This study assesses the prevalence and determinants of postpartum depression (PPD). 396 women delivering in Beirut and a rural area (Beka'a Valley) were interviewed 24 hours and 3-5 months after delivery. During the latter visit, they were screened using the Edinburgh postnatal depression scale. The overall prevalence of PPD was 21% but was significantly lower in Beirut than the Beka'a Valley (16% vs. 26%). Lack of social support and prenatal depression were significantly associated with PPD in both areas, whereas stressful life events, lifetime depression, vaginal delivery, little education, unemployment, and chronic health problems were significantly related to PPD in one of the areas. Prenatal depression and more than one chronic health problem increased significantly the risk of PPD. Caesarean section decreased the risk of PPD, particularly in Beirut but also in the Beka'a Valley. Caregivers should use pre- and postnatal assessments to identify and address women at risk of PPD.

ObjectiveTo prospectively document experiences of frontline maternal and newborn healthcare providers during the COVID-19 pandemic. DesignCross-sectional study via an online survey disseminated through professional networks and social media in 12 languages. We analysed responses using descriptive statistics and qualitative thematic analysis disaggregating by low-and middle-income countries (LMICs) and high-income countries (HICs).Setting 81 countries, between March 24 and April 10, 2020.Participants 714 maternal and newborn healthcare providers. Main outcome measuresPreparedness for and response to COVID-19, experiences of health workers providing care to women and newborns, and adaptations to 17 outpatient and inpatient care processes during the pandemic. ResultsOnly one third of respondents received training on COVID-19 from their health facility and nearly all searched for information themselves. Half of respondents in LMICs received updated guidelines for care provision compared with 82% in HICs. Overall, only 47% of participants in LMICs, and 69% in HICs felt mostly or completely knowledgeable in how to care for COVID-19 maternity patients. Facility-level responses to COVID-19 (signage, screening, testing, and isolation rooms) were more common in HICs than LMICs. Globally, 90% of respondents reported somewhat or substantially higher levels of stress. There was a widespread perception of reduced use of routine maternity care services, and of modification in care processes, some of which were not evidence-based. ConclusionsSubstantial knowledge gaps exist in guidance on management of maternity cases with or without COVID-19. Formal information sharing channels for providers must be established and mental health support provided. Surveys of maternity care providers can help track the situation, capture innovations, and support rapid development of effective responses. We would like to thank the study participants who took time to respond to this survey despite the difficult circumstances and increased workload. We acknowledge the Institutional

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Purpose Primary care databases are increasingly used for researching pregnancy, eg, the effects of maternal drug exposures. However, ascertaining pregnancies, their timing, and outcomes in these data is challenging. While individual studies have adopted different methods, no systematic approach to characterise all pregnancies in a primary care database has yet been published. Therefore, we developed a new algorithm to establish a Pregnancy Register in the UK Clinical Practice Research Datalink (CPRD) GOLD primary care database. Methods We compiled over 4000 read and entity codes to identify pregnancy‐related records among women aged 11 to 49 years in CPRD GOLD. Codes were categorised by the stage or outcome of pregnancy to facilitate delineation of pregnancy episodes. We constructed hierarchical rule systems to handle information from multiple sources. We assessed the validity of the Register to identify pregnancy outcomes by comparing our results to linked hospitalisation records and Office for National Statistics population rates. Results Our algorithm identified 5.8 million pregnancies among 2.4 million women (January 1987‐February 2018). We observed close agreement with hospitalisation data regarding completeness of pregnancy outcomes (91% sensitivity for deliveries and 77% for pregnancy losses) and their timing (median 0 days difference, interquartile range 0‐2 days). Miscarriage and prematurity rates were consistent with population figures, although termination and, to a lesser extent, live birth rates were underestimated in the Register. Conclusions The Pregnancy Register offers huge research potential because of its large size, high completeness, and availability. Further validation work is underway to enhance this data resource and identify optimal approaches for its use.