Assessment of microplastics pollution level on clam farming and bathing beaches: a case study of Thanh Phu in Ben Tre, Vietnam.

This study focused on the investigation microplastics (MPs) with a size of ≤1.0 mm in sand samples from Thanh Phu beach, Ben Tre, Vietnam. MPs in sand from the clam beach (from 39.67 ± 6.67 to 92.00 ± 12.93 items kg-1 dried sand) were higher than those from the bathing beach (from 21.33 ± 8.76 to 51.67 ± 16.11 items kg-1 dried sand), indicating a direct contribution of MPs from coastal aquaculture. For the clam beach, MPs in surface samples (0-4 cm) were lower than in deep samples (4-6 cm). In contrast, MPs in surface samples (0-2 cm) from the bathing beach were higher than deep samples (2-5 cm). A combination of microscopy and Fourier-transform infrared spectroscopy methods confirmed that 62.5% of the representative MPs samples or 18.9% of the suspected MPs samples were plastics. Low-density polyethylene, polypropylene and polyethylene terephthalate were the largest in abundance. Further studies are needed to assess the environmental risk of MPs accumulation.

Dry eye rate and its relationship with disease stage in patients with primary hypertension: a cross-sectional study in Vietnam.

AIM: To determine the dry eye (DE) rate and its relationship with disease stage in patients with primary hypertension. METHODS: A cross-sectional study included 432 patients with primary hypertension (with an equal number of patients in each group: 144 in stage I, II, and III hypertension) and 144 healthy subjects as a control group. The Ocular Surface Disease Index (OSDI) and Schirmer I test without anesthetics were conducted on all 576 subjects. Subjects with OSDI scores <13 and Schirmer I values equal to or under 10 mm were diagnosed with DE. RESULTS: The ratio of DE in hypertension patients was higher than in the control group (41.7% versus 18.8%; P<0.001). The proportion of patients with DE increased gradually according to the hypertension stage: 27.1% in stage I, 40.3% in stage II, and 57.6% in stage III, P<0.001. Age, duration of hypertension, plasma urea, creatinine, and high-sensitivity C-reactive protein (CRP-hs) levels in hypertension patients with DE were higher than those without DE, P<0.001. Advanced age, a long duration of hypertension, diabetes mellitus, elevated plasma creatinine, and CRP-hs levels were independent factors associated with DE in primary hypertension patients, P<0.001. CONCLUSION: DE is a common disorder associated with advanced age, a long duration of hypertension, diabetes mellitus, elevated plasma CRP-hs, and creatinine levels in patients with primary hypertension.

Quiescence enables unrestricted cell fate in naive embryonic stem cells.

Quiescence in stem cells is traditionally considered as a state of inactive dormancy or with poised potential. Naive mouse embryonic stem cells (ESCs) can enter quiescence spontaneously or upon inhibition of MYC or fatty acid oxidation, mimicking embryonic diapause in vivo. The molecular underpinning and developmental potential of quiescent ESCs (qESCs) are relatively unexplored. Here we show that qESCs possess an expanded or unrestricted cell fate, capable of generating both embryonic and extraembryonic cell types (e.g., trophoblast stem cells). These cells have a divergent metabolic landscape comparing to the cycling ESCs, with a notable decrease of the one-carbon metabolite S-adenosylmethionine. The metabolic changes are accompanied by a global reduction of H3K27me3, an increase of chromatin accessibility, as well as the de-repression of endogenous retrovirus MERVL and trophoblast master regulators. Depletion of methionine adenosyltransferase Mat2a or deletion of Eed in the polycomb repressive complex 2 results in removal of the developmental constraints towards the extraembryonic lineages. Our findings suggest that quiescent ESCs are not dormant but rather undergo an active transition towards an unrestricted cell fate.

A comparison of severity of illness between the SARS-CoV-2 Omicron variant and Delta variant.

Background: The COVID-19 pandemic has disproportionally affected traditionally marginalized groups. Both the Delta and Omicron variants raised concern amongst public health officials due to potentially higher infectivity rates and disease severity than prior variants. This study sought to compare disease severity between adults infected with the Omicron variant and adults infected with the Delta variant who presented to the Emergency Department at an academic, safety-net hospital in Virginia. Methods: This retrospective cohort study used electronic medical record data of patients who presented to the Emergency Department and received a positive SARS-CoV-2 test between September 1, 2021, and January 31, 2022. Positive tests were stratified by genotypic variant through whole genome sequencing. Participants with the Omicron variant were propensity scores matched with individuals with the Delta variant. Results: Among 500 Delta and 500 Omicron participants, 279 propensity score-matched pairs were identified. Participants were predominantly unvaccinated, with medical comorbidities, and self-identified as Black. Individuals infected with the Delta variant had more severe disease compared to those with the Omicron variant, regardless of vaccination status. Patients with kidney, liver, and respiratory disease, as well as cancer, are at higher risk for severe disease. Patients with 2 doses of COVID-19 immunization trended toward less severe disease. Conclusions: Overall, these data further support the literature regarding the disproportionate effects of the COVID-19 pandemic on vulnerable patient populations - such as those with limited access to care, people of color, and those with chronic medical conditions - and can be used to inform public health interventions.

Prevalence and impact of metabolic syndrome on in-hospital outcomes in patients with acute myocardial infarction: A perspective from a developing country.

Acute myocardial infarction (AMI) often suffers from a high prevalence of metabolic syndrome (MetS). However, few studies in developing countries have focused on the effect of MetS on in-hospital outcomes in patients with AMI. We analyzed 199 patients with AMI who underwent primary percutaneous coronary intervention. This study aimed to determine the impact of MetS and factors related to in-hospital outcomes in patients with AMI. The study included 199 patients who met the criteria, with a mean age of 64.5 ±â€…11.3 years. Out Of the total number of patients, 136 (68.3%) were found to have MetS. Patients with MetS were more likely to be female, have a higher body mass index, larger waist circumference, and a higher prevalence of hypertension and diabetes than those without MetS. The rates of major complications, such as cardiogenic shock, heart failure, mechanical complications, and arrhythmias, were not significantly different between the 2 groups. MetS was not associated with in-hospital mortality with OR, 4.92 (95% CI 0.62-39.31, P = .13). In this study, increased waist circumference was associated with an increased all-cause mortality rate. However, the MetS group had a significantly higher rate of cardiovascular mortality than the group without MetS (P = .03). Among patients with AMI, the prevalence of metabolic syndrome was high. Patients with MetS did not exhibit an increased all-cause in-hospital mortality rate. Increased waist circumference is associated with increased all-cause mortality.

Key Role of Corncob Based-Hydrochar (HC) in the Enhancement of Visible Light Photocatalytic Degradation of 2,4-Dichlorophenoxyacetic Acid Using a Derivative of ZnBi-Layered Double Hydroxides.

A superior heterojunction of HC-ZnBi-LDO was synthesized in two steps, namely hydrothermal carbonization, followed by co-precipitation. The 2% HC-ZnBi-LDO heterojunction photocatalysts could degrade over 90.8% of 30 mg/L 2,4-dichlorophenoxyacetic acid (2,4-D) using 1.0 g/L of the catalyst after 135 min of visible light exposure at pH 4. The activity of 2% HC-ZnO-LDO was remarkably stable. Approximately 86.4-90.8% of 30 mg/L 2,4-D was degraded, and more than 79-86.4% of TOC was mineralized by 2% HC-ZnBi-LDO at pH 4 after 135 min of visible light exposure during four consecutive cycles. The rapid separation and migration of charge carriers at the interfaces between HC and ZnBi-LDO were achieved within 2% HC-ZnBi-LDO. Moreover, the electron acceptor characteristic of HC in 2% HC-ZnBi-LDO caused the recombination of charge carriers to decrease significantly, thus generating more reactive radicals, such as hydroxyl radicals (OH●) and superoxide radicals (O2●-). These results demonstrate that the novel 2% HC-ZnBi-LDO is a superior photocatalyst for the remediation of hazardous organic pollutants.

Endovascular management of massive hemoptysis due to pulmonary artery pseudoaneurysm in a COVID-19 patient in Vietnam: A case report.

Pulmonary artery pseudoaneurysm with massive hemoptysis is extremely rare in patients with coronavirus disease 2019 (COVID-19)-induced pneumonia, especially in its late stage. We report a case who presented with massive hemoptysis and pulmonary artery pseudoaneurysm without pulmonary thromboembolism in their ninth week of COVID-19 infection, which was treated by endovascular embolization. The endovascular intervention was technically and clinically successful, with complete hemoptysis cessation after the procedure. This is the first case reported in Vietnam.

Prediction of obstructive coronary artery disease in patients undergoing heart valve surgery: A cross-sectional study in a tertiary care hospital.

Introduction: Estimating the probability of obstructive coronary artery disease in patients undergoing noncoronary cardiac surgery should be considered compulsory. Our study sought to evaluate the prevalence of obstructive coronary artery disease in patients undergoing valvular heart surgery and to utilize predictive methodology of concomitant obstructive coronary artery disease in these patients. Methods: The retrospective study cohort was derived from a tertiary care hospital registry of patients undergoing coronary angiogram prior to valvular heart operations. Decision tree, logistic regression, and support vector machine models were built to predict the probability of the appearance of obstructive coronary artery disease. A total of 367 patients from 2016 to 2019 were analyzed. Results: The mean age of the study population was 57.3±9.3 years, 45.2% of the patients were male. Of 367 patients, 76 (21%) patients had obstructive coronary artery disease. The decision tree, logistics regression, and support vector machine models had an area under the curve of 72% (95% CI: 62% - 81%), 67% (95% CI: 56% - 77%), and 78% (95% CI: 68% - 87%), respectively. Multivariate analysis indicated that hypertension (OR 1.98; P=0.032), diabetes (OR 2.32; P=0.040), age (OR 1.05; P=0.006), and typical angina (OR 5.46; P<0.001) had significant role in predicting the presence of obstructive coronary artery disease. Conclusion: Our study revealed that approximately one-fifth of patients who underwent valvular heart surgery had concomitant obstructive coronary artery disease. The support vector machine model showed the highest accuracy compared to the other model.

Endovascular management of giant post-traumatic pseudoaneurysm in cavernous sinus: A case report.

A 20-year-old male was admitted with the history of a traumatic head injury after traffic accident. The physical examination revealed blurred vision, swelling of the right face, and minor epistaxis. CT and MRI findings revealed a giant pseudoaneurysm of cavernous carotid artery. The patient was enrolled endovascular coils embolization of the internal carotid artery. After the procedure, the patient recovered well. Endovascular treatment is an effective therapy in cavernous carotid pseudoaneurysm.

Endovascular management of rectus abdominis hematoma: A report of two cases.

Nontraumatic spontaneous hematoma of the rectus abdominis is frequently related to anticoagulation therapy. In most cases, this condition is spontaneously self-limited or can be controlled with conservative therapy. Nevertheless, in some patients, despite early and adequate medical therapy, continuous development of the condition requires rapid and complete hemostasis. Currently, endovascular management by selective transarterial embolization of the bleeding vessel is the most common treatment option. We report 2 cases of endovascular management of rectus abdominis hematoma using a mixture of n-butylcyanoacrylate and lipiodol to embolize the bleeding point of the superior epigastric artery. Clinical symptoms improved without noticeable complications.

Classification of Tetanus Severity in Intensive-Care Settings for Low-Income Countries Using Wearable Sensing.

Infectious diseases remain a common problem in low- and middle-income countries, including in Vietnam. Tetanus is a severe infectious disease characterized by muscle spasms and complicated by autonomic nervous system dysfunction in severe cases. Patients require careful monitoring using electrocardiograms (ECGs) to detect deterioration and the onset of autonomic nervous system dysfunction as early as possible. Machine learning analysis of ECG has been shown of extra value in predicting tetanus severity, however any additional ECG signal analysis places a high demand on time-limited hospital staff and requires specialist equipment. Therefore, we present a novel approach to tetanus monitoring from low-cost wearable sensors combined with a deep-learning-based automatic severity detection. This approach can automatically triage tetanus patients and reduce the burden on hospital staff. In this study, we propose a two-dimensional (2D) convolutional neural network with a channel-wise attention mechanism for the binary classification of ECG signals. According to the Ablett classification of tetanus severity, we define grades 1 and 2 as mild tetanus and grades 3 and 4 as severe tetanus. The one-dimensional ECG time series signals are transformed into 2D spectrograms. The 2D attention-based network is designed to extract the features from the input spectrograms. Experiments demonstrate a promising performance for the proposed method in tetanus classification with an F1 score of 0.79 ± 0.03, precision of 0.78 ± 0.08, recall of 0.82 ± 0.05, specificity of 0.85 ± 0.08, accuracy of 0.84 ± 0.04 and AUC of 0.84 ± 0.03.

The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021.

Background: Tackling the spread of COVID-19 remains a crucial part of ending the pandemic. Its highly contagious nature and constant evolution coupled with a relative lack of immunity make the virus difficult to control. For this, various strategies have been proposed and adopted including limiting contact, social isolation, vaccination, contact tracing, etc. However, given the heterogeneity in the enforcement of these strategies and constant fluctuations in the strictness levels of these strategies, it becomes challenging to assess the true impact of these strategies in controlling the spread of COVID-19. Methods: In the present study, we evaluated various transmission control measures that were imposed in 10 global urban cities and provinces in 2021- Bangkok, Gauteng, Ho Chi Minh City, Jakarta, London, Manila City, New Delhi, New York City, Singapore, and Tokyo. Findings: Based on our analysis, we herein propose the population-level Swiss cheese model for the failures and pitfalls in various strategies that each of these cities and provinces had. Furthermore, whilst all the evaluated cities and provinces took a different personalized approach to managing the pandemic, what remained common was dynamic enforcement and monitoring of breaches of each barrier of protection. The measures taken to reinforce the barriers were adjusted continuously based on the evolving epidemiological situation. Interpretation: How an individual city or province handled the pandemic profoundly affected and determined how the entire country handled the pandemic since the chain of transmission needs to be broken at the very grassroot level to achieve nationwide control. Funding: The present study did not receive any external funding.

Predicting Anxiety and Depression Among Patients With COVID-19 in Concentrated Isolation at Medical Camps in Vietnam: A Descriptive Cross-Sectional Study.

Introduction: This study aims to assess the requirement for anxiety and depression treatment for patients with coronavirus disease 2019 (COVID-19) in medical camps in Bac Giang province, Vietnam. This information can help improve the government policy to reduce anxiety and depression in patients with COVID-19. Methods: A total of patients with 427 COVID-19 participated in the survey conducted from 5 to 15 June 2021 in Bac Giang province. The survey included 17 questions about the general characteristics of the patients, 15 questions to assess common COVID-19 symptoms, the Patient Health Questionnaire-9 (PHQ-9), and General Anxiety Disorder-7 (GAD-7) scores, and four questions to assess hospital reviews, including facilities, food, medical staff, and living conditions. Logistics regression analyses were conducted to assess the association between COVID-19 symptoms and high anxiety and depression (HAD) status. Results: A logistic regression analysis evaluated the risk factors in need of intervention. Our study showed that lower hospital review scores (odd ratio = 0.98; 95% confident interval = 0.97-0.99) were found to be a risk needing intervention. It was also identified that older patients (odd ratio = 1.1; 95% confident interval = 1.03-1.18), women (odd ratio = 1.31; 95% confident interval = 1.09-1.31), patients who were primary income earners in the family (odd ratio = 1.15; 95% confident interval = 1.03-1.28), patients who had headaches (odd ratio = 1.16; 95% confident interval = 1.06-1.21), and patients who had joint pain (odd ratio = 1.17; 95% confident interval = 1.06- 1.3) were risk factors for HAD status. Conclusion: Our research shows that every 10-year age increase was associated with a 10% increase in the likelihood of HAD status. Study subjects being primary income earners were also associated with a 15% increased risk of having HAD status. This study showed that a decrease in family income due to COVID-19 caused an increase in high-level anxiety/depression status.

Chest X-ray Severity Score as a Putative Predictor of Clinical Outcome in Hospitalized Patients: An Experience From a Vietnamese COVID-19 Field Hospital.

Background Through the coronavirus disease 2019 (COVID-19) pandemic, portable radiography was particularly useful for assessing and monitoring the COVID-19 disease in Vietnamese field hospitals. It provides a convenient and precise picture of the progression of the disease. The purpose of this study was to evaluate the predictive value of chest radiograph reporting systems (Brixia and total severity score (TSS)) and the National Early Warning Score (NEWS) clinical score in a group of hospitalized patients with COVID-19. Methods This retrospective cohort study used routinely collected clinical data from polymerase chain reaction (PCR)-positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients admitted to Field Hospital District 8, Ho Chi Minh City, Vietnam, from August 2021 to September 2021. The initial chest radiographs were scored based on the TSS and Brixia scoring systems to quantify the extent of lung involvement. After the chest radiograph score was reported, two residents calculated the rate of all-cause in-hospital mortality with the consultation of expert radiologists. In this study, NEWS2 scores on hospital admission were calculated. The gradient boosting machines (GBMs) and Shapley additive exPlanations (SHAP) were applied to access the important variable and improve the accuracy of mortality prediction. The adjusted odds ratio for predictor was presented by univariate analysis and multivariate analysis. Results The chest X-rays (CXRs) at the admission of 273 patients (mean age 59 years +/-16, 42.1% were male) were scored. In the univariate analysis, age, vaccination status, previous disease, NEWS2, a saturation of peripheral oxygen (Sp02), the Brixia and TSS scores were significant predictors of mortality (p-value < 0.05). In multivariate analysis, there were statistically significant differences in mortality between age, Sp02, Brixia score, and patients with previous diseases were independent predictors of mortality and hospitalization. A gradient boosting machine was performed in the train data set, which showed that the best hyperparameters for predicting the mortality of patients are the Brixia score (exclude TSS score). In the top five predictors, an increase in Brixia, age, and BMI increased the logarithmic number of probability clarifying as death status. Although the TSS and Brixia scores evaluated chest imaging, the TSS score was not essential as the Brixia score (rank 6/11). It was clear that the BMI and NEWS2 score was positively correlated with the Brixia score, and age did not affect this correlation. Meanwhile, we did not find any trend between the TSS score versus BMI and NEWS2. Conclusion When integrated with the BMI and NEWS2 clinical classification systems, the severity score of COVID-19 chest radiographs, particularly the Brixia score, was an excellent predictor of all-cause in-hospital mortality.

Antibiotic usage in surgical sperm retrievals among IVF centers.

Surgical sperm retrieval (SSR) is currently one of the most common procedures in in vitro fertilization (IVF). However, a gap between the guidelines and routine clinical practice regarding antibiotic use in SSR, which might lead to antibiotic resistance, is a challenging problem worldwide. A cross-sectional survey was conducted from May 1, 2021, to July 15, 2021, to investigate antibiotic usage by medical professionals when performing SSR in IVF centers in Vietnam. The confidential questionnaire comprised 12 items, including characteristics of the study population, awareness of antimicrobial resistance, attitude toward prescribing antibiotics, and current practice of prescribing antibiotics when performing SSR. Surveys were completed by 30 of 45 registered IVF centers (66.7%). Among 67 physicians working at those centers, the age and work-experience years (mean ± standard deviation [s.d.]) were 38.6 ± 6.6 years and 11.2 ± 7.0 years, respectively. Over 60% of them held a degree in Obstetrics and Gynecology, and over four-fifths were men. Most respondents "often/very often/always" raised awareness of antimicrobial resistance to their patients (83.3%), but only half of them "often/occasionally" prescribed antibiotics to patients with SSR in cases where the prescription would be optional. About one-tenth of respondents followed the recommendation from the American Urological Association using "prophylaxis only" for SSR patients. For more invasive SSR, physicians tended to prescribe more complicated and sometimes inappropriate regimens. In conclusion, antibiotic usage in SSR was not always appropriate among IVF centers. Further studies may define specific recommendations for regimens, intervention strategies, and programs to promote appropriate antibiotic use for SSR patients among IVF specialists.

The effects of the COVID-19 lockdown on patients with chronic cardiovascular disease in Vietnam.

INTRODUCTION: We evaluated the impact of the lockdown policy during the COVID-19 pandemic on cardiovascular outpatients of a cardiology clinic in Vietnam from April to June 2020. We estimated the occurrence of different cardiovascular problems in general and the stability of blood pressure. METHODOLOGY: During the Covid-19 outbreak in Vietnam, we conducted a cross-sectional study to evaluate its impact on blood pressure stability of hypertensive patients treated as outpatients at the clinic of the University Medical Center (UMC), Ho Chi Minh City. RESULTS: The mean age of the recruited 493 patients was 62.2 ± 10.2 years. The stable blood pressure group consisted of 87% patients, while the unstable blood pressure group consisted of 13% patients. We found that 68% of the study population attended their follow-up appointments as scheduled: 87% with stable blood pressure versus only 13% with unstable blood pressure. Significant differences were noticed in body weight changes and cardiovascular problems between the two groups: body weight increase (22.6% vs. 10.2%), body weight decrease (3.2% vs. 6.7%), worsening of cardiovascular problems (35.5% vs. 17.9%) in the unstable and stable blood pressure groups, respectively. Multivariable regression analysis reflected the impact of the increase in body weight and occurrence of cardiovascular problems on the patients with unstable blood pressure. CONCLUSIONS: Our study provided concrete proof of the impact of the lockdown on chronic patients, which should warrant further surveys, and evaluation of the lockdown policy.

Regional personality assessment through social media language.

OBJECTIVE: We explore the personality of counties as assessed through linguistic patterns on social media. Such studies were previously limited by the cost and feasibility of large-scale surveys; however, language-based computational models applied to large social media datasets now allow for large-scale personality assessment. METHOD: We applied a language-based assessment of the five factor model of personality to 6,064,267 U.S. Twitter users. We aggregated the Twitter-based personality scores to 2,041 counties and compared to political, economic, social, and health outcomes measured through surveys and by government agencies. RESULTS: There was significant personality variation across counties. Openness to experience was higher on the coasts, conscientiousness was uniformly spread, extraversion was higher in southern states, agreeableness was higher in western states, and emotional stability was highest in the south. Across 13 outcomes, language-based personality estimates replicated patterns that have been observed in individual-level and geographic studies. This includes higher Republican vote share in less agreeable counties and increased life satisfaction in more conscientious counties. CONCLUSIONS: Results suggest that regions vary in their personality and that these differences can be studied through computational linguistic analysis of social media. Furthermore, these methods may be used to explore other psychological constructs across geographies.

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

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 naive 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 StatementThis 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.