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Objective: To determine whether a deprescribing effort reduced several key classes of medications, and the overall number of medication classes per patient, among long-term residents of skilled nursing facilities (SNFs). Design: Retrospective, longitudinal pre/post evaluation. Data from before and during the implementation of the deprescribing effort (2017 through 2019) were compared with data from the post-intervention year (2020). Setting and Patients: Long-term resident data reported through annual comprehensive reviews conducted at two SNFs located in central New York State between 2017 and 2020 (N = 12,144). Interventions: Multifaceted, interdisciplinary deprescribing effort to reduce medications in SNF residence including clinician education, guideline development, and individual chart reviews began in 2019. Results: The mean number of medications prescribed per resident was lower at both facilities after the intervention (mean = 1.74 at both facilities) versus preintervention (1.90 at Facility 1, 1.86 at Facility 2). Significant decreases were observed in the usage rates for diuretics (-4.2%; P = 0.001), opioids (-3.8%; P = 0.001), and antipsychotics (-2.4%; P = 0.010). The raw antidepressant usage rate increased by 1.5% after the intervention but the change was not significant. Effects were robust to covariate adjustment. Conclusion: A combined, comprehensive approach to deprescribing was associated with a reduction in the overall number of medication classes per resident and in several key classes of medications. Additional research with more data and covariate control is in progress for verification of these findings.

Background and Objectives: Educational components and electives that may influence medical student choice of primary care careers have been studied individually, but not reviewed or synthesized. Examining educational components and electives in a comprehensive manner may inform evidence-based approaches to raise the number of primary care physicians in the United States and help optimize use of finite resources. We sought to determine evidence-based educational components and electives associated with increased medical student choice of primary care careers. Methods: We searched PubMed, Scopus, and CINAHL for undergraduate medical education articles in English describing an educational component or elective and outcome relevant to primary care specialty choice. We assessed titles, then abstracts, and finally full texts for inclusion in a narrative synthesis. Results: The searches returned 11,211 articles and we found 42 that met the inclusion criteria. The most described components were outpatient clinical rotations, preclinical courses, and preceptorships. The most common electives were international health, summer preceptorships, and rural medicine. While most articles described curricula that appeared to have a positive correlation with primary care specialty choice, six articles found limited benefit. In sum, results were mixed. Conclusions: The current literature is limited, and many contemporary electives have not been studied with respect to primary care choice. Increased attention and funding to studying the impact of electives and other educational components on primary care specialty choice is warranted.

Background and Objectives: There is a persistent shortage of primary care physicians in the United States. Medical schools can help meet societal primary care health needs by graduating more students who select family medicine and other primary care careers. The objective of this narrative review was to evaluate the relationship between clerkships and primary care specialty choice. Methods: We conducted a systematic literature search and narrative review of research articles examining the association between clerkships and primary care specialty choice. We evaluated the quality of included articles using a validated scale, assessed for methodology and outcomes, and synthesized using a narrative approach. Results: We identified 59 articles meeting our research criteria. A required primary care clerkship in the core clerkship year was associated with increased primary care specialty choice. This finding was strongest for family medicine clerkships and family medicine specialty choice. Clerkships that were longer, were of higher quality, exposed students to a wider scope of primary care practice, and occurred within an institutional climate supportive of primary care were also correlated with more students choosing a primary care specialty. While student self-reported interest in primary care often increased following a primary care clerkship, this interest was not always sustained or consistently associated with a primary care residency match or primary care career. Conclusions: Required family medicine and primary care clerkships were correlated with primary care specialty choice. More high-quality research is needed to better understand how to maximize the impact of clerkships on primary care specialty choice.

Background and Objectives: Medical schools should understand how to matriculate students who are more likely to enter primary care specialties and put admissions processes into place that achieve this result. However, there are no existing reviews that have systematically evaluated medical school admission practices and primary care specialty choice. Methods: We conducted a narrative synthesis utilizing a systematic literature search to evaluate the effectiveness of medical school admission strategies designed to increase the percentage of graduates entering primary care specialties. Results: We included 34 articles in the narrative review. Multiple prematriculation programs that appear to produce students with a high likelihood of entering primary care have been described in the literature. However, all of these studies are from single institutions, were observational, and limited by selection bias. Applicants who self-identify an interest in primary care, grew up with a rural background, and are older at matriculation are more likely to enter primary care, with stated interest in primary care being most predictive. Gender and race have been associated with primary care specialty choice in some studies, but not all. Insufficient literature on admissions policies and procedures exists to draw conclusions about best practices. Conclusions: Medical schools that want to increase the percentage of graduates entering primary care should consider developing a prematriculation program that attracts and prepares motivated and talented students with primary care interest. Admissions committees should understand which demographic criteria are associated with increased likelihood of entering primary care. The most important identifiable trait is an applicant’s stated interest in primary care.

Background and Objectives: Primary care is associated with improved patient health and reductions in health disparities. Consequently, the demand for primary care physicians is increasing. To meet this demand, medical schools have employed strategies to graduate students interested in primary care careers, including medical education pathways—structured, longitudinal experiences that are explicitly separate from the main curricular scope of the undergraduate medical education experience. Our goal was to explore and identify common characteristics of medical education pathways that influence primary care specialty choice. Methods: Using research articles identified through a scoping review, we performed a qualitative content analysis of studies that evaluated the impact of medical education pathways on medical students’ choices of primary care careers. Results: Sixty-three papers described 43 medical education pathways; most studies used quantitative methods to describe outcomes. Program characteristics mapped onto five levels of an emerging socioecological model: state or national, community, institutional, relational, and individual. Conclusions: Successful medical education pathway programs complement a medical school curriculum that supports a common goal, and demonstrate multiple levels of structural and institutional factors that develop community connectedness, relatedness, and longitudinal community engagement in students. Further work is needed to better understand how each of these levels influence career choice and to reassess how to measure and report medical education outcomes that will more accurately predict the student choice of primary care careers.

Background and Objectives: Student-directed activities such as family medicine interest groups (FMIG) and student-run free clinics (SRFC) have been examined to discover their impact on entry into family medicine and primary care. The objective of this review was to synthesize study results to better incorporate and optimize these activities to support family medicine and primary care choice. Methods: We conducted a comprehensive literature search using PubMed, Scopus, and CINAHL to identify all English-language research articles on FMIG and SRFC. We examined how participation relates to entry into family medicine and primary care specialties. Exclusion criteria were nonresearch articles, review articles, and research conducted outside the United States, Canada, Australia, and New Zealand. We used a 16-point quality rubric to evaluate 18 (11 FMIG, seven SRFC) articles that met our criteria. Results: Of the nine articles that examined whether FMIG participation impacted entry into family medicine, five papers noted a positive relationship, one paper noted unclear correlation, and three papers noted that FMIG did not impact entry into family medicine. Of the seven articles about SRFC, only one showed a positive relationship between SRFC activity and entry into primary care. Conclusions: Larger-scale and higher quality studies are necessary to determine the impact of FMIG and SRFC on entry into family medicine and primary care. However, available evidence supports that FMIG participation is positively associated with family medicine career choice. In contrast, SRFC participation is not clearly associated with primary care career choice.

Purpose Three New York State practice-based research networks provided quality improvement strategies to improve screening rates for breast, cervical, and colorectal (BCC) cancers in safety-net primary care, over 7 years. In the final year (Y7), the United States experienced the COVID-19 pandemic. The impact of the COVID-19 pandemic on BCC cancer screening rates was assessed qualitatively. Methods A total of 12 primary care practices participated in Y7 of the quality improvement project. BCC cancer screening rates at year beginning and end were assessed. Practice staff were asked about how COVID-19 impacted screening. Average pre/postintervention screening rates and qualitative thematic analysis regarding how COVID-19 impacted cancer screening were ascertained. Results In Y7, there was an increase in breast cancer and a decrease in colorectal and cervical cancer screening rates compared to the previous project year. Many practices were able to continue pre-COVID-19 cancer screening processes. Overall, practices reported loss of staff, changes in data entry, and a shift from preventive screening to care of sick patients. Telehealth was vital for practices to continue serving patients but had a less positive impact on patients with financial/technological disadvantages. BCC cancer screenings were impacted at various levels. Conclusions The COVID-19 pandemic negatively impacted primary care practice cancer screening; however, some practices were able to mitigate effects by shifting focus to processes supporting screening outside of in-person office visits.

Fecal immunochemical testing (FIT) has become the most utilized test for colorectal cancer (CRC) screening. This retrospective quality assurance report analyzed data for 411 patients from one academic center in Central New York who underwent FIT between September 2015 and September 2016. All 67 positive tests and 344 of 952 negative tests were analyzed. Subjects from the FIT-negative “control group” were chosen at random. The mean age was 67 years and the male/female distribution was 391/20, with differences between the FIT-positive and -negative groups. FIT was inappropriately used in 210 (51%) of the 411 patients. The most common reasons for inappropriate FIT use were a documented refusal of colonoscopy (39.60% of inappropriate use), FIT occurring within the recommended surveillance interval from previous colonoscopy (27.98%), and a Charlson Co-Morbidity Index score ≥5 (22.87%). Other reasons were a history of adenoma (9.25%), family history of CRC/high-risk adenoma

Ticks transmit several arthropod-borne pathogens in New York state. The primary human-biting ticks in this region are Ixodes scapularis, Amblyomma americanum, and Dermacentor variabilis. Tick body-segment preference varies depending on tick and host species, with the human bite-site located on the head or lower extremities and abdomen. A community tick submission system was used to acquire information about bite-site location prior to pathogen testing to understand species and life stage-specific body-segment preferences. This identified species-specific preferences for location, with D. variabilis preferentially biting the head and neck and A. americanum preferring the thighs, groin, and abdomen. Ixodes scapularis was found across the body, although it showed a significant life stage difference with adults preferring the head, midsection, and groin while nymphs/larvae preferred the extremities. Infection with Borrelia burgdorferi related to a significant change in attachment site. This provides an assessment of which body segments ticks of the most common species in New York are likely to be found. This can be applied to tick protection or clinically to inform the search for biting ticks or cutaneous signs of tick-borne illness such as erythema migrans or eschar.

Background and Objectives: The United States, like many other nations, faces a chronic shortage of primary care physicians. The purpose of this scoping review was to synthesize literature describing evidence-based institutional practices and interventions that support medical students’ choices of primary care specialties, published in the United States, Canada, Australia, and New Zealand. Methods: We surveyed peer-reviewed, published research. An experienced medical librarian conducted searches of multiple databases. Articles were selected for inclusion based on explicit criteria. We charted articles by topic, methodology, year of publication, journal, country of origin, and presence or absence of funding. We then scored included articles for quality. Finally, we defined and described six common stages of development of institutional interventions. Results: We reviewed 8,083 articles and identified 199 articles meeting inclusion criteria and 41 related articles. As a group, studies were of low quality, but improved over time. Most were quantitative studies conducted in the United States. Many studies utilized one of four common methodologic approaches: retrospective surveys, studies of programs or curricula, large-scale multi-institution comparisons, and single-institution exemplars. Most studies developed groundwork or examined effectiveness or impact, with few studies of planning or piloting. Few studies examined state or regional workforce outcomes. Conclusions: Research examining medical school interventions and institutional practices to support primary care specialty choice would benefit from stronger theoretical grounding, greater investment in planning and piloting, consistent use of language, more qualitative methods, and innovative approaches. Robust funding mechanisms are needed to advance these goals.

Background and Objectives: Role modeling and mentoring are key aspects of identity formation in medical school and likely influence student specialty choice. No reviews have examined the ways that mentorship relationships impact primary care career choice. Methods: We conducted a systematic literature search to identify articles describing the influence of role models and mentorship on primary care interest, intention, or choice. A content analysis of the included articles determined which articles focused on mentorship versus role modeling and the definitions of each. We coded articles as groundwork, effectiveness, or impact depending on the methodology and outcomes of each study. Results: Searches yielded 362 articles, of which 30 met inclusion criteria. Three offered definitions of role modeling, and one compared and contrasted definitions of mentoring; 17 articles laid groundwork that indicated that role modeling and mentorship are important factors in career choice and specifically in primary care. Thirteen articles reported the effectiveness and impact of role modeling and mentoring in influencing intent to enter primary care or actual career choice. Primary care and non-primary care physicians influenced student interest, intent, and choice of primary care careers; this influence could be positive or negative. Conclusions: Role modeling and mentorship influence primary care career choice. Very few articles defined the studied relationships. More work on the impact of mentorship and role modeling on career choice is needed.

Background and Objectives: There is an ongoing shortage of primary care physicians in the United States. Medical schools are under pressure to address this threat to the nation’s health by producing more primary care graduates, including family physicians. Our objective was to identify institutional characteristics associated with more medical students choosing primary care. Methods: We conducted a systematic literature review with narrative synthesis to identify medical school characteristics associated with increased numbers or proportions of primary care graduates. We included peer-reviewed, published research from the United States, Canada, Australia, and New Zealand. The existing literature on characteristics, including institutional geography, funding and governance, mission, and research emphasis, was analyzed and synthesized into summary statements. Results: Ensuring a strong standing of the specialty of family medicine and creating an atmosphere of acceptance of the pursuit of primary care as a career are likely to increase an institution’s percentage of medical students entering primary care. Training on regional campuses or providing primary care experiences in rural settings also correlates with a larger percentage of graduates entering primary care. A research-intensive culture is inversely correlated with primary care physician production among private, but not public, institutions. The literature on institutional financial incentives is not of high enough quality to make a firm statement about influence on specialty choice. Conclusions: To produce more primary care providers, medical schools must create an environment where primary care is supported as a career choice. Medical schools should also consider educational models that incorporate regional campuses or rural educational settings.

Introduction: Operating in-person instruction, residential living, and other activities at institutions of higher education (IHEs) in the context of the pandemic of severe acute respiratory syndrome—coronavirus 2 (SARS-Cov2) have posed a multitude of challenges. Identification of asymptomatic cases at IHEs is crucial, as a large reservoir of virus can potentially develop among students. Unfortunately, despite the advantages, rapid antigen tests (RATs) have variously been shown to perform poorly when used with asymptomatic individuals. Methods: In order to address the appropriateness of RAT use in screening asymptomatic populations like those at IHEs, we conducted a rapid review of published evaluations of RATs available in the United States, where sensitivity and specificity were reported specifically from asymptomatic populations. We extracted sensitivity and specificity for asymptomatic populations reported in each article, along with location and important notes. The data are presented narratively. Results: A total of 11 articles were included for evaluation and presentation, representing tests from four manufacturers. Sensitivity ranged from 35.8% to a high of about 71%, with caveats to the higher number about exposure. Both the low and high sensitivity rates were observed in Abbott BinaxNOW RATs. Due to heterogeneity and publishing differences, a meta-analysis was not feasible, but RAT tests in asymptomatic populations tended to identify roughly half of those identified as infected via reverse transcription-polymerase chain reaction. Specificity ranged from 97.8% to 100%. Conclusion: The results of this rapid review indicate serious issues in misidentifying asymptomatic individuals as COVID-19 negative, when in fact they are infected and carrying the SARS-Cov2 virus.

Background and Objectives: Public health training became particularly important for family medicine (FM) residency training programs amid the COVID-19 pandemic; the Accreditation Council for Graduate Medical Education (ACGME IV.C.19) requires a structured curriculum in which residents address population health. Our primary goal was to understand if, and to what extent, public health interventions trainings were incorporated into FM residency training programs amid the COVID-19 pandemic. We hypothesized programs with more resources (eg, university affiliates) would be better able to incorporate the training compared to those without such resources (ie, nonuniversity affiliates). Methods: In 2021, we incorporated items addressing COVID-19 public health training competencies into the 2021 Council of Academic Family Medicine Educational Research Alliance national survey of FM residency program directors. The items addressed the type of training provided, mode of delivery, barriers to providing training, perceived importance of training, and support in delivering training. Results: The overall survey response rate was 46.4% (n=287/619). All programs offered at least some training to residents. There were no statistically significant differences in training intensity between university and nonuniversity affiliates. The length of time an FM residency director spent in their position was positively associated with training intensity (r=0.1430, P=.0252). The biggest barrier to providing the trainings was the need to devote time to other curriculum requirements. Conclusions: FM residency programs were able to provide some public health interventions training during the pandemic. With increased support and resources, FM resident training curricula may better prepare FM residents now in anticipation of a future pandemic.

Background As a priority group, healthcare personnel (HCP) will be key to the success of coronavirus disease 2019 (COVID-19) vaccination programs. This study assessed HCP willingness to get vaccinated and identified specific concerns that would undermine vaccination efforts. Methods We conducted a cross-sectional survey of HCP, including clinical and nonclinical staff, researchers, and trainees, between 23 November and 5 December 2020. The survey evaluated attitudes, beliefs, and willingness to get vaccinated. Results There were 5287 respondents with a mean (SD) age of 42.5 (13.56) years; 72.8% were female (n = 3842). Overall, 57.5 % of individuals expressed intent to receive COVID-19 vaccine; 80.4% were physicians and scientists representing the largest group. 33.6% of registered nurses, 31.6% of allied health professionals, and 32% of master’s level clinicians were unsure they would take the vaccine (P Conclusions We observed that self-reported willingness to receive vaccination against COVID-19 differs by hospital roles, with physicians and research scientists showing the highest acceptance. These findings highlight important heterogeneity in personal attitudes among HCPs around COVID-19 vaccines and highlight a need for tailored communication strategies.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub ( https://covid19forecasthub.org/ ) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of 1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

Background Postpartum contraception prevents unintended pregnancies and short interpregnancy intervals. The Pregnancy Risk Assessment Monitoring System (PRAMS) collects population-based data on postpartum contraception nonuse and reasons for not using postpartum contraception. In addition to quantitative questions, PRAMS collects open-text responses that are typically left unused by secondary quantitative analyses. However, abundant preexisting open-text data can serve as a resource for improving quantitative measurement accuracy and qualitatively uncovering unexpected responses. We used PRAMS survey questions to explore unprompted reasons for not using postpartum contraception and offer insight into the validity of categorical responses. Methods and findings We used 31,208 categorical 2012 PRAMS survey responses from postpartum women in the US to calculate original prevalences of postpartum contraception use and nonuse and reasons for contraception nonuse. A content analysis of open-text responses systematically recoded data to mitigate survey bias and ensure consistency, resulting in adjusted prevalence calculations and identification of other nonuse themes. Recoded contraception nonuse slightly differed from original reports (21.5% versus 19.4%). Both calculations showed that many respondents reporting nonuse may be at a low risk for pregnancy due to factors like tubal ligation or abstinence. Most frequent nonuse reasons were not wanting to use birth control (27.1%) and side effect concerns (25.0%). Other open-text responses showed common themes of infertility, and breastfeeding as contraception. Comparing quantitative and qualitative responses revealed contradicting information, suggesting respondent misinterpretation and confusion surrounding the term “pregnancy prevention.” Though this analysis may be limited by manual coding error and researcher biases, we avoided coding exhaustion via 1-hour coding periods and validated reliability through intercoder kappa scores. Conclusions In this study, we observed that respondents reporting contraception nonuse often described other methods of pregnancy prevention and contraception barriers that were not included in categorical response options. Open-text responses shed light on a more comprehensive list of pregnancy prevention methods and nonuse options. Our findings contribute to survey questions that can lead to more accurate depiction of postpartum contraceptive behavior. Additionally, future use of these qualitative methods may be used to improve other health behavior survey development and resulting data., In a mixed-methods inquiry, Nicole Richards and colleagues investigate how open-text responses can provide insight into categorical reasons for postpartum contraception use and non-use among women in the US., Author summary Why was this study done? Survey respondents can occasionally provide open-ended answers that may be overlooked during quantitative data analysis. This study was conducted to study how qualitative inquiry of open-text responses to a survey question related to postpartum contraception use can be used to provide insight into data accuracy within quantitative surveys. What did the researchers do and find? Using a mixed-method approach, we calculated descriptive statistics from Pregnancy Risk Assessment Monitoring System (PRAMS) survey responses from 31,208 postpartum women in the US who provided categorized reasons for not using contraception and qualitatively analyzed respondents’ adjacent open-ended written answers to uncover more detailed information about respondents’ postpartum contraception behavior and interpretations of the survey question. Through systematic recategorization, we found that qualitative responses added to and altered quantitative contraception behavior reports and that reasons for contraception nonuse are incompletely captured by existing response categories. What do these findings mean? These findings suggest that researchers may be able to gain a better understanding of postpartum pregnancy prevention by using mixed-method analyses on categorical and open-ended responses. While qualitative inquiry may yield subjective interpretation, rigorous pragmatic data management can strengthen survey questions through open-text responses not captured in existing quantitative data. Family planning professionals may be able to obtain significant and detailed information about contraceptive behavior from open-ended responses, and this information may be useful to adjust clinical approaches to postpartum contraception conversations.

Introduction: Vaccines against SARS-CoV-2 have been developed with unprecedented speed. The phased introduction of vaccines may be serving to offset the impact of new viral variants and policy relaxation. In order to assess the impact of vaccination, we examined a snapshot of vaccination rates across counties in a single state, at a single time point, comparing them with population-adjusted case counts. Methods: We calculated descriptive statistics and bivariate correlations for vaccination rates and cases across counties in New York State (NYS). We conducted a linear regression using cases/100K population per NYS county, frozen at a single snapshot in time, as the outcome variable, predicted by percentage of each county’s population (completed series/two doses), controlling for county population. Results: Percentages with one dose and with two doses were highly correlated (r=.935, P

Purpose: In the United States, cancer screening rates are often below national targets. This project implemented practice facilitation and academic detailing aimed at increasing breast, cervical, and colorectal cancer screening rates in safety-net primary care practices. Methods: Three practice-based research networks across western and central New York State partnered to provide quality improvement strategies on breast, cervical, and colorectal cancer screening. Pre/postintervention screening rates for all participating practices were collected annually, as were means across all practices over 7 years. Simple ordinary least squares linear regression was used to calculate the trend for each cancer type and test for statistical significance (ie, P ≤ 0.05), using the ordinal time point as a fixed effect. Results: An overall increase in mean screening rates was seen over the duration of this project for colorectal (24.6% preintervention to 48.0% in year 7 of intervention; P < 0.001) and breast cancer (37.0% preintervention to 48.6% in year 7; P = 0.460). Mean cervical cancer screening rates decreased (35.5% preintervention to 31.4% in year 7; P = 0.209). Success in increasing screening rates varied across regions of New York State. Conclusions: Practice facilitation and academic detailing were successful in significantly increasing, on average, colorectal cancer screening rate. Cervical cancer screening showed an overall decrease, likely due to difficulties for primary care practices in tracking and implementation, as many patients seek this service at outside gynecology facilities. Regional differences, guideline changes, and practice reorganization each may have played a part in observed trends. A standardization of queries being used to pull screening rates is an important step in increasing the reliability of these data.

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P −52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P −58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P −113), further highlighting the advantages of incorporating data from diverse human populations.

Background and Objectives: The United States needs more family physicians. Projections based on current trends show a deficit of 52,000 primary care physicians by 2025. Eight national family medicine (FM) organizations have set an ambitious goal of increasing the proportion of US medical school graduates who enter FM residencies to 25% by 2030. This paper describes the most recent number and percentage of students from each US medical school entering Accreditation Council for Graduate Medical Education (ACGME)-accredited FM residency programs, long-term trends in the contribution of allopathic and osteopathic medical schools to the FM workforce, and medical school characteristics associated with higher proportions of FM graduates. Methods: Data about graduates entering US ACGME-accredited FM residency programs were collected using an annual program census and supplemental sources. Longitudinal census data from allopathic and osteopathic schools were combined to examine trends over time. ANOVA analyses were conducted to compare schools by percent of graduates entering FM, public/private ownership, allopathic/osteopathic, size, and presence of FM department. Medical school length of operation was correlated with percentage of students entering FM. Results: The overall proportion of US students entering ACGME-accredited FM programs has increased modestly over the past decade. Currently, only 12.6% of US allopathic and osteopathic seniors enter ACGME-accredited FM programs. Individual medical schools’ contributions to the FM workforce are described. Conclusions: The proportion of US medical students beginning ACGME-accredited FM residency programs has increased slightly over the last decade. However, significant changes to undergraduate medical education are needed to meet the nation’s primary care needs.

Background We previously reported on coronavirus disease 2019 (COVID-19) vaccination intent among healthcare personnel (HCP) before emergency use authorization. We found widespread hesitancy and a substantial proportion of HCP did not intend to vaccinate. Methods We conducted a cross-sectional survey of HCP, including clinical and nonclinical staff, researchers, and trainees between 21 February and 19 March 2021. The survey evaluated vaccine attitudes, beliefs, intent, and acceptance. Results Overall, 3981 (87.7%) of respondents had already received a COVID-19 vaccine or planned to get vaccinated. There were significant differences in vaccine acceptance by gender, age, race, and hospital role. Males (93.7%) were more likely than females (89.8%) to report vaccine acceptance (P < .001). Mean age was higher among those reporting vaccine acceptance (P < .001). Physicians and scientists showed the highest acceptance rate (97.3%), whereas staff in ancillary services showed the lowest acceptance rate (79.9%). Unvaccinated respondents were more likely to be females, to have refused vaccines in the past due to reasons other than illness or allergy, to care for COVID-19 patients, or to rely on themselves when making vaccination decision. Vaccine acceptance was more than twice previous intent among Black respondents, an increase from 30.8% to 73.8%, and across all hospital roles with all > 80% vaccine acceptance. Conclusions The majority of HCP were vaccinated, much higher than reporting intent before vaccine was available. However, many HCP—particularly ancillary services—are still hesitant. Feasible and effective interventions to address the hesitant, including individually-tailored education strategies are needed, or vaccine can be mandated.

Aim: To understand how remote Certified Diabetes Care and Education Specialists (CDCES) helped adults with type 1 diabetes (T1D) transition from provider in-person to tele-visits. Methods: Adults with T1D were referred to remote CDCES to fulfill needs from 4/16/2020 - 8/14/2020. Pertinent information from the EMR was provided to the CDCES who were not previously known to the patients. A summary of the remote CDCES encounter was communicated to the provider. Data analysis used t-tests to assess differences in means and Pearson correlation coefficients to assess relationship between the number of encounters and insurance and age. SPSS v. 27 was used. Results: Adults (n=1089) with T1D [mean age 46 (range 18-90 yrs); 50% female; 20% Medicaid, 23% Medicare, 54% private coverage; mean A1c 8.4% (range 4.6 to >14.0%); 52% pump and 61% CGM users], had 1662 encounters with remote CDCES. Of those referred, 232 (21%) could not be reached or did not receive education/support. Older age was associated with more encounters (r=0.126, p Conclusions: Most remote CDCES encounters in adults with T1D were successfully completed, assisting the majority with CGM education/data review and nearly half with device download training in preparation for their provider tele-visit. Older adults and those with Medicare required more encounters to fulfill needs. Future study could assess whether remote encounters result in improved glycemic control or quality of life. Disclosure M. Greenfield: None. D. L. Stuber: None. D. Stegman-barber: None. K. Kemmis: None. B. A. Wells: None. T. S. Mcarthur: None. B. Matthews: None. C. P. Morley: None. R. S. Weinstock: Research Support; Self; Boehringer Ingelheim International GmbH, Diasome Pharmaceuticals, Inc., Eli Lilly and Company, Insulet Corporation, Kowa Research Institute, Inc., Medtronic, Tolerion, Inc. Funding The Leona M. and Harry B. Helmsley Charitable Trust; T1D Exchange QI Learning Collaborative

The global pandemic of coronavirus disease 2019 (COVID-19) has killed almost two million people worldwide and over 400 thousand in the United States (US). As the pandemic evolves, informed policy-making and strategic resource allocation relies on accurate forecasts. To predict the spread of the virus within US counties, we curated an array of county-level demographic and COVID-19-relevant health risk factors. In combination with the county-level case and death numbers curated by John Hopkins university, we developed a forecasting model using deep learning (DL). We implemented an autoencoder-based Seq2Seq model with gated recurrent units (GRUs) in the deep recurrent layers. We trained the model to predict future incident cases, deaths and the reproductive number

The global pandemic of coronavirus disease 2019 (COVID-19) has killed almost two million people worldwide and over 400 thousand in the United States (US). As the pandemic evolves, informed policy-making and strategic resource allocation relies on accurate forecasts. To predict the spread of the virus within US counties, we curated an array of county-level demographic and COVID-19-relevant health risk factors. In combination with the county-level case and death numbers curated by John Hopkins university, we developed a forecasting model using deep learning (DL). We implemented an autoencoder-based Seq2Seq model with gated recurrent units (GRUs) in the deep recurrent layers. We trained the model to predict future incident cases, deaths and the reproductive number, R. For most counties, it makes accurate predictions of new incident cases, deaths and R values, up to 30 days in the future. Our framework can also be used to predict other targets that are useful indices for policymaking, for example hospitalization or the occupancy of intensive care units. Our DL framework is publicly available on GitHub and can be adapted for other indices of the COVID-19 spread. We hope that our forecasts and model can help local governments in the continued fight against COVID-19.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance Statement This paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.

The year 2020 has been marked by historic protests across the United States and the globe sparked by the deaths of George Floyd, Ahmaud Arbery, Breonna Taylor, and so many other Black people. The protests heightened awareness of racism as a public health crisis and triggered an antiracism movement.

The year 2020 has been marked by historic protests across the United States and the globe sparked by the deaths of George Floyd, Ahmaud Arbery, Breonna Taylor, and so many other Black people. The protests heightened awareness of racism as a public health crisis and triggered an anti-racism movement

EBioMedicine 72, 103588 (2021). doi:10.1016/j.ebiom.2021.103588, Published by Elsevier, Amsterdam [u.a.]

Background: Continuous glucose monitors (CGMs) help people with type 1 diabetes (T1D) improve their glycemic profiles but are underutilized. To better understand why, perceived CGM burdens and benefits in nonusers versus users with type 1 diabetes across the lifespan were assessed. Methods: Burdens (BurCGM) and benefits of CGM (BenCGM) questionnaires were completed during T1D outpatient visits ( n = 1334) from February 2019 to February 2020. Mean scores were calculated (scale one to five; higher scores reflect greater perceived burdens/benefits). Data were collected from medical records including glycated hemoglobin (HbA1c) within 3 months of the visit. Results: Individuals of all ages using CGM described more benefits and less burdens (mean scores 4.48 and 1.69, respectively) when compared with those who were not using CGM (mean score 4.19 and 2.35, respectively) ( P < .001). There were no differences in burdens or benefits by sex. Non-CGM users aged ≥50 years had higher mean BurCGM scores than those aged Conclusions: CGM was perceived as having more burdens and less benefits in nonusers, with differences in concerns varying across the lifespan. Lower costs and age-appropriate education are needed to address these barriers.

By meta-analyzing the whole-exomes of 24,248 cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in ten genes as conferring substantial risk for schizophrenia (odds ratios 3 - 50, P < 2.14 × 10-6), and 32 genes at a FDR < 5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure, and function of the synapse. The associations of NMDA receptor subunit GRIN2A and AMPA receptor subunit GRIA3 provide support for the dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We find significant evidence for an overlap of rare variant risk between schizophrenia, autism spectrum disorders (ASD), and severe neurodevelopmental disorders (DD/ID), supporting a neurodevelopmental etiology for schizophrenia. We show that protein-truncating variants in GRIN2A, TRIO, and CACNA1G confer risk for schizophrenia whereas specific missense mutations in these genes confer risk for DD/ID. Nevertheless, few of the strongly associated schizophrenia genes appear to confer risk for DD/ID. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk, suggesting that common and rare genetic risk factors at least partially converge on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, implying that more schizophrenia risk genes await discovery using this approach.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). In the absence of robust preventive or curative strategies, the implementation of social distancing has been a key component of limiting the spread of the virus. METHODS: Daily estimates of R(t) were calculated and compared with measures of social distancing made publicly available by Unacast. Daily generated variables representing an overall grade for distancing, changes in distances traveled, encounters between individuals, and daily visitation, were modeled as predictors of average R value for the following week, using linear regression techniques for 8 counties surrounding the city of Syracuse, New York. Supplementary analysis examined differences between counties. RESULTS: A total of 225 observations were available across the 8 counties, with 166 meeting the mean R(t) < 3 outlier criterion for the regression models. Measurements for distance (s = 1.002, P = .012), visitation (s = .887, P = .017), and encounters (s = 1.070, P = .001) were each predictors of R(t) for the following week. Mean R(t) drops when overall distancing grades move from D+ to C-. These trends were significant (P < .001 for each). CONCLUSIONS: Social distancing, when assessed by free and publicly available measures such as those shared by Unacast, has an impact on viral transmission rates. The scorecard may also be useful for public messaging about social distance, in hospital planning, and in the interpretation of epidemiological models.

Objective: To describe perceived burdens and benefits of continuous glucose monitor (CGM) use in CGM non-users vs. users with type 1 diabetes across the lifespan. Research Design and Methods: The Burdens of CGM (BurCGM) and Benefit of CGM (BenCGM) questionnaires were completed at clinic visits from Feb 2019 to Nov 2019. Mean scores were calculated (scale 1-5; higher score reflects greater perceived burdens and benefits). Data collected from medical records included demographic information, CGM and insulin pump use, and HbA1c within 3 months of the visit. Results: Participant characteristics (n=1143) and the 3 most common perceived CGM burdens (in non-CGM users) and benefits (in non-CGM users and CGM users) are shown in the Table. Individuals using real time (RT) and non-RT CGM described more benefits (mean scores 34.9 and 34.0) when compared to those who never used CGM (mean score 30.2) (p9.0%. Conclusions: Cost is a barrier to CGM use, particularly in adults. In non-CGM users (vs. users), CGM was perceived as having less benefit and to be associated with pain and concern that readings cannot be trusted. Advocacy (for lower cost) and education are needed to address these barriers. Disclosure V. Divan: None. M. Greenfield: None. C.P. Morley: None. R.S. Weinstock: Board Member; Self; JDRF. Consultant; Self; Insulogic LLC. Research Support; Self; Boehringer Ingelheim International GmbH, Diasome Pharmaceuticals, Inc., Eli Lilly and Company, Insulet Corporation, Jaeb Center for Health Research, Kowa Research Institute, Inc., Medtronic, Tolerion, Inc. Funding Type 1 Diabetes Exchange QI Learning Collaborative

Prevention amounts to stopping a disease from occurring, either through avoidance of risk factors, or through prophylactic measures, such as vaccination, use of barrier methods during sexual encounters, and so forth. However, as one delves into the topic of prevention, it becomes apparent that there are multiple points for intervention into a disease, that the stage of disease matters as to what preventive actions are appropriate, the type of disease, and even the overlapping concepts of disease versus illness.

Within the National Institutes of Health, the Office of Behavioral and Social Sciences Research (OBSSR) coordinates behavioral and social sciences research (BSSR) efforts across institutes. As part of its authorizing legislation, Congress asked OBSSR to “develop a standard definition of the field