Social distancing and mental health among pregnant women during the coronavirus pandemic.

BACKGROUND: The effect of social distancing due to the COVID-19 pandemic on the mental health of pregnant women is of particular concern, given potential effects on physical health, family functioning, and child development. METHODS: Pregnant women were recruited for the "Implications of and Experiences Surrounding being Pregnant during the COVID-19 Pandemic" study at Woman's Hospital in Baton Rouge, Louisiana. Participants enrolled at any point during their pregnancy and surveys were delivered weekly until the participant indicated that she had delivered her baby; a postpartum survey followed four weeks after delivery. This analysis includes 1037 participants with baseline, 596 with follow-up, and 302 with postpartum surveys. Questions on social distancing behaviors were asked at baseline and grouped based on whether they involved social distancing from work, friends and family, or public places. Symptoms of anxiety, stress, depression, and pregnancy-related anxiety were measured. Each type of social distancing was examined as a predictor of mental health using linear model with control for confounders. RESULTS: The study population was largely white (84.1%), married (81.8%), and educated (76.2% with a bachelor's or higher degree). Women who were younger, Black, unmarried, or had less education or income reported fewer social distancing behaviors. Mean anxiety score in the highest quartile of overall social distancing was 8.3 (SD 5.6), while in the lowest quartile it was 6.0 (SD 5.0) (p < 0.01), while perceived stress postpartum and pregnancy-related stress were not associated with social distancing. Associations were substantially diminished when controlled for baseline levels of anxiety symptoms. CONCLUSIONS: Greater social distancing was associated with more anxiety symptoms, but worse mental health, particularly anxiety, may also have contributed to greater social distancing behaviors.

Vaccines and fertility: Why worry?

In this issue of the Journal, Wesselink et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX)) present findings that indicate that the COVID-19 vaccine does not cause any reduction in fertility in either men or women, while COVID-19 infection may reduce fertility temporarily among men. These are reassuring findings for those seeking pregnancy, clinicians, and the public. There was no scientific reason to be concerned about effects of the COVID-19 vaccine on fertility, so some of the psychological, ethical, and historical reasons for concern are discussed. These include perceptions of risk around "unnatural", unusual, or dreaded outcomes; vaccine resistance as part of a social and political identity; and the tendency for moral panics to occur around women's reproductive capacity. On this and other topics, there is a broad need for reproductive health to be better incorporated into clinical trials, and fertility research to advance in measurement and include a more diverse and global population.

Assessing the effects of disasters and their aftermath on pregnancy and infant outcomes: A conceptual model.

Although many studies have examined broad patterns of effects on pregnancy and infant outcomes after disasters, the causes of adverse outcomes are not always clear. Disasters cause interrelated exposure to environmental pollutants, psychological stressors, and lack of health care, and interacts with other social determinants of health. This topical review examines the short- and long-term effects of disasters on pregnancy and how they are mediated by social, behavioral, and environmental effects. In the short term, disasters are associated with physical trauma, adverse environmental exposures, and unstable housing. In the longer term, disasters may lead to relocation, changes in family functioning, and negative economic effects. These aspects of disaster exposure, in turn, lead to lack of access to health care, increased stress and negative mental health outcomes, and negative behavioral changes, including smoking and substance use, poor nutrition, physical overexertion and limited activity, and reduction in breastfeeding. All of these factors interact with social determinants of health to worsen effects on the most vulnerable women, infants, and communities. Few interventions after disasters have been tested. With the increase in disasters due to climate change and the ongoing coronavirus pandemic, the models of effects of disasters and their human health consequences need increasing refinement, and, more importantly, should be applied to interventions that improve disaster prevention, mitigation, and response.

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters.

The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.

Using Prenatal Blood Samples to Evaluate COVID-19 Rapid Serologic Tests Specificity.

INTRODUCTION: Background cross-reactivity with other coronaviruses may reduce the specificity of COVID-19 rapid serologic tests. The vast majority of women attend prenatal care, which is a unique source of population-based blood samples appropriate for validation studies. We used stored 2018 serum samples from an existing pregnancy cohort study to evaluate the specificity of COVID-19 serologic rapid diagnostic tests. METHODS: We randomly selected 120 stored serum samples from pregnant women enrolled in a cohort in 2018 in Tegucigalpa, Honduras, at least 1 year before the COVID-19 pandemic. We used stored serum to evaluate four lateral flow rapid diagnostic tests, following manufacturers' instructions. Pictures were taken for all tests and read by two blinded trained evaluators. RESULTS: We evaluated 120, 80, 90, and 90 samples, respectively. Specificity for both IgM and IgG was 100% for the first two tests (95% confidence intervals [CI] 97.0-100 and 95.5-100, respectively). The third test had a specificity of 98.9% (95% CI 94.0-100) for IgM and 94.4% (95% CI 87.5-98.2) for IgG. The fourth test had a specificity of 88.9% (95% CI 80.5-94.5) for IgM and 100% (95% CI 96.0-100) for IgG. DISCUSSION: COVID-19 serologic rapid tests are of variable specificity. Blood specimens from sentinel prenatal clinics provide an opportunity to validate serologic tests with population-based samples.