In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.

A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.

We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.

The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.

Depression is an independent risk factor for cardiovascular disease (CVD), but it is unknown if successful depression treatment reduces CVD risk.

Using eIMPACT trial data, we examined the effect of modernized collaborative care for depression on indicators of CVD risk. A total of 216 primary care patients with depression and elevated CVD risk were randomized to 12 months of the eIMPACT intervention (internet cognitive-behavioral therapy [CBT], telephonic CBT, and select antidepressant medications) or usual primary care. CVD-relevant health behaviors (self-reported CVD prevention medication adherence, sedentary behavior, and sleep quality) and traditional CVD risk factors (blood pressure and lipid fractions) were assessed over 12 months. Incident CVD events were tracked over four years using a statewide health information exchange.

The intervention group exhibited greater improvement in depressive symptoms (p < 0.01) and sleep quality (p < 0.01) than the usual care group, but there was no intervention effect on systolic blood pressure (p = 0.36), low-density lipoprotein cholesterol (p = 0.38), high-density lipoprotein cholesterol (p = 0.79), triglycerides (p = 0.76), CVD prevention medication adherence (p = 0.64), or sedentary behavior (p = 0.57). There was an intervention effect on diastolic blood pressure that favored the usual care group (p = 0.02). The likelihood of an incident CVD event did not differ between the intervention (13/107, 12.1%) and usual care (9/109, 8.3%) groups (p = 0.39).

Successful depression treatment alone is not sufficient to lower the heightened CVD risk of people with depression. Alternative approaches are needed.

ClinicalTrials.gov Identifier: NCT02458690

Knowledge of sex differences in risk factors for posttraumatic stress disorder (PTSD) can contribute to the development of refined preventive interventions. Therefore, the aim of this study was to examine if women and men differ in their vulnerability to risk factors for PTSD.

As part of the longitudinal AURORA study, 2924 patients seeking emergency department (ED) treatment in the acute aftermath of trauma provided self-report assessments of pre- peri- and post-traumatic risk factors, as well as 3-month PTSD severity. We systematically examined sex-dependent effects of 16 risk factors that have previously been hypothesized to show different associations with PTSD severity in women and men.

Women reported higher PTSD severity at 3-months post-trauma. Z-score comparisons indicated that for five of the 16 examined risk factors the association with 3-month PTSD severity was stronger in men than in women. In multivariable models, interaction effects with sex were observed for pre-traumatic anxiety symptoms, and acute dissociative symptoms; both showed stronger associations with PTSD in men than in women. Subgroup analyses suggested trauma type-conditional effects.

Our findings indicate mechanisms to which men might be particularly vulnerable, demonstrating that known PTSD risk factors might behave differently in women and men. Analyses did not identify any risk factors to which women were more vulnerable than men, pointing toward further mechanisms to explain women's higher PTSD risk. Our study illustrates the need for a more systematic examination of sex differences in contributors to PTSD severity after trauma, which may inform refined preventive interventions.

The primary objective of this study was to determine whether Healthy Eating Index (HEI) and Alternative Healthy Eating Index (AHEI) scores were associated with incident metabolic syndrome.

This study is a secondary analysis of data from the Jackson Heart Study. HEI and AHEI scores were divided into quintiles and Cox proportional hazards regression models were analysed for 1864 African American adults free from metabolic syndrome at Exam 1 to examine the incidence of metabolic syndrome by quintile of dietary quality score.

Hinds, Madison and Rankin counties, Mississippi, USA.

African American adults, ages 21–94 years, 60·9 % female.

Over a mean follow-up time of 6·7 years, we observed 932 incident cases of metabolic syndrome. After adjusting for multiple covariates, a higher HEI score at Exam 1 was not associated with the risk of incident metabolic syndrome, except when looking at the trend analysis for the subgroup of adults with two metabolic syndrome components at Exam 1 (P-trend = 0·03). A higher AHEI score at Exam 1 was associated with the risk of incident metabolic syndrome (hazard ratio for those in the highest quintile compared to the lowest: 0·80 (95 % CI: 0·65, 0·99), P-trend = 0·03).

These findings suggest that a dietary pattern that scores higher on the AHEI may help reduce the risk of metabolic syndrome, even for adults who already have two of the minimum of three components required for a diagnosis of metabolic syndrome.

Parkinsonism and Parkinson's disease (PD) have been described as consequences of repetitive head impacts (RHI) from boxing, since 1928. Autopsy studies have shown that RHI from other contact sports can also increase risk for neurodegenerative diseases, including chronic traumatic encephalopathy (CTE) and Lewy bodies. In vivo research on the relationship between American football play and PD is scarce, with small samples, and equivocal findings. This study leveraged the Fox Insight study to evaluate the association between American football and parkinsonism and/or PD Diagnosis and related clinical outcomes.

Fox Insight is an online study of people with and without PD who are 18+ years (>50,000 enrolled). Participants complete online questionnaires on motor function, cognitive function, and general health behaviors. Participants self-reported whether they "currently have a diagnosis of Parkinson's disease, or parkinsonism, by a physician or other health care professional." In November 2020, the Boston University Head Impact Exposure Assessment was launched in Fox Insight for large-scale data collection on exposure to RHI from contact sports and other sources. Data used in this abstract were obtained from the Fox Insight database https://foxinsight-info.michaeljfox.org/insight/explore/insight.jsp on 01/06/2022. The sample includes 2018 men who endorsed playing an organized sport. Because only 1.6% of football players were women, analyses are limited to men. Responses to questions regarding history of participation in organized football were examined. Other contact and/or non-contact sports served as the referent group. Outcomes included PD status (absence/presence of parkinsonism or PD) and Penn Parkinson's Daily Activities Questionnaire-15 (PDAQ-15) for assessment of cognitive symptoms. Binary logistic regression tested associations between history and years of football play with PD status, controlling for age, education, current heart disease or diabetes, and family history of PD. Linear regressions, controlling for these variables, were used for the PDAQ-15.

Of the 2018 men (mean age=67.67, SD=9.84; 10, 0.5% Black), 788 (39%) played football (mean years of play=4.29, SD=2.88), including 122 (16.3%) who played youth football, 494 (66.0%) played high school, 128 (17.1%) played college football, and 5 (0.7%) played at the semi-professional or professional level. 1738 (86.1%) reported being diagnosed with parkinsonism/PD, and 707 of these were football players (40.7%). History of playing any level of football was associated with increased odds of having a reported parkinsonism or PD diagnosis (OR=1.52, 95% CI=1.14-2.03, p=0.004). The OR remained similar among those age <69 (sample median age) (OR=1.45, 95% CI=0.97-2.17, p=0.07) and 69+ (OR=1.45, 95% CI=0.95-2.22, p=0.09). Among the football players, there was not a significant association between years of play and PD status (OR=1.09, 95% CI=1.00-1.20, p=0.063). History of football play was not associated with PDAQ-15 scores (n=1980) (beta=-0.78, 95% CI=-1.59-0.03, p=0.059) among the entire sample.

Among 2018 men from a data set enriched for PD, playing organized football was associated with increased odds of having a reported parkinsonism/PD diagnosis. Next steps include examination of the contribution of traumatic brain injury and other sources of RHI (e.g., soccer, military service).

Former professional American football players have a high relative risk for neurodegenerative diseases like chronic traumatic encephalopathy (CTE). Interpreting low cognitive test scores in this population occasionally is complicated by performance on validity testing. Neuroimaging biomarkers may help inform whether a neurodegenerative disease is present in these situations. We report three cases of retired professional American football players who completed comprehensive neuropsychological testing, but “failed” performance validity tests, and underwent multimodal neuroimaging (structural MRI, Aß-PET, and tau-PET).

Three cases were identified from the Focused Neuroimaging for the Neurodegenerative Disease Chronic Traumatic Encephalopathy (FIND-CTE) study, an ongoing multimodal imaging study of retired National Football League players with complaints of progressive cognitive decline conducted at Boston University and the UCSF Memory and Aging Center. Participants were relatively young (age range 55-65), had 16 or more years of education, and two identified as Black/African American. Raw neuropsychological test scores were converted to demographically-adjusted z-scores. Testing included standalone (Test of Memory Malingering; TOMM) and embedded (reliable digit span, RDS) performance validity measures. Validity cutoffs were TOMM Trial 2 < 45 and RDS < 7. Structural MRIs were interpreted by trained neurologists. Aß-PET with Florbetapir was used to quantify cortical Aß deposition as global Centiloids (0 = mean cortical signal for a young, cognitively normal, Aß negative individual in their 20s, 100 = mean cortical signal for a patient with mild-to-moderate Alzheimer’s disease dementia). Tau-PET was performed with MK-6240 and first quantified as standardized uptake value ratio (SUVR) map. The SUVR map was then converted to a w-score map representing signal intensity relative to a sample of demographically-matched healthy controls.

All performed in the average range on a word reading-based estimate of premorbid intellect. Contribution of Alzheimer’s disease pathology was ruled out in each case based on Centiloids quantifications < 0. All cases scored below cutoff on TOMM Trial 2 (Case #1=43, Case #2=42, Case #3=19) and Case #3 also scored well below RDS cutoff (2). Each case had multiple cognitive scores below expectations (z < -2.0) most consistently in memory, executive function, processing speed domains. For Case #1, MRI revealed mild atrophy in dorsal fronto-parietal and medial temporal lobe (MTL) regions and mild periventricular white matter disease. Tau-PET showed MTL tau burden modestly elevated relative to controls (regional w-score=0.59, 72nd%ile). For Case #2, MRI revealed cortical atrophy, mild hippocampal atrophy, and a microhemorrhage, with no evidence of meaningful tau-PET signal. For Case #3, MRI showed cortical atrophy and severe white matter disease, and tau-PET revealed significantly elevated MTL tau burden relative to controls (w-score=1.90, 97th%ile) as well as focal high signal in the dorsal frontal lobe (overall frontal region w-score=0.64, 74th%ile).

Low scores on performance validity tests complicate the interpretation of the severity of cognitive deficits, but do not negate the presence of true cognitive impairment or an underlying neurodegenerative disease. In the rapidly developing era of biomarkers, neuroimaging tools can supplement neuropsychological testing to help inform whether cognitive or behavioral changes are related to a neurodegenerative disease.

There is increasing interest in examining a general psychopathology factor (p factor) in children and adolescents. In previous work, the relationship between the p factor and cognition in youth has largely focused on general intelligence (IQ) and executive functions (EF). Another cognitive construct, processing speed (PS), is dissociable from these cognitive constructs, but has received less research attention despite being related to many different mental health symptoms. This study aimed to examine the association between a latent processing speed factor and the p factor in youth.

The present sample included 795 youth, ages 11-16 from the Colorado Learning Disability Research Center (CLDRC) sample. Confirmatory factor analyses tested multiple p factor models, with the primary model being a novel second-order, multireporter p factor where caregivers reported on externalizing symptoms (oppositional defiant disorder and conduct disorder modules from the Diagnostic Interview for Children and Adolescents [DICA]; aggression, delinquency, and attention problems subscales from the Child Behavior Checklist; and inattentive and hyperactive/impulsive subscales from the Disruptive Behavior Rating Scale) and youth self-reported on internalizing symptoms (Child Depression Inventory, generalized anxiety module from the DICA, and withdrawn, anxious/depression, and somatic subscales from the Youth Self Report). We then tested the correlation between the p factor and a latent PS factor. The latent PS factor was composed of WISC Symbol Search, WISC Coding, Colorado Perceptual Speed Test, and Identical Pictures Test. Three secondary p factor models were examined for comparison to previous literature, including (1) a bifactor, multi-reporter model, (2) a second-order model with just caregiver-report, and (3) a bifactor model with just caregiver-report.

There was a significant, negative correlation between the p factor and PS (r=-0.42, p<.001), indicating that slower processing speed is associated with higher general mental health symptoms. This finding was robust across models that used different raters (youth and caregiver-report vs. caregiver-report only) and modeling approaches (second-order vs. bifactor). This association is stronger than previously reported associations with IQ or EF in the p factor literature. Further, in this sample, we found that the association between PS and the p factor was robust to covariation for general cognition, whereas the correlation between general cognition and the p factor was fully accounted for by PS.

Our findings indicate that PS is related to general psychopathology symptoms, expanding the existing literature relating PS to specific, distinct disorders by showing that PS is related to what is shared across psychopathology. As cognition and psychopathology both undergo significant development across childhood and adolescence, elucidating neurodevelopmental mechanisms that relate to risk for a broad range of symptoms may be critical to informing early intervention and prevention approaches. This research points to processing speed as an important transdiagnostic construct that warrants further attention and exploration across development.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.

Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.

Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.

Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Cognitive symptoms are common during and following episodes of depression. Little is known about the persistence of self-reported and performance-based cognition with depression and functional outcomes.

This is a secondary analysis of a prospective naturalistic observational clinical cohort study of individuals with recurrent major depressive disorder (MDD; N = 623). Participants completed app-based self-reported and performance-based cognitive function assessments alongside validated measures of depression, functional disability, and self-esteem every 3 months. Participants were followed-up for a maximum of 2-years. Multilevel hierarchically nested modelling was employed to explore between- and within-participant variation over time to identify whether persistent cognitive difficulties are related to levels of depression and functional impairment during follow-up.

508 individuals (81.5%) provided data (mean age: 46.6, s.d.: 15.6; 76.2% female). Increasing persistence of self-reported cognitive difficulty was associated with higher levels of depression and functional impairment throughout the follow-up. In comparison to low persistence of objective cognitive difficulty (<25% of timepoints), those with high persistence (>75% of timepoints) reported significantly higher levels of depression (B = 5.17, s.e. = 2.21, p = 0.019) and functional impairment (B = 4.82, s.e. = 1.79, p = 0.002) over time. Examination of the individual cognitive modules shows that persistently impaired executive function is associated with worse functioning, and poor processing speed is particularly important for worsened depressive symptoms.

We replicated previous findings of greater persistence of cognitive difficulty with increasing severity of depression and further demonstrate that these cognitive difficulties are associated with pervasive functional disability. Difficulties with cognition may be an indicator and target for further treatment input.

Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an exciting opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks.

To describe the amount of data collected during a multimodal longitudinal RMT study, in an MDD population.

RADAR-MDD is a multi-centre, prospective observational cohort study. People with a history of MDD were provided with a wrist-worn wearable, and several apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks and cognitive assessments and followed-up for a maximum of 2 years.

A total of 623 individuals with a history of MDD were enrolled in the study with 80% completion rates for primary outcome assessments across all timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. Data availability across all RMT data types varied depending on the source of data and the participant-burden for each data type. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. 110 participants had > 50% data available across all data types, and thus able to contribute to multiparametric analyses.

RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible.

No significant relationships.

Racial and ethnic groups in the USA differ in the prevalence of posttraumatic stress disorder (PTSD). Recent research however has not observed consistent racial/ethnic differences in posttraumatic stress in the early aftermath of trauma, suggesting that such differences in chronic PTSD rates may be related to differences in recovery over time.

As part of the multisite, longitudinal AURORA study, we investigated racial/ethnic differences in PTSD and related outcomes within 3 months after trauma. Participants (n = 930) were recruited from emergency departments across the USA and provided periodic (2 weeks, 8 weeks, and 3 months after trauma) self-report assessments of PTSD, depression, dissociation, anxiety, and resilience. Linear models were completed to investigate racial/ethnic differences in posttraumatic dysfunction with subsequent follow-up models assessing potential effects of prior life stressors.

Racial/ethnic groups did not differ in symptoms over time; however, Black participants showed reduced posttraumatic depression and anxiety symptoms overall compared to Hispanic participants and White participants. Racial/ethnic differences were not attenuated after accounting for differences in sociodemographic factors. However, racial/ethnic differences in depression and anxiety were no longer significant after accounting for greater prior trauma exposure and childhood emotional abuse in White participants.

The present findings suggest prior differences in previous trauma exposure partially mediate the observed racial/ethnic differences in posttraumatic depression and anxiety symptoms following a recent trauma. Our findings further demonstrate that racial/ethnic groups show similar rates of symptom recovery over time. Future work utilizing longer time-scale data is needed to elucidate potential racial/ethnic differences in long-term symptom trajectories.

There are minimal data directly comparing plasma neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) in aging and neurodegenerative disease research. We evaluated associations of plasma NfL and plasma GFAP with brain volume and cognition in two independent cohorts of older adults diagnosed as clinically normal (CN), mild cognitive impairment (MCI), or Alzheimer’s dementia.

We studied 121 total participants (Cohort 1: n = 50, age 71.6 ± 6.9 years, 78% CN, 22% MCI; Cohort 2: n = 71, age 72.2 ± 9.2 years, 45% CN, 25% MCI, 30% dementia). Gray and white matter volumes were obtained for total brain and broad subregions of interest (ROIs). Neuropsychological testing evaluated memory, executive functioning, language, and visuospatial abilities. Plasma samples were analyzed in duplicate for NfL and GFAP using single molecule array assays (Quanterix Simoa). Linear regression models with structural MRI and cognitive outcomes included plasma NfL and GFAP simultaneously along with relevant covariates.

Higher plasma GFAP was associated with lower white matter volume in both cohorts for temporal (Cohort 1: β = −0.33, p = .002; Cohort 2: β = −0.36, p = .03) and parietal ROIs (Cohort 1: β = −0.31, p = .01; Cohort 2: β = −0.35, p = .04). No consistent findings emerged for gray matter volumes. Higher plasma GFAP was associated with lower executive function scores (Cohort 1: β = −0.38, p = .01; Cohort 2: β = −0.36, p = .007). Plasma NfL was not associated with gray or white matter volumes, or cognition after adjusting for plasma GFAP.

Plasma GFAP may be more sensitive to white matter and cognitive changes than plasma NfL. Biomarkers reflecting astroglial pathophysiology may capture complex dynamics of aging and neurodegenerative disease.

To develop a fully automated algorithm using data from the Veterans’ Affairs (VA) electrical medical record (EMR) to identify deep-incisional surgical site infections (SSIs) after cardiac surgeries and total joint arthroplasties (TJAs) to be used for research studies.

Retrospective cohort study.

This study was conducted in 11 VA hospitals.

Patients who underwent coronary artery bypass grafting or valve replacement between January 1, 2010, and March 31, 2018 (cardiac cohort) and patients who underwent total hip arthroplasty or total knee arthroplasty between January 1, 2007, and March 31, 2018 (TJA cohort).

Relevant clinical information and administrative code data were extracted from the EMR. The outcomes of interest were mediastinitis, endocarditis, or deep-incisional or organ-space SSI within 30 days after surgery. Multiple logistic regression analysis with a repeated regular bootstrap procedure was used to select variables and to assign points in the models. Sensitivities, specificities, positive predictive values (PPVs) and negative predictive values were calculated with comparison to outcomes collected by the Veterans’ Affairs Surgical Quality Improvement Program (VASQIP).

Overall, 49 (0.5%) of the 13,341 cardiac surgeries were classified as mediastinitis or endocarditis, and 83 (0.6%) of the 12,992 TJAs were classified as deep-incisional or organ-space SSIs. With at least 60% sensitivity, the PPVs of the SSI detection algorithms after cardiac surgeries and TJAs were 52.5% and 62.0%, respectively.

Considering the low prevalence rate of SSIs, our algorithms were successful in identifying a majority of patients with a true SSI while simultaneously reducing false-positive cases. As a next step, validation of these algorithms in different hospital systems with EMR will be needed.

Due to shortages of N95 respirators during the coronavirus disease 2019 (COVID-19) pandemic, it is necessary to estimate the number of N95s required for healthcare workers (HCWs) to inform manufacturing targets and resource allocation.

We developed a model to determine the number of N95 respirators needed for HCWs both in a single acute-care hospital and the United States.

For an acute-care hospital with 400 all-cause monthly admissions, the number of N95 respirators needed to manage COVID-19 patients admitted during a month ranges from 113 (95% interpercentile range [IPR], 50–229) if 0.5% of admissions are COVID-19 patients to 22,101 (95% IPR, 5,904–25,881) if 100% of admissions are COVID-19 patients (assuming single use per respirator, and 10 encounters between HCWs and each COVID-19 patient per day). The number of N95s needed decreases to a range of 22 (95% IPR, 10–43) to 4,445 (95% IPR, 1,975–8,684) if each N95 is used for 5 patient encounters. Varying monthly all-cause admissions to 2,000 requires 6,645–13,404 respirators with a 60% COVID-19 admission prevalence, 10 HCW–patient encounters, and reusing N95s 5–10 times. Nationally, the number of N95 respirators needed over the course of the pandemic ranges from 86 million (95% IPR, 37.1–200.6 million) to 1.6 billion (95% IPR, 0.7–3.6 billion) as 5%–90% of the population is exposed (single-use). This number ranges from 17.4 million (95% IPR, 7.3–41 million) to 312.3 million (95% IPR, 131.5–737.3 million) using each respirator for 5 encounters.

We quantified the number of N95 respirators needed for a given acute-care hospital and nationally during the COVID-19 pandemic under varying conditions.