Corrigendum: Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: an individual-level analysis within 13 months in the ORCHESTRA cohort.

[This corrects the article DOI: 10.3389/fimmu.2022.1079884.].

Investigation of Health Misinformation During the Covid-19 Pandemic

This study examines how misinformation related to Covid-19 on social media exacerbates individuals' perceptions of health threats. Informed by the Health Belief Model, we analyze over 5K fact-checked articles to identify different categories or topics of misinformation. We also analyze the veracity and temporal trends of the misinformation topics. Overall, thirteen topics emerged from our analysis, with most of the misinformation questioning the benefits of preventive actions and undermining the severity of the pandemic. We also found significant misinformation related to official sources such as health agencies and research institutes communicating about the pandemic. The findings have implications for social media and health research. Public health experts and policymakers might find insights helpful in designing better communication and intervention strategies to counter the false narrative about the pandemic. The study lays the ground to examine further motivations, mechanisms, and impacts of sharing health misinformation on social media. © 2023 IEEE Computer Society. All rights reserved.

Geographical Disparity in Cardiorespiratory Fitness among 3,189,540 Japanese Children and Adolescents before and during the Coronavirus 2019 Pandemic: An Ecological Study.

This ecological study aimed to use nationally representative physical fitness (PF) data to investigate the geographical disparities in cardiorespiratory fitness (CRF) among Japanese children across prefectures before and during the coronavirus 2019 (COVID-19) pandemic. The publicly available descriptive PF data of children from Grade 5 (10-11 years; n = 1,946,437) and adolescents from Grade 8 (13-14 years; n = 1,243,103) at the prefecture level (47 prefectures) were obtained from the annual census PF survey in 2019 (before the pandemic) and 2021 (during the pandemic). The 20 m shuttle run performance was used as a measure of CRF. Geographical disparity was evaluated using the coefficient of variation (CV) for CRF across prefectures. There were significant negative relationships between the magnitude of infections (evaluated as the number of confirmed cases) and changes in CRF at the prefecture level (r ≤ -0.293, p < 0.05). This study also found a substantial increase in CVs of CRF across prefectures for Grade 8 students, suggesting that COVID-19-related restrictions had widened the geographical disparity in CRF among Japanese adolescents. Adolescents' CRF is an important marker for current and future health; hence, the findings of widening geographical disparities in CRF are suggestive of widening geographical disparities in health among the Japanese population.

Physical fitness before and during the COVID-19 pandemic: Results of annual national physical fitness surveillance among 16,647,699 Japanese children and adolescents between 2013 and 2021.

BACKGROUND: The primary aim was to examine the temporal trends in physical fitness (PF) for Japanese children and adolescents before and during the coronavirus disease 2019 pandemic. The secondary aim was to estimate the concurrent trends in body size (measured as body mass and height) and movement behaviors (exercise, screen, and sleep time). METHODS: Census PF data for children in Grade 5 (aged 10-11 years) and adolescents in Grade 8 (aged 13-14 years) were obtained for the years 2013-2021 from the National Survey of Physical Fitness, Athletic Performance, and Exercise Habits in Japan (n = 16,647,699). PF and body size were objectively measured, and movement behaviors were self-reported. Using sample-weighted linear regression, temporal trends in mean PF were calculated before the pandemic (2013-2019) and during the pandemic (2019-2021) with adjustments for age, sex, body size, and exercise time. RESULTS: When adjusted for age, sex, body size, and exercise time, there were significant declines in PF during the pandemic, with the largest declines observed in 20-m shuttle run (standardized (Cohen's) effect size (ES) =  - 0.109 p.a.) and sit-ups performance (ES = - 0.133 p.a.). The magnitude of the declines in 20-m shuttle run and sit-ups performances were 18- and 15-fold larger, respectively, than the improvements seen before the pandemic (2013-2019), after adjusting for age, sex, body size, and exercise time. During the pandemic, both body mass and screen time significantly increased, and exercise time decreased. CONCLUSION: Declines in 20-m shuttle run and sit-ups performances suggest corresponding declines in population health during the COVID-19 pandemic.

Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: An individual-level analysis within 13 months in the ORCHESTRA cohort.

Short summary: We investigated changes in serologic measurements after COVID-19 vaccination in 19,422 subjects. An individual-level analysis was performed on standardized measurements. Age, infection, vaccine doses, time between doses and serologies, and vaccine type were associated with changes in serologic levels within 13 months. Background: Persistence of vaccine immunization is key for COVID-19 prevention. Methods: We investigated the difference between two serologic measurements of anti-COVID-19 S1 antibodies in an individual-level analysis on 19,422 vaccinated healthcare workers (HCW) from Italy, Spain, Romania, and Slovakia, tested within 13 months from first dose. Differences in serologic levels were divided by the standard error of the cohort-specific distribution, obtaining standardized measurements. We fitted multivariate linear regression models to identify predictors of difference between two measurements. Results: We observed a progressively decreasing difference in serologic levels from <30 days to 210-240 days. Age was associated with an increased difference in serologic levels. There was a greater difference between the two serologic measurements in infected HCW than in HCW who had never been infected; before the first measurement, infected HCW had a relative risk (RR) of 0.81 for one standard deviation in the difference [95% confidence interval (CI) 0.78-0.85]. The RRs for a 30-day increase in time between first dose and first serology, and between the two serologies, were 1.08 (95% CI 1.07-1.10) and 1.04 (95% CI 1.03-1.05), respectively. The first measurement was a strong predictor of subsequent antibody decrease (RR 1.60; 95% CI 1.56-1.64). Compared with Comirnaty, Spikevax (RR 0.83, 95% CI 0.75-0.92) and mixed vaccines (RR 0.61, 95% CI 0.51-0.74) were smaller decrease in serological level (RR 0.46; 95% CI 0.40-0.54). Conclusions: Age, COVID-19 infection, number of doses, time between first dose and first serology, time between serologies, and type of vaccine were associated with differences between the two serologic measurements within a 13-month period.

Determinants of Anti-S Immune Response at 9 Months after COVID-19 Vaccination in a Multicentric European Cohort of Healthcare Workers-ORCHESTRA Project.

Background: The persistence of antibody levels after COVID-19 vaccination has public health relevance. We analyzed the determinants of quantitative serology at 9 months after vaccination in a multicenter cohort. Methods: We analyzed data on anti-SARS-CoV-2 spike antibody levels at 9 months from the first dose of vaccinated HCW from eight centers in Italy, Germany, Spain, Romania and Slovakia. Serological levels were log-transformed to account for the skewness of the distribution and normalized by dividing them by center-specific standard errors. We fitted center-specific multivariate regression models to estimate the cohort-specific relative risks (RR) of an increase of one standard deviation of log antibody level and the corresponding 95% confidence interval (CI), and combined them in random-effects meta-analyses. Finally, we conducted a trend analysis of 1 to 7 months' serology within one cohort. Results: We included 20,216 HCW with up to two vaccine doses and showed that high antibody levels were associated with female sex (p = 0.01), age (RR = 0.87, 95% CI = 0.86-0.88 per 10-year increase), 10-day increase in time since last vaccine (RR = 0.97, 95% CI 0.97-0.98), previous infection (3.03, 95% CI = 2.92-3.13), two vaccine doses (RR = 1.22, 95% CI = 1.09-1.36), use of Spikevax (OR = 1.51, 95% CI = 1.39-1.64), Vaxzevria (OR = 0.57, 95% CI = 0.44-0.73) or heterologous vaccination (OR = 1.33, 95% CI = 1.12-1.57), compared to Comirnaty. The trend in the Bologna cohort, based on 3979 measurements, showed a decrease in mean standardized antibody level from 8.17 to 7.06 (1-7 months, p for trend 0.005). Conclusions: Our findings corroborate current knowledge on the determinants of COVID-19 vaccine-induced immunity and declining trend with time.

Temporal trends in health worker social media communication during the COVID-19 pandemic.

During the COVID-19 pandemic, healthcare professionals are exposed to extreme hazards and workplace stressors. Social media postings by physicians and nurses related to COVID-19 from January 21 to June 1, 2020 were obtained from the Reddit website. Topic modeling via Latent Dirichlet Allocation (LDA) using a machine-learning approach was performed on 1723 documents, each posted in a unique Reddit discussion. We selected the optimal number of topics using a heuristic approach based on examination of the rate of perplexity change (RPC) across LDA models. A two-step multiple linear regression was done to identify differences across time and between nurses versus physicians. Prevalent topics included excessive workload, positive emotional expression and collegial support, anger and frustration, testing positive for COVID-19 and treatment, use of personal protective equipment, impacts on healthcare jobs, disruption of medical procedures, and general healthcare issues. Nurses' posts initially reflected concern about workload, personal danger, safety precautions, and emotional support to their colleagues. Physicians posted initially more often than nurses about technical aspects of the coronavirus disease, medical equipment, and treatment. Differences narrowed over time: nurses increasingly made technical posts, while physicians' posts increasingly were in the personal domain, suggesting a convergence of the professions over time.

The resiliency of elective total shoulder arthroplasty case volumes in the United States during the COVID-19 pandemic: a nationwide temporal trends analysis.

BACKGROUND: Total shoulder arthroplasty (TSA) is one of the fastest growing procedures in terms of volume performed in hospitals in the United States. In 2020, elective surgery was suspended nationwide as a result of the SARS-CoV-2 (COVID-19) pandemic, and the use trends in the wake of the pandemic have yet to be evaluated substantially. Nationwide case volume reduction for TSA is unknown; therefore, the aim of this study is to compare patient demographics, complications, and temporal trends in case volume of elective TSA in the calendar year 2019 (prepandemic) to 2020 in the United States. METHODS: Using a multicenter, nationwide representative sample from 2019 to 2020, a retrospective query was conducted for all patients undergoing elective TSA. Patients undergoing surgery pre-COVID (2019 and 2020 Q1) were compared to those during COVID (2020 Q2-Q4). Temporal trends in case volumes were compared between time frames. TSA use, patient demographics, complications, and length of stay were compared between years. Linear regression was used to evaluate for changes in the case volume over the study period. A statistical significance threshold of P <.05 was used. RESULTS: In total, 9667 patients underwent elective TSA in 2019 (n = 5342) and 2020 (n = 4325). The proportion of patients who underwent outpatient TSA in 2020 was significantly greater than the year prior (20.6% vs. 13.9%; P < .001). Overall, elective TSA case volume declined by 19.0% from 2019 to 2020. There was no significant difference in the volume of cases in 2019 Q1 (n = 1401) through 2020 Q1 (n = 1296) (P = .216). However, elective TSA volumes declined by 54.6% in 2020 Q2. Elective TSA case volumes recovered to prepandemic baseline in 2020 Q3 and 2020 Q4. The average length of stay was comparable in 2020 vs. 2019 (1.29 vs. 1.32 days; P = .371), with the proportion of same-day discharge increasing per quarter from 2019 to 2020 (from 11.8% to 26.8% of annual cases). There was no significant difference in the total complication rates in 2019 (4.6%) vs. 2020 (4.9%) (P = .441). CONCLUSION: Using a nationwide sample, elective TSA precipitously declined during the second quarter of 2020. Patient demographics of those undergoing elective TSA in 2020 were similar in comorbidity burden. A large proportion of surgeries were transitioned to the outpatient setting, with rates of same-day discharge doubling over the study period despite no change in overall complication rates.

The evolution of urban competitiveness studies over the past 30 years. A bibliometric analysis

Since the 1990s, the scientific debate on territorial competitiveness has gone through different phases due to the various events that have occurred such as uncontrolled urbanisation, globalisation and digitalisation. Initially linked to competition between companies and, subsequently, to the productivity of countries, today, competitiveness is played out between territories and, above all, between cities. For this reason, competitiveness has become a characteristic of the city and can therefore be considered multidimensional from a systemic perspective typical of urban studies. Researchers agree in defining it as the ability to attract investments, business, creativity, talents and visitors, which is possible by enhancing various urban dimensions. The review presented in this paper analyses the foremost definitions and paradigms, investigates quantitative approaches and identifies the main trends and research gaps concerning the topic of urban competitiveness, through a bibliometric analysis. We have selected almost 1600 documents published between 1967 and 2020 from the Scopus database and we have examined them using bibliometric tools such as VOSiewer and ScientoPy. The aim is to analyse the diachronic and geographical evolution of research, to define future development and directions. The result is that the approach to the research depends on a wide variety of factors, including the time of publication, the scientific framework, the models and, lastly, the region the study comes from. We found that the ability to cope with future challenges has gradually taken on an essential role in defining how competitive a city is on an international scale, especially following the 2008 global financial crisis and the more recent COVID-19 crisis.

Extracting Major Topics of COVID-19 Related Tweets

With the outbreak of the Covid-19 virus, the activity of users on Twitter has significantly increased. Some studies have investigated the hot topics of tweets in this period;however, little attention has been paid to presenting and analyzing the spatial and temporal trends of Covid-19 topics. In this study, we use the topic modeling method to extract global topics during the nationwide quarantine periods (March 23 to June 23, 2020) on Covid-19 tweets. We implement the Latent Dirichlet Allocation (LDA) algorithm to extract the topics and then name them with the "reopening", "death cases", "telecommuting", "protests", "anger expression", "masking", "medication", "social distance", "second wave", and "peak of the disease"titles. We additionally analyze temporal trends of the topics for the whole world and four countries. By analyzing the graphs, fascinating results are obtained from altering users' focus on topics over time. © 2021 IEEE.

A learning health system approach to the COVID-19 pandemic: System-wide changes in clinical practice and 30-day mortality among hospitalized patients.

Introduction: Rapid, continuous implementation of credible scientific findings and regulatory approvals is often slow in large, diverse health systems. The coronavirus disease 2019 (COVID-19) pandemic created a new threat to this common "slow to learn and adapt" model in healthcare. We describe how the University of Pittsburgh Medical Center (UPMC) committed to a rapid learning health system (LHS) model to respond to the COVID-19 pandemic. Methods: A treatment cohort study was conducted among 11 429 hospitalized patients (pediatric/adult) from 22 hospitals (PA, NY) with a primary diagnosis of COVID-19 infection (March 19, 2020 - June 6, 2021). Sociodemographic and clinical data were captured from UPMC electronic medical record (EMR) systems. Patients were grouped into four time-defined patient "waves" based on nadir of daily hospital admissions, with wave 3 (September 20, 2020 - March 10, 2021) split at its zenith due to high volume with steep acceleration and deceleration. Outcomes included changes in clinical practice (eg, use of corticosteroids, antivirals, and other therapies) in relation to timing of internal system analyses, scientific publications, and regulatory approvals, along with 30-day rate of mortality over time. Results: The mean (SD) daily number of admissions across hospitals was 26 (29) with a maximum 7-day moving average of 107 patients. System-wide implementation of the use of dexamethasone, remdesivir, and tocilizumab occurred within days of release of corresponding seminal publications and regulatory actions. After adjustment for differences in patient clinical profiles over time, each month of hospital admission was associated with an estimated 5% lower odds of 30-day mortality (adjusted odds ratio [OR] = 0.95, 95% confidence interval: 0.93-0.97, P < .001). Conclusions: In our large LHS, near real-time changes in clinical management of COVID-19 patients happened promptly as scientific publications and regulatory approvals occurred throughout the pandemic. Alongside these changes, patients with COVID-19 experienced lower adjusted 30-day mortality following hospital admission over time.

Acceleration of opioid-related EMS runs in the spring of 2020: The National Emergency Medical Services Information System data for 2018-2020.

BACKGROUND: State- and county-level reports suggest that the COVID-19 pandemic exacerbated the opioid crisis. We examined US national trends of nonfatal opioid overdose in 2020 in comparison to pre-COVID years 2018-2019. METHODS: We used National Emergency Medical Services Information System (NEMSIS) data to conduct a temporal analysis from 2018 to 2020. Opioid-related EMS run was defined using five scenarios of naloxone administration. To determine annual patterns and slope inflection points, we used the Prophet model of the time series analysis. Linear slopes and their 95% confidence intervals (CIs) were calculated for pre-stay-at-home (pre-SaH) and SaH periods in 2020 and compared to the slopes during the same time in 2018-2019. Three cut-points for SaH start were considered: March 19, 24, and 29. RESULTS: We identified 91,065, 144,802, and 242,904 opioid-related EMS runs in 2018-2020, respectively. In 2020, opioid-related runs increased in January-June, with a pronounced acceleration in March, which coincides with the stay-at-home (SaH) orders. In both 2018 and 2019, opioid-related runs increased in January-August without the spring acceleration. In 2020, weekly increases (95% CI) during SaH for all examined cut-points were significantly greater than in pre-SaH: 18.09 (16.03-20.16) vs. 6.44 (3.42-9.47) for March 19, 17.77 (15.57-19.98) vs. 4.85 (2.07-7.64) for March 24, 18.03 (15.68-20.39) vs. 4.97(2.4-7.54) for March 29. No significant difference was found between these periods in 2018-2019. CONCLUSIONS: The acceleration of opioid-related EMS runs during the SaH period of 2020 suggests that EMS data may serve as an early warning system for local health jurisdictions to deploy harm reduction/prevention resources.

Vaping and COVID-19: Insights for Public Health and Clinical Care from Twitter.

This study describes key topics of discussions on Twitter at the intersection of vaping and COVID-19 and documents public reactions to announcements from authoritative health agencies. Twitter posts containing vaping and COVID-19-related terms were collected from 1 December 2019 to 3 May 2020 (n = 23,103 posts). Text classifiers and unsupervised machine learning were used to identify topics in posts. Predominant topics included COVID-19 Respiratory Health (18.87%), COVID-19 Susceptibility (17.53%), Death (10.07%), Other COVID-19 Health Effects (9.62%), and Severity of COVID-19 (7.72%), among others. Public conversations on topics, such as Severity of COVID-19, Transmission, Susceptibility, Health Effects, Death, and Smoking cessation, were shaped by announcements from U.S. and international health agencies. Armed with the insights from this study, medical providers should be prepared to discuss vaping-related health risks with their patients in the era of COVID-19. Misconceptions around vaping as a protective behavior from, and an effective treatment against, COVID-19 should also be corrected.

[Social inequalities in the regional spread of SARS-CoV-2 infections]. / Soziale Ungleichheit in der regionalen Ausbreitung von SARS-CoV-2.

BACKGROUND AND OBJECTIVE: It has not been adequately answered whether the spread of SARS-CoV­2 is influenced by social and economic factors. Earlier studies generally looked at cumulative incidences up to the analysis date and did not take into account the development of the spread over time. This study therefore focuses on the regional dynamic of new infections and their relationship to socioeconomic factors. Based on the literature we describe the state of knowledge and present our own analyses of administrative data from Germany. METHODS: For this study, we examined regional progress data of reported COVID-19 cases for 401 cities and counties in Germany and associated them with socioeconomic characteristics of the areas. Age-standardized weekly incidence rates were calculated for the period from 3 February 2020 to 28 March 2021. Macroindicators were added from the INKAR database (e.g., income, employment rate, and crowding). RESULTS: While areas with higher incomes and lower poverty had higher incidences in the first and at the beginning of the second wave of the pandemic, they increased significantly in low-income regions from December 2020 on. Regions with a high proportion of gainfully employed people in general and especially those in the manufacturing sector had high incidences, especially in the second wave and at the beginning of the third wave. A low mean living space per inhabitant was related to higher incidence rates since November 2020. CONCLUSION: The regional temporal course of the pandemic correlates with social and economic indicators. A differentiated consideration of these differences could provide information on target group-specific protection and test strategies and help to identify social factors that generally favor infections. An English full-text version of this article is available at SpringerLink as Supplementary Information.

Trends of COVID-19 Admissions in an Italian Hub during the Pandemic Peak: Large Retrospective Study Focused on Older Subjects.

Older multimorbid frail subjects have been severely involved in the coronavirus disease-19 (COVID-19) pandemic. The aim of this retrospective study is to compare the clinical features and outcomes of patients admitted in different phases of the outbreak in a COVID-19 hospital hub, with a particular focus on age, multimorbidity, and functional dependency. The clinical records of 1264 patients with clinical and radiological features compatible with COVID-19 pneumonia admitted in February-June, 2020, were analyzed, retrieving demographical, clinical, laboratory data, and outcomes. All variables were compared after stratification by the period of admission (first phase: rising slope of pandemic wave; second phase: plateau and falling slope), age, results of the first reverse transcriptase-polymerase chain reaction (RT-PCR) test for detection of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), multimorbidity (≥2 chronic diseases), and presence of disability. Factors independently associated with hospital mortality were determined by multivariate forward-selection logistic regression. Patients admitted during the second phase were older, more frequently multimorbid, disabled, and of female gender. However, on admission they exhibited milder respiratory impairment (PaO2/FiO2 268, IQR 174-361, vs. 238, IQR 126-327 mmHg, p < 0.001) and lower mortality (22% vs. 27%, p < 0.001). Age, respiratory exchanges, positive RT-PCR test, number of chronic diseases (odds ratio (OR) 1.166, 95% confidence interval (CI) 1.036-1.313, p = 0.011), and disability (OR 1.927, 95% CI 1.027-3.618, p = 0.022) were positively associated with mortality, while admission during the second phase exhibited an inverse association (OR 0.427, 95% CI 0.260-0.700, p = 0.001). In conclusion, older multimorbid patients were mainly hospitalized during the second phase of the pandemic wave. The prognosis was strongly influenced by the COVID-19 phenotype and period of admission, not just by age, multimorbidity, and disability.

Temporal changes of haematological and radiological findings of the COVID-19 infection-a review of literature.

BACKGROUND: COVID-19 is a systemic viral infection which mainly targets the human respiratory system with many secondary clinical manifestations especially affecting the hematopoietic system and haemostasis. Few studies have highlighted the prognostic value of blood findings such as lymphopenia, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, LDH, CRP, cardiac troponin, low-density lipoproteins and chest radiographic abnormality. A study of progressions of blood and radiological results may help to identify patients at high risk of severe outcomes. This systematic review aimed to assess the temporal progression of blood and radiology findings of patients with COVID-19. METHODS: Comprehensive systematic literature search was conducted on Medline, Embase and Cochrane databases to identify articles published for peripheral blood investigation and radiological results of COVID-19 patients. RESULTS: A total of 27 studies were included in this review. The common laboratory features reported include lymphopenia, elevated levels of C-reactive proteins and lactate dehydrogenase. For radiological signs, ground-glass opacifications, consolidations, and crazy paving patterns were frequently reported. There is a correlation between lymphocyte count, neutrophil count and biomarkers such as C-reactive proteins and lactate dehydrogenase; at a later phase of the disease (more than 7 days since onset of symptoms), lymphopenia worsens while neutrophil count, C-reactive protein levels and lactate dehydrogenase levels increase. Frequencies of ground-glass opacifications and ground-glass opacifications with consolidations decrease at a later phase of the disease while that of consolidation and crazy paving pattern rises as the disease progresses. More extensive lung involvement was also seen more frequently in the later phases. CONCLUSION: The correlation between temporal progression and the reported blood and radiological results may be helpful to monitor and evaluate disease progression and severity.