Monitoramento das Produções

by Victor Hugo Aquino, Marcilio J. Fumagalli, Angélica Silva, Bento Vidal de Moura Negrini, Alejandra Rojas, Yvalena Guillen, Cynthia Bernal, Luiz Tadeu Moraes Figueiredo

The arrival of the Zika virus (ZIKV) in dengue virus (DENV)-endemic areas has posed challenges for both differential diagnosis and vaccine development. Peptides have shown promise in addressing these issues. The aim of this study was to identify the linear epitope profile recognized by serum samples from dengue and Zika patients in the E and NS1 proteins of DENV and ZIKV. This cross-sectional study included individuals of all ages with laboratory-confirmed DENV and ZIKV infections, who were selected through convenience sampling. The serum samples from dengue and Zika patients detected epitopes evenly distributed across the viral proteins in a peptide microarray platform. However, several epitopes were located within “epitope hotspots”, characterized by clusters of peptides recognized in more than 30% of the sub-arrays analyzed using individual or pooled serum samples. The serum samples from dengue and Zika patients showed a high level of cross-reactivity with peptides in the DENV and ZIKV proteins. Analysis using an additional peptide microarray platform, which contained peptides selected based on the results of the initial screening, revealed that two DENV and one ZIKV peptide, highly specific to their related viruses, were located within the epitope hotspots; however, they presented low detection rates (32.5, 35.0, and 28.6%, respectively). In addition, two DENV peptides detected at similarly high rates by both dengue and Zika patients were also found within the epitope hotspots. These hotspots contain several immunodominant epitopes that are recognized by a larger number of individuals when compared to 15-amino acid (aa) sequence peptides. Thus, epitope hotspots may have greater potential to serve as antigens in diagnostic tests and vaccine development than peptides composed of only 15 amino acids.

by Jonathan Franceschi, Lorenzo Pareschi, Elena Bellodi, Marco Gavanelli, Marco Bresadola

The SARS-CoV-2 pandemic reminded us how vaccination can be a divisive topic on which the public conversation is permeated by misleading claims, and thoughts tend to polarize, especially on online social networks. In this work, motivated by recent natural language processing techniques to systematically extract and quantify opinions from text messages, we present a differential framework for bivariate opinion formation dynamics that is coupled with a compartmental model for fake news dissemination. Thanks to a mean-field analysis we demonstrate that the resulting Fokker-Planck system permits to reproduce bimodal distributions of opinions as observed in polarization dynamics. The model is then applied to sentiment analysis data from social media platforms in Italy, in order to analyze the evolution of opinions about Covid-19 vaccination. We show through numerical simulations that the model is capable to describe correctly the formation of the bimodal opinion structure observed in the vaccine-hesitant dataset, which is witness of the known polarization effects that happen within closed online communities.

by Halil Özekicioğlu, Burcu Yilmaz, Gamze Alkan, Suzan Oğuz, Ceren Kocabaş, Fatih Boz

The present study attempts to explore the impacts of COVID-19 on the intra-group electronic product trade of the world’s seven largest economies. In line with this purpose, we performed a complex network analysis of the electronic product trade of the group of seven (G-7) countries and China, as well as a panel data study comprising solely the G-7 countries. In this regard, we investigated the trade networks within the G-7 countries, to which China has been added, and determined the prominent countries in the network during the pandemic to be China, the USA and Canada. The findings also revealed that China, one of the pioneering countries in electronic product trade, has the most ties in electronic products exports with the USA, the other countries with which the USA had the most ties were Japan and Germany, apart from Canada. It was discovered that Germany was the most active country in the network, following the USA, in terms of export ties and the number of export countries in its network. The panel data analysis, on the other hand, yielded two different models, namely import and export, based on 22 months of data, from March 2020 to December 2021, considering the World Health Organization’s (WHO) declaration of COVID-19 as a pandemic on March 11, 2020. The findings showed that independent variables affecting the electronic product trade within G-7 countries bore different effects in both models, that the deaths/cases ratio, the tests/cases ratio and the number of cases had adverse impacts while the population had positive impacts on exports in the first model, and that the tests/population ratio had adverse effects while the number of tests and the population had positive impacts on intra-group electronic product imports.

by Naseem Cassim, Lindi Marie Coetzee, Manuel Pedro da Silva, Wendy Susan Stevens, Deborah Kim Glencross
Background Coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first reported in Wuhan, China. Due to the rapid spread globally, it was declared a pandemic in March 2020. Social distancing and lockdown measures were introduced to limit transmission. These strategies could potentially impact the diagnosis and treatment of patients with advanced HIV who are susceptible to secondary infections like cryptococcal disease. In South Africa, reflexed cryptococcal antigenaemia (CrAg) testing and pre-emptive antifungal treatment are recommended preceding antiretroviral therapy initiation for patients with a CD4

by Prashant Mahajan, Vaishali Patil

Engineering profession for students and diverse students for Engineering Campuses (ECs) is the prestige to have for both. Worldwide higher education has been impacted by COVID-19 pandemic, but particularly pulling padlocked doors of Indian engineering campuses (ECs) down. Students’ attitudes regarding choice, liking, and preferences were also affected. Knowing how tough ’college choice’ was before the pandemic, one can guess how difficult it will be today. The objective of this study was to explore students’ perceptions of choice characteristics related to ECs and diverse students enabling choice decisions under the COVID-19 situation, and to discover any possible relationships among them. Research questions were qualitatively examined with the statistical confirmation of related hypothesizes by utilizing ANOVA and Regression analysis. A self-reported quantitative survey composed of a closed-ended structured questionnaire was administered on the students of first-year engineering who had recently enrolled in ECs of North Maharashtra Region of India, after pandemic hitting India. According to the study, ECs have several characteristics impacting students’ selection of ECs under pandemic. The influence of proximity, image and reputation, educational quality, and curriculum delivery was significant in contributing sustainability of ECs. This influence was significant across students’ psychological and behavioural biases on likes, choices, and preferences. Furthermore, multiple relationships were noted within the sub-groups of demographic, geographic, socioeconomic, academic performance, and psychological and behavioural traits due to the impact of ECs’ characteristics on sustainability. The study has provided a framework for policymakers and administrators to strengthen repositioning towards sustainability while capturing potentially diverse enrolments. Even if we have to coexist with pandemic forever or with more similar pandemics, the findings of this study may undergo a fundamental transformation for ECs (existing and forthcoming). On the other hand, by understanding the importance and relations of choice characteristics may smoothen the complex nature of "college choice" for prospective students.

by Karl Stattin, Michael Hultström, Robert Frithiof, Miklos Lipcsey, Rafael Kawati

COVID-19 is associated with prolonged intensive care unit (ICU) stay and considerable mortality. The onset of persistent critical illness, defined as when prior illness predicts death better than acute physiological derangement, has not been studied in COVID-19. This national cohort study based on the Swedish Intensive Care Registry (SIR) included all patients admitted to a Swedish ICU due to COVID-19 from 6 March 2020 to 9 November 2021. Simplified Acute Physiology Score-3 (SAPS3) Box 1 was used as a measure of prior illness and Box 3 as a measure of acute derangement to evaluate the onset and importance of persistent critical illness in COVID-19. To compare predictive capacity, the area under receiver operating characteristic (AUC) of SAPS3 and its constituent Box 1 and 3 was calculated for 30-day mortality. In 7 969 patients, of which 1 878 (23.6%) died within 30 days of ICU admission, the complete SAPS3 score had acceptable discrimination: AUC 0.75 (95% CI 0.74 to 0.76) but showed under prediction in low-risk patients and over prediction in high-risk patients. SAPS3 Box 1 showed markedly better discrimination than Box 3 (AUC 0.74 vs 0.65, P

by Anoop D. Shah, Anuradhaa Subramanian, Jadene Lewis, Samir Dhalla, Elizabeth Ford, Shamil Haroon, Valerie Kuan, Krishnarajah Nirantharakumar
Background Long Covid is a widely recognised consequence of COVID-19 infection, but little is known about the burden of symptoms that patients present with in primary care, as these are typically recorded only in free text clinical notes. Aims To compare symptoms in patients with and without a history of COVID-19, and investigate symptoms associated with a Long Covid diagnosis. Methods We used primary care electronic health record data until the end of December 2020 from The Health Improvement Network (THIN), a Cegedim database. We included adults registered with participating practices in England, Scotland or Wales. We extracted information about 89 symptoms and ‘Long Covid’ diagnoses from free text using natural language processing. We calculated hazard ratios (adjusted for age, sex, baseline medical conditions and prior symptoms) for each symptom from 12 weeks after the COVID-19 diagnosis. Results We compared 11,015 patients with confirmed COVID-19 and 18,098 unexposed controls. Only 20% of symptom records were coded, with 80% in free text. A wide range of symptoms were associated with COVID-19 at least 12 weeks post-infection, with strongest associations for fatigue (adjusted hazard ratio (aHR) 3.46, 95% confidence interval (CI) 2.87, 4.17), shortness of breath (aHR 2.89, 95% CI 2.48, 3.36), palpitations (aHR 2.59, 95% CI 1.86, 3.60), and phlegm (aHR 2.43, 95% CI 1.65, 3.59). However, a limited subset of symptoms were recorded within 7 days prior to a Long Covid diagnosis in more than 20% of cases: shortness of breath, chest pain, pain, fatigue, cough, and anxiety / depression. Conclusions Numerous symptoms are reported to primary care at least 12 weeks after COVID-19 infection, but only a subset are commonly associated with a GP diagnosis of Long Covid.

by Corinne M. Hohl, Amber Cragg, Elizabeth Purssel, Finlay A. McAlister, Daniel K. Ting, Frank Scheuermeyer, Maja Stachura, Lars Grant, John Taylor, Josephine Kanu, Jeffrey P. Hau, Ivy Cheng, Clare L. Atzema, Rajan Bola, Laurie J. Morrison, Megan Landes, Jeffrey J. Perry, Rhonda J. Rosychuk, the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) investigators for the Network of Canadian Emergency Researchers , the Canadian Critical Care Trials Group
Introduction Not all patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop symptomatic coronavirus disease 2019 (COVID-19), making it challenging to assess the burden of COVID-19-related hospitalizations and mortality. We aimed to determine the proportion, resource utilization, and outcomes of SARS-CoV-2 positive patients admitted for COVID-19, and assess the impact of using the Center for Disease Control’s (CDC) discharge diagnosis-based algorithm and the Massachusetts state department’s drug administration-based classification system on identifying admissions for COVID-19. Methods In this retrospective cohort study, we enrolled consecutive SARS-CoV-2 positive patients admitted to one of five hospitals in British Columbia between December 19, 2021 and May 31,2022. We completed medical record reviews, and classified hospitalizations as being primarily for COVID-19 or with incidental SARS-CoV-2 infection. We applied the CDC algorithm and the Massachusetts classification to estimate the difference in hospital days, intensive care unit (ICU) days and in-hospital mortality and calculated sensitivity and specificity. Results Of 42,505 Emergency Department patients, 1,651 were admitted and tested positive for SARS-CoV-2, with 858 (52.0%, 95% CI 49.6–54.4) admitted for COVID-19. Patients hospitalized for COVID-19 required ICU admission (14.0% versus 8.2%, p

by Conan Brady, Ellie Shackleton, Caoimhe Fenton, Orlaith Loughran, Blánaid Hayes, Martina Hennessy, Agnes Higgins, Iracema Leroi, Deirdre Shanagher, Declan M. McLoughlin
Background Mental health issues in nursing home staff during the COVID-19 pandemic have been significant; however, it is not known if these issues persist following widespread vaccination and easing of restrictions. Objective To quantify the mental health of nursing home staff at different timepoints during the COVID-19 pandemic in the Republic of Ireland. Design/Methods Two identical, online, cross-sectional, nationwide, anonymous surveys of Republic of Ireland nursing home staff at two timepoints (survey 1 (S1, n = 390): November 2020 to January 2021; survey 2 (S2, N = 229: November 2021 to February 2022) during the COVID-19 pandemic. Convenience sampling was used with staff self-selecting for participation. Methods included the World Health Organisation’s Well-Being Index (WHO-5), the Impact of Events Scale-Revised (IES-R), the Moral Injury Events Scale (MIES), two Likert-scale items regarding suicidal ideation and planning, the Work Ability Score (WAS), the Brief Coping Orientation to Problems Experienced (Brief-COPE) Scale, and a 15-item questionnaire assessing perceptions of the outbreak with one additional Likert-scale item on altruism. Descriptive analysis examined differences between staff based on their classification in one of three groups: nurses, healthcare assistants (HCA) and nonclinical staff. Pseudonymous identifiers were used to link responses across surveys. Results An insufficient number of participants completed both surveys for linked analyses to be performed; therefore, we performed an ecological comparison between these two independent surveys. More staff reported moderate-severe post-traumatic stress symptoms (S1 45%; S2 65%), depression (S1: 39%; S2 57%), suicidal ideation (S1: 14%; S2 18%) and suicidal planning (S1: 9%; S2 15%) later in the pandemic. There was a higher degree of moral injury at S2 (S1: 20.8 standard deviation (SD) 9.1; S2: 25.7 SD (11.3)) and use of avoidant (maladaptive) coping styles at S2 (S1: 20.8 (6.3); S2 23.0 (6.3)) with no notable differences found in the use of approach (adaptive) coping styles. Staff reported more concerns at S2 regarding contracting COVID-19, social stigma, job stress, doubts about personal protective equipment and systems and processes. Conclusion In comparison to our previous survey, mental health outcomes appear to have worsened, coping did not improve, and staff concerns, and worries appear to have increased as the pandemic progressed. Follow-up studies could help to clarify is there are any lingering problems and to assess if these issues are related to the pandemic and working conditions in nursing homes.

by Erlina Burhan, Keibun Liu, Eva M. Marwali, Samuel Huth, Navy G. H. M. L. Wulung, Dafsah A. Juzar, Muhammad A. Taufik, Surya O. Wijaya, Dyah K. Wati, Neurinda P. Kusumastuti, Saptadi Yuliarto, Bhirowo Y. Pratomo, Erwin Pradian, Dadang H. Somasetia, Desy Rusmawatiningtyas, Arie Z. Fatoni, Jose M. Mandei, Eka Y. Lantang, Fajar Perdhana, Bambang P. Semedi, Muhammad Rayhan, Tiffany R. S. Tarigan, Nicole White, Gianluigi L. Bassi, Jacky Y. Suen, John F. Fraser
Background Indonesia’s national response to COVID-19 evolved rapidly throughout 2020. Understanding pandemic response and outcomes is crucial for better mitigation strategies ahead. This study describes the characteristics and outcomes of patients admitted to ICU during the early stages of the pandemic. Methods This is a multi-centre prospective observational study including patients from twelve collaborating hospitals in Indonesia. All patients were clinically suspected or laboratory-confirmed COVID-19 cases admitted to ICU between January 2020 and March 2021. The primary outcome was monthly ICU mortality. Descriptive statistics of patient characteristics and treatment were generated as secondary outcomes. Results From 559 subjects, the overall mortality was 68% and decreased over the study period, while the mortality of patients that received mechanical ventilation was 92%, consistently high over the study period. Fatal cases showed 2- and 4-day delays from symptoms onset to hospital admissions and ICU admissions, respectively. Evidence-backed approaches which could influence patient outcome, such as extracorporeal membrane oxygenation, prone positioning, renal replacement therapy, and neuromuscular blockade were scarcely administered. Conclusions The mortality rate of COVID-19 patients in Indonesia was extremely high during the first major outbreak of disease, particularly in those mechanically ventilated. Delayed admission and unavailability of evidence-based approaches due to high burden on health facility during COVID-19 crisis could be addressed by efficient public health measures and enhancing health infrastructure to improve the future pandemic response.

by Jeremy Bingham, Stefano Tempia, Harry Moultrie, Cecile Viboud, Waasila Jassat, Cheryl Cohen, Juliet R.C. Pulliam
Objectives The aim of this study was to quantify transmission trends in South Africa during the first four waves of the COVID-19 pandemic using estimates of the time-varying reproduction number (R) and to compare the robustness of R estimates based on three different data sources, and using data from public and private sector service providers. Methods R was estimated from March 2020 through April 2022, nationally and by province, based on time series of rt-PCR-confirmed cases, hospitalisations, and hospital-associated deaths, using a method that models daily incidence as a weighted sum of past incidence, as implemented in the R package EpiEstim. R was also estimated separately using public and private sector data. Results Nationally, the maximum case-based R following the introduction of lockdown measures was 1.55 (CI: 1.43–1.66), 1.56 (CI: 1.47–1.64), 1.46 (CI: 1.38–1.53) and 3.33 (CI: 2.84–3.97) during the first (Wuhan-Hu), second (Beta), third (Delta), and fourth (Omicron) waves, respectively. Estimates based on the three data sources (cases, hospitalisations, deaths) were generally similar during the first three waves, but higher during the fourth wave for case-based estimates. Public and private sector R estimates were generally similar except during the initial lockdowns and in case-based estimates during the fourth wave. Conclusion Agreement between R estimates using different data sources during the first three waves suggests that data from any of these sources could be used in the early stages of a future pandemic. The high R estimates for Omicron relative to earlier waves are interesting given a high level of exposure pre-Omicron. The agreement between public and private sector R estimates highlights that clients of the public and private sectors did not experience two separate epidemics, except perhaps to a limited extent during the strictest lockdowns in the first wave.

by Suely Deysny de Matos Celino, Nailton José Brandão de Albuquerque Filho, Monalisa da Nóbrega Cesarino Gomes, Gabriela Maria Cavalcanti Costa, Ana Elza Oliveira de Mendonça
Objective To evaluate the primary health care (PHC) attributes and associated factors during the COVID-19 pandemic using the perspective of users. Methods This cross-sectional, quantitative study included 422 PHC users from 96 Family Health Teams in a city in Brazil. The assessment used the Primary Care Assessment Tool (PCATool) and a structured questionnaire on the sociodemographic and epidemiological characteristics of users and basic health units (BHU). The Person’s chi-square test was used to analyze the association between high overall scores in PCATool and characteristics of users and BHU. Crude and adjusted prevalence ratios (PR) with a 95% confidence interval were also calculated. Poisson regression and Rao Scott’s Chi-square test were used to estimate crude PR. Results Most users were aged 30 to 39 years (26.3%), women (75.4%), registered at the BHU for over ten years (59.5%), and had incomplete secondary education (30.6%). The mean of PHC essential attributes and overall scores were low (6.10 ± 0.81 and 5.78 ± 0.77, respectively). "First-contact care–use" received the highest score (9.22 ± 1.62), while "first-contact care–accessibility" received the lowest (2.82 ± 0.90). High overall scores were associated with an average employment time of professionals (doctors and nurses) at the BHU (PR = 1.31; 95% CI 1.17–1.48; p 0.001) and lower educational level of users (PR = 1.71; 95% CI 1.54–1.90; p 0.001. Conclusion "First-contact care–use" was the best evaluated, while "first-contact care–accessibility" was the worst. High scores were associated with a lower educational level of users and BHU with more experienced professionals.

by Yongxian Fan, Meng Liu, Guicong Sun

Coronaviruses have affected the lives of people around the world. Increasingly, studies have indicated that the virus is mutating and becoming more contagious. Hence, the pressing priority is to swiftly and accurately predict patient outcomes. In addition, physicians and patients increasingly need interpretability when building machine models in healthcare. We propose an interpretable machine framework(KISM) that can diagnose and prognose patients based on blood test datasets. First, we use k-nearest neighbors, isolated forests, and SMOTE to pre-process the original blood test datasets. Seven machine learning tools Support Vector Machine, Extra Tree, Random Forest, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, Logistic Regression, and ensemble learning were then used to diagnose and predict COVID-19. In addition, we used SHAP and scikit-learn post-hoc interpretability to report feature importance, allowing healthcare professionals and artificial intelligence models to interact to suggest biomarkers that some doctors may have missed. The 10-fold cross-validation of two public datasets shows that the performance of KISM is better than that of the current state-of-the-art methods. In the diagnostic COVID-19 task, an AUC value of 0.9869 and an accuracy of 0.9787 were obtained, and ultimately Leukocytes, platelets, and Proteina C reativa mg/dL were found to be the most indicative biomarkers for the diagnosis of COVID-19. An AUC value of 0.9949 and an accuracy of 0.9677 were obtained in the prognostic COVID-19 task and Age, LYMPH, and WBC were found to be the most indicative biomarkers for identifying the severity of the patient.

by Daniel T. L. Shek, Tingyin Wong, Xiang Li, Lu Yu

The use of online teaching mode has grown rapidly in recent years, particularly under the COVID-19 pandemic. To promote the learning motivation of students and teaching effectiveness, development of attractive online teaching material such as videos is important. In the present study, we developed 15 theory-related videos and 9 case-based videos in the context of a leadership course focusing on psychological well-being and psychosocial competence. Using a qualitative research methodology via focus groups (N = 48 students) to evaluate these videos, six themes emerged from the data, including video arrangement, design of videos, content of videos, benefits to students’ pre-lesson self-learning, benefits to students’ learning of course content, and contribution to students’ class participation. The findings suggest that the videos can elicit positive perceptions of the students in a flipped classroom arrangement. Students also benefit from the videos in terms of their understanding of course content and their participation in class discussion. Besides, the study suggests that the videos promote the learning efficiency of the students. The present qualitative findings concurred with the previous quantitative findings, suggesting the value of using virtual teaching and learning to promote psychosocial competence in university students.

by Cydney Low, Isabel Tejero, Nelly Toledano, Caroline Mariano, Shabbir Alibhai, Manon Lemonde, Kristen Haase, Martine Puts

The COVID-19 pandemic and health services impacts related to physical distancing posed many challenges for older adults with cancer. The goal of this study was to examine the impact of the pandemic on cancer treatment plans and cancer treatment experiences of older adults (ie, aged 65 years and older) and their caregiver’ experiences of caring for older adults during the pandemic to highlight gaps in care experienced. In this multi-centre qualitative study guided by an interpretive descriptive research approach we interviewed older adults diagnosed with cancer and caregivers caring for them. Participants were recruited via cancer treatment centres in the provinces of British Columbia and Ontario (Vancouver and Toronto), Canada, and through an online ad sent out through patient advocacy organization newsletters. Interviews were recorded and transcribed verbatim and data were analyzed using an interpretive thematic analysis approach. A total of 27 individuals (17 older adults, 52.9% female; 10 caregivers, 90% female) participated in interviews lasting on average 45 minutes. Older adults with cancer described many impacts and pressures created by the pandemic on their cancer experiences, though they generally felt that the pandemic did not impact treatment decisions made and access to care. We grouped our findings into two main themes with their accompanying sub-themes, related to: (1) alterations in the individual and dyadic cancer experience; and (2) navigating health and cancer systems during the pandemic. The additional stressors the pandemic placed on older adults during their treatment and decision-making process and their caregivers expose the need to create or avail additional supports for future disruptions in care.

by Ryan Murphy, Lauren Pomerantz, Prabhani Kuruppumullage Don, Jun Sung Kim, Bradley A. Long
Introduction Vaccine hesitancy during the COVID-19 pandemic impacted many higher education institutions. Understanding the factors associated with vaccine hesitancy and uptake is instrumental in directing policies and disseminating reliable information during public health emergencies. Objective This study evaluates associations between age, gender, and political leaning in relationship to COVID-19 vaccination status among a large, multi-campus, public university in Pennsylvania. Methods From October 5—November 30, 2021, a 10-minute REDCap survey was available to students, faculty, and staff 18 years of age and older at the Pennsylvania State University (PSU). Recruitment included targeted email, social media, digital advertisements, and university newspapers. 4,231 responses were received. Associations between the selected factors and vaccine hesitancy were made with Chi-square tests and generalized linear regression models using R version 4.3.1 (2023-06-16). Results Logistic regression approach suggested that age and political leaning have a statistically significant association with vaccine hesitancy at the 5% level. Adjusted for political leaning, odds of being vaccinated is 4 times higher for those aged 56 years or older compared to the ones aged 18 to 20 (OR = 4.35, 95% CI = (2.82, 6.85), p-value 0.05). The results also showed that adjusted for age, the odds of being vaccinated is about 3 times higher for liberal individuals compared to far-left individuals (OR = 2.85, 95% CI = (1.45, 5.41), p-value = 0.001). Conclusions Age and political leaning are key predictors of vaccine uptake among members of the PSU community, knowledge of which may inform campus leadership’s public health efforts such as vaccine campaigns and policy decisions.

by Maya R. Sternberg, Amelia Johnson, Justice King, Akilah R. Ali, Lauren Linde, Abiola O. Awofeso, Jodee S. Baker, Nagla S. Bayoumi, Steven Broadway, Katherine Busen, Carolyn Chang, Iris Cheng, Mike Cima, Abi Collingwood, Vajeera Dorabawila, Cherie Drenzek, Aaron Fleischauer, Ashley Gent, Amanda Hartley, Liam Hicks, Mikhail Hoskins, Amanda Jara, Amanda Jones, Saadiah I. Khan, Ishrat Kamal-Ahmed, Sarah Kangas, FNU Kanishka, Alison Kleppinger, Anna Kocharian, Tomás M. León, Ruth Link-Gelles, B. Casey Lyons, John Masarik, Andrea May, Donald McCormick, Stephanie Meyer, Lauren Milroy, Keeley J. Morris, Lauren Nelson, Enaholo Omoike, Komal Patel, Michael Pietrowski, Melissa A. Pike, Tamara Pilishvili, Xandy Peterson Pompa, Charles Powell, Kevin Praetorius, Eli Rosenberg, Adam Schiller, Mayra L. Smith-Coronado, Emma Stanislawski, Kyle Strand, Buddhi P. Tilakaratne, Hailey Vest, Caleb Wiedeman, Allison Zaldivar, Benjamin Silk, Heather M. Scobie
Background SARS-CoV-2 Omicron variants have the potential to impact vaccine effectiveness and duration of vaccine-derived immunity. We analyzed U.S. multi-jurisdictional COVID-19 vaccine breakthrough surveillance data to examine potential waning of protection against SARS-CoV-2 infection for the Pfizer-BioNTech (BNT162b) primary vaccination series by age. Methods Weekly numbers of SARS-CoV-2 infections during January 16, 2022–May 28, 2022 were analyzed by age group from 22 U.S. jurisdictions that routinely linked COVID-19 case surveillance and immunization data. A life table approach incorporating line-listed and aggregated COVID-19 case datasets with vaccine administration and U.S. Census data was used to estimate hazard rates of SARS-CoV-2 infections, hazard rate ratios (HRR) and percent reductions in hazard rate comparing unvaccinated people to people vaccinated with a Pfizer-BioNTech primary series only, by age group and time since vaccination. Results The percent reduction in hazard rates for persons 2 weeks after vaccination with a Pfizer-BioNTech primary series compared with unvaccinated persons was lowest among children aged 5–11 years at 35.5% (95% CI: 33.3%, 37.6%) compared to the older age groups, which ranged from 68.7%–89.6%. By 19 weeks after vaccination, all age groups showed decreases in the percent reduction in the hazard rates compared with unvaccinated people; with the largest declines observed among those aged 5–11 and 12–17 years and more modest declines observed among those 18 years and older. Conclusions The decline in vaccine protection against SARS-CoV-2 infection observed in this study is consistent with other studies and demonstrates that national case surveillance data were useful for assessing early signals in age-specific waning of vaccine protection during the initial period of SARS-CoV-2 Omicron variant predominance. The potential for waning immunity during the Omicron period emphasizes the importance of continued monitoring and consideration of optimal timing and provision of booster doses in the future.

by Eric Osei, Hubert Amu, Gideon Kye-Duodu, Mavis Pearl Kwabla, Evans Danso, Fred N. Binka, So Yoon Kim
Introduction The Coronavirus disease 2019 (COVID-19) burden, coupled with unprecedented control measures including physical distancing, travel bans, and lockdowns of cities, implemented to stop the spread of the virus, have undoubtedly far-reaching aftereffects on other diseases. In low and middle-income countries (LMICs), a particular worry is the potential impact on Human Immunodeficiency Virus (HIV) and Tuberculosis (TB), as a consequence of possible disruption to health services and limiting access to needed life-saving health care. In Ghana, there is a paucity of information regarding the impact of COVID-19 on disease control, particularly TB and HIV control. This study sought to contribute to bridging this knowledge gap. Method The study involved the analysis of secondary data obtained from the District Health Information Management System-2 (DHIMS-2) database of Ghana Health Service, from 2016 to 2020. Data were analysed using an interrupted time-series regression approach to estimate the impact of COVID-19 on TB case notification, HIV testing, and Antiretroviral Therapy (ART) initiations, using March 2020 as the event period. Results The study showed that during the COVID-19 pandemic period, there was an abrupt decline of 20.5% (955CI: 16.0%, 24.5%) in TB case notifications in April and 32.7% (95%CI: 28.8%, 39.1%) in May 2020, with a median monthly decline of 21.4% from April-December 2020. A cumulative loss of 2,128 (20%; 95%CI: 13.3%, 26.7%) TB cases was observed nationwide as of December 2020. There was also a 40.3% decrease in people presenting for HIV tests in the first month of COVID-19 (April 2020) and a cumulative loss of 262620 (26.5%) HIV tests as of December 2020 attributable to the COVID-19 pandemic. ART initiations increased by 39.2% in the first month and thereafter decreased by an average of 10% per month from May to September 2020. Cumulatively, 443 (1.9%) more of the people living with HIV initiated ART during the pandemic period, however, this was not statistically significant. Conclusion This study demonstrated that the COVID-19 pandemic negatively impacted TB case notifications and HIV testing and counselling services, However, ART initiation was generally not impacted during the first year of the pandemic. Proactive approaches aimed at actively finding the thousands of individuals with TB who were missed in 2020 and increasing HIV testing and counselling and subsequent treatment initiations should be prioritised.

by Nameer Ascandar, Nikhil Chervu, Syed Shahyan Bakhtiyar, Nam Yong Cho, Shineui Kim, Manuel Orellana, Peyman Benharash
Background Cardiac device infection (CDI) can occur in up to 2.2% of patients after device placement, with mortality rates exceeding 15%. Although device removal is standard management, the COVID-19 pandemic has been associated with resource diversion and decreased patient presentation for cardiovascular disease. We ascertained the association of the COVID-19 pandemic with outcomes and resource utilization after admission for CDI. Methods The 2016–2020 National Inpatient Sample was used to retrospectively study all adult admissions for CDI. Patients admitted between March and December, 2020 were classified as the pandemic cohort, with the rest pre-pandemic. The primary outcome was major adverse events (MAE), with secondary outcomes of overall length of stay (LOS), post-device removal LOS, time to device replacement, and hospitalization costs. MAE was a combination of in-hospital mortality and select complications. Multivariable regression models were developed to determine the relationship between the pandemic and the aforementioned outcomes. Results Of an estimated 190,160 patients, 14.3% comprised the pandemic cohort; 2.4% of these patients were COVID-19 positive. The pandemic cohort was older, less commonly female, and had higher rates of congestive heart failure. After adjustment, the pandemic was not associated with altered odds of MAE, device removal, or subsequent device replacement. The pandemic was, however, associated with decreased adjusted overall LOS (β -0.38 days) and days to device replacement (β -0.83 days). The pandemic was likewise associated with $2,000 increased adjusted hospitalization costs. Conclusion The pandemic did not have a significant impact on clinical outcomes in patients admitted for CDI, despite higher hospitalization costs and decreased length of stay.

by Madison Hooper, Morgan Reinhart, Stacie B. Dusetzina, Colin Walsh, Kevin N. Griffith
Importance The COVID-19 pandemic represents a unique stressor in Americans’ daily lives and access to health services. However, it remains unclear how the pandemic impacted perceived health status and engagement in health-related behaviors. Objective To assess changes in self-reported health outcomes during the COVID-19 pandemic, and to explore trends in health-related behaviors that may underlie the observed health changes. Design Interrupted time series stratified by age, gender, race/ethnicity, educational attainment, household income, and employment status. Setting United States. Participants All adult respondents to the 2016–2020 Behavioral Risk Factor Surveillance System (N = 2,146,384). Exposure Survey completion following the U.S. public health emergency declaration (March-December 2020). January 2019 to February 2020 served as our reference period. Main outcomes and measures Self-reported health outcomes included the number of days per month that respondents spent in poor mental health, physical health, or when poor health prevented their usual activities of daily living. Self-reported health behaviors included the number of hours slept per day, number of days in the past month where alcohol was consumed, participation in any exercise, and current smoking status. Results The national rate of days spent in poor physical health decreased overall (-1.00 days, 95% CI: -1.10 to -0.90) and for all analyzed subgroups. The rate of poor mental health days or days when poor health prevented usual activities did not change overall but exhibited substantial heterogeneity by subgroup. We also observed overall increases in mean sleep hours per day (+0.09, 95% CI 0.05 to 0.13), the percentage of adults who report any exercise activity (+3.28%, 95% CI 2.48 to 4.09), increased alcohol consumption days (0.27, 95% CI 0.18 to 0.37), and decreased smoking prevalence (-1.11%, 95% CI -1.39 to -0.83). Conclusions and relevance The COVID-19 pandemic had deleterious but heterogeneous effects on mental health, days when poor health prevented usual activities, and alcohol consumption. In contrast, the pandemic’s onset was associated with improvements in physical health, mean hours of sleep per day, exercise participation, and smoking status. These findings highlight the need for targeted outreach and interventions to improve mental health in individuals who may be disproportionately affected by the pandemic.

by Alejandro Martínez-Portillo, David Garcia-Garcia, Inmaculada Leon, Rebeca Ramis-Prieto, Diana Gómez-Barroso
Background Social restrictions and vaccination seem to have shaped the pandemic development in Europe, but the influence of geographical position is still debated. This study aims to verify whether the pandemic spread through Europe following a particular direction, during the period between the start of the pandemic and November 2021. The existence of a spatial gradient for epidemic intensity is also hypothesized. Methods Daily COVID-19 epidemiological data were extracted from Our World in Data COVID-19 database, which also included vaccination and non-pharmacological interventions data. Latitude and longitude of each country’s centroid were used as geographic variables. Epidemic periods were delimited from epidemic surge data. Multivariable linear and Cox’s regression models were performed for each epidemic period to test if geographical variables influenced surge dates. Generalized additive models (GAM) were used to test the spatial gradient hypothesis with three epidemic intensity measures. Results Linear models suggest a possible west-east shift in the first epidemic period and features a significant association of NPIs with epidemic surge delay. Neither latitude nor longitude had significant associations with epidemic surge timing in both second and third periods. Latitude displays strong negative associations with all epidemic intensity measures in GAM models. Vaccination was also negatively associated with intensity. Conclusions A longitudinal spread of the pandemic in Europe seems plausible, particularly concerning the first wave. However, a recurrent trend was not observed. Southern Europe countries may have experienced increased transmissibility and incidence, despite climatic conditions apparently unfavourable to the virus.

by Jennifer A. Palmer, Megan Mccullough, Jolie Wormwood, Renda Soylemez Wiener, Nathan Mesfin, Michael Still, Chris S. Xu, Amy M. Linsky

Clinician moral distress has been documented over the past several decades as occurring within numerous healthcare disciplines, often in relation to clinicians’ involvement in patients’ end-of-life decision-making. The resulting harms impact clinician well-being, patient well-being, and healthcare system functioning. Given Covid-19’s catastrophic death toll and associated demands on end-of-life decision-making processes, the pandemic represents a particularly important context within which to understand clinician moral distress. Thus, we conducted a convergent mixed methods study to examine its prevalence, associations with clinicians’ demographic and professional characteristics, and contributing circumstances among Veterans Health Administration (VA) clinicians. The study, conducted in April 2021, consisted of a cross-sectional on-line survey of VA clinicians at 20 VA Medical Centers with professional jurisdiction to place life-sustaining treatment orders working who were from a number of select specialties. The survey collected quantitative data on respondents’ demographics, clinical practice characteristics, attitudes and behaviors related to goals of care conversations, intensity of moral distress during “peak-Covid,” and qualitative data via an open-ended item asking for respondents to describe contributing circumstances if they had indicated any moral distress. To understand factors associated with heightened moral distress, we analyzed quantitative data using bivariate and multivariable regression analyses and qualitative data using a hybrid deductive/inductive thematic approach. Mixed methods analysis followed, whereby we compared the quantitative and qualitative datasets and integrated findings at the analytic level. Out of 3,396 eligible VA clinicians, 323 responded to the survey (9.5% adjusted response rate). Most respondents (81%) reported at least some moral distress during peak-Covid. In a multivariable logistic regression, female gender (OR 3.35; 95% CI 1.53–7.37) was associated with greater odds of moral distress, and practicing in geriatrics/palliative care (OR 0.40; 95% CI 0.18–0.87) and internal medicine/family medicine/primary care (OR 0.46; 95% CI 0.22–0.98) were associated with reduced odds of moral distress compared to medical subspecialties. From the 191 respondents who completed the open-ended item, five qualitative themes emerged as moral distress contributors: 1) patient visitation restrictions, 2) anticipatory actions, 3) clinical uncertainty related to Covid, 4) resource shortages, and 5) personal risk of contracting Covid. Mixed methods analysis found that quantitative results were consistent with these last two qualitative themes. In sum, clinician moral distress was prevalent early in the pandemic. This moral distress was associated with individual-, system-, and situation-level contributors. These identified contributors represent leverage points for future intervention to mitigate clinician moral distress and its negative outcomes during future healthcare crises and even during everyday clinical care.

by Moon Ho Do, Hua Li, Su Yeon Cho, Subin Oh, Ju Hwan Jeong, Min-Suk Song, Jong-Moon Jeong

In a short time, several types of injectable and oral therapeutics have been developed and used to effectively manage patients with coronavirus disease 2019 (COVID-19). BEN815 is an improved mixture of three extracts (Psidium guajava, Camellia sinensis, and Rosa hybrida) recognized by the Ministry of Food and Drug Safety of Korea as a health food ingredient that alleviates allergic rhinitis. The current animal efficacy study was performed to assess its probability of improving COVID-19 symptoms. BEN815 treatment significantly increased the survival of K18-hACE2 transgenic mice and reduced viral titers in the lungs at 5 days post infection (DPI). Furthermore, the lungs of the treated mice showed mild tissue damage at 5 DPI and nearly complete recovery from COVID-19 at 14 DPI. BEN815 appears to be an effective and minimally toxic anti-SARS-CoV-2 agent in mice and has potential for clinical applications.

by Maris Lohmöller, Tania Zieschang, Jessica Koschate

The closure of all sports facilities during the two lockdowns in Germany favoured a reduction of leisure time physical activity during the COVID-19 pandemic. The aim of this study was to compare leisure time physical activity during the 1st and 2nd lockdown and to examine exercise performance before and after resumption of exercise. Leisure time physical activity was measured by the Longitudinal Urban Cohort Ageing Study (LUCAS) functional ability index and energy expenditure in the Minnesota Leisure Time Physical Activity Questionnaire. Participants’ exercise performance was extracted from a chip-controlled fitness circuit. Differences were tested for statistical significance using Friedman tests. 35 participants above 60 years were included from the Oldenburg area (20 women, 15 men, mean age and standard deviation 71±6 years). The decline in energy expenditure was higher during the 2nd lockdown (1st lockdown: Median -55.7 kcal.day-1, Q0.25−121.3 kcal.day-1, Q0.75 132.9 kcal.day-1; 2nd lockdown: Median -119.7 kcal.day-1, Q0.25−255.6 kcal.day-1, Q0.75−65.1 kcal.day-1; Friedman test: p

by Daniela Luethy, Traci M. Krueger, Erica Cuneo, Julia R. Varnes, Jorge A. Hernandez

Mental illness is an important public health concern in veterinary students. Recent literature has demonstrated a negative effect of the COVID-19 pandemic on veterinary students’ mental health. Little literature to date has evaluated the mental health of veterinary students affected by the COVID-19 pandemic after most pandemic measures have been lifted. The objective of this study was to describe physical activity, diet, and mental health in veterinary students after pandemic measures were lifted. A secondary objective was to examine the association between depression symptoms and exposure factors in this cohort of veterinary students. In a cross-sectional study, veterinary students (n = 487) at a public university received an online survey with questions regarding their physical activity, diet, stress, and self-rated symptoms across 11 mental health domains. Logistic regression was used to quantify the association between exposure factors and depression symptoms. One-hundred and twelve students completed the survey. Sixty-three (56%) respondents met the criteria for concern within the mental health domain of depression, 75 (67%) for anxiety, and 16 (14%) for suicidal ideation. Fourth year students had the lowest weekly vigorous physical activity (median 0.5 hours). The odds of self-reported depression symptoms were 8 times lower in students engaged in high levels of vigorous exercise compared to students engaged in low levels, after controlling for number of years in the program (p = 0.02). Mental health concerns were high in this group of veterinary students.

by Linda Ashman Kröönström, Åsa Lundgren-Nilsson, Gunilla Kjellby-Wendt, Katharina Stibrant Sunnerhagen
Background We aimed to assess symptomatology post discharge from the hospital in patients with COVID-19 treated during the first wave of the COVID-19 pandemic, and to follow care consumption and healthcare costs six months post discharge. Methods This study was a descriptive observational study over time. Data were retrieved from the Sahlgrenska University (SU) hospital registry for patients admitted to an SU hospital during March 2020 to August 2020. Of these, 1014 received a questionnaire approximately six weeks post discharge regarding symptoms. Data regarding care consumption were retrieved from the registry in the Region Västra Götaland for 529 (52.2%) patients who completed the questionnaire. Of these, 466 patients were included in the analysis of care consumption. Results There was a reported decrease in mobility from admission to discharge in both men (p = 0.02) and women (p = 0.01). The costs of inpatient care amounted to a total of 9 601 459.20 Euro (EUR). Symptoms were reported in 436 (93.6%) patients post discharge, of which weight loss during COVID-19 was most common in both men (n = 220, 77.5%) and women (n = 107, 58.8%). During six-month follow-up, 409 (87%) patients consumed care. Of the registered visits, 868 (27.1%) were related to a COVID-19 diagnosis. The total sum of outpatient care (i.e. visits with a registered COVID-19 diagnosis) was 77 311.30 EUR. Conclusions At discharge from the hospital, there was a decrease in mobility. Most patients had remaining sequelae post discharge. At six months post discharge, nearly 90% of patients had consumed care, with approximately 20% related to COVID-19. This indicates a persisting need for rehabilitation post discharge from hospital in patients treated for COVID-19.

by Micaela White, Lauren Hisatomi, Alex Villegas, Dagoberto Pina, Alec Garfinkel, Garima Agrawal, Nisha Punatar, Barton L. Wise, Polly Teng, Hai Le
Purpose This study determined whether initiation of pharmacologic treatment was delayed for newly diagnosed osteoporosis patients during the COVID-19 pandemic. Methods 1,189 patients ≥50 years with newly diagnosed osteoporosis using dual-energy x-ray absorptiometry (DXA) screening at a single academic institution were included. Patients with previous osteoporosis were excluded. Patients diagnosed between March 1, 2018—January 31, 2020 (pre-pandemic cohort, n = 576) were compared to those diagnosed between March 1, 2020—January 31, 2022 (pandemic cohort, n = 613). Age, sex, race, ethnicity, ordering providers (primary vs specialty), and pharmacological agents were evaluated. Primary outcomes included proportion of patients prescribed therapy within 3 and 6-months of diagnosis, and mean time from diagnosis to treatment initiation. Results The pre-pandemic cohort had more White patients (74.3 vs 68.4%, p = .02) and no differences between remaining demographic variables. Only 40.5% of newly diagnosed patients initiated pharmacologic therapy within 6 months. Patients treated at 3-months (31.8 vs 35.4%, p = 0.19) and 6-months (37.8 vs 42.9, p = 0.08) were comparable between cohorts (47.2 vs 50.2% p = 0.30). Mean time from diagnosis to treatment initiation was similar (46 vs 45 days, p = 0.72). There were no treatment differences based on gender, race, or ethnicity or between ordering providers (65.1 vs 57.4% primary care, p = 0.08). Bisphosphonates were most often prescribed in both cohorts (89% vs 82.1%). Conclusions This is the first study assessing COVID-19’s impact on pharmacologic treatment of newly diagnosed osteoporosis. 40.5% of newly diagnosed patients were treated pharmacologically within six months of diagnosis, and the pandemic did not significantly affect treatment rates.

by Weizhe Weng, Lingxiao Yan, Kevin J. Boyle, George Parsons

Central Park is an iconic feature of New York City, which was the first and one of the hardest hit cities in the United States by the Coronavirus. State-level stay-at-home order, raising COVID-19 cases, as well as the public’s personal concerns regarding exposure to the virus, led to a significant reduction of Central Park visitation. We utilized extensive cellphone tracking data to conduct one of the pioneering empirical studies assessing the economic impact of COVID-19 on urban parks. We integrated the difference-in-difference (DID) design with the recreation-demand model. The DID design aids in identifying the causal impacts, controlling for unobservable factors that might confound the treatment effects of interest. Concurrently, the recreational demand model examines the driving factors of visitation changes and enables us to estimate the welfare changes experienced by New York City’s residents. Our findings shine a light on the substantial, yet often overlooked, welfare loss triggered by the pandemic. The analysis indicates that the pandemic resulted in a 94% reduction in visitation, corresponding to an annual consumer surplus loss of $450 million. We noted a rebound in visitation following the initial outbreak, influenced by shifts in government policy, weather conditions, holiday periods, and personal characteristics.

by Hugo D. G. van Willigen, Elke Wynberg, Anouk Verveen, Maartje Dijkstra, Bas J. Verkaik, Orlane J. A. Figaroa, Marianne C. de Jong, Annelou L. I. P. van der Veen, Agata Makowska, Nelleke Koedoot, Pythia T. Nieuwkerk, Anders Boyd, Maria Prins, Menno D. de Jong, Godelieve J. de Bree, Joost G. van den Aardweg, the RECoVERED Study Group
Background There is increasing data that show a persistently impaired pulmonary function upon recovery after severe infection. Little is known however about the extent, recovery and determinants of pulmonary impairment across the full spectrum of COVID-19 severity over time. Methods In a well characterized, prospective cohort of both hospitalised and non-hospitalised individuals with SARS-CoV-2 infection, the RECoVERED study, pulmonary function (diffusing capacity for carbon monoxide (DLCO)) and spirometry) was measured until one year after disease onset. Additionally, data on sociodemographics, clinical characteristics, symptoms, and health-related quality of life (HRQL) were collected. Pulmonary function and these determinants were modelled over time using mixed-effect linear regression. Determinants of pulmonary function impairment at 12 months after disease onset were identified using logistic regression. Findings Between May 2020 and December 2021, 301 of 349 participants underwent at least one pulmonary function test. After one year of follow-up, 25% of the participants had an impaired pulmonary function which translates in 11%, 22%, and 48% of the participants with mild, moderate and severe/critical COVID-19. Improvement in DLCO among the participants continued over the period across one, six and twelve months. Being older, having more than three comorbidities (p

by Ahlam H. Tolba, Abdisalam Hassan Muse, Aisha Fayomi, Hanan M. Baaqeel, Ehab M. Almetwally

The Gull Alpha Power Lomax distribution is a new extension of the Lomax distribution that we developed in this paper (GAPL). The proposed distribution’s appropriateness stems from its usefulness to model both monotonic and non-monotonic hazard rate functions, which are widely used in reliability engineering and survival analysis. In addition to their special cases, many statistical features were determined. The maximum likelihood method is used to estimate the model’s unknown parameters. Furthermore, the proposed distribution’s usefulness is demonstrated using two medical data sets dealing with COVID-19 patients’ mortality rates, as well as extensive simulated data applied to assess the performance of the estimators of the proposed distribution.