The OOBr is an interactive monitoring platform with scientifically based public data analyses (health, socioeconomic, and environmental) and dissemination of relevant information in the maternal-child health field.
The dashboards were built in ShinyApps, and all the analyses were performed in the free R software. The documentation and data built into each dashboard are available for reproducibility and transparency. The methods used in each article can be found in the project’s specific publications.
The OOBr dashboard is a dynamic panel that analyzes COVID-19 vaccination data and cases of severe acute respiratory syndrome (SARS) in pregnant and postpartum women. It also provides information on the deaths of pregnant and postpartum women recorded in Brazil’s Mortality Information System, along with quality indicators for public data related to maternal health at national, state, and municipal levels. Users can select variables of interest and analyze them through cross-referenced tables and graphs, with the option for various selections. The smallest unit of analysis is at the municipality (county) level. The dashboard is updated weekly as soon as new data are made available by the Ministry of Health.
Key findings include an analysis of maternal deaths from COVID-19, highlighting significant inequalities in access to health services across different Brazilian states. The case-fatality rate in intensive care units (ICUs) ranged from 20.3% to 88.3%. The access to ICUs among women who died ranged from 0% to 50%, and the lack of mechanical ventilation among deceased women ranged from 0% to 51.5%. Postpartum women exhibited higher odds of severe outcomes compared to pregnant women, with the odds of ICU admission being 1.97 times higher, the odds of requiring invasive mechanical ventilation 2.71 times higher, and the odds of death 2.51 times higher for postpartum women compared to their pregnant counterparts.In 2021, while all hospitalized Brazilian patients showed increased odds of developing severe outcomes from COVID-19, the maternal population faced even greater risks, with an odds ratio (OR) of 2.60 for death, nearly double the OR of 1.44 observed in other population groups. For non-pregnant women, the odds ratio was 1.31. Additionally, pregnant and postpartum women had higher odds of requiring intensive care and intubation, as well as a greater likelihood of presenting oxygen desaturation in 2021 compared to the first year of the pandemic. An analysis of the impact of cardiac diseases on pregnant and postpartum women hospitalized for COVID-19 revealed that patients with cardiovascular disease (CVD) had higher odds of ICU admission (OR = 1.22, 95% CI 1.10-1.35) and orotracheal intubation during the third trimester (OR = 1.30, 95% CI 1.04-1.62) compared to patients without CVD. An evaluation of COVID-19 cases by race indicated that Black and Brown individuals comprised a higher percentage of deaths in the maternal population hospitalized for SARS. A retrospective cohort analysis compared the demographic profiles, clinical aspects, and mortality rates of 5,888 women hospitalized during the H1N1 influenza pandemic (2,190 pregnant and 3,698 non-pregnant) and 64,515 hospitalized during the COVID-19 pandemic (5,151 pregnant and 59,364 non-pregnant), utilizing data from the SIVEP-Gripe database. Finally, an analysis of the influenza vaccine’s effect on pregnant and postpartum women with severe cases of COVID-19 showed that receiving the influenza vaccine reduced the odds of ICU admission by 38%, the odds of requiring invasive mechanical support by 47%, and the odds of death from COVID-19 by 67% among pregnant and postpartum women experiencing severe forms of the disease.
Facilitating access to public data in a responsible and well-organized manner is vital for society. Such access empowers individuals to acquire information, assists public managers in making evidence-based decisions, and ensures that public policy discussions are grounded in reliable data. In the field of Obstetrics, there are ongoing debates concerning public policies affecting pregnant women, fetuses, and newborns, which often do not rely on scientific data or comprehensive analyses of public data.
The Observatory’s findings can back discussions on public policies and demonstrate the importance of Data Sciences in the health field, especially in maternal-child health. Importantly, a multidisciplinary team with statisticians, computer scientists, obstetricians, and pediatricians has contributed significantly to the project’s success.
The visualization panels will be regularly updated, and the team plans to conduct new research based on public data analysis to establish themselves as a reference source in maternal and child health.
