Nursing workforce allocation in the intensive care units of COVID-19-designated hospitals: A nationwide cross-sectional survey in China.

AIM: To explore the nursing workforce allocation in intensive care units (ICUs) of COVID-19-designated hospitals during the epidemic peak in China. DESIGN: A nationwide cross-sectional online survey. METHODS: A total of 37 head nurses and 262 frontline nurses in 37 ICUs of COVID-19-designated tertiary hospitals located in 22 cities of China were surveyed. The self-reported human resource allocation questionnaire was used to assess the nursing workforce allocation. RESULTS: The average patient-to-nurse ratio was 1.89 ± 1.14, and the median working hours per shift was 5 h. The top four majors of front-line nurses in ICUs were respiratory (31.30%), lemology (27.86%), intensive care (21.76%) and emergency (17.18%). We also found that a smaller average patient-to-nurse ratio (odds ratio [OR]: 0.328, 95% CI: 0.108, 1.000), longer average weekly rest time per person (OR: 0.193, 95% CI: 0.051, 0.729) and larger proportion of 6-9 working years (OR: 0.002, 95% CI: 0.001, 1.121) decreased the occurrence of nursing adverse events.

Advances in the study of nervous system infections in COVID‐19

Shortly after its outbreak, coronavirus disease 2019 (COVID‐19) has very rapidly spread to become a global epidemic. Early clinical findings mainly included typical symptoms such as fever and cough with a very high transmission rate. Recent findings have demonstrated neurological manifestations of atypical symptoms, which is associated with poor prognosis. In this paper, we describe the neurological aspects of COVID‐19 pneumonia in terms of relevant neurons, virus‐associated receptors, and olfactory and neurological clinical manifestations and offer insights on treatment.

Risk assessment of infectious disease epidemic based on fuzzy Bayesian network.

The prevention and control of infectious disease epidemic (IDE) is an important task for every country and region. Risk assessment is significant for the prevention and control of IDE. Fuzzy Bayesian networks (FBN) can capture complex causality and uncertainty. The study developed a novel FBN model, integrating grounded theory, interpretive structural model, and expert weight determination algorithm for the risk assessment of IDE. The algorithm is proposed by the authors for expert weighting in fuzzy environment. The proposed FBN model comprehensively takes into account the risk factors and the interaction among them, and quantifies the uncertainty of IDE risk assessment, so as to make the assessment results more reliable. Taking the epidemic situation of COVID-19 in Wuhan as a case, the application of the proposed model is illustrated. And sensitivity analysis is performed to identify the important risk factors of IDE. Moreover, the effectiveness of the model is checked by the three-criterion-based quantitative validation method including variation connection, consistent effect, and cumulative limitation. Results show that the probability of the outbreak of COVID-19 in Wuhan is as high as 82.26%, which is well-matched with the actual situation. "Information transfer mechanism," "coordination and cooperation among various personnel," "population flow," and "ability of quarantine" are key risk factors. The constructed model meets the above three criteria. The application potential and effectiveness of the developed FBN model are demonstrated. The study provides decision support for preventing and controlling IDE.

Survival outcomes following treatment delays among patients with early-stage female cancers: a nationwide study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) severely hindered the timely receipt of health care for patients with cancer, especially female patients. Depression and anxiety were more pronounced in female patients than their male counterparts with cancer during treatment wait-time intervals. Herein, investigating the impact of treatment delays on the survival outcomes of female patients with early-stage cancers can enhance the rational and precise clinical decisions of physicians. METHODS: We analyzed five types of cancers in women from the Surveillance, Epidemiology, and End Results (SEER) program between Jan 2010 and Dec 2015. Univariate and multivariate Cox regression analyses were used to determine the impacts of treatment delays on the overall survival (OS) and cancer-specific survival (CSS) of the patients. RESULTS: A total of 241,661 females with early-stage cancer were analyzed (12,617 cases of non-small cell lung cancer (NSCLC), 166,051 cases of infiltrating breast cancer, 31,096 cases of differentiated thyroid cancer, 23,550 cases of colorectal cancer, and 8347 cases of cervical cancer). Worse OS rates were observed in patients with treatment delays ≥ 3 months in stage I NSCLC (adjustedHazard ratio (HR) = 1.11, 95% Confidence Interval (CI): 1.01-1.23, p = 0.044) and stage I infiltrating breast cancer (adjustedHR = 1.23, 95% CI 1.11-1.37, p < 0.001). When the treatment delay intervals were analyzed as continuous variables, similar results were observed in patients with stage I NSCLC (adjustedHR = 1.04, 95% CI 1.01-1.06, p = 0.010) and in those with stage I breast cancer (adjustedHR = 1.03, 95% CI 1.00-1.06, p = 0.029). However, treatment delays did not reduce the OS of patients with differentiated thyroid cancer, cervical cancer, or colorectal cancer in the early-stage. Only intermediate treatment delays impaired the CSS of patients with cervical cancer in stage I (adjustedHR = 1.31, 95% CI 1.02-1.68, p = 0.032). CONCLUSION: After adjusting for confounders, the prolonged time from diagnosis to the initiation of treatment (< 6 months) showed limited negative effects on the survival of most of the patients with early-stage female cancers. Whether our findings serve as evidence supporting the treatment deferral decisions of clinicians for patients with different cancers in resource-limited situations needs further validation.

A High-throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19.

An ongoing clinical trial, Autoimmunity Screening for Kids (ASK), is the first screening study in the general population for type 1 diabetes (T1D) and celiac disease in the United States. With the coronavirus disease 2019 (COVID-19) pandemic, the epidemiology of COVID-19 in the general population and knowledge about the association between COVID-19 infection and T1D development are urgently needed. The currently standard screening method of the radio-binding assay (RBA) has met two great challenges: low efficiency with a single assay format and low disease specificity with a large proportion of low-affinity antibodies generated in screening. With the platform of the multiplex electrochemiluminescence (ECL) assay we established previously, a novel 6-Plex ECL assay was developed that combines, in a single well, all four islet autoantibodies (IAbs) to insulin, glutamic acid decarboxylase (GAD65), insulinoma antigen 2 (IA-2), and Zinc transporter 8 (ZnT8) for T1D, transglutaminase autoantibodies (TGA) for celiac disease, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor-binding domain (RBD) antibodies for COVID-19. The assay was validated in blind using 880 samples from the ASK study, including 325 positive samples and 555 all antibody-negative samples, and compared with the standard RBAs and a single ECL assay. With the advantages of high efficiency, low cost, and low serum volume, this assay has been accepted as the primary screening tool for the ASK study.

The impact of public health emergencies on hotel demand - Estimation from a new foresight perspective on the COVID-19.

This paper proposes a new foresight approach to estimate the impact of public health emergencies on hotel demand. The forecasting-based influence evaluation consists of four modules: decomposing hotel demand before an emergency, matching each decomposed component to a forecasting model, combining the predictions as the expected demand after the emergency, and estimating the impact by comparing actual demand against that predicted. The method is applied to analyze the impact of COVID-19 on Macao's hotel industry. The empirical results show that: 1) the new approach accurately estimates COVID-19's impact on hotel demand; 2) the seasonal and industry development components contribute significantly to the estimate of expected demand; 3) COVID-19's impact is heterogeneous across hotel services.

High-Throughput Multiplex Electrochemiluminescence Assay Applicable to General Population Screening for Type 1 Diabetes and Celiac Disease.

Objective: Large-scale screening of the general population for islet autoantibodies (IAbs) to detect type 1 diabetes (T1D) has started worldwide. The standard screening method of separate radio-binding assay (RBA) for each IAb is an inefficient bottleneck. Furthermore, most positive results by RBA in screening of general population individuals without a clinical diagnosis of T1D are low-affinity and not predictive of future diabetes. Research Design and Methods: We have developed and validated a novel 6-Plex assay based on electrochemiluminescence (ECL) technology that combines in a single well high-affinity IAbs (to insulin, GAD, IA-2, and ZnT8), transglutaminase autoantibodies for celiac disease, and severe acute respiratory syndrome coronavirus 2 antibodies. The Autoimmunity Screening for Kids (ASK) provided 880 serum samples, from 828 children aged 1-17 years without diabetes who were previously tested for IAbs using single ECL assays and RBA assays. Results: Levels of all six antibodies in the 6-Plex ECL assay correlated well with respective single ECL assay levels. Similar to single ECL assays, the 6-Plex ECL assay positivity was congruent with the RBA in 95% (35/37) of children who later developed T1D and in 88% (105/119) high-risk children with multiple IAbs. In contrast, only 56% (86/154, P < 0.0001) of children with persistent single IAb by RBA were found to be positive by 6-Plex ECL assay. Of 555 samples negative for all IAbs by RBA, few (0.2%-0.5%) were positive at low levels in the 6-Plex ECL assay. Conclusions: The study demonstrated that the 6-Plex ECL assay compares favorably to the standard RBAs in terms of disease specificity for general population screening in children. The 6-Plex ECL assay was therefore adopted as the primary screening tool in the general population screening ASK program with advantages of high efficiency, low cost, and low serum volume.

Perspectives of nursing directors on emergency nurse deployment during the pandemic of COVID-19: A nationwide cross-sectional survey in mainland China.

AIMS: The aim of this study is to investigate the situation and perceptions of nursing directors about emergency nursing staff deployment in designated hospitals during the pandemic of COVID-19 in mainland China. BACKGROUND: The pandemic of COVID-19 has significantly depleted health care resources, leading to increased burden of nursing care and staffing and exacerbating the crisis in health care facilities. Currently, how to effectively plan and schedule nursing staffing in the pandemic still remains unknown. METHODS: From 14 July 2020 to 8 September 2020, 62 nursing directors of designated hospitals in mainland China were invited to participate in a cross-sectional online survey for their perceptions of nursing human-resource allocation during the pandemic of COVID-19. RESULTS: A total of 55 valid questionnaires were collected, showing that 96.36% of the hospitals had emergency nursing organizations and management systems during the pandemic, 96.36% had well-established scheduling principles for nursing human resources and 54.55% of hospitals had human-resource scheduling platforms. All the hospitals had trained emergency nursing staff in infection control (55, 100%), work process (51, 92.73%) and emergency skills (50, 90.91%). Most of the participants were satisfied with the nursing staffing deployments at their institutions (52, 94.55%). However, more than two thirds of them believed that their human-resource deployment plans need further improvements (39, 70.91%). CONCLUSIONS: Most of the designated hospitals investigated had established emergency nursing organizations, and management systems, and related regulations for the epidemic. However, the contents mentioned above still need to be further standardized. IMPLICATIONS FOR NURSING MANAGEMENT: The surge of patients in the epidemic was considerable challenge for the emergency capacity of hospitals. In the future, we should pay more attention to the following aspects: building emergency nursing staffing platforms, increasing emergency human-resource reserves, establishing reliable communication channels for emergency response teams, improving the rules and regulations of emergency human-resource management, offering more training and drills for emergency-related knowledge and skills and giving more focus on bio-psycho-social wellbeing of nurses.

Decisive role of ozone formation control in winter PM2.5 mitigation in Shenzhen, China.

During the COVID-19 lockdown, atmospheric PM2.5 in the Pearl River Delta (PRD) showed the highest reduction in China, but the reasons, being a critical question for future air quality policy design, are not yet clear. In this study, we analyzed the relationships among gaseous precursors, secondary aerosols and atmospheric oxidation capacity in Shenzhen, a megacity in the PRD, during the lockdown period in 2020 and the same period in 2021. The comprehensive observational datasets showed large lockdown declines in all primary and secondary pollutants (including O3). We found that, however, the daytime concentrations of secondary aerosols during the lockdown period and normal period were rather similar when the corresponding odd oxygen (Ox≡O3+NO2, an indicator of photochemical processing avoiding the titration effect of O3 by freshly emitted NO) were at similar levels. Therefore, reduced Ox, rather than the large reduction in precursors, was a direct driver to achieve the decline in secondary aerosols. Moreover, Ox was also found to determine the spatial distribution of intercity PM2.5 levels in winter PRD. Thus, an effective strategy for winter PM2.5 mitigation should emphasize on control of winter O3 formation in the PRD and other regions with similar conditions.

The Unequal Effect of the COVID-19 Pandemic on the Labour Market and Income Inequality in China: A Multisectoral CGE Model Analysis Coupled with a Micro-Simulation Approach.

The COVID-19 pandemic had an unequal impact on the employment and earnings of different labourers, consequently affecting households' per capita income and income inequality. Combining a multisector computable general equilibrium model of China with a micro-simulation approach, this study aims to analyse the unequal effect of the COVID-19 pandemic on China's labour market and income inequality. The results confirm the unequal impact of the pandemic on the employment and earnings of different labourer types. Labourers who are female, live in urban areas, and have relatively low education levels would suffer greater losses in employment and earnings. The pandemic would reduce household per capita income by 8.75% for rural residents and 6.13% for urban residents. While the pandemic would have a larger negative impact on the employment and earnings of urban labourers, it would have a greater negative impact on the household per capita income of rural residents. Moreover, the per capita income of low-income households is more vulnerable to the pandemic, and the number of residents living below the poverty line would increase significantly. Thus, the pandemic would aggravate income inequality in China and threaten the livelihoods of poor families. This study could inform researchers exploring the distributional effect of the COVID-19 pandemic in developing countries.

Nursing allocation in isolation wards of COVID-19 designated hospitals: a nationwide study in China.

BACKGROUND: Appropriate allocation of nursing staff is key to ensuring efficient nursing in hospitals, and is significantly correlated with patient safety, nursing quality, and nurse job satisfaction. However, there are few studies on nursing workforce allocation in the isolation wards of COVID-19 designated hospitals globally. This study aims to better understand the nursing workforce allocation in the isolation wards of COVID-19 designated hospitals in China, and provide a theoretical basis for efficiently deploying first-line nurses in China and across the world in the future. METHODS: An online survey was conducted among the head nurses (n = 229) and nurses (n = 1378) in the isolation wards of 117 hospitals (selected by stratified sampling), using a self-reported human resource allocation questionnaire. RESULTS: The average bed-to-nurse ratios of different isolation wards were different (Z = 36.742, P = 0.000). The bed-to-nurse ratios of the ICU, suspected COVID-19 cases ward, and confirmed COVID-19 cases ward, were 1:1.88, 1:0.56, and 1:0.45, respectively. The nurse work hours per shift in different isolation wards were also different (Z = 8.468, P = 0.014), with the specific values of the ICU, suspected COVID-19 cases ward, and confirmed COVID-19 cases ward, being 5, 6, and 6 h, respectively. A correlation analysis showed that the average work hours per shift was proportional to the overtime work of nurses (rs = 0.146), the proportion of nurse practitioners was proportional to the overall utilization rate of nursing human resources in the wards (rs = 0.136), and the proportion of nurses with college degrees was proportional to teamwork (rs = 0.142). The proportion of nurses above grade 10 was inversely proportional to teamwork and psychological problems (rs = 0.135, rs = 0.203). The results of multiple stepwise regression analyses showed that the work hours of nurses per shift was the main factor affecting nurse satisfaction and that the proportion of nurses and the work hours of nurses per shift were both independent factors affecting the length of stay (LOS) of patients. CONCLUSION: Hospitals in China have made good nursing workforce allocations during the COVID-19 pandemic, but there are certain shortcomings. Therefore, scientific and efficient nursing workforce allocation practice plans should be established to improve the ability of hospitals to deal with public health emergencies and are urgent problems that need to be addressed soon.

Associations of sleep and circadian phenotypes with COVID-19 susceptibility and hospitalization: an observational cohort study based on the UK Biobank and a two-sample Mendelian randomization study.

STUDY OBJECTIVES: Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes. METHODS: Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Odds ratios (ORs) and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods. RESULTS: In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR = 1.24, 95% CI = 1.02-1.5; daytime napping [sometimes vs. never]: RR = 1.12, 95% CI = 1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR = 1.04, 95% CI = 1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes. CONCLUSIONS: Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate.

Critical Role of Simultaneous Reduction of Atmospheric Odd Oxygen for Winter Haze Mitigation.

The lockdown due to COVID-19 created a rare opportunity to examine the nonlinear responses of secondary aerosols, which are formed through atmospheric oxidation of gaseous precursors, to intensive precursor emission reductions. Based on unique observational data sets from six supersites in eastern China during 2019-2021, we found that the lockdown caused considerable decreases (32-61%) in different secondary aerosol components in the study region because of similar-degree precursor reductions. However, due to insufficient combustion-related volatile organic compound (VOC) reduction, odd oxygen (Ox = O3 + NO2) concentration, an indicator of the extent of photochemical processing, showed little change and did not promote more decreases in secondary aerosols. We also found that the Chinese provinces and international cities that experienced reduced Ox during the lockdown usually gained a greater simultaneous PM2.5 decrease than other provinces and cities with an increased Ox. Therefore, we argue that strict VOC control in winter, which has been largely ignored so far, is critical in future policies to mitigate winter haze more efficiently by reducing Ox simultaneously.

Social media exposure during COVID-19 lockdowns could lead to emotional overeating via anxiety: The moderating role of neuroticism.

China was a major hotspot during the beginning of the COVID-19 pandemic. Several studies have reported changes in residents' eating behaviors and appetite during city wide lockdowns and home confinements. However, few have investigated how neuroticism interacts with the impact of COVID-19 to influence eating behaviors during city lockdowns. Thus, the current study aims to establish a pathway model to understand social media exposure, negative affect, neuroticism, and their interaction with eating behaviors during the COVID-19 lockdowns. We present data from 1,128 participants (Mage = 24.34 ± 10.48 years) who completed an online survey between February 17 and 27, 2020. The extent of respondents' social media exposure, negative affect, eating behaviors, and desire for high-calorie food during city lockdowns, as well as the personality trait of neuroticism, were measured. Results show that city lockdowns and home confinements had a negative impact on residents' eating behaviors and appetite. Forty-eight percent of respondents showed moderate to constant emotional overeating, and respondents' desire for high-calorie food significantly increased. Correlation analysis showed that emotional overeating is positively associated with social media exposure, neuroticism, and anxiety. Then, a moderated mediation model was established, showing that heavy social media exposure could lead to emotional overeating through anxiety, and the association between social media exposure and anxiety varies depending on the extent of neuroticism. The current study provides novel insight into how the interaction of a personality trait and the stressful situation of COVID-19 influence people's negative emotions and eating behaviors.

The effect of COVID-19 lockdowns on sleep time perception: Comparing actigraphy and sleep diary measures.

COVID-19 has become a long-term problem, and global pandemic conditions may persist for years. Researchers are providing mounting evidence of relationships between COVID-19 lockdowns and sleep problems. However, few studies have investigated the impact of home isolation on sleep time perception, especially in comparable social isolation situations with similar pressures. Subjective sleep time perception parameters were derived from sleep diaries. Objective parameters were derived from actigraphy. Subjective and objective data were obtained between February 17 and February 27, 2020 from 70 adult participants subject to COVID-19 related lockdown provisions in China. We divided participants into a home stayers (HS) group (subject to full stay-at home orders) and an area-restricted workers (ARW) group (permitted to work at their nearby workplaces). The HS group demonstrated significantly delayed actigraphy-defined sleep onset time compared to self-reported sleep onset time; this effect was absent in the ARW group. Between-group differences in actigraphy-defined sleep onset time and significant between-group differences for actigraphy-defined and self-reported wake-up time were observed. HS group participants also presented significantly delayed actigraphy-defined wake-up time compared with self-reported wake-up time. No significant effect was found on total sleep time perception. Moreover, sleep/wake time misperception were found to be associated with daylight exposure and physical activity levels respectively. To the extent they are generalizable, these results suggest that lockdown restrictions can affect sleep onset and wake-up time perception but not total sleep time perception. Public health policy should consider such effects in the present pandemic situation and in future emergent public health situations.

Effects of physical activity and sleep quality on well-being: A wrist actigraphy study during the pandemic.

Previous studies identified the effects of daytime activity, sleep quality and ambient light exposure on individual well-being. These factors have been greatly changed as people are required to stay home during the COVID-19 pandemic; thus, it is necessary to verify whether these factors effect well-being during the pandemic. We recruited 70 adults (females: 46; age range: 31-60) during a high incidence of COVID-19 in China (17-27 February 2020). Both subjective measurements based on self-report scales and objective measurements collected using wrist actigraphy were employed to investigate the effects of night-time sleep and daytime activity on subjective well-being. The actigraphy data show that participants' total sleep time (>8 hr) is sufficient. Self-reported sleep quality was significantly worse than pre-pandemic, and self-reported daytime activity levels significantly decreased during the pandemic. Physical activity was positively related to well-being, both for self-reported daytime activity (r = .346, p = .003) and for objective measurements (r = .234, p = .051). Our study found that sleep and daytime activity levels were negatively affected by the pandemic. However, increased daytime physical activity could potentially reduce these negative effects.

The impacts of COVID-19 pandemic on China's transport sectors based on the CGE model coupled with a decomposition analysis approach.

As one of the most vulnerable sectors exposed to the COVID-19 pandemic, transport sectors have been severely affected. However, the shocks and impact mechanisms of infectious diseases on transport sectors are not fully understood. This paper employs a multi-sectoral computable general equilibrium model of China, CHINAGEM, with highly disaggregated transport sectors to examine the impacts of the COVID-19 pandemic on China's transport sectors and reveal the impact mechanisms of the pandemic shocks with the decomposition analysis approach. This study suggests that, first, multiple shocks of the COVID-19 pandemic to transport sectors are specified, including the supply-side shocks that raised the protective cost and reduced the production efficiency of transport sectors, and the demand-side shocks that reduced the demand of households and production sectors for transportation. Second, the outputs of all transport sectors in China have been severely affected by the COVID-19 pandemic, and passenger transport sectors have larger output decreases than freight transport sectors. While the outputs of freight transport sectors are expected to decline by 1.03-2.85%, the outputs of passenger transport sectors would decline by 3.08-11.44%. Third, with the decomposition analysis, the impacts of various exogenous shocks are quite different, while the changes in the output of different transport sectors are dominated by different exogenous shocks. Lastly, while the supply-side shocks of the pandemic would drive output decline in railway, waterway, and aviation transport sectors, the demand-side shocks would drive so in the road, pipeline, and other transport sectors. Moreover, the COVID-19 pandemic has negative impacts on the output of most non-transport sectors and the macro-economy in China. Three policy implications are recommended to mitigate the damages caused by the COVID-19 pandemic to the transport sectors.

Prevalence of SARS-CoV-2 Antibodies in Children and Adults with Type 1 Diabetes.

Objective: As diabetes is a risk factor for severe symptoms, hospitalization, and death with COVID-19 disease, we aimed to assess the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in children and adults with and without type 1 diabetes in Colorado during 2020. Research Design and Methods: We developed a highly sensitive and specific test for antibodies against SARS-CoV-2 and measured the antibodies in children and adults with new-onset (n = 129) and established type 1 diabetes (n = 94) seen for routine diabetes care at our center between January and October 2020. The antibodies were also measured in 562 children and 102 adults from the general population of Colorado. Results: The prevalence of SARS-CoV-2 antibodies in persons with new-onset type 1 diabetes (0.8%; 95% confidence interval 0.1%-4.2%) or those with established disease (4.3%; 1.7%-10.4%) did not differ from that in the general population children (2.8%; 1.8%-4.6%) or adults (3.9%; 1.5%-9.7%). In a subset of individuals with positive antibodies (n = 31), antibodies remained positive for up to 9 months, although the levels decreased starting 3 months after the infection (P = 0.007). Conclusions: From January to October 2020, the prevalence of SARS-CoV-2 antibodies were not different in children and adults with and without type 1 diabetes in Colorado. We found no evidence for increased prevalence of COVID-19 infections among youth with newly diagnosed type 1 diabetes. (COMIRB Protocol 20-1007).