Provider confidence in counseling preconception, pregnant, and postpartum patients regarding COVID-19 vaccination: A cross-sectional survey study.

Background and Aims: Healthcare provider counseling surrounding COVID-19 vaccine in pregnancy and lactation is essential to vaccination uptake in this population; however, provider knowledge and confidence are not well characterized. We aimed to assess knowledge and confidence in COVID-19 vaccine counseling among practitioners who provide care to pregnant persons and to describe factors associated with confidence in counseling. Methods: A web-based anonymous survey was distributed via email to a cross-sectional convenience sample of Obstetrics and Gynecology, Primary Care, and Internal Medicine faculty at three hospitals in a single healthcare network in Massachusetts, United States. Individual demographics and institution-specific variables were included in the survey along with questions assessing both attitudes toward COVID-19 illness and confidence in counseling regarding the use of the vaccine in pregnancy. Results: Almost all providers (151, 98.1%) reported that they received a COVID-19 vaccine, and most (111, 72.1%) reported that they believe the benefits of the vaccine in pregnancy outweigh the risks. Forty-one (26.6%) reported feeling very confident in counseling patients who primarily speak English about the evidence for messenger ribonucleic acid vaccination in pregnancy, and 36 (23%) reported feeling very confident in counseling patients who are not primarily English-speaking. Forty-three providers (28.1%) expressed strong confidence in their comfort talking to individuals with vaccine hesitancy based on historic and continued racism and systemic injustices. The sources that survey respondents most used to find information regarding COVID-19 vaccination in pregnancy were the Centers for Disease Control (112, 74.2%), hospital-specific resources (94, 62.3%), and the American College of Obstetricians and Gynecologists (82, 54.3%). Conclusion: Ensuring that providers feel comfortable bridging the gap between their belief that the vaccine is beneficial for pregnant patients and their comfort with holding conversations with patients regarding vaccination is paramount to ensure equitable access to vaccines for pregnant patients.

Deterministic skill of ENSO predictions from the North American Multimodel Ensemble.

Hindcasts and real-time predictions of the east-central tropical Pacific sea surface temperature (SST) from the North American Multimodel Ensemble (NMME) system are verified for 1982-2015. Skill is examined using two deterministic verification measures: mean squared error skill score (MSESS) and anomaly correlation. Verification of eight individual models shows somewhat differing skills among them, with some models consistently producing more successful predictions than others. The skill levels of MME predictions are approximately the same as the two best performing individual models, and sometimes exceed both of them. A decomposition of the MSESS indicates the presence of calibration errors in some of the models. In particular, the amplitudes of some model predictions are too high when predictability is limited by the northern spring ENSO predictability barrier and/or when the interannual variability of the SST is near its seasonal minimum. The skill of the NMME system is compared to that of the MME from the IRI/CPC ENSO prediction plume, both for a comparable hindcast period and also for a set of real-time predictions spanning 2002-2011. Comparisons are made both between the MME predictions of each model group, and between the average of the skills of the respective individual models in each group. Acknowledging a hindcast versus real-time inconcsistency in the 2002-2012 skill comparison, the skill of the NMME is slightly higher than that of the prediction plume models in all cases. This result reflects well on the NMME system, with its large total ensemble size and opportunity for possible complementary contributions to skill.

Assessing probabilistic predictions of ENSO phase and intensity from the North American Multimodel Ensemble.

Here we examine the skill of three, five, and seven-category monthly ENSO probability forecasts (1982-2015) from single and multi-model ensemble integrations of the North American Multimodel Ensemble (NMME) project. Three-category forecasts are typical and provide probabilities for the ENSO phase (El Niño, La Niña or neutral). Additional forecast categories indicate the likelihood of ENSO conditions being weak, moderate or strong. The level of skill observed for differing numbers of forecast categories can help to determine the appropriate degree of forecast precision. However, the dependence of the skill score itself on the number of forecast categories must be taken into account. For reliable forecasts with same quality, the ranked probability skill score (RPSS) is fairly insensitive to the number of categories, while the logarithmic skill score (LSS) is an information measure and increases as categories are added. The ignorance skill score decreases to zero as forecast categories are added, regardless of skill level. For all models, forecast formats and skill scores, the northern spring predictability barrier explains much of the dependence of skill on target month and forecast lead. RPSS values for monthly ENSO forecasts show little dependence on the number of categories. However, the LSS of multimodel ensemble forecasts with five and seven categories show statistically significant advantages over the three-category forecasts for the targets and leads that are least affected by the spring predictability barrier. These findings indicate that current prediction systems are capable of providing more detailed probabilistic forecasts of ENSO phase and amplitude than are typically provided.

Predictable Components of ENSO Evolution in Real-time Multi-Model Predictions.

The most predictable components of the El Niño-Southern Oscillation (ENSO) evolution in real-time multi-model predictions are identified by applying an empirical orthogonal function analysis of the model data that maximizes the signal-to-noise ratio (MSN EOF). The normalized Niño3.4 index is analyzed for nine 3-month overlapping seasons. In this sense, the first most predictable component (MSN EOF1) is the decaying phase of ENSO during the Northern Hemisphere spring, followed by persistence through autumn and winter. The second most predictable component of ENSO evolution, with lower prediction skill and smaller explained variance than MSN EOF1, corresponds to the growth during spring and then persistence in summer and autumn. This result suggests that decay phase of ENSO is more predictable than the growth phase. Also, the most predictable components and the forecast skills in dynamical and statistical models are similar overall, with some differences arising during spring season initial conditions. Finally, the reconstructed predictions, with only the first two MSN components, show higher skill than the model raw predictions. Therefore this method can be used as a diagnostic for model comparison and development, and it can provide a new perspective for the most predictable components of ENSO.

Creation and Validation of Sintered PTFE BRDF Targets & Standards.

Sintered polytetrafluoroethylene (PTFE) is an extremely stable, near-perfect Lambertian reflecting diffuser and calibration standard material that has been used by national labs, space, aerospace and commercial sectors for over two decades. New uncertainty targets of 2 % on-orbit absolute validation in the Earth Observing Systems community have challenged the industry to improve is characterization and knowledge of almost every aspect of radiometric performance (space and ground). Assuming "near perfect" reflectance for angular dependent measurements is no longer going to suffice for many program needs. The total hemispherical spectral reflectance provides a good mark of general performance; but, without the angular characterization of bidirectional reflectance distribution function (BRDF) measurements, critical data is missing from many applications and uncertainty budgets. Therefore, traceable BRDF measurement capability is needed to characterize sintered PTFE's angular response and provide a full uncertainty profile to users. This paper presents preliminary comparison measurements of the BRDF of sintered PTFE from several laboratories to better quantify the BRDF of sintered PTFE, assess the BRDF measurement comparability between laboratories, and improve estimates of measurement uncertainties under laboratory conditions.