Adherence to Healthy Lifestyle Prior to Infection and Risk of Post-COVID-19 Condition.

Importance: Few modifiable risk factors for post-COVID-19 condition (PCC) have been identified. Objective: To investigate the association between healthy lifestyle factors prior to SARS-CoV-2 infection and risk of PCC. Design, Setting, and Participants: In this prospective cohort study, 32 249 women in the Nurses' Health Study II cohort reported preinfection lifestyle habits in 2015 and 2017. Healthy lifestyle factors included healthy body mass index (BMI, 18.5-24.9; calculated as weight in kilograms divided by height in meters squared), never smoking, at least 150 minutes per week of moderate to vigorous physical activity, moderate alcohol intake (5 to 15 g/d), high diet quality (upper 40% of Alternate Healthy Eating Index-2010 score), and adequate sleep (7 to 9 h/d). Main Outcomes and Measures: SARS-CoV-2 infection (confirmed by test) and PCC (at least 4 weeks of symptoms) were self-reported on 7 periodic surveys administered from April 2020 to November 2021. Among participants with SARS-CoV-2 infection, the relative risk (RR) of PCC in association with the number of healthy lifestyle factors (0 to 6) was estimated using Poisson regression and adjusting for demographic factors and comorbidities. Results: A total of 1981 women with a positive SARS-CoV-2 test over 19 months of follow-up were documented. Among those participants, mean age was 64.7 years (SD, 4.6; range, 55-75); 97.4% (n = 1929) were White; and 42.8% (n = 848) were active health care workers. Among these, 871 (44.0%) developed PCC. Healthy lifestyle was associated with lower risk of PCC in a dose-dependent manner. Compared with women without any healthy lifestyle factors, those with 5 to 6 had 49% lower risk (RR, 0.51; 95% CI, 0.33-0.78) of PCC. In a model mutually adjusted for all lifestyle factors, BMI and sleep were independently associated with risk of PCC (BMI, 18.5-24.9 vs others, RR, 0.85; 95% CI, 0.73-1.00, P = .046; sleep, 7-9 h/d vs others, RR, 0.83; 95% CI, 0.72-0.95, P = .008). If these associations were causal, 36.0% of PCC cases would have been prevented if all participants had 5 to 6 healthy lifestyle factors (population attributable risk percentage, 36.0%; 95% CI, 14.1%-52.7%). Results were comparable when PCC was defined as symptoms of at least 2-month duration or having ongoing symptoms at the time of PCC assessment. Conclusions and Relevance: In this prospective cohort study, pre-infection healthy lifestyle was associated with a substantially lower risk of PCC. Future research should investigate whether lifestyle interventions may reduce risk of developing PCC or mitigate symptoms among individuals with PCC or possibly other postinfection syndromes.

Risk of Malnutrition in Hospitalized COVID-19 Patients: A Systematic Review and Meta-Analysis.

(1) Background: Studies have reported that COVID-19 may increase the risk of malnutrition among patients. However, the prevalence of such risk in hospitalized COVID-19 patients is uncertain due to the inconsistent use of assessment methods. (2) Methods: PubMed, Web of Science, and EMBASE were searched to identify studies on the nutritional status of hospitalized COVID-19 patients. A pooled prevalence of malnutrition risk evaluated by Nutrition Risk Score (NRS-2002) was obtained using a random effects model. Differences by study-level characteristics were examined by hospitalization setting, time of assessment, age, and country. Risk of bias was assessed using the Newcastle−Ottawa Scale. (3) Results: 53 studies from 17 countries were identified and summarized. A total of 17 studies using NRS-2002, including 3614 COVID-19 patients were included in the primary meta-analysis. The pooled prevalence of risk of malnutrition was significantly higher among ICU patients (92.2%, 95% CI: 85.9% to 96.8%) than among general ward patients (70.7%, 95% CI: 56.4% to 83.2%) (p = 0.002). No significant differences were found between age groups (≥65 vs. <65 years, p = 0.306) and countries (p = 0.893). (4) Conclusions: High risk of malnutrition is common and concerning in hospitalized patients with COVID-19, suggesting that malnutrition screening and nutritional support during hospitalization are needed.

Automatic CT Whole-Lung Segmentation in Radiomics Discrimination: Methodology and Application in Pneumonia Diagnosis and Distinguishment

Radiomics based on lesion segmentation has been widely accepted for disease diagnosis;however, it is difficult to precisely determine the boundary for pneumonia due to its diffuse characteristics. In this study, we aimed to propose an automatic radiomics method using whole-lung segmentation in pneumonia discrimination and assist clinical practitioners in fast and accurate diagnosis. In the discovery set, data from 151 participants diagnosed with type A or B influenza virus pneumonia, 63 diagnosed with coronavirus disease 2019 (COVID-19) and 50 healthy participants were collected. The three groups of data were compared in pairs. A total of 117 radiomics features were extracted from whole-lung images segmented by a four-layer U-net. We then utilized a logistic regression model to train the model and used the area under the receiver operating characteristic curve (AUC) to assess its performance. The L1 regularization term was used in feature selection, and 10-fold cross-validation was used to tune the hyperparameters. Fourteen radiomics features were selected to classify influenza pneumonia and health, and the AUC was 0.957 (95% confidential interval (CI): 0.939, 0.976) in the training set and 0.914 (95% CI: 0.866, 0.963) in the testing set. Eighteen features were selected for COVID-19 and health, and the AUC was 0.949 (95% CI: 0.926, 0.973)in the training set and 0.911 (95% CI: 0.859, 0.963) in the testing set. Twenty-eight features were selected for influenza virus pneumonia and COVID-19, and the AUC was 0.895 (95% CI: 0.870, 0.920) in the training set and 0.839 (95% CI: 0.791, 0.887) in the testing set. The results show that the automatic radiomics model based on whole lung segmentation is effective in distinguishing influenza virus pneumonia, COVID-19 and health, and may assist in the diagnosis of influenza virus pneumonia and COVID-19.

Predicting COVID-19 epidemiological trend by applying population mobility data in two-stage modeling.

:To predict the epidemiological trend of coronavirus disease 2019 (COVID-19) by mathematical modeling based on the population mobility and the epidemic prevention and control measures. : As of February 8，2020，the information of 151 confirmed cases in Yueqing，Zhejiang province were obtained，including patients' infection process，population mobility between Yueqing and Wuhan，etc. To simulate and predict the development trend of COVID-19 in Yueqing, the study established two-stage mathematical models，integrating the population mobility data with the date of symptom appearance of confirmed cases and the transmission dynamics of imported and local cases. : It was found that in the early stage of the pandemic，the number of daily imported cases from Wuhan (using the date of symptom appearance) was positively associated with the number of population travelling from Wuhan to Yueqing on the same day and 6 and 9 days before that. The study predicted that the final outbreak size in Yueqing would be 170 according to the number of imported cases estimated by consulting the population number travelling from Wuhan to Yueqing and the susceptible-exposed-infectious-recovered (SEIR) model; while the number would be 165 if using the reported daily number of imported cases. These estimates were close to the 170，the actual monitoring number of cases in Yueqing as of April 27，2020. : The two-stage modeling approach used in this study can accurately predict COVID-19 epidemiological trend.

Impact of socioeconomic status，population mobility and control measures on COVID-10 development in major cities of China.

:To evaluate the impact of socioeconomic status，population mobility，prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19，2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspects，that is, socioeconomic status，population mobility，and control measures for the pandemic. : According to the analysis on the 51 cities，4 development patterns of COVID-19 were obtained，including a high-incidence pattern (in Xinyu)，a late high-incidence pattern (in Ganzi)，a moderate incidence pattern (in Wenzhou and other 12 cities)，and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in China，possibly affected by socioeconomic status，population mobility and prevention and control measures that were taken. Therefore，a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.

Impact of Wuhan lockdown on the spread of COVID-19 in China: a study based on the data of population mobility.

This study aimed to quantitatively assess the effectiveness of the Wuhan lockdown measure on controlling the spread of coronavirus diesase 2019 (COVID-19). : Firstly，estimate the daily new infection rate in Wuhan before January 23，2020 when the city went into lockdown by consulting the data of Wuhan population mobility and the number of cases imported from Wuhan in 217 cities of Mainland China. Then estimate what the daily new infection rate would have been in Wuhan from January 24 to January 30th if the lockdown measure had been delayed for 7 days，assuming that the daily new infection in Wuhan after January 23 increased in a high，moderate and low trend respectively (using exponential, linear and logarithm growth models). Based on that，calculate the number of infection cases imported from Wuhan during this period. Finally，predict the possible impact of 7-day delayed lockdown in Wuhan on the epidemic situation in China using the susceptible-exposed-infectious-removed (SEIR) model. : The daily new infection rate in Wuhan was estimated to be 0.021%，0.026%，0.029%，0.033% and 0.070% respectively from January 19 to January 23. And there were at least 20 066 infection cases in Wuhan by January 23，2020. If Wuhan lockdown measure had been delayed for 7 days，the daily new infection rate on January 30 would have been 0.335% in the exponential growth model，0.129% in the linear growth model，and 0.070% in the logarithm growth model. Correspondingly，there would have been 32 075，24 819 and 20 334 infection cases travelling from Wuhan to other areas of Mainland China，and the number of cumulative confirmed cases as of March 19 in Mainland China would have been 3.3-3.9 times of the officially reported number. Conclusions: Timely taking city-level lockdown measure in Wuhan in the early stage of COVID-19 outbreak is essential in containing the spread of the disease in China.

Changes in dietary patterns among youths in China during COVID-19 epidemic: The COVID-19 impact on lifestyle change survey (COINLICS).

Limited studies have focused on how COVID-19 outbreak and thereby lockdown have affected the youth's diet patterns. This study aimed to assess changes in diet patterns among youths in China under the COVID-19 lockdown, based on the COVID-19 Impact on Lifestyle Change Survey (COINLICS), a nationwide retrospective survey distributed via social media platforms during 9-12 May 2020 where 10,082 youth participants in China have voluntarily reported their basic sociodemographic information and routine diet patterns in the months before and after COVID-19 lockdown. We used paired t-tests or χ2 tests to evaluate the significance of differences in consumption patterns of 12 major food groups and beverages across educational levels, between sexes, and before and after COVID-19 lockdown. During the COVID-19 lockdown, significant decreases were observed in the frequency of intake of rice, meat, poultry, fresh vegetables, fresh fruit, soybean products, and dairy products, with significant sex differences (females consuming more rice, fresh vegetables and fruit and less meat, poultry, soybean and dairy products than males). Significant increases were observed in the frequency of consumption of wheat products, other staple foods, and preserved vegetables, with males consuming these foods more frequently than females. Graduate students consumed most foods more frequently except rice and other staple foods and preserved vegetables. The frequency of sugar-sweetened beverage consumption had decreased while frequency of tea drinking had increased. The participating youths' diet patterns had significantly changed during the COVID-19 lockdown, with heterogeneities observed to different extents between sexes and across educational levels. Our findings would inform policy-makers and health professionals of these changes in time for better policy making and public health practice.

Information Disclosure During the COVID-19 Epidemic in China: City-Level Observational Study.

BACKGROUND: Information disclosure is a top priority for official responses to the COVID-19 pandemic. The timely and standardized information published by authorities as a response to the crisis can better inform the public and enable better preparations for the pandemic; however, there is limited evidence of any systematic analyses of the disclosed epidemic information. This in turn has important implications for risk communication. OBJECTIVE: This study aimed to describe and compare the officially released content regarding local epidemic situations as well as analyze the characteristics of information disclosure through local communication in major cities in China. METHODS: The 31 capital cities in mainland China were included in this city-level observational study. Data were retrieved from local municipalities and health commission websites as of March 18, 2020. A checklist was employed as a rapid qualitative assessment tool to analyze the information disclosure performance of each city. Descriptive analyses and data visualizations were produced to present and compare the comparative performances of the cities. RESULTS: In total, 29 of 31 cities (93.5%) established specific COVID-19 webpages to disclose information. Among them, 12 of the city webpages were added to their corresponding municipal websites. A majority of the cities (21/31, 67.7%) published their first cases of infection in a timely manner on the actual day of confirmation. Regarding the information disclosures highlighted on the websites, news updates from local media or press briefings were the most prevalent (28/29, 96.6%), followed by epidemic surveillance (25/29, 86.2%), and advice for the public (25/29, 86.2%). Clarifications of misinformation and frequently asked questions were largely overlooked as only 2 cities provided this valuable information. The median daily update frequency of epidemic surveillance summaries was 1.2 times per day (IQR 1.0-1.3 times), and the majority of these summaries (18/25, 72.0%) also provided detailed information regarding confirmed cases. The reporting of key indicators in the epidemic surveillance summaries, as well as critical facts included in the confirmed case reports, varied substantially between cities. In general, the best performance in terms of timely reporting and the transparency of information disclosures were observed in the municipalities directly administered by the central government compared to the other cities. CONCLUSIONS: Timely and effective efforts to disclose information related to the COVID-19 epidemic have been made in major cities in China. Continued improvements to local authority reporting will contribute to more effective public communication and efficient public health research responses. The development of protocols and the standardization of epidemic message templates-as well as the use of uniform operating procedures to provide regular information updates-should be prioritized to ensure a coordinated national response.