Household transmission of SARS-CoV-2 during the Omicron wave in Shanghai, China: A case-ascertained study.

OBJECTIVES: We used a case-ascertained study to determine the features of household transmission of SARS-CoV-2 Omicron variant in Shanghai, China. METHODS: In April 2022, we carried out a household transmission study from 309 households of 335 SARS-CoV-2 pediatric cases referred to a designated tertiary Children's Hospital. The detailed information can be collected from the 297 households for estimating the transmission parameters. The 236 households were qualified for estimating the secondary infection attack rates (SARI ) and secondary clinical attack rates (SARC ) among adult household contacts, characterizing the transmission heterogeneities in infectivity and susceptibility, and assessing the vaccine effectiveness. RESULTS: We estimated the mean incubation period and serial interval of Omicron variant to be 4.6 ± 2.1 and 3.9 ± 3.7 days, respectively, with 57.2% of the transmission events occurring at the presymptomatic phase. The overall SARI and SARC among adult household contacts were 77.11% (95% confidence interval [CI]: 73.58%-80.63%) and 67.03% (63.09%-70.98%). We found higher household susceptibility in females. Infectivity was not significantly different between children and adults and symptomatic and asymptomatic cases. Two-dose and booster-dose of inactivated COVID-19 vaccination were 14.8% (5.8%-22.9%) and 18.9% (9.0%-27.7%) effective against Omicron infection and 21.5% (10.4%-31.2%) and 24.3% (12.3%-34.7%) effective against the symptomatic disease. CONCLUSIONS: We found high household transmission during the Omicron wave in Shanghai due to presymptomatic and asymptomatic transmission despite implementation of strict interventions, indicating the importance of early detection and timely isolation of SARS-CoV-2 infections. Marginal effectiveness of inactivated vaccines against Omicron infection poses a great challenge for outbreak containment.

Long-term diet and risk of SARS -CoV-2 infection and Coronavirus Disease 2019 (COVID-19) severity.

BACKGROUND: The role of diet on COVID-19 is emerging. METHODS: We included 42,935 participants aged 55 to 99 years in two ongoing cohort studies, Nurses' Health Study II and Health Professionals Follow-up Study, who completed a series of COVID-19 surveys in 2020 and 2021. Using data from food frequency questionnaires prior to COVID-19, we assessed diet quality using the Alternative Healthy Eating Index (AHEI)-2010, the alternative Mediterranean Diet (AMED) score, an Empirical Dietary Index for Hyperinsulinemia (EDIH), and an Empirical Dietary Inflammatory Pattern (EDIP). We calculated multivariable adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) for SARS-CoV-2 infection and severity of COVID-19 after controlling for demographic, medical, and lifestyle factors. RESULTS: Among 19,754 participants tested for SARS-CoV-2, 1,941 participants reported a positive result. Of these, 1,327 reported symptoms needing assistance and another 109 were hospitalized. Healthier diet, represented by higher AHEI-2010 and AMED scores and lower EDIH and EDIP scores, were associated with lower likelihood of SARS-CoV-2 infection (ORs Q (quartile) 4 vs. Q1 (95%CI) were 0.80 (0.69, 0.92) for AHEI-2010; 0.78 (0.67, 0.92) for AMED; 1.36 (1.16, 1.57) for EDIH; and 1.13 (0.99, 1.30) for EDIP; all p for trend ≤ 0.01). In the analysis of COVID-19 severity, participants with healthier diet had lower likelihood of severe infection and were less likely to be hospitalized due to COVID-19. However, associations were no longer significant after controlling for BMI and pre-existing medical conditions. CONCLUSION: Diet may be an important modifiable risk factor for SARS-CoV-2 infection, as well as for severity of COVID-19. This association is partially mediated by BMI and pre-existing medical conditions.

Physical Activity, Sedentary Behavior, and Risk of Coronavirus Disease 2019.

INTRODUCTION: Data on the associations of prepandemic physical activity and sedentary behavior with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity, particularly milder illness, have been limited. METHODS: We used data from 43,913 participants within the Nurses' Health Study II and Health Professionals Follow-Up Study who responded to periodic COVID-related surveys from May 2020 through March 2021. History of physical activity from the prepandemic period was assessed as the metabolic equivalents of task (MET)-hours per week of various activities of different intensity and sedentary behavior assessed from reports of time spent sitting from questionnaires completed 2016-2017. Multivariable logistic regression models were fitted to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for risk of SARS-CoV-2 infection and COVID-19 severity, as well as predicted COVID-19 defined using a validated symptom-based algorithm. RESULTS: Higher levels of prepandemic physical activity were associated with a lower risk for SARS-CoV-2 infection. Compared to participants with <3 MET-hours per week, the multivariable-adjusted OR was 0.86 (95% CI: 0.74, 0.99; P trend =.07) for those with ≥27 MET-hours per week. Higher physical activity levels were also associated with lower risk of symptomatic SARS-CoV-2 infection (OR: 0.84; 95% CI: 0.72, 0.99; P trend = .05) and predicted COVID-19 (OR: 0.87; 95% CI: 0.78, 0.97; P trend = .01). Longer time sitting at home watching TV (OR: 0.85; 95% CI: 0.73, 0.97) or for other tasks (OR: 0.78; 95% CI: 0.66, 0.92) was associated with a lower risk of SARS-CoV-2 infection. CONCLUSIONS: Our findings support a protective association between prepandemic physical activity and lower risk and severity of COVID-19.

The mental health burden of racial and ethnic minorities during the COVID-19 pandemic.

Racial/ethnic minorities have been disproportionately impacted by COVID-19. The effects of COVID-19 on the long-term mental health of minorities remains unclear. To evaluate differences in odds of screening positive for depression and anxiety among various racial and ethnic groups during the latter phase of the COVID-19 pandemic, we performed a cross-sectional analysis of 691,473 participants nested within the prospective smartphone-based COVID Symptom Study in the United States (U.S.) and United Kingdom (U.K). from February 23, 2021 to June 9, 2021. In the U.S. (n=57,187), compared to White participants, the multivariable odds ratios (ORs) for screening positive for depression were 1·16 (95% CI: 1·02 to 1·31) for Black, 1·23 (1·11 to 1·36) for Hispanic, and 1·15 (1·02 to 1·30) for Asian participants, and 1·34 (1·13 to 1·59) for participants reporting more than one race/other even after accounting for personal factors such as prior history of a mental health disorder, COVID-19 infection status, and surrounding lockdown stringency. Rates of screening positive for anxiety were comparable. In the U.K. (n=643,286), racial/ethnic minorities had similarly elevated rates of positive screening for depression and anxiety. These disparities were not fully explained by changes in leisure time activities. Racial/ethnic minorities bore a disproportionate mental health burden during the COVID-19 pandemic. These differences will need to be considered as health care systems transition from prioritizing infection control to mitigating long-term consequences.

COVID-19 vaccine counseling and safety assessment in children and teenagers with underlying medical conditions in China: a single center study.

Safety concerns about novel vaccines and necessity of COVID-19 vaccination for children, especially with underlying medical conditions, are the obstacle of COVID-19 vaccination program among pediatric population. The study was conducted to investigate the vaccine hesitancy reasons among the parents, and to monitor the adverse events of inactivated COVID-19 vaccines in children and teenagers with underlying medical conditions in China. Children with underlying medical conditions encountered to the Immunization Advisory Clinic for COVID-19 vaccine counseling were enrolled. They were given immunization recommendation and followed up at 72 h and 28 d after immunization to monitor the immunization compliance after consultation and adverse events. A total of 324 children aged 3-17 y were included. The top three primary medical conditions for counseling were allergy (33.6%), neurological diseases (31.2%) and rheumatic diseases (8.3%). COVID-19 vaccination was promptly recommended for 242 (74.7%) children. Seventy-one (65.7%) children who had allergy issues were recommend to take vaccination, which was significantly lower than that of other medical conditions (p < .05). The follow-up record showed that 180 children received 340 doses of inactivated COVID-19 vaccine after consultation. Overall, 39 (21.6%) children reported at least one adverse event within 28 d of either vaccination. No serious adverse reactions were observed. No difference of adverse effects between the first dose and the second dose of vaccination except fever. Parents' hesitancy in COVID-19 vaccination for children with underling medical conditions are mainly due to the safety concerns. Specialist consultation is helpful to improve the vaccine uptake.

Associations between predicted vitamin D status, vitamin D intake, and risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity.

BACKGROUND: Vitamin D may have a role in immune responses to viral infections. However, data on the association between vitamin D and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity have been limited and inconsistent. OBJECTIVE: We examined the associations of predicted vitamin D status and intake with risk of SARS-CoV-2 infection and COVID-19 severity. METHODS: We used data from periodic surveys (May 2020 to March 2021) within the Nurses' Health Study II. Among 39,315 participants, 1768 reported a positive test for SARS-CoV-2 infection. Usual vitamin D intake from foods and supplements were measured using a semiquantitative, pre-pandemic food-frequency questionnaire in 2015. Predicted 25-hydroxyvitamin D [25(OH)D] concentration were calculated based on a previously validated model including dietary and supplementary vitamin D intake, UV-B, and other behavioral predictors of vitamin D status. RESULTS: Higher predicted 25(OH)D concentrations, but not vitamin D intake, were associated with a lower risk of SARS-CoV-2 infection. Comparing participants in the highest quintile of predicted 25(OH)D concentrations with the lowest, the multivariable-adjusted OR was 0.76 (95% CI: 0.58, 0.99; P-trend = 0.04). Participants in the highest quartile of UV-B (OR: 0.76; 95% CI: 0.66, 0.87; P-trend = 0.002) and UV-A (OR: 0.76; 95% CI: 0.66, 0.88; P-trend < 0.001) also had a lower risk of SARS-CoV-2 infection compared with the lowest. High intake of vitamin D from supplements (≥400 IU/d) was associated with a lower risk of hospitalization (OR: 0.51; 95% CI: 0.29, 0.91; P-trend = 0.04). CONCLUSIONS: Our study provides suggestive evidence on the association between higher predicted circulating 25(OH)D concentrations and a lower risk of SARS-CoV-2 infection. Greater intake of vitamin D supplements was associated with a lower risk of hospitalization. Our data also support an association between exposure to UV-B or UV-A, independently of vitamin D and SARS-CoV-2 infection, so results for predicted 25(OH)D need to be interpreted cautiously.

Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom.

Worldwide, racial and ethnic minorities have been disproportionately impacted by COVID-19 with increased risk of infection, its related complications, and death. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy may result in differences in uptake. We performed a cohort study among U.S. and U.K. participants who volunteered to take part in the smartphone-based COVID Symptom Study (March 2020-February 2021) and used logistic regression to estimate odds ratios of vaccine hesitancy and uptake. In the U.S. (n = 87,388), compared to white participants, vaccine hesitancy was greater for Black and Hispanic participants and those reporting more than one or other race. In the U.K. (n = 1,254,294), racial and ethnic minority participants showed similar levels of vaccine hesitancy to the U.S. However, associations between participant race and ethnicity and levels of vaccine uptake were observed to be different in the U.S. and the U.K. studies. Among U.S. participants, vaccine uptake was significantly lower among Black participants, which persisted among participants that self-reported being vaccine-willing. In contrast, statistically significant racial and ethnic disparities in vaccine uptake were not observed in the U.K sample. In this study of self-reported vaccine hesitancy and uptake, lower levels of vaccine uptake in Black participants in the U.S. during the initial vaccine rollout may be attributable to both hesitancy and disparities in access.

Diet quality and risk and severity of COVID-19: a prospective cohort study.

OBJECTIVE: Poor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation. DESIGN: We used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively. RESULTS: Over 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation. CONCLUSIONS: A diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.

Multi-Classification Network for Identifying COVID-19 Cases Using Deep Convolutional Neural Networks

The novel coronavirus 2019 (COVID-19) rapidly spreading around the world and turns into a pandemic situation, consequently, detecting the coronavirus (COVID-19) affected patients are now the most critical task for medical specialists. The deficiency of medical testing kits leading to huge complexity in detecting COVID-19 patients worldwide, resulting in the number of infected cases is expanding. Therefore, a significant study is necessary about detecting COVID-19 patients using an automated diagnosis method, which hinders the spreading of coronavirus. In this paper, the study suggests a Deep Convolutional Neural Network-based multi-classification framework (COVMCNet) using eight different pre-trained architectures such as VGG16, VGG19, ResNet50V2, DenseNet201, InceptionV3, MobileNet, InceptionResNetV2, Xception which are trained and tested on the X-ray images of COVID-19, Normal, Viral Pneumonia, and Bacterial Pneumonia. The results from 4-class (Normal vs. COVID-19 vs. Viral Pneumonia vs. Bacterial Pneumonia) demonstrated that the pre-trained model DenseNet201 provides the highest classification performance (accuracy: 92.54%, precision: 93.05%, recall: 92.81%, F1-score: 92.83%, specificity: 97.47%). Notably, the DenseNet201 (4-class classification) pre-trained model in the proposed COV-MCNet framework showed higher accuracy compared to the rest seven models. Important to mention that the proposed COV-MCNet model showed comparatively higher classification accuracy based on the small number of pre-processed datasets that specifies the designed system can produce superior results when more data become available. The proposed multi-classification network (COV-MCNet) significantly speeds up the existing radiology based method which will be helpful for the medical community and clinical specialists to early diagnosis the COVID-19 cases during this pandemic.

Race, ethnicity, community-level socioeconomic factors, and risk of COVID-19 in the United States and the United Kingdom.

BACKGROUND: There is limited prior investigation of the combined influence of personal and community-level socioeconomic factors on racial/ethnic disparities in individual risk of coronavirus disease 2019 (COVID-19). METHODS: We performed a cross-sectional analysis nested within a prospective cohort of 2,102,364 participants from March 29, 2020 in the United States (US) and March 24, 2020 in the United Kingdom (UK) through December 02, 2020 via the COVID Symptom Study smartphone application. We examined the contribution of community-level deprivation using the Neighborhood Deprivation Index (NDI) and the Index of Multiple Deprivation (IMD) to observe racial/ethnic disparities in COVID-19 incidence. ClinicalTrials.gov registration: NCT04331509. FINDINGS: Compared with non-Hispanic White participants, the risk for a positive COVID-19 test was increased in the US for non-Hispanic Black (multivariable-adjusted odds ratio [OR], 1.32; 95% confidence interval [CI], 1.18-1.47) and Hispanic participants (OR, 1.42; 95% CI, 1.33-1.52) and in the UK for Black (OR, 1.17; 95% CI, 1.02-1.34), South Asian (OR, 1.39; 95% CI, 1.30-1.49), and Middle Eastern participants (OR, 1.38; 95% CI, 1.18-1.61). This elevated risk was associated with living in more deprived communities according to the NDI/IMD. After accounting for downstream mediators of COVID-19 risk, community-level deprivation still mediated 16.6% and 7.7% of the excess risk in Black compared to White participants in the US and the UK, respectively. INTERPRETATION: Our results illustrate the critical role of social determinants of health in the disproportionate COVID-19 risk experienced by racial and ethnic minorities.

Depressive State in the Emergency Department During COVID-19: A National Cross-Sectional Survey in China.

Chinese emergency department (ED) staff encountered significant mental stress while fighting the coronavirus disease 2019 (COVID-19) pandemic. We sought to investigate the prevalence and associated factors for depressive symptoms among ED staff (including physicians, nurses, allied health, and auxiliary ED staff). A cross-sectional national survey of ED staff who were on duty and participated in combating the COVID-19 pandemic was conducted March 1-15, 2020. A total of 6,588 emergency medical personnel from 1,060 hospitals responded to this survey. A majority of respondents scored above 10 points on the PHQ-9 standardized test, which is associated with depressive symptoms. Those aged 31-45, those working in the COVID-19 isolation unit, and those with relatives ≤ 16 or ≥70 years old at home all had statistically significant associations with scoring >10 points. Depressive symptoms among Chinese emergency medical staff were likely quite common during the response to the COVID-19 pandemic and reinforce the importance of targeted ED staff support during future outbreaks.

Association of social distancing and face mask use with risk of COVID-19.

Given the continued burden of COVID-19 worldwide, there is a high unmet need for data on the effect of social distancing and face mask use to mitigate the risk of COVID-19. We examined the association of community-level social distancing measures and individual face mask use with risk of predicted COVID-19 in a large prospective U.S. cohort study of 198,077 participants. Individuals living in communities with the greatest social distancing had a 31% lower risk of predicted COVID-19 compared with those living in communities with poor social distancing. Self-reported 'always' use of face mask was associated with a 62% reduced risk of predicted COVID-19 even among individuals living in a community with poor social distancing. These findings provide support for the efficacy of mask-wearing even in settings of poor social distancing in reducing COVID-19 transmission. Despite mass vaccination campaigns in many parts of the world, continued efforts at social distancing and face mask use remain critically important in reducing the spread of COVID-19.

PvCT: A Publicly Verifiable Contact Tracing Algorithm in Cloud Computing

Contact tracing is a critical tool in containing epidemics such as COVID-19. Researchers have carried out a lot of work on contact tracing. However, almost all of the existing works assume that their clients and authorities have large storage space and powerful computation capability and clients can implement contact tracing on their own mobile devices such as mobile phones, tablet computers, and wearable computers. With the widespread outbreaks of the epidemics, these approaches are of less robustness to a larger scale of datasets when it comes to resource-constrained clients. To address this limitation, we propose a publicly verifiable contact tracing algorithm in cloud computing (PvCT), which utilizes cloud services to provide storage and computation capability in contact tracing. To guarantee the integrity and accuracy of contact tracing results, PvCT applies a novel set accumulator-based authentication data structure whose computation is outsourced, and the client can check whether returned results are valid. Furthermore, we provide rigorous security proof of our algorithm based on the q-Strong Bilinear Diffie–Hellman assumption. Detailed experimental evaluation is also conducted on three real-world datasets. The results show that our algorithm is feasible within milliseconds of client CPU time and can significantly reduce the storage overhead from the size of datasets to a constant 128 bytes.

Symptoms and syndromes associated with SARS-CoV-2 infection and severity in pregnant women from two community cohorts.

We tested whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity, and we extended previous investigations on hospitalized pregnant women to those who did not require hospitalization. Two female community-based cohorts (18-44 years) provided longitudinal (smartphone application, N = 1,170,315, n = 79 pregnant tested positive) and cross-sectional (web-based survey, N = 1,344,966, n = 134 pregnant tested positive) data, prospectively collected through self-participatory citizen surveillance in UK, Sweden and USA. Pregnant and non-pregnant were compared for frequencies of events, including SARS-CoV-2 testing, symptoms and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity, except for gastrointestinal symptoms. Pregnant were more likely to have received testing, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with syndromic severity in pregnant hospitalized. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant who were hospitalized. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.

Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app.

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic - area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

Depressive Symptoms, Sleep Quality and Diet During the 2019 Novel Coronavirus Epidemic in China: A Survey of Medical Students.

The psychological condition of medical students may be influenced by the 2019 novel coronavirus (COVID-19) outbreak. This study investigated the prevalence and influencing factors of depressive symptoms, poor sleep quality and poor diet in students at Kunming Medical University during the early part of the COVID-19 outbreak. A cross-sectional study was used from a questionnaire survey in February 2020. Of a total of 1,026 study participants, the prevalence of depressive symptoms, poor sleep quality, and poor diet was, respectively, 22.4, 33.2, and 17.4%. Male students and students with a low degree of focus on COVID-19 had a high risk of depressive symptoms. A high percentage of females and students in the fifth grade, as well as students with high levels of concern about the negative impact of COVID-19 on their education or employment, comprised those with poor sleep quality. Students in the fifth grade and students with high levels of concern about the negative impact of COVID-19 on their education or employment were more likely to report poor diet. This study suggests the importance of monitoring medical students' depressive state during the COVID-19 outbreak, and universities are encouraged to institute policies and programs to provide educational counseling and psychological support to help students to cope with these problems.

SARS-CoV-2 (COVID-19) infection in pregnant women: characterization of symptoms and syndromes predictive of disease and severity through real-time, remote participatory epidemiology.

OBJECTIVE: To test whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity. To extend previous investigations on hospitalized pregnant women to those who did not require hospitalization. DESIGN: Observational study prospectively collecting longitudinal (smartphone application interface) and cross-sectional (web-based survey) data. SETTING: Community-based self-participatory citizen surveillance in the United Kingdom, Sweden and the United States of America. POPULATION: Two female community-based cohorts aged 18-44 years. The discovery cohort was drawn from 1,170,315 UK, Sweden and USA women (79 pregnant tested positive) who self-reported status and symptoms longitudinally via smartphone. The replication cohort included 1,344,966 USA women (134 pregnant tested positive) who provided cross-sectional self-reports. METHODS: Pregnant and non-pregnant were compared for frequencies of symptoms and events, including SARS-CoV-2 testing and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. RESULTS: Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity. Pregnant were more likely to have received testing than non-pregnant, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with the syndromic severity in pregnant hospitalized women. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among all non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant women who were hospitalized. CONCLUSIONS: Symptom characteristics and severity were comparable among pregnant and non-pregnant women, except for gastrointestinal symptoms. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.