Gauging urban resilience in the United States during the COVID-19 pandemic via social network analysis.

Social distancing policies and other restrictive measures have demonstrated efficacy in curbing the spread of the COVID-19 pandemic. However, these interventions have concurrently led to short- and long-term alterations in social connectedness. Comprehending the transformation in intracity social interactions is imperative for facilitating post-pandemic recovery and development. In this research, we employ social network analysis (SNA) to delve into the nuances of urban resilience. Specifically, we constructed intricate networks utilizing human mobility data to represent the impact of social interactions on the structural attributes of social networks while assessing urban resilience by examining the stability features of social connectedness. Our findings disclose a diverse array of responses to social distancing policies regarding social connectedness and varied social reactions across U.S. Metropolitan Statistical Areas (MSAs). Social networks generally exhibited a shift from dense to sparse configurations during restrictive orders, followed by a transition from sparse to dense arrangements upon relaxation of said orders. Furthermore, we analyzed the alterations in social connectedness as demonstrated by network centrality, which can presumably be attributed to the rigidity of policies and the inherent qualities of the examined MSAs. Our findings contribute valuable scientific insights to support informed decision-making for post-pandemic recovery and development initiatives.

Diverged landscape of restaurant recovery from the COVID-19 pandemic in the United States.

The COVID-19 pandemic has imposed catastrophic impacts on the restaurant industry as a crucial socioeconomic sector that contributes to the global economy. However, the understanding of how the restaurant industry was recovered from COVID-19 remains underexplored. This study constructs a spatially explicit evaluation of the effect of COVID-19 on the restaurant industry in the US, drawing on the attributes of +200,000 restaurants from Yelp and +600 million individual-level restaurant visitations provided by SafeGraph from 1st January 2019 to 31st December 2021. We produce quantitative evidence of lost restaurant visitations and revenue amid the pandemic, the changes in the customers' origins, and the retained visitation law of human mobility-the number of restaurant visitations decreases as the inverse square of their travel distances-though such a distance-decay effect becomes marginal at the later pandemic. Our findings support policy makers to monitor economic relief and design place-based policies for economic recovery.

Geospatial Modeling of Health, Socioeconomic, Demographic, and Environmental Factors with COVID-19 Incidence Rate in Arkansas, US

The COVID-19 pandemic has posed numerous challenges to human society. Previous studies explored multiple factors in virus transmission. Yet, their impacts on COVID-19 are not universal and vary across geographical regions. In this study, we thoroughly quantified the spatiotemporal associations of 49 health, socioeconomic, demographic, and environmental factors with COVID-19 at the county level in Arkansas, US. To identify the associations, we applied the ordinary least squares (OLS) linear regression, spatial lag model (SLM), spatial error model (SEM), and multiscale geographically weighted regression (MGWR) model. To reveal how such associations change across different COVID-19 times, we conducted the analyses for each season (i.e., spring, summer, fall, and winter) from 2020 to 2021. We demonstrate that there are different driving factors along with different COVID-19 variants, and their magnitudes change spatiotemporally. However, our results identify that adult obesity has a positive association with the COVID-19 incidence rate over entire Arkansas, thus confirming that people with obesity are vulnerable to COVID-19. Humidity consistently negatively affects COVID-19 across all seasons, denoting that increasing humidity could reduce the risk of COVID-19 infection. In addition, diabetes shows roles in the spread of both early COVID-19 variants and Delta, while humidity plays roles in the spread of Delta and Omicron. Our study highlights the complexity of how multifactor affect COVID-19 in different seasons and counties in Arkansas. These findings are useful for informing local health planning (e.g., vaccine rollout, mask regulation, and testing/tracing) for the residents in Arkansas.

Concurrence of immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura: a case report and review of the literature.

BACKGROUND: Immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura are both causes of thrombocytopenia. Recognizing thrombotic thrombocytopenic purpura is crucial for subsequent treatment and prognosis. In clinical practice, corticosteroids and rituximab can be used to treat both immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura; plasma exchange therapy is the first-line treatment in thrombotic thrombocytopenic purpura, while corticosteroids are strongly recommended as first-line treatment in immune thrombocytopenic purpura. The differential diagnosis of immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura is essential in clinical practice. However, case reports have suggested that immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura can occur concurrently. CASE PRESENTATION: We report the case of a 32-year-old Asian female without previous disease who presented with pancytopenia, concurrent with immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura. The morphology of the megakaryocytes in the bone marrow indicated immune-mediated thrombocytopenia. The patient received glucocorticoid treatment, and her platelet count increased; however, schistocytes remained high during the course of the therapy. Further investigations revealed ADAMTS13 activity deficiency and positive ADAMTS13 antibodies. The high titer of antinuclear antibody and positive anti-U1-ribonucleoprotein/Smith antibody indicated a potential autoimmune disease. However, the patient did not fulfill the current criteria for systemic lupus erythematosus or mixed connective tissue disease. The patient responded well to plasma exchange therapy, and her platelet count remained normal on further follow-up. CONCLUSIONS: Concurrence of immune thrombocytopenic purpura and thrombotic thrombocytopenic purpura is rare, but clinicians should be aware of this entity to ensure prompt medical intervention. Most of the reported cases involve young women. Human immunodeficiency virus infection, pregnancy, and autoimmune disease are the most common underlying conditions.

How much urban air quality is affected by local emissions: A unique case study from a megacity in the Pearl River Delta, China

In March 2022, the resurgence of COVID-19 cases in Shenzhen, a megacity in the Pearl River Delta (PRD) region of China, led to unusual restrictions on anthropogenic activities within a single city, in contrast to the restrictions COVID-19 caused on a national scale at the beginning of 2020. In this unique event, we found that only under unfavorable meteorological conditions did substantial urban local emission reductions have an impact on air pollutant changes (−42.4%–6.6%), whereas the deweathered changes were very small (−8.3%–3.4%) under favorable meteorological conditions. Primary anthropogenic pollutants, such as NO2, toluene, BC, and primary organic aerosol (POA), responded most considerably to emission reductions from early morning to noon during unfavorable meteorological days;for secondary organic aerosol (SOA), regulating the daytime total oxidant (Ox = O3 + NO2) was found to be more effective than controlling its precursors within the city scale, whereas secondary nitrate displayed the opposite trend. Since Ox changed little during the urban lockdown despite the remarkable decrease in precursors, it is emphasized that regionally coordinated control of VOCs and NOx is necessary to effectively reduce Ox levels. In addition, Shenzhen's NOx emission reduction efforts should be sustained in order to control PM2.5 and O3 pollution synergistically for long-term attainment.

A global portrait of expressed mental health signals towards COVID-19 in social media space.

Globally, the COVID-19 pandemic has induced a mental health crisis. Social media data offer a unique opportunity to track the mental health signals of a given population and quantify their negativity towards COVID-19. To date, however, we know little about how negative sentiments differ across countries and how these relate to the shifting policy landscape experienced through the pandemic. Using 2.1 billion individual-level geotagged tweets posted between 1 February 2020 and 31 March 2021, we track, monitor and map the shifts in negativity across 217 countries and unpack its relationship with COVID-19 policies. Findings reveal that there are important geographic, demographic, and socioeconomic disparities of negativity across continents, different levels of a nation's income, population density, and the level of COVID-19 infection. Countries with more stringent policies were associated with lower levels of negativity, a relationship that weakened in later phases of the pandemic. This study provides the first global and multilingual evaluation of the public's real-time mental health signals to COVID-19 at a large spatial and temporal scale. We offer an empirical framework to monitor mental health signals globally, helping international authorizations, including the United Nations and World Health Organization, to design smart country-specific mental health initiatives in response to the ongoing pandemic and future public emergencies.

Hematopoietic stem cell transplantation activity in China 2020-2021 during the SARS-CoV-2 pandemic: a report from the Chinese Blood and Marrow Transplantation Registry Group.

Between 2020 and 2021, 31,525 hematopoietic stem cell transplantations (HSCTs) were reported to the Chinese Blood and Marrow Transplantation Registry Group (CBMTRG) throughout mainland China. In this report, we describe the activity and current trends for HSCT in China during the SARS-CoV-2 pandemic. In 2020, a total of 13,415 cases of HSCT were reported from 166 transplant teams, and 75% (10,042 cases) were allogeneic HSCTs. In 2021, a total of 18,110 cases of HSCT were reported from 174 transplant teams, and 70% (12,744 cases) were allogeneic HSCTs. Haploidentical donor (HID) transplantation accounted for 63% (7977 cases) of allogeneic HSCTs in 2021. The most common indications for allogeneic HSCT for malignant disease were acute myeloid leukemia (AML) (37%) and acute lymphoblastic leukemia (ALL) (23%), and the largest proportion of nonmalignant disease comprised aplastic anemia (AA) (13%). The PB stem cell source accounted for 41% of HIDs and 75% of MSDs. The BuCy-based regimen (57%) was the most popular conditioning regimen for allogeneic HSCT, followed by the BuFlu-based regimen (28%) and TBI-based regimen (11%). This survey provides comprehensive information about the current activities and might benefit clinical physicians' decision planning for HSCT.

Geospatial Modeling of Health, Socioeconomic, Demographic, and Environmental Factors with COVID-19 Incidence Rate in Arkansas, US

The COVID-19 pandemic has posed numerous challenges to human society. Previous studies explored multiple factors in virus transmission. Yet, their impacts on COVID-19 are not universal and vary across geographical regions. In this study, we thoroughly quantified the spatiotemporal associations of 49 health, socioeconomic, demographic, and environmental factors with COVID-19 at the county level in Arkansas, US. To identify the associations, we applied the ordinary least squares (OLS) linear regression, spatial lag model (SLM), spatial error model (SEM), and multiscale geographically weighted regression (MGWR) model. To reveal how such associations change across different COVID-19 times, we conducted the analyses for each season (i.e., spring, summer, fall, and winter) from 2020 to 2021. We demonstrate that there are different driving factors along with different COVID-19 variants, and their magnitudes change spatiotemporally. However, our results identify that adult obesity has a positive association with the COVID-19 incidence rate over entire Arkansas, thus confirming that people with obesity are vulnerable to COVID-19. Humidity consistently negatively affects COVID-19 across all seasons, denoting that increasing humidity could reduce the risk of COVID-19 infection. In addition, diabetes shows roles in the spread of both early COVID-19 variants and Delta, while humidity plays roles in the spread of Delta and Omicron. Our study highlights the complexity of how multifactor affect COVID-19 in different seasons and counties in Arkansas. These findings are useful for informing local health planning (e.g., vaccine rollout, mask regulation, and testing/tracing) for the residents in Arkansas.

Functional HIV-1/HCV cross-reactive antibodies isolated from a chronically co-infected donor.

Despite prolific efforts to characterize the antibody response to human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) mono-infections, the response to chronic co-infection with these two ever-evolving viruses is poorly understood. Here, we investigate the antibody repertoire of a chronically HIV-1/HCV co-infected individual using linking B cell receptor to antigen specificity through sequencing (LIBRA-seq). We identify five HIV-1/HCV cross-reactive antibodies demonstrating binding and functional cross-reactivity between HIV-1 and HCV envelope glycoproteins. All five antibodies show exceptional HCV neutralization breadth and effector functions against both HIV-1 and HCV. One antibody, mAb688, also cross-reacts with influenza and coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We examine the development of these antibodies using next-generation sequencing analysis and lineage tracing and find that somatic hypermutation established and enhanced this reactivity. These antibodies provide a potential future direction for therapeutic and vaccine development against current and emerging infectious diseases. More broadly, chronic co-infection represents a complex immunological challenge that can provide insights into the fundamental rules that underly antibody-antigen specificity.

Stress, Burnout, and Coping Strategies of Frontline Nurses During the COVID-19 Epidemic in Wuhan and Shanghai, China.

Background: Nurses at the frontline of caring for COVID-19 patients might experience mental health challenges and supportive coping strategies are needed to reduce their stress and burnout. The aim of this study was to identify stressors and burnout among frontline nurses caring for COVID-19 patients in Wuhan and Shanghai and to explore perceived effective morale support strategies. Method: A cross-sectional survey was conducted in March 2020 among 110 nurses from Zhongshan Hospital, Shanghai, who were deployed at COVID-19 units in Wuhan and Shanghai. A COVID-19 questionnaire was adapted from the previous developed "psychological impacts of SARS" questionnaire and included stressors (31 items), coping strategies (17 items), and effective support measures (16 items). Burnout was measured with the Maslach Burnout Inventory. Results: Totally, 107 (97%) nurses responded. Participants mean age was 30.28 years and 90.7% were females. Homesickness was most frequently reported as a stressor (96.3%). Seven of the 17 items related to coping strategies were undertaken by all participants. Burnout was observed in the emotional exhaustion and depersonalization subscales, with 78.5 and 92.5% of participants presenting mild levels of burnout, respectively. However, 52 (48.6%) participants experienced a severe lack of personal accomplishment. Participants with longer working hours in COVID-19 quarantine units presented higher emotional exhaustion (OR = 2.72, 95% CI 0.02-5.42; p = 0.049) and depersonalization (OR = 1.14, 95% CI 0.10-2.19; p = 0.033). Participants with younger age experienced higher emotional exhaustion (OR = 2.96, 95% CI 0.11-5.82; p = 0.042) and less personal accomplishment (OR = 3.80, 95% CI 0.47-7.13; p = 0.033). Conclusions: Nurses in this study experienced considerable stress and the most frequently reported stressors were related to families. Nurses who were younger and those working longer shift-time tended to present higher burnout levels. Psychological support strategies need to be organized and implemented to improve mental health among nurses during the COVID-19 pandemic.

Treatment with quercetin inhibits SARS-CoV-2 N protein-induced acute kidney injury by blocking Smad3-dependent G1 cell-cycle arrest.

Increasing evidence shows that SARS-CoV-2 can infect kidneys and cause acute kidney injury (AKI) in critically ill COVID-19 patients. However, mechanisms through which COVID-19 induces AKI are largely unknown, and treatment remains ineffective. Here, we report that kidney-specific overexpressing SARS-CoV-2 N gene can cause AKI, including tubular necrosis and elevated levels of serum creatinine and BUN in 8-week-old diabetic db/db mice, which become worse in those with older age (16 weeks) and underlying diabetic kidney disease (DKD). Treatment with quercetin, a purified product from traditional Chinese medicine (TCM) that shows effective treatment of COVID-19 patients, can significantly inhibit SARS-CoV-2 N protein-induced AKI in diabetic mice with or without underlying DKD. Mechanistically, quercetin can block the binding of SARS-CoV-2 N protein to Smad3, thereby inhibiting Smad3 signaling and Smad3-mediated cell death via the p16-dependent G1 cell-cycle arrest mechanism in vivo and in vitro. In conclusion, SARS-CoV-2 N protein is pathogenic and can cause severe AKI in diabetic mice, particularly in those with older age and pre-existing DKD, via the Smad3-dependent G1 cell-cycle arrest mechanism. Importantly, we identify that quercetin may be an effective TCM compound capable of inhibiting COVID-19 AKI by blocking SARS-CoV-2 N-Smad3-mediated cell death pathway.

Quantifying COVID-19 recovery process from a human mobility perspective: An intra-city study in Wuhan.

The COVID-19 pandemic has brought huge challenges to sustainable urban and community development. Although some recovery signals and patterns have been uncovered, the intra-city recovery process remains underexploited. This study proposes a comprehensive approach to quantify COVID-19 recovery leveraging fine-grained human mobility records. Taking Wuhan, a typical COVID-19 affected megacity in China, as the study area, we identify accurate recovery phases and select appropriate recovery functions in a data-driven manner. We observe that recovery characteristics regarding duration, amplitude, and velocity exhibit notable differences among urban blocks. We also notice that the recovery process under a one-wave outbreak lasts at least 84 days and has an S-shaped form best fitted with four-parameter Logistic functions. More than half of the recovery variance can be well explained and estimated by common variables from auxiliary data, including population, economic level, and built environments. Our study serves as a valuable reference that supports data-driven recovery quantification for COVID-19 and other crises.

Prevalence of and Risk Factors Associated With Mental Health Symptoms Among the General Population in China During the Coronavirus Disease 2019 Pandemic.

Importance: People exposed to coronavirus disease 2019 (COVID-19) and a series of imperative containment measures could be psychologically stressed, yet the burden of and factors associated with mental health symptoms remain unclear. Objective: To investigate the prevalence of and risk factors associated with mental health symptoms in the general population in China during the COVID-19 pandemic. Design, Setting, and Participants: This large-sample, cross-sectional, population-based, online survey study was conducted from February 28, 2020, to March 11, 2020. It involved all 34 province-level regions in China and included participants aged 18 years and older. Data analysis was performed from March to May 2020. Main Outcomes and Measures: The prevalence of symptoms of depression, anxiety, insomnia, and acute stress among the general population in China during the COVID-19 pandemic was evaluated using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Insomnia Severity Index, and Acute Stress Disorder Scale. Logistic regression analyses were used to explore demographic and COVID-19-related risk factors. Results: Of 71 227 individuals who clicked on the survey link, 56 932 submitted the questionnaires, for a participation rate of 79.9%. After excluding the invalid questionnaires, 56 679 participants (mean [SD] age, 35.97 [8.22] years; 27 149 men [47.9%]) were included in the study; 39 468 respondents (69.6%) were aged 18 to 39 years. During the COVID-19 pandemic, the rates of mental health symptoms among the survey respondents were 27.9% (95% CI, 27.5%-28.2%) for depression, 31.6% (95% CI, 31.2%-32.0%) for anxiety, 29.2% (95% CI, 28.8%-29.6%) for insomnia, and 24.4% (95% CI, 24.0%-24.7%) for acute stress. Participants with confirmed or suspected COVID-19 and their family members or friends had a high risk for symptoms of depression (adjusted odds ratios [ORs], 3.27 [95% CI, 1.84-5.80] for patients; 1.53 [95% CI, 1.26-1.85] for family or friends), anxiety (adjusted ORs, 2.48 [95% CI, 1.43-4.31] for patients; 1.53 [95% CI, 1.27-1.84] for family or friends), insomnia (adjusted ORs, 3.06 [95% CI, 1.73-5.43] for patients; 1.62 [95% CI, 1.35-1.96] for family or friends), and acute stress (adjusted ORs, 3.50 [95% CI, 2.02-6.07] for patients; 1.77 [95% CI, 1.46-2.15] for family or friends). Moreover, people with occupational exposure risks and residents in Hubei province had increased odds of symptoms of depression (adjusted ORs, 1.96 [95% CI, 1.77-2.17] for occupational exposure; 1.42 [95% CI, 1.19-1.68] for Hubei residence), anxiety (adjusted ORs, 1.93 [95% CI, 1.75-2.13] for occupational exposure; 1.54 [95% CI, 1.30-1.82] for Hubei residence), insomnia (adjusted ORs, 1.60 [95% CI, 1.45-1.77] for occupational exposure; 1.20 [95% CI, 1.01-1.42] for Hubei residence), and acute stress (adjusted ORs, 1.98 [95% CI, 1.79-2.20] for occupational exposure; 1.49 [95% CI, 1.25-1.79] for Hubei residence). Both centralized quarantine (adjusted ORs, 1.33 [95% CI, 1.10-1.61] for depression; 1.46 [95% CI, 1.22-1.75] for anxiety; 1.63 [95% CI, 1.36-1.95] for insomnia; 1.46 [95% CI, 1.21-1.77] for acute stress) and home quarantine (adjusted ORs, 1.30 [95% CI, 1.25-1.36] for depression; 1.28 [95% CI, 1.23-1.34] for anxiety; 1.24 [95% CI, 1.19-1.30] for insomnia; 1.29 [95% CI, 1.24-1.35] for acute stress) were associated with the 4 negative mental health outcomes. Being at work was associated with lower risks of depression (adjusted OR, 0.85 [95% CI, 0.79-0.91]), anxiety (adjusted OR, 0.92 [95% CI, 0.86-0.99]), and insomnia (adjusted OR, 0.87 [95% CI, 0.81-0.94]). Conclusions and Relevance: The results of this survey indicate that mental health symptoms may have been common during the COVID-19 outbreak among the general population in China, especially among infected individuals, people with suspected infection, and people who might have contact with patients with COVID-19. Some measures, such as quarantine and delays in returning to work, were also associated with mental health among the public. These findings identify populations at risk for mental health problems during the COVID-19 pandemic and may help in implementing mental health intervention policies in other countries and regions.

Social Network Analysis of Nonprofits in Disaster Response: The Case of Twitter During the COVID-19 Pandemic in the United States

The COVID-19 pandemic has created complex problems that require organizations to collaborate within and across the sector line. Social media data can provide insights into how nonprofits interact for the pandemic response from both social network and geographical perspectives. This study innovatively investigated the connection and interaction patterns among 74 National Voluntary Organizations Active in Disaster (NVOAD) nonprofits and three government agencies based on structural analyses and content analyses of their Twitter communications during the long-term global COVID-19 pandemic. The daily tweeting quantities of all nonprofits were generally consistent with the pandemic severity in the United States before July 2020 and remained stable afterward. Nonprofits’ tweets can reflect their purposes of sharing information, building communities, and taking actions for disaster response. Government agencies played leadership roles in providing COVID-19 guidelines and information. Human services, International and Foreign Affairs, and Public and Societal Benefit nonprofits, especially American Red Cross played central roles in the nonprofit communication network. Possible explanations include the following: (1) Geographically, connections and interactions among nonprofits are more likely to happen within the same city or in neighboring states. (2) Both mission homophily and heterophily contribute to connections and interactions among nonprofits, depending on their subsectors. The findings not only help the public better understand how nonprofits are collaboratively fighting the pandemic, but also provide guidance for nonprofits to plan for better interactions and communications in future disaster response. [ FROM AUTHOR] Copyright of Social Science Computer Review is the property of Sage Publications Inc. 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.)

Social media mining under the COVID-19 context: Progress, challenges, and opportunities.

Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.

GDP Forecasting Model for China’s Provinces Using Nighttime Light Remote Sensing Data

In order to promote the economic development of China’s provinces and provide references for the provinces to make effective economic decisions, it is urgent to investigate the trend of province-level economic development. In this study, DMSP/OLS data and NPP/VIIRS data were used to predict economic development. Based on the GDP data of China’s provinces from 1992 to 2016 and the nighttime light remote sensing (NTL) data of corresponding years, we forecast GDP via the linear model (LR model), ARIMA model, ARIMAX model, and SARIMA model. Models were verified against the GDP records from 2017 to 2019. The experimental results showed that the involvement of NTL as exogenous variables led to improved GDP prediction.

Elevated levels of fructosamine are independently associated with SARS-CoV-2 reinfection: A 12-mo follow-up study.

BACKGROUND: The association between blood levels of fructosamine (FMN) and recurrent coronavirus disease 2019 (COVID-19) is currently unclear. AIM: To investigate a prospective relationship between blood levels of FMN and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection. METHODS: A total of 146 Chinese hospitalized patients infected with SARS-CoV-2 were consecutively collectively recruited and followed from January 2020 to May 2021. Diagnosis of COVID-19 and SARS-CoV-2 reinfection was based on the diagnostic criteria and treatment protocol in China. The levels of FMN were determined in blood and divided into tertiles based on their distribution in the cohort of COVID-19 patients. Multivariate-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated for SARS-CoV-2 reinfection across the tertiles of FMN levels. A Cox regression model was used to generate the HR for SARS-CoV-2 reinfection in the participants in the top tertile of FMN levels compared with those at the bottom. Disease-free survival was used as the time variable, and relapse was used as the state variable, adjusted for age, gender, influencing factors such as diabetes mellitus, hypertension, and corticosteroid therapy, and clinical indexes such as acute liver failure, acute kidney failure, white blood cell (WBC) count, C-reactive protein, prognostic nutritional index (PNI), and blood lipids. Kaplan-Meier analysis with log-rank tests was used to compare the survival rate between patients with elevated FMN levels (FMN > 1.93 mmol/L, the top tertile) and those with nonelevated levels. RESULTS: Clinical data for the 146 patients with confirmed COVID-19 [age 49 (39-55) years; 49% males] were analyzed. Eleven patients had SARS-CoV-2 reinfection. The SARS-CoV-2 reinfection rate in patients with elevated FMN levels was significantly higher than that in patients with nonelevated FMN (17% vs 3%; P = 0.008) at the end of the 12-mo follow-up. After adjustments for gender, age, diabetes mellitus, hypertension, corticosteroid therapy, WBC count, PNI, indexes of liver and renal function, and blood lipids, patients with nonelevated FMN levels had a lower risk of SARS-CoV-2 reinfection than those with elevated FMN levels (HR = 6.249, 95%CI: 1.377-28.351; P = 0.018). Kaplan-Meier analysis showed that the cumulative survival rate of patients infected with SARS-CoV-2 was higher in patients with nonelevated FMN levels than in those with elevated FMN levels (97% vs 83%; log rank P = 0.002). CONCLUSION: Elevated levels of FMN are independently associated with SARS-CoV-2 reinfection, which highlights that patients with elevated FMN should be cautiously monitored after hospital discharge.