H1N1 Infection in Pregnancy; A Retrospective Study of Feto-Maternal Outcome and Impact of the Timing of Antiviral Therapy

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.

Views and experiences of maternal healthcare providers regarding influenza vaccine during pregnancy globally: A systematic review and qualitative evidence synthesis

BACKGROUND

The World Health Organization (WHO) recommends that pregnant women receive influenza vaccination; however, uptake of the vaccine remains low. Maternity health care professionals (MHCPs) play an important role in motivating pregnant women to receive the influenza vaccine. However, factors such as MHCPs' views and knowledge about the vaccine, and time constraints due to workload may influence MHCPs' practices and opinions about women receiving the influenza vaccine during pregnancy. To date, the qualitative evidence exploring MHCPs' views and experiences around influenza vaccine uptake in pregnant women has not been synthesised.

AIM

To systematically review and thematically synthesise qualitative evidence that explores the views and experiences of MHCPs involved in the provision of the maternal influenza vaccine worldwide.

METHODS

Five databases (MEDLINE, EMBASE, PsycINFO, CINAHL, Web of Science) were searched, supplemented with searches of included paper reference lists and grey literature. Study selection was conducted by up to three researchers applying pre-specified inclusion/exclusion criteria. Quality assessment was undertaken, data were extracted, coded and synthesised to develop descriptive and analytical themes.

RESULTS

Eight studies involving 277 participants were included. Seventeen descriptive themes were interpreted, embedded within six analytical themes. MHCPs perceived that maternal influenza vaccination delivery can be facilitated by trusting relationships, good communication, knowledge about the vaccine leading to confidence in recommending vaccine, electronic vaccination prompts, and presence of national guidelines. However, workload, time constraints, MHCP's perception of pregnant women's concerns, and social/cultural/environmental influences could prevent the likelihood of delivery of influenza vaccine. Knowledgeable MHCPs who were regularly updated about vaccination based on scientific evidence were more confident when discussing and recommending the influenza vaccine to pregnant women. In addition, the presence of national policies and guidelines and electronic prompts for maternal influenza vaccination would enhance the delivery of the vaccine.

CONCLUSION

Our findings suggest that approaches to enhance the vaccination uptake rate in pregnant women include addressing MHCPs barriers to discussing influenza vaccination through education, sufficient time for discussions, and electronic prompts about vaccination, as well as evidence based local and national guidelines.

Seasonal influenza during pregnancy

Seasonal Influenza is an acute respiratory illness caused by Influenza A or B viruses. Its presentation is commonly with signs and symptoms of upper respiratory tract involvement such as cough, sore throat and runny nose, associated with generalized systemic symptoms such as fever, headaches, myalgia, and weakness. The severity of symptoms is very variable, ranging from mild self-limiting infection to severe acute respiratory illness requiring intensive interventions. It usually occurs during the winter season and can lead to outbreaks and epidemics worldwide. Influenza is associated with increased morbidity and mortality in high-risk populations including pregnant women and up to two weeks postpartum. Rapid and accurate diagnosis of Influenza is necessary for prompt treatment to reduce morbidity. General public health measures and vaccination are recommended to reduce morbidity and control the spread of the disease. There are many published articles on the several Influenza epidemics that have occurred in this century. In this article, we aim to review the epidemiology, clinical manifestations, diagnosis, treatment, and prevention of seasonal Influenza during pregnancy. We performed an electronic search on PubMed, Cochrane database, National guidelines clearing house and Google Scholar databases.