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Bivalent COVID-19 vaccines that contain two mRNAs encoding Wuhan-1 and Omicron BA.4/5 spike proteins are successful in preventing infection from the original strain and Omicron variants, but the quality of adaptive immune responses is still not well documented. This study aims at characterizing adaptive immune responses to the bivalent booster vaccination in 46 healthy participants. Plasma and PBMC were collected prior and three weeks after bivalent booster. We measured anti-N, anti-S, and RBD IgM, IgA, IgG plasma titers against original, Omicron BA.1, and BA.5 variants (pending) as well as total anti-S IgG titers and surrogate Virus Neutralization capacity against the Alpha, Delta, and BA.1 variant. With spectral flow-cytometry we identified peripheral blood B-cells specific for the RBD of the S-protein of the original and BA.1 variants. T-cell-specific responses were assessed by cytokine release assay after stimulation with SARS-CoV-2 peptides from the original, BA.1, BA.4, and BA.5 variants (pending). Finally, we performed TRB and IGH repertoire studies on sorted CD4+, CD8+, CD19+ lymphocytes, to study breadth of SARS-CoV-2 specific clonotypes (pending). 27/46 participants were analyzed;9 had SARS-CoV-2 infection (COVID+), while 18 are infection naive (COVID-). In both groups, median time since last dose of SARS-CoV-2 vaccine (3rd or 4th) was 11 months. All subjects were positive for anti-S IgG prior to bivalent booster. The COVID + group displayed anti-S IgG pre-booster levels and neutralization against BA.1 higher than the COVID- group. Significant increase post-boost of total anti-S IgG and BA.1 neutralizing activity was detected in the COVID- but not in the COVID+ group;however, no difference in neutralization activity post-boost was detected between the two groups. Furthermore, the COVIDgroup showed significant increase in the frequency of CD19+ and CD27+ switched memory B-cells specific for BA.1 RBD in post-boost compared to pre-boost samples. However, post-boost frequencies of the same B-cells were higher in the COVID+ compared to the COVID- group. These preliminary findings confirm that among individual immunized with the original COVID-19 mRNAvaccine, prior COVID infection provides increased protection against SARS-CoV-2 variants. They also demonstrate that booster immunization with the bivalent vaccine induces robust adaptive immune responses against Omicron variant.[Formula presented][Formula presented]Copyright © 2023 Elsevier Inc.
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Background & Aim: The long-term effects of human mesenchymal stem cell (MSC) treatment on COVID-19 patients have not been fully characterized. The aim of this study was to evaluate the safety and efficacy of a MSC treatment administered to severe COVID-19 patients enrolled in a randomized, double-blind, placebo-controlled clinical trial (NCT 04288102). Methods, Results & Conclusion(s): A total of 100 patients experiencing severe COVID-19 received either MSC treatment (n = 65, 4x107 cells per infusion) or a placebo (n = 35) combined with standard of care on days 0, 3, and 6. Patients were subsequently evaluated 18 and 24 months after treatment to evaluate the long-term safety and efficacy of the MSC treatment. The outcomes measured included: 6-minute walking distance (6-MWD), lung imaging, quality of life according to the Short Form 36 questionnaire, COVID-19-related symptoms, titers of SARS-CoV-2 neutralizing antibodies, MSC-related adverse events (AEs), and tumor markers. Two years after treatment, a marginally smaller proportion of patients had a 6-MWD below the lower limit of the normal range in the MSC group than in the placebo group (OR = 0.19, 95% CI: 0.04-0.80, Fisher's exact test, p = 0.015). On the SF-36 questionnaire, a marginally higher general health score was received by the MSC group at month 18 compared with the placebo group (50.00 vs. 35.00;95% CI: 0.00-20.00, Wilcoxon rank sum test, p = 0.016). In contrast, there were no differences in the total severity score of lung imaging or the titer of neutralizing antibodies between the two groups. Meanwhile, there were no MSC-related AEs reported at the 18- or 24-month follow-ups. The serum levels of most of the tumor markers examined remained within normal ranges and were similar between the MSC and placebo groups. Long-term safety was observed for the COVID-19 patients who received MSC treatment. Yet few sustained efficacy of MSC treatment was observed at the end of the 2-year follow-up period. Funding(s): The National Key Research and Development Program of China (2022YFA1105604, 2020YFC0860900), the specific research fund of The Innovation Platform for Academicians of Hainan Province (YSPTZX202216) and the Fund of National Clinical Center for Infectious Diseases, PLA General Hospital (NCRCID202105,413FZT6). [Figure presented]Copyright © 2023 International Society for Cell & Gene Therapy
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The epidemiological data were collected from travellers who returned from Guinea on the 23rd of September, 2020 and were diagnosed with malaria at a C OVID -19 quarantine site in Qingdao, Shandong Province. The epidemiological characteristics, diagnosis and treatment of the cases and the epidemiology investigation and the rapid test screening results for other travellers on from the same flight and the interventions in reaction to the imported malaria cases were analyzed. The results showed that 4 out of 231 Guinean returned travellers had developed malaria symptoms, including chills and fever, during the isolation period. Rapid diagnostic test (RDT) indicated Plasmodium falciparum infection. Considering the patients ' travel history, clinical manifestations, and laboratory RDT test results, a confirmed diagnosis of imported P. falciparum malaria was made. The four malaria cases, who are male workers aged 29 to 55, were transferred to Jiaozhou People ' s Hospital for treatment. All four patients were administrated of artemether tablets upon diagnosis. One of the cases experienced severe malaria complications and were administrated with 12 doses (60 mg/dose) of artesunate intravenously for five days. The other three patients were treated with dihydroartemisinin and piperaquine phosphate tablets for one course of 8 tablets in 2 days (40 mg dihydroartemisinin and 320 mg piperaquine phosphate), respectively. Among the 231 returned travellers, 111 (48.1 %) had a history of malaria overseas. There were 23 positive cases detected by RDT, including the four symptomatic cases. The other 19 cases were asymptomatic. One of the asymptomatic cases became symptomatic three months later and was diagnosed as an imported P. malariae infection. Laboratory blood smear microscopic tests at the Jiaozhou City and Qingdao Municipal Center For Disease Control and Prevention showed negative results for the four malaria cases and the 19 RDT positive case. The samples from the four malaria cases were rechecked by the provincial reference laboratory of Shandong Institute of parasitic Disease. The results were negative for malaria infection by microscopic examination but positive for P. falciparum infection by nucleic acid test. It is suggested that during the routine control of COVID-19, the awareness of COVID-19 and malaria should be established among the returned travellers from high malaria-endemic areas. The health education "gate" should be moved forward to improve the treatment compliance for malaria cases and reduce the relapse or recrudescence caused by sub-optimal treatment.Copyright © 2022, Chin J Parasitol Parasit Dis. All rights reserved.
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Ninety-six million people are symptomatically infected with Dengue globally every year. Under the current standard-of-care, up to 20% of Dengue patients may be hospitalized, while only 500,000 develop Dengue Haemorrhagic Fever (DHF) and require hospitalization. This leads to unnecessary overwhelming of hospitals in tropical countries during large Dengue epidemics, especially when healthcare systems are grappling with large numbers of COVID-19 patients. Our research team set out to discover biomarkers to prognosticate Dengue patients, and augment the infectious disease clinician's decision-making process to hospitalize Dengue patients. Host biomarkers with concentrations significantly different between pooled serum samples of Dengue Fever (DF) patients and DHF patients were identified using protein array. The prognostication capabilities of selected biomarkers were then validated over 283 adult Dengue patients recruited from three Singapore tertiary hospitals, prior to the diagnosis of DHF. Three biomarkers (A2M, CMA1 and VEGFA) were identified that provide independent prognostication value from one another, and from clinical parameters commonly monitored in Dengue patients. The combination of all three biomarkers was able to identify from as early as Day 1 after the onset of fever, DF patients whose conditions will deteriorate into DHF. The biomarkers are robust and able to predict DHF well when trained on different AI/ML algorithms (logistic regression, support vector machine, decision tree, random forest, AdaBoost and gradient boosting). When stacked, prediction models based on the biomarkers were able to predict DHF with 97.3% sensitivity, 92.7% specificity, 66.7% PPV, 99.6% NPV and an AUC of 0.978. To the best of our knowledge, our panel of three biomarkers offers the highest accuracy in prognosticating Dengue to date. Further studies are required to validate the biomarkers in different geographical settings and pilot their implementation as part of the standard-of-care workflow for Dengue patients. [ FROM AUTHOR] Copyright of International Journal of Infectious Diseases is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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The emergence of the Covid-19 pandemic has drawn great attention to vulnerable people affected by major diseases. Among them, Alzheimer's disease (AD) is the most prevalent disease. However, a long-standing challenge is to achieve early diagnosis of AD by detecting biomarkers such as amyloid beta (Aβ42), thus avoiding the labor of specialized hospital personnel and the high cost of imaging examinations using positron emission tomography. In this paper, we report a straightforward approach to realize a non-invasive lab-around fiber (LaF) optical sensor for AD biomarker detection, which is based on a tilted fiber Bragg grating (TFBG) combined with a nanoscale metallic thin film. We successfully demonstrated the detection of Aβ42 in complex biological matrices with a detection limit of 5 pg/mL. Therefore, our TFBG-SPR biosensor platform enables large-scale early disease screening and has great potential for clinical applications in early AD diagnosis. © 2022 IEEE.
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Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance. © Wolters Kluwer Health, Inc. All rights reserved.
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Misinformation is an important topic in the Information Retrieval (IR) context and has implications for both system-centered and user-centered IR. While it has been established that the performance in discerning misinformation is affected by a person's cognitive load, the variation in cognitive load in judging the veracity of news is less understood. To understand the variation in cognitive load imposed by reading news headlines related to COVID-19 claims, within the context of a fact-checking system, we conducted a within-subject, lab-based, quasi-experiment (N=40) with eye-tracking. Our results suggest that examining true claims imposed a higher cognitive load on participants when news headlines provided incorrect evidence for a claim and were inconsistent with the person's prior beliefs. In contrast, checking false claims imposed a higher cognitive load when the news headlines provided correct evidence for a claim and were consistent with the participants' prior beliefs. However, changing beliefs after examining a claim did not have a significant relationship with cognitive load while reading the news headlines. The results illustrate that reading news headlines related to true and false claims in the fact-checking context impose different levels of cognitive load. Our findings suggest that user engagement with tools for discerning misinformation needs to account for the possible variation in the mental effort involved in different information contexts. © 2023 ACM.
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Now in the context of the novel coronavirus pneumonia outbreak, the control and removal of microbial aerosols has once again attracted academic attention, while conventional air purification methods such as filtration, chemical agents and UV have their own defects and deficiencies. With the advantages of high efficiency, wide spectrum, green, no residue, dynamic continuous disinfection, photocatalysis has broad application prospects. In this paper, the research on the inactivation of microbial aerosols with photocatalysis system is summarized and analyzed from the aspects of the types of photocatalysts, the load of photocatalysts, the light source and the structure and operation of reactors. TiO2 or its derivative materials are selected as photocatalysts in most studies, and more novel and efficient photocatalysts should be applied. Porous, multi-channel and large surface area catalyst carriers can effectively improve the efficiency of photocatalysis system. The light source still depends on UV light, and the application of visible light needs more research. There are few studies on improving the photocatalysis system by optimizing the reactor structure, and the most commonly used is the ring reactor. Researchers have developed photocatalytic air purifiers or combined photocatalysis systems with indoor air duct systems. In the future, photocatalysis system will become an important means for indoor microbial aerosol control. © 2023 Chemical Industry Press. All rights reserved.
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Coronavirus disease 2019 (COVID-19) has rapidly spread worldwide. Traditional Chinese Medicine (TCM) was considered important by Chinese health authorities in the fight against COVID-19. This review systematically analyzed and evaluated the safety and efficacy of TCM combined with Western Medicine (WM) for the treatment of COVID-19. We sought to provide summary evidence for clinicians when using TCM. We searched for studies in PubMed, Web of Science, Embase, Medline, the Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data from database inception to June 1, 2021. Overall, 31 studies (14,579 participants) were involved in the final systematic review, including 15 randomized controlled trials and 16 observational studies. TCM combined with WM showed main outcomes of a higher clinical efficacy rate (odds ratio [OR] =2.48, 95% confidence interval [CI] =1.90-3.24, I 2 = 4%) and lower case fatality rate (OR = 0.31, 95% CI = 0.19-0.49, I 2 = 80%) compared with WM treatment alone. No significant overall adverse events were found between TCM plus WM group and WM group (OR = 1.43, 95% CI = 0.63-2.23, I 2 = 75%). Some larger randomized control trials would assist in defining the effect of TCM combined with WM on the treatment of COVID-19 complications such as cardiac injury. TCM combined with WM may be safe and effective for the treatment of COVID-19. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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This cross-sectional survey evaluated well-being and family dynamics before and during the COVID-19 pandemic in 1287 (16 + years of age, 68.3% female) Chinese participants. Structural equation modeling was used to test the association of well-being and systemic family dynamics, and related moderating factors. Results indicated some subscales of well-being and systemic family dynamics significantly worsened during the pandemic. A modified model fits well for both data before and during the pandemic in which well-being was significantly associated with systemic family dynamic and by family income. Age also positively related systemic family dynamics. The relationship between family income and well-being and the relationship between systemic family dynamics and well-being were moderated by the pandemic. The results suggest that well-being and systemic family dynamics and their associations are impacted by the COVID-19 pandemic. Systemic family dynamics could be a potential resource for enhancing well-being during the COVID-19 pandemic by some interventions. © The Author(s) 2023.
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Motivated by the trend of overseas/cross-regional firms returning to domestic/local and the background of COVID-19 normalization, a sourcing decision model is proposed based on the cost-signal game under the demand uncertainty and forecast inaccuracy. We explore the trade-off between the efficient cross-regional sourcing and responsive local sourcing. The results show that the sourcing decision depends on the linkage performances of cost and information. Cross-regional sourcing always brings mighty cost performance, while the local sourcing can not always give full play to information performance advantage. Because if both firms choose local sourcing, the correlation effect between forecast information will hedge signal accuracy effect. Greater demand uncertainty and more accurate cross-regional sourcing forecast are driving films to return. Interestingly, this return may benefit all the firms, and break the Prisoner's Dilemma of symmetric cross-regional sourcing. The reason is that the returning can alleviate competition by inducing a new equilibrium sourcing structure. In response, this mixed equilibrium endows firms with "follower advantage” to realize local-Pareto improvement. With the increase of demand uncertainty and forecast inaccuracy, this mixed equilibrium will turn to the symmetric local sourcing, which temporarily reaches the overall Pareto-optimum. However, it will eventually fall into the Prisoner's Dilemma of lose-lose situation. In addition, it is also found that the poor local sourcing forecast will endow firms with "mover advantage”, which will lead to the mover becoming better while the follower becoming worse. © 2022 Systems Engineering Society of China. All rights reserved.
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PurposeThis paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.Design/methodology/approachThe authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.FindingsThe authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).Research limitations/implicationsThe authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.Practical implicationsThe authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.Social implicationsUnderstanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.Originality/valueIt uncovers subjects' intelligent interactively trading behaviors.
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This study examines the effectiveness of COVID-19 mortgage forbearance programs using data from the largest national bank servicers. Analyses of the data indicate that the forbearance entry rate was higher for borrowers with lower credit scores and in areas with higher unemployment rates. Some borrowers under forbearance had high credit scores, and a significant proportion continued to pay. Borrowers who had higher credit scores, made more payments under forbearance, and experienced greater labor market recovery were the earliest to exit the forbearance. Borrowers exited forbearance via different forms, with a large proportion delaying the payments of the forborne amount at maturity, refinance, or the property sale. One potential downside of nonpayment under forbearance is its adverse impact on ability to be refinanced, which is supported by some empirical evidence. However, the effect was short-lived, likely due to programs that attempted to alleviate this adverse effect. These pieces of evidence support an interpretation that forbearance programs supported borrowers adversely affected by COVID-19 event, but incentives should be built in to encourage exits to facilitate wealth accumulation.
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Since the global pandemic of coronavirus disease 2019 (COVID-19) in late 2019, artificial intelligence technology has shown increasing values in the research and control of tropical infectious diseases. The introduction of artificial intelligence technology has shown remarkable effectiveness to reduce the diagnosis and treatment burdens, reduce missing diagnosis and misdiagnosis, improve the surveillance and forecast ability and enhance the medicine and vaccine development efficiency. This paper summarizes the current applications of artificial intelligence in tropical infectious disease control and research and discusses the important values of artificial intelligence in disease diagnosis and treatment, disease surveillance and forecast, vaccine and drug discovery, medical and public health services and global health governance. However, artificial intelligence technology suffers from problems of single and inaccurate diagnosis, poor disease surveillance and forecast ability in open environments, limited capability of intelligent system services, big data management and model interpretability. Hereby, we propose suggestions with aims to improve multimodal intelligent diagnosis of multiple tropical infectious diseases, emphasize intelligent surveillance and forecast of vectors and high-risk populations in open environments, accelerate the research and development of intelligent management system, strengthen ethical security, big data management and model interpretability.
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COVID-19 , Medicine , United States , Humans , Artificial Intelligence , COVID-19/diagnosis , Communicable Disease Control , PandemicsABSTRACT
This study investigates the transport of air pollutants around the Yangtze River Delta with an aim to identify if there would be a relationship towards health effects during the COVID-19 lockdown period. It is well-known that due to lockdown, the number of socio-economical activities are reduced and hence there is an observable reduction in air pollution. We would like to investigate if this consequential reduction of air pollution would lead to improvement in health amongst its population. A number of integrated methodologies are utilized, including collection and correlation of statistical data and numerical modeling to correlate the mortality rates difference with and without COVID-19 lockdown. In particular air quality changes during the COVID-19 lockdown period are compared with similar periods of the previous years using Brute Force Method. It is found that in general there is significant reduction in air-pollution related mortality, like stroke, ischemic cardio diseases, obstructive pulmonary disease, lung cancer and acute lower respiratory infection are all reduced as a result of relative improvement in PM2.5 level during the lockdown period. Further investigation of the trajectories suggests that these PM2.5 originate from afar with multiple sources, and do not suggest COVID-19 are transported to the region via long-range transport. Our results demonstrate the need for more stringent policy measure to tackle air pollution as it has strong evidence that it increases mortality rate. © 2022 Elsevier Inc. All rights reserved.
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BACKGROUND Despite growing concern regarding the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant of concern (VOC), the respiratory and physical functions of patients with delta VOC post-discharge have not been investigated compared to those of patients with ancestral SARS-CoV-2.METHODS Sixty-three discharged patients with coronavirus disease (COVID-19) were included. Patients were divided into delta VOC and ancestral SARS-CoV-2 groups. On Day 14 post-discharge, differences in chest computed tomography, modified Medical Research Council and Borg Dyspnoea Scale scores, and Manual Muscle Test scores were compared. Prognoses of respiratory and physical function were compared between patients who recovered from moderate and severe COVID-19.RESULTS Of the 63 patients, respectively 28 and 35 were in the delta VOC and ancestral SARS-CoV-2 groups. On Day 14 post-discharge, 35 patients (56.5%) had abnormalities on imaging. Visual semi-quantitative scores of both lungs were significantly higher in the severe group. However, there was no difference in this or any other score ratings between the groups.CONCLUSION At 14 days post-discharge, ground glass opacities and pleural thickening were the most common residual findings; no difference in respiratory and physical functions during the convalescence period were noted in patients with SARS-CoV-2 delta VOC and ancestral SARS-CoV-2.
Subject(s)
COVID-19 , SARS-CoV-2 , Aftercare , Humans , Patient DischargeABSTRACT
Background: Obesity, physical inactivity, excessive alcohol consumption, and poor diet are all modifiable risk factors for cancer. These unhealthy behaviors are disproportionally concentrated in racial and ethnic minorities and these disparities may have been exacerbated during the COVID-19 pandemic. This study examined racial and ethnic disparities in weight gain and other undesirable lifestyle changes during the COVID-19 pandemic and explored mechanisms underlying these lifestyle disparities. Methods: We used data from the 2020 Health, Ethnicity and Pandemic Study, a national survey representative of US households conducted in October 2020. Racial and ethnic minorities were oversampled. Participants were asked to report lifestyle behaviors before and during the COVID-19 pandemic. We examined two outcomes in this study: weight gain and experiencing any undesirable lifestyle changes (i.e., reduced exercise time, increased alcohol drinking, or increased fast-food meal consumption). The primary exposure was race-ethnicity (non-Hispanic (NH) white, NH black, Hispanic, NH Asian, NH other race). Four sets of mediators were examined: socioeconomic status (education, household income, and undesirable job changes), family and friend social relationship change, perceived and experienced racism, and psychological distress. Weighted multivariable logistic regression models were performed. Mediation effects were examined with variance decomposition method. Results: A total of 2,709 participants were included in our sample. Compared with white respondents, black (OR = 1.71;p < 0.001) and Hispanic respondents (OR = 2.17;p < 0.001) were more likely to experience weight gain, controlling for age and sex. Among the hypothesized mediators, undesirable job changes during the pandemic, experiencing worse family relationship, and higher levels of psychological distress were all linked to higher odds of weight gain, but none of these variables played a salient role in mediating the black-white and Hispanic-white disparities in weight gain during the pandemic. As to the odds of experiencing undesirable lifestyle changes, black (OR = 1.76;p < 0.001), Hispanic (OR = 2.12;p < 0.001), and Asian respondents (OR = 1.42;p < 0.01) all exhibited disadvantages relative to white respondent. These disadvantages were largely attributable to perceived racism toward one's own group and psychological distress for all three minority groups. Conclusions: Racial and ethnic minorities were more likely to experience unhealthy lifestyle changes relative to white individuals during the pandemic in the United States, which can be partly attributable to higher levels of perceived racism and psychological distress. The long-term effects of racial/ethnic disparities of lifestyle change during the pandemic on cancer prevention warrant further research.