COVID-19 fake news on Twitter: A statistical and sentimental analysis

There have been increasing concerns about spreading COVID-19 fake news and misinformation from social media sites (SNSs) such as Facebook and Twitter, as they facilitate connection and communication on a large scale. Because of the massive amount of information transmitted through SNSs, manual verification of such information is impossible, prompting the development and implementation of automated methods for fake news identification, aka automatic fact-checking. Fake news creators employ a variety of aesthetic tactics to increase their success rates, one of which is to excite the readers' sentiment. Therefore, this research uses sentiment analysis to analyze whether sentimental and emotional words in SNSs content could explain the situations between the spreading of true and fake news. In this way, governments and platform providers could take action to help the general public identify fake news and misinformation and curb them at their source. This research also offers insights to the public on the importance and impacts of sentiment words in SNS content. © 2023, IGI Global. All rights reserved.

Modern pandemic crises and default risk: Worldwide evidence

This article examines the relationship between modern health pandemic crises and financial stability. Specifically, it collects data on 250,223 firms in 43 countries (or regions) during five modern pandemic crises, SARS (2003), H1N1 (2009), MERS (2012), Ebola (2014), and Zika (2016), and finds that pandemic crises significantly increase the default risk of enterprises. Further analysis shows that formal and informal institutions acted as a "cushion” against the pandemic crisis. The earlier a country adopts IFRS, the more unimpeded access to information, and the more stable religious and ethnic relations within the country can reduce the negative impact of a pandemic on financial stability. This article addresses the hitherto inadequacy of COVID-related data. In addition, this article argues that governments should build sound state institutions to withstand macroeconomic shocks and highlights the heterogeneity of default risk for enterprises operating in countries with different institutions. © 2023 John Wiley & Sons Ltd.

Influence of institutional differences on trade credit use during pandemics

This study examines the formal and informal institutions that affected trade credit during the pandemic periods. To this end, we analyze 590,025 firm-year observations across 107 countries during six recent pandemic crises: SARS (2003), H1N1 (2009), MERS (2012), Ebola (2014), Zika (2016), and COVID-19 (2020). The study finds that formal legal institutions and firms' information transparency during pandemic periods act as a "brake” for trade credit usage. By contrast, informal institutions with religious connotations or attributes, social trust, and policy stability play a "cushion” role in softening the impact of pandemic crises when a firm applies for trade credit. These results remain robust after alternating the estimation techniques, trade credits, pandemic variables, and different samples. This study offers new evidence on the role of trade credit from the perspectives of formal and informal institutions during pandemic crises. The outcomes thus provide information worthy of consideration by policymakers when faced with informal institutional conditions and support government efforts to improve unstable formal systems and prevent severe shocks in the future. © 2022

When Privacy, Distrust, and Misinformation Cause Worry About Using COVID-19 Contact-Tracing Apps

Public health authorities worldwide are advocating for contact-tracing apps to help track COVID-19 infections during the pandemic and interrupt virus transmission. However, app users have to share their personally identifiable information, whereabouts, and in some cases, their vaccination records with authorities via mobile Internet. This situation creates grave concerns about how such personal information is transmitted, stored, archived, and disposed. In addition, the apps'technical design would also impact the adoption, such as whether the apps would drain the battery. Further, citizens'high distrust of governments also reduces app adoption. This article reviews recent research on contact-tracing apps and examines how privacy concerns, distrust in governments, and misinformation affect people's perceptions of contact-tracing apps. We recommend possible solutions for promoting these apps by analyzing what we learn from recent literature. IEEE

The Effect of the Covid-19 Vaccine and Covid-19 Infection on Menstrual Cycle Length: An Analysis of 10,922 Patients

Objective: To evaluate whether receiving a COVID-19 vaccine or infection with COVID-19 had an impact on the length of menstrual cycles in women of reproductive age. Material(s) and Method(s): Cross-sectional, nationwide study of reproductive age females users of the menstrual tracker app Glow. All participants were aged 18-55 and lived in the United States. From 3/3/22 to 4/7/22, participants who had at least 6 months of continuous app use prior to and after April 2021 (defined as logging of menstrual cycle data) were invited to participate in a short questionnaire asking about vaccine status, COVID infection status, and symptoms around the time of vaccination and/or infection. This study was approved by the University of California IRB. Result(s): Out of 218,977 eligible individuals, 11,591 completed the study. 10,922 (representing 269,278 cycles) were included. Some patients were excluded due to not having 6 cycles of data before or after the vaccine or infection and for reporting hormonal birth control use. 75% received two doses of the vaccine (60% Pfizer-BioNTech, 34% Moderna, and 7% J&J), 5% received one dose (63% Pfizer-BioNTech, 37% Moderna, and 1% J&J), and 20% were unvaccinated. There was no change in menstrual cycle length after one or two doses of the vaccine (-0.01 day, 95% CI -0.05 to 0.03 and -0.01 days, 95% CI -0.06 to 0.03, respectively), as was the case in unvaccinated patients (0.05 days, 95% CI -0.02 to 0.12). While participants who reported a COVID infection were noted to have a shorter first cycle after infection (-0.07 days, 95% CI -0.11 to -0.02), this difference was not clinically significant. There were no differences in months 2-6 after infection, or in average cycle length in the 6 months after infection. Of note, whether a patient was symptomatic or asymptomatic with vaccination or infection did not meaningfully impact the menstrual cycle length. Conclusion(s): The COVID-19 vaccine and COVID-19 infection do not result in meaningful menstrual cycle changes compared to unvaccinated or uninfected individuals, respectively. Impact Statement: This is the largest study to date to describe that the COVID-19 vaccine and COVID-19 infection do not appear to result in menstrual cycle changes and adds to the body of literature supporting the safety of the COVID-19 vaccine. Support: No financial support. Copyright © 2022

VALIDATION OF A MACHINE LEARNING MODEL IN A PROSPECTIVE COHORT: THE RISQ STUDY

Introduction Previously our group had identified 20 features which were associated with the development of upper gastrointestinal (UGI) cancers using a machine learning approach.[1] We sought to refine this model and to validate this in an independent dataset to assess its generalisability in an interim analysis. Methods We selected patients who were recruited for the multicentre Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study to develop our model. Patients were recruited from 2-week wait suspected UGI pathways and additionally enriched with patients with confirmed oesophageal adenocarcinoma admitted as inpatients. We used regularised logistic regression (glmnet) from the caret package in R software to create the model. 60% of the data with 10-fold cross validation was used for training, with the remaining 40% for testing. For validation, we used data from the predicting RIsk of disease uSing detailed Questionnaires (RISQ) study, an ongoing prospective multicentre study using the questionnaire based on the our previous work.1 We evaluated the model using area under the receiver operating characteristic curve (AUC). Results We included 93 cancer and 715 non-cancer patients for training and testing and 21 cancer and 203 non-cancer patients for validation. We further reduced the model to 18 features without significant detriment to model performance. In the training and testing data AUC was 0.86 (95%CI: 0.81- 0.91) and 0.75 (95%CI: 0.67-0.83) respectively. We set a threshold of 0.03 as a cut off based on a cost function where false negatives had a 50-time greater impact than false positive cases (figure 1). For the validation cohort we achieved an AUC of 0.95 (95%CI: 0.90-1.00). This equated to a sensitivity 0.952 and a specificity of 0.897 for detecting cancer. Conclusions Initial results from our model compare favourably with the Edinburgh Dysphagia Scale, which has a sensitivity and specificity of 0.984 and 0.093 respectively.2 It also appears to have a high specificity, potentially helping to reduce unnecessary endoscopies. We aim to further increase the size of the validation cohort to ensure its robustness and generalisability. Our model could be applied to triaging and prioritising endoscopic referral backlogs as a result of COVID- 19.3.

USING MACHINE LEARNING TO DEVELOP MODELS FOR THE PREDICTION OF UPPER GASTROINTESTINAL CANCERS

Introduction Machine learning methods have been used to develop predictive models in gastroenterology.1 Previously we identified features including age, history of psychological disorders and severity of dysphagia symptoms which were correlated with upper gastrointestinal (UGI) cancers.2 We sought to create a machine learning based model which could be used to predict the presence of UGI in patients referred for endoscopy. Methods Patients were recruited as part of the Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study. Patients were recruited from 2-week wait suspected UGI pathway referrals at 20 hospitals in the United Kingdom. We enriched the cohort with additional patients admitted with confirmed oesophageal adenocarcinoma. 60% of the data was used for model generation with 10-fold cross validation, while the models were tested on the remaining 40% of the data. We used seven methods to generate our models: Linear Discriminant Analysis (lda), Classification and Regression Tree (cart), k-Nearest Neighbour (knn), Support Vector Machines (svm), Random Forest (rf), Logistic Regression (glm) and Regularised Logistic Regression (glmnet). Model performance was assessed using area under the receiver operating characteristic curve (AUC) and DeLong test was used for model comparison. Results 93 cancer and 715 non-cancer patients were included. The best three models with 18 features were glmnet, lda and glm which all achieved an AUC of greater than 0.80 (figure 1). For the testing dataset, AUC was 0.75 (95%CI: 0.67- 0.83), 0.74 (95%CI: 0.66-0.82) and 0.75 (95%CI: 0.68-0.83) (p=ns for all 3 pairwise comparisons) respectively. When applying a cost function, the three models all achieved a sensitivity of 0.973 and a specificity of 0.234 to 0.388 for the testing dataset. Conclusions Our models compare favourably with the Edinburgh Dysphagia Scale, which has a sensitivity and specificity of 0.984 and 0.093 respectively.3 Our models have the advantage of an improved specificity, which could equate to fewer endoscopies being performed for low risk patients. Given rising waiting lists as a direct result of COVID-19, our tool could be used to prioritise patients who should be investigated sooner.4 We plan next to validate our models on a validation cohort to assess its generalisability.

IMPACT OF COVID-19 ON THE CLINICAL OUTCOMES AND MANAGEMENT OF IGG4 RELATED DISEASE PATIENTS WITH PANCREATOBILIARY INVOLVEMENT: A MULTICENTER RETROSPECTIVE STUDY

Background: Coronavirus disease 2019 (COVID-19) has affected more than 249 million people worldwide as of November 2021. Patients with chronic immune-mediated inflammatory diseases are at risk of viral infections either related to their underlying immune dysfunction or the immunosuppressive therapy, but little is known about the impact of COVID19 on outcomes and management of pancreatobiliary IgG4 related disease (IgG4 RD) patients. Methods: This was a multicenter retrospective cohort study aiming to investigate the impact of COVID-19 on the clinical outcomes and management of pancreatobiliary IgG4 RD patients in different geographic areas with COVID-19 outbreak. Pancreatobiliary IgG4 RD patients aged 18 years or older from 7 referral centers in Hong Kong, Japan, Thailand, Singapore, the United States and Italy were included. Case definition of IgG4 RD: elevated serum IgG4 serology with typical features of pancreatobiliary involvement on imaging, EUS, ERCP and/ or typical histopathologic features of IgG4 RD. Medical records were reviewed for IgG4 RD status (organ involvement, disease activity, treatment status), COVID-19 infection and outcome. Outcome measures were incidence and severity of COVID-19 in pancreatobiliary IgG4 RD patients, medical treatment for the IgG4 disease during COVID-19 and incidence of postponement or discontinuation of indicated medical treatment for IgG4 RD during COVID-19. Results: 101 pancreatobiliary IgG4 RD patients (mean age 66.4 +/- 12.1 years, male 74.3%) from 7 referral centers were included from January 2020 to November 2020. Major comorbidities of patients: none in 21.8%, diabetes in 45.5%, hypertension in 49.5%, ischemic heart disease in 8.9%, chronic liver disease in 8.9%, chronic kidney disease in 9.9% and cancer in 5.0% of patients. IgG4 RD organ involvement: pancreas only in 36.6%, pancreas and bile duct in 16.8%, bile duct only in 14.9%, pancreatobiliary and other organs in 26.7% of patients. The mean serum IgG4 serology level was 4.72+/-7.31 g/L. In 2020, 27.7% of patients had active IgG4 disease while 72.3% of patients were in remission. In 2020, 65.3% of patients received treatment (steroid in 48.5%, thiopurines in 22.7%, steroid and thiopurines in 25.8%, rituximab in 1.5%), while 30.7% of patients were not on treatment. 2 patients (2.0%) had COVID-19 infection, with 1 patient requiring ICU admission. All infected patients recovered from COVID-19 without flare up of IgG4 RD. In 2020, 6.9% of patients had postponement or discontinuation of indicated medical treatment for IgG4 RD during COVID-19 outbreak due to concern of COVID-19 infection while on immunosuppressive therapy. Conclusion: In this study, low incidence of COVID-19 infection and low rates of postponement or discontinuation of indicated medical treatment were observed in pancreatobiliary IgG4 RD patients during COVID-19 outbreak in 2020. (Table Presented)

Challenges to Social Mobility in Singapore: Facilitating social mobility

Singapore has achieved impressive economic growth together with a high level of upward mobility since its independence in 1965. However, the growth process seems to have become more uneven, in addition to diminishing growth for a matured economy such as Singapore, which is also a highly open city-state subject to competitive forces from other economies. Recently, Singapore has fared well, evident from the 2020 social mobility findings reported by the World Economic Forum and the decline in the Gini coefficients for the past decade. This chapter discusses the education system in Singapore and the recently formed National Jobs Council, both important institutions for the advancement of social mobility, followed by some forthcoming policies on foreign manpower, and other related policies to tackle inequality and issues of social mobility. Covid-19 gave rise to four consecutive budgets addressing not just immediate and short-term concerns but also planning for recovery and growth in the future. This chapter examines the challenges to social mobility: future growth prospects and processes, fiscal sustainability expecting greater social spending, and opportunities for the middle-income class together with other familial challenges in Singapore. Using a simple model that endogenises inequality and upward mobility, the chapter analyses important past events and future scenarios: the past influx of and future reduction in migrant unskilled workers;preference shift towards equity;early education intervention;and jobs in the future. An office dedicated to coordinating and evaluating various social mobility programmes is recommended. Strengthening the social compact via policies encouraging concern for others will contribute a positive spillover to both social well-being and social mobility in Singapore. © 2020 section and editorial matter, Hain Teck Hoon.

The case of Singapore

The economic impact of the Covid-19 pandemic on Singapore was more severe and protracted than the global financial crisis. Singapore responded with easing of the monetary policy stance, reinforcing financial stability, helping individuals to reduce debt obligations, easing business cashflow constraints, adjusting financial regulatory and supervisory protocols to cope with immediate challenges, and enabling the financial sectors to build long-term capabilities. Fiscal responses were unprecedented with four consecutive budgets and two ministerial statements, initially focusing on immediate assistance in respect of jobs, businesses, households, and later refined to providing more sector-specific assistance as the pandemic evolved with more detailed information available, and preparing for post-pandemic recovery and growth. Singapore has accumulated sufficient reserves over the years, which are a strategic asset, enabling it to tackle the negative impact of the pandemic without incurring national debt, thanks to the fiscal prudence and sustainability institutionalized in the constitution. Together with decisive public health measures to curb the spread of the virus, the monetary–fiscal policy mix has been appropriate so far, and the eventual long-term policy effectiveness and transformation of the small and highly open economy of Singapore depend hugely on the global containment of the pandemic, the effectiveness and allocation of the vaccine, and the pace of global economic recovery. © 2022 selection and editorial matter, Bernadette Andreosso-O’Callaghan, Woosik Moon and Wook Sohn;individual chapters, the contributors.

SARS-CoV-2 PREVALENCE in CHILDREN and ADULTS in 15 US COMMUNITIES: The COMPASS STUDY

Background: There have been few estimates of SARS-CoV-2 seroprevalence in rigorously sampled and geographically broad populations that include children, who have accounted for fewer diagnosed COVID-19 cases compared to adults. The COMPASS study assessed cross-sectional, population-based SARS-CoV-2 seroprevalence and PCR positivity among adults and children in 15 US communities. Methods: Time-location sampling was used to recruit adults and children >2 months of age from randomly selected venues in communities near participating research sites. Demographics, history of COVID-19 and willingness (likely, very likely or already received) to receive an approved COVID-19 vaccine were captured via an interviewer-administered questionnaire. Serologic analysis was performed using a SARS-CoV-2 IgG nucleocapsid antibody (Ab) assay (Abbott Diagnostics, Abbott Park, IL). PCR testing was performed on a mid-turbinate swab using an assay approved by the HPTN Laboratory Center. Prevalence estimates were constructed, overall and by age group (<18 y, 18-39 y, 40-59 y, 60+ y), for each community using survey weights that accounted for the sampling design. Results: A total of 22,732 persons were enrolled (median per community 1,246, range 511 to 2,925) from Jan 2021 to Aug 2021;of these, 2,151 (9.5%) were <18 y. Overall, SARS-CoV-2 seroprevalence (Ab+) ranged from 3.8 to 17.3% (median 12.5%) and SARS-CoV-2 PCR positivity ranged from 0 to 1.9% (median 0.7%). About half of Ab+ and half of PCR+ persons reported no prior or recent (within 14 days) COVID-19 symptoms, respectively [median by community 49.7% (IQR 45.8, 63.9) and 53.6% (IQR 44.3, 58.3)]. Most adults (18+ y) (median 77.3% [69.6 to 92.7%]) reported willingness to get a COVID-19 vaccination;willingness was higher among persons aged 60 y+ [median 88.1%, IQR 83.5, 90.6] compared to those aged 18-39 [median 72.5%, IQR 64.1, 79.8] and 40-59 [median 75.6%, IQR 72.5, 78.4]. The combined prevalence of prior (Ab+) or active (PCR+) SARS-CoV-2 infection across all communities ranged from 4.4 to 17.6% (median 12.7%), and was similar for children (median 12.7%, range 4.4 to 19.7%) and adults (median 12.5%, range 4.4% to 17.8%) among communities enrolling > 25 children (Figure). Conclusion: In this population-based survey, evidence of prior and active SARS-CoV-2 infection varied widely by community but, contrasting with earlier reports, not by age. These findings suggest that acquisition of SARS-CoV-2 is similar across all ages.

Utilization of the Youth Quitline as an opportunity for an undergraduate nursing students to deliver smoking cessation counseling as their clinical placement: An implementation of a service-learning model.

BACKGROUND: Smoking is an important modifiable risk factor of morbidities and mortality. Although healthcare professionals play an important role in smoking cessation, their adoption of such practices is relatively low because of inadequate training. To address this issue, we incorporated a service-learning model to operate the Youth Quitline. Undergraduate nursing students were trained and received supervision while delivering smoking cessation counseling through the Youth Quitline as their clinical placement. OBJECTIVES: We evaluated the effectiveness of the placement by assessing students' knowledge, attitudes and practices regarding smoking cessation and tobacco control. DESIGN: One-group pretest-posttest design. SETTING: Youth Quitline. PARTICIPANTS: A total of 61 third-year students in a mental health nursing program. METHODS: Students were required to complete 80 h at the Youth Quitline. The 80 h were divided into 20 sessions; students used four sessions to approach and recruit youth smokers in the community, then provided them with telephone counseling for the rest of the time. Prior to the placement, students attended a 2-day workshop. The outcomes were changes in students' knowledge, attitudes and practices regarding smoking cessation and tobacco control 3 months after the placement compared with baseline. RESULTS: From January-June 2021, students conducted 105 outreach activities to identify 3142 smokers in the community, and provided telephone counseling for 336 smokers via Youth Quitline. Compared with baseline, significant improvements were observed in students' knowledge, attitudes and practices regarding smoking cessation and tobacco control at 3-month follow-up. CONCLUSIONS: The clinical placement improved students' knowledge, attitudes and practices regarding smoking cessation and tobacco control, enhancing their competency in providing support to assist smokers to quit in their future practice. Incorporating the service-learning model in existing community-based services can provide additional venues for nursing students to practice. This is particularly important because many venues have restricted access during the COVID-19 pandemic.

College students' Twitter usage and psychological well-being from the perspective of generalised trust: comparing changes before and during the COVID-19 pandemic

Purpose: This study investigated the relationship between generalised trust and psychological well-being in college students, considering the social support obtained from their social networks via Twitter and face-to-face (FTF) interactions. Initially, the authors planned to collect data at the beginning of the first semester in 2019 for fine-tuning the model as a pilot study, and in 2020 for the main study. However, due to the coronavirus disease 2019 (COVID-19) pandemic, the data helped authors to analyse changes in young people's psychological situation before and during the pandemic in Japan. Design/methodology/approach: The study conducted a self-report survey targeting college students in the Kanto region in Japan. Data were collected from mid-May to the end of June 2019, as well as in early to mid-June 2020, with 304 and 584 responses, respectively. The collected data were analysed using structural equation modelling and a multiple regression analysis. Findings: The findings using the 2019 data set indicated that (a) students mostly used Twitter for information gathering and sharing of hobbies, and they received both informatics and emotional support from Twitter, and from FTF interactions;(b) there were direct positive effects of generalised trust and social skills on their psychological well-being;and (c) students with lower levels of generalised trust tended to interact with very intimate individuals using Twitter to obtain social support, which did not have any effects on their improvement of psychological well-being. From the 2020 data set, the authors also found that, like 2019, generalised trust and social skills had direct effects on the improvement of psychological well-being. Additionally, we observed that students spent more time using Twitter and received more emotional support from it, as most people tried not to meet other people in person due to the first State of Emergency in Japan. Similarly, the authors found that in 2019, only social support from very intimate partners via FTF communication had slightly significant effects on improving their psychological well-being, whereas in 2020, their expectation for social networks via FTF had decreased their levels of psychological well-being, but their social support from Twitter had slightly significant effects on their improvement of psychological well-being. One of the main reasons for this might be due to the challenge of meeting with others in person, and therefore, social support from Twitter partially played a role that traditionally was only beneficial through FTF communication. Originality/value: We understand that this is one of the few social psychological studies on social media that collected data both before and during the COVID-19 pandemic. It provides unique evidence in demonstrating how the COVID-19 pandemic has changed college students communication behaviours. © 2022, Emerald Publishing Limited.

Strong government responses? Reflections on the management of COVID-19 in Hong Kong and Taiwan

Purpose: A debate emerged among members of public administration academia soon after COVID-19 appeared on the roles and measures that governments ought to deploy to prevent infection. One prevalent discourse is the strength of “strong government” in the fight against the virus—the administrative capacity to launch prompt, appropriate and effective actions that entail collaboration with citizens. A notable development in governance is that new public management (NPM) principles, such as the value of money and the pluralisation of service delivery, are gradually put aside when governments urgently need to curb the spread of infection. The roles of bureaucracy and centralised action are re-emphasised in the policymaking and implementation of anti-epidemic measures. Such a trend allows us to examine if the COVID-19 public health crisis has fundamentally reversed the trend of government retreat in public service within neoliberal regimes since the 1980s. Design/methodology/approach: For this research, the authors selected two “strong governments” in Asia—Hong Kong and Taiwan—by showing how administrators outline their anti-pandemic strategies, examining the role of government in coordinating responses and how bureaucracy interacts with the other two key domains of the governance mechanism: civil society and the market. These two offshore Chinese capitalist economies and pluralistic societies are perceived to have “strong government capacity” in the fight against COVID-19, presumably as a key attribute to their success confining the spread of infection during the early stages of the first outbreak. Both societies reported low infection rates and low mortality rates until September 2020. The authors browsed databases developed by scholars (Cheng et al., 2020;Hale et al., 2020) and referred to two “rubrics” to assess and compare government actions in both places in response to COVID-19. The authors itemised, categorised and counted the policy actions in both places according to the rubrics, noticed that the policy footprint appeared in over two-thirds of indicators of proactive government interventions and identified double-digit counts in nearly half of the categories. Findings: The authors found that both governments attempted to establish strong stewardship and quick measures to contain the infection. The pattern of “strong government” is, however, not the same as that superficially exhibited. Taiwan took limited steps to regulate business activities but proactively intervened and coordinated the supply of hygienic utilities. Hong Kong launched aggressive attempts to reduce human mobility but remained non-active despite the “face mask run” in society. The “strong government” aspect also received divergent reactions from society. There was extensive cross-sectoral collaboration under the centralised “National Team” advocacy in Taiwan, and there has been no record of local infection for over 10 months. The Hong Kong government was repeatedly doubted for its undesirable stewardship in anti-epidemic measures, the effectiveness of policy interventions and the impartiality of law enforcement. Spontaneous actions during the health crisis from civil societies and private markets were noted, but they seemed uncoordinated with official attempts. Originality/value: The initial findings enable us to rethink correlations between state capacity and legitimacy in the fight against the virus and its development post-COVID-19. Apparently, Taiwan and Hong Kong demonstrated a “re-expansion” of their public sector during the public health crisis, but not in the same format. This can be understood based on their varying regime values and administrative systems. The pandemic has been a catalyst, pushing both regimes back to their original track of public administration establishments. The concept of “path dependence” might explain the initial development and project the longer-term transformation of the public sector in both places. © 2022, Emerald Publishing Limited.

The relationship between obesity classifications and outcomes in COVID-19 infection in New York

Background: Despite its high prevalence, published data on COVID-19 infection in obese subjects remains limited. When compared to early-onset diabetes, chronic obstructive pulmonary disease (COPD), advanced age, hypertension (HTN), immunosuppression, and chronic kidney disease (CKD), obesity was the only comorbidity that conferred an increased risk of death exclusively for COVID-19 compared to non-COVID- 19 patients. Any degree of obesity has been associated with poor prognosis in patients with COVID-19 and the risk of mechanical ventilation (MV) is the greatest in patients with BMI > 35 kg/m2, independent of age, diabetes, and hypertension. The aim of our study is to examine the association between various degrees of obesity and the clinical outcomes of patients with COVID-19 infection. Methods: This is a retrospective multicenter cohort study of adult patients with a BMI ≥30 kg/m2 presenting to six hospitals in the New York metropolitan region between March 7 and June 7, 2020, with COVID-19 infection. The clinical outcome assessed included hospitalization, in-hospital mortality, intensive care unit (ICU) admission, and MV. Outcomes were compared using a multivariate Cox regression model and Propensity Score matching model. Results: The study population comprised 9,991 patients, of whom 53.43% were obese (BMI ≥30 kg/m2). Higher comorbidity burdens, including HTN, Diabetes, CKD, and smoking, were noted in those with Class I and II obesity, relative to Class III obesity (44.54% & 38.00% vs. 22.94%). Obesity increases the risk for in-hospital mortality and intubation across all BMI ranges. Individuals with a BMI ≥ 30 were observed to have the highest risk of ICU admissions (OR 1.29;1.2-1.48;p < 0.001). There were higher rates of in-hospital mortality among obese patients across all BMI [BMI ≥ 30 (OR 1.23;1.09-1.40, p < 0.001);BMI ≥ 35 (OR 1.48;1.28-1.70, p < 0.001);BMI ≥ 40 (OR 1.81;1.55-2.13, p < 0.001). Conclusions: Obesity is an independent risk factor for increased mortality in those with COVID-19 infection. Data from this study supports and further expands the existing knowledge on the relationship between obesity and COVID-19 infection. Clinicians must focus on early prevention and management of obesity.