ARIMA), and Neural Networks Autoregression (NNA). We utilized a retrospective time series spanning twenty-five years (1996-2021) to forecast the BMMR under both a COVID-19 pandemic scenario and a controlled COVID-19 scenario. RESULTS: Brazil consistently exhibited high maternal mortality values (mean BMMR [1996-2019] = 57.99 ±6.34/100,000 live births) according to World Health Organization criteria. The country experienced its highest mortality peak in the historical BMMR series in the second quarter of 2021 (197.75/100,000 live births), representing a more than 200% increase compared to the previous period. Holt-Winter and ARIMA models demonstrated better agreement with prediction results beyond the sample data, although NNA provided a better fit to previous data. CONCLUSIONS: 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.

How Did COVID-19 Impact the Antimicrobial Consumption and Bacterial Resistance Profiles in Brazil?

The indiscriminate use of antibiotics has favored the selective pressure of multidrug resistance among microorganisms. This research evaluated the pattern of antibiotic prescriptions among the Brazilian population between January 2018 and December 2021. Additionally, the study sought to analyze the incidence rates of central line-associated bloodstream infection (CLABSI) and examine the profiles of antibiotic resistance. We assessed the hospital and community antimicrobial consumption from the National Health Surveillance Agency Database and correlated it to microorganisms. The consumption of antimicrobials in the hospital environment increased by 26% in 2021, highlighting polymyxin B, which increased by 204%. In 2021, 244,266 cases of CLABSI were reported, indicating a nosocomial infection rate of 7.9%. The rate of resistance to polymyxin B was higher in Pseudomonas aeruginosa (1400%) and Klebsiella pneumoniae (514%). Azithromycin emerged as the predominant antibiotic utilized within the community setting, accounting for 24% of the overall consumption. Pearson's correlation analysis revealed a significant and positive correlation (r = 0.71) between the elevated usage of azithromycin and the incidence of COVID-19. Our results indicate an increase in antimicrobial consumption during the COVID-19 pandemic and reinforce the fact that the misuse of antimicrobials may lead to an expansion in antimicrobial resistance.