A Critical Analysis of UK Media Characterisations of Long Covid in Children and Young People (preprint)

Long Covid is the continuation or development of symptoms related to a SARSCoV2 infection. Those with Long Covid may face epistemic injustice, where they are unjustifiably viewed as unreliable evaluators of their own illness experiences. Media articles both reflect and influence perception and subsequently how people regard children and young people (CYP) with Long Covid, and may contribute to epistemic injustice.? We aimed to explore how the UK media characterises Long Covid in CYP through examining three key actor groups: parents, healthcare professionals, and CYP with Long Covid, through the lens of epistemic injustice. A systematic search strategy resulted in the inclusion of 103 UK media articles. We used an adapted corpus-assisted Critical Discourse Analysis in tandem with thematic analysis. Specifically, we utilised search terms to locate concordances of key actor groups. In the corpus, parents highlighted minimisation of Long Covid, barriers to care, and experiences of personal attacks. Mothers were presented as also having Long Covid. Fathers were not mentioned once. Healthcare professionals emphasised the rarity of Long Covid in CYP, avoided pathologizing Long Covid, and overemphasised psychological components. CYP rarely were consulted in media articles but were presented as formerly very able. Manifestations of Long Covid in CYP were validated or invalidated in relation to adults. Media characterisations contributed to epistemic injustice. The disempowering portrayal of parents promote stigma and barriers to care. Healthcare professionals' narratives often contributed to negative healthcare experiences and enacted testimonial injustice, where CYP and parents credibility was diminished due to unfair identity prejudice, in their invalidation of Long Covid. Media characterisations reveal and maintain a lack of societal framework for understanding Long Covid in CYP. The findings of this study illustrate the discursive practices employed by journalists that contribute to experiences of epistemic injustice. Based on our findings, we propose recommendations for journalists.

Precision Phenotyping for Curating Research Cohorts of Patients with Post-Acute Sequelae of COVID-19 (PASC) as a Diagnosis of Exclusion (preprint)

Scalable identification of patients with the post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms and the suboptimal accuracy, demographic biases, and underestimation of the PASC diagnosis code (ICD-10 U09.9). In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying research cohorts of PASC patients, defined as a diagnosis of exclusion. We used longitudinal electronic health records (EHR) data from over 295 thousand patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to exclude sequelae that prior conditions can explain. We performed independent chart reviews to tune and validate our precision phenotyping algorithm. Our PASC phenotyping algorithm improves precision and prevalence estimation and reduces bias in identifying Long COVID patients compared to the U09.9 diagnosis code. Our algorithm identified a PASC research cohort of over 24 thousand patients (compared to about 6 thousand when using the U09.9 diagnosis code), with a 79.9 percent precision (compared to 77.8 percent from the U09.9 diagnosis code). Our estimated prevalence of PASC was 22.8 percent, which is close to the national estimates for the region. We also provide an in-depth analysis outlining the clinical attributes, encompassing identified lingering effects by organ, comorbidity profiles, and temporal differences in the risk of PASC. The PASC phenotyping method presented in this study boasts superior precision, accurately gauges the prevalence of PASC without underestimating it, and exhibits less bias in pinpointing Long COVID patients. The PASC cohort derived from our algorithm will serve as a springboard for delving into Long COVID's genetic, metabolomic, and clinical intricacies, surmounting the constraints of recent PASC cohort studies, which were hampered by their limited size and available outcome data.

SARS-CoV-2 Antigen Rapid Detection Tests: test performance during the COVID-19 pandemic and the impact of COVID-19 vaccination (preprint)

IntroductionDuring the COVID-19 pandemic, SARS-CoV-2 antigen rapid detection tests (RDTs) emerged as point-of-care diagnostics in addition to the RT-qPCR as the gold standard for SARS-CoV-2 diagnostics. Facing the course of the COVID-19 pandemic to an endemic characterised by several SARS-CoV-2 virus variants of concern (VOC) and an increasing public COVID-19 vaccination rate the aim of the study was to investigate the long-term test performance of SARS-CoV-2 RDT in large-scale, clinical screening use during and its influencing factors, above all SARS-CoV-2 VOC and COVID-19 vaccination. MethodsIn a prospective performance assessment conducted at a single centre tertiary care hospital, RDTs from three manufacturers (NADAL(R), Panbio, MEDsan(R)) were compared to RT-qPCR among individuals aged [≥] 6 month. The evaluation involved the determination of standardised viral load from oropharyngeal swabs as well as the evaluation of their influencing factors, especially the COVID-19 vaccination, for detecting SARS-CoV-2 in a clinical point-of-care environment spanning from 12 November 2020 to 30 June 2023 among patients, staff, and visitors of the hospital. ResultsAmong the 78,798 RDT/RT-qPCR tandems analysed, 2,016 (2.6%) tandems tested positive for SARS-CoV-2, with an overall sensitivity of 34.5% (95% CI 32.4-36.6%). A logistic regression revealed that typical COVID-19 symptoms significantly declined over the course of the study and throughout the COVID-19 pandemic, and that among the vaccinated, significantly fewer presented with an infection exhibiting typical symptoms. The employed lasso regression model indicated that only higher viral load and typical COVID-19 symptoms significantly increase the likelihood of a positive RDT result in the case of a SARS-CoV-2 infection directly. ConclusionOur findings indicate that only viral load and COVID-19 symptoms directly influence RDT performance while the obtained effects of COVID-19 vaccination and Omicron VOC both reducing RDT performance were mediated by these two factors. RDTs remain an adequate diagnostic tool for detecting SARS-CoV-2 in individuals showing respiratory symptoms. RDTs show promise beyond SARS-CoV-2, proving adaptable for detecting other pathogens like Influenza and RSV, highlighting their ongoing importance in infection control and prevention efforts.

Psychosocial Predictors of Sleep Disturbances during COVID-19: differential contributions of demographic, psychological, pandemic-related factors to sleep health. (preprint)

Aim: Since the declaration of COVID-19 as a Public Health Emergency of International Concern on January 30, 2020, the disease escalated into a global pandemic forcing governments around the world to impose measures that affected all aspects of life. Among other countries, Greece adopted social restriction, lockdowns, and quarantines to reduce transmission from person to person.  Subjects and Methods: This cross-sectional study aimed to investigate the impact of those measures on sleep health in a Greek adult sample. An online questionnaire collected data during from 650 participant.  Results: 60% of responders scored below the clinical cut-off on the RU-SATED, indicating they experienced poor sleep health. Better sleep health was reported with increased age and years of education. On the other hand, higher trauma-related distress, depression, anxiety and stress symptomatology were related to poorer sleep health. No gender differences were observed, and degree of compliance to pandemic restrictions did not influence sleep health. Hierarchical regression analysis indicated difficulty in securing enough/healthy food, testing positive for COVID-19, experiencing an increase in verbal arguments/conflicts at home and an increase in responsibilities were the strongest predictors of poor sleep heath.  Conclusions: Results highlight the importance of maintaining good sleep health as a pillar of general physical and mental health.

The abortive SARS-CoV-2 infection of osteoclast precursors promotes their differentiation into osteoclasts (preprint)

The COVID-19 pandemic has resulted in the loss of millions of lives, although a majority of those infected have managed to survive. Consequently, a set of outcomes, identified as long COVID, is now emerging. While the primary target of SARS-CoV-2 is the respiratory system, the impact of COVID-19 extends to various body parts, including the bone. This study aims to investigate the effects of acute SARS-CoV-2 infection on osteoclastogenesis, utilizing both ancestral and Omicron viral strains. Monocyte-derived macrophages (MDM), which serve as precursors to osteoclasts, were exposed to both viral variants. However, the infection proved abortive, even though ACE2 receptor expression increased post-infection, with no significant impact on cellular viability and redox balance. Both SARS-CoV-2 strains heightened osteoclast formation in a dose-dependent manner, as well as CD51/61 expression and bone resorptive ability. Notably, SARS-CoV-2 induced early pro-inflammatory M1 macrophage polarization, shifting towards an M2-like profile. Osteoclastogenesis-related genes (RANK, NFATc1, DC-STAMP, MMP9) were upregulated, and surprisingly, SARS-CoV-2 variants promoted RANKL-independent osteoclast formation. This thorough investigation illuminates the intricate interplay between SARS-CoV-2 and osteoclast precursors, suggesting potential implications for bone homeostasis and opening new avenues for therapeutic exploration in COVID-19.

Early detection of disease outbreaks and non-outbreaks using incidence data (preprint)

Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management. Here, we develop a general model, with no real-world training data, that accurately forecasts outbreaks and non-outbreaks. We propose a novel framework, using a feature-based time series classification method to forecast outbreaks and non-outbreaks. We tested our methods on synthetic data from a Susceptible-Infected-Recovered model for slowly changing, noisy disease dynamics. Outbreak sequences give a transcritical bifurcation within a specified future time window, whereas non-outbreak (null bifurcation) sequences do not. We identified incipient differences in time series of infectives leading to future outbreaks and non-outbreaks. These differences are reflected in 22 statistical features and 5 early warning signal indicators. Classifier performance, given by the area under the receiver-operating curve, ranged from 0.99 for large expanding windows of training data to 0.7 for small rolling windows. Real-world performances of classifiers were tested on two empirical datasets, COVID-19 data from Singapore and SARS data from Hong Kong, with two classifiers exhibiting high accuracy. In summary, we showed that there are statistical features that distinguish outbreak and non-outbreak sequences long before outbreaks occur. We could detect these differences in synthetic and real-world data sets, well before potential outbreaks occur.

Understanding Human-COVID-19 Dynamics using Geospatial Big Data: A Systematic Literature Review (preprint)

The COVID-19 pandemic has changed human life. To mitigate the pandemic's impacts, different regions implemented various policies to contain COVID-19 and residents showed diverse responses. These human responses in turn shaped the uneven spatial-temporal spread of COVID-19. Consequently, the human-pandemic interaction is complex, dynamic, and interconnected. Delineating the reciprocal effects between human society and the pandemic is imperative for mitigating risks from future epidemics. Geospatial big data acquired through mobile applications and sensor networks have facilitated near-real-time tracking and assessment of human responses to the pandemic, enabling a surge in researching human-pandemic interactions. However, these investigations involve inconsistent data sources, human activity indicators, relationship detection models, and analysis methods, leading to a fragmented understanding of human-pandemic dynamics. To assess the current state of human-pandemic interactions research, we conducted a synthesis study based on 67 selected publications between March 2020 and January 2023. We extracted key information from each article across six categories, e.g., research area and time, data, methodological framework, and results and conclusions. Results reveal that regression models were predominant in relationship detection, featured in 67.16% of papers. Only two papers employed spatial-temporal models, notably underrepresented in the existing literature. Studies examining the effects of policies and human mobility on the pandemic's health impacts were the most prevalent, each comprising 12 articles (17.91%). Only 3 papers (4.48%) delved into bidirectional interactions between human responses and the COVID-19 spread. These findings shed light on the need for future research to spatially and temporally model the long-term, bidirectional causal relationships within human-pandemic systems.

Microgliosis, astrogliosis and loss of aquaporin-4 polarity in frontal cortex of COVID-19 patients (preprint)

The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), causing human coronavirus disease 2019 (COVID-19), not only affects the respiratory tract, but also impacts other organs including the brain. A considerable number of COVID-19 patients develop neuropsychiatric symptoms that may linger for weeks and months and contribute to \"long-COVID\". While the neurological symptoms of COVID-19 are well described, the cellular mechanisms of neurologic disorders attributed to the infection are still enigmatic. Here, we studied the effect of an infection with SARS-CoV-2 on the structure and expression of marker proteins of astrocytes and microglial cells in the frontal cortex of patients who died from COVID-19 in comparison to non-COVID-19 controls. Most of COVID-19 patients had microglial cells with retracted processes and rounded and enlarged cell bodies in both gray and white matter, as visualized by anti-Iba1 staining and confocal fluorescence microscopy. In addition, gray matter astrocytes in COVID-19 patients were frequently labeled by intense anti-GFAP staining, whereas in non-COVID-19 controls, most gray matter astrocytes expressed little GFAP. The most striking difference between astrocytes in COVID-19 patients and controls was found by anti-aquaporin-4 (AQP4) staining. In COVID-19 patients, a large number of gray matter astrocytes showed an increase in AQP4. In addition, AQP4 polarity was lost and AQP4 covered the entire cell, including the cell body and all cell processes, while in controls, AQP4 immunostaining was mainly detected in endfeet around blood vessels and did not visualize the cell body. In summary, our data suggest neuroinflammation upon SARS-CoV-2 infection including microgliosis and astrogliosis, including loss of AQP4 polarity.

Exploring Key Challenges for Healthcare Providers and Stakeholders in delivering adolescent sexual and Reproductive Health Services and information during the COVID-19 Pandemic in Malawi, Zambia and Zimbabwe: A Qualitative Study (preprint)

Introduction: This study aimed to explore the direct and indirect influences of COVID-19-related restrictions on adolescents and young people's SRHR in Malawi, Zambia, and Zimbabwe, with a focus on teenage pregnancy and access to and utilization of HIV testing and counselling services. Methods: A qualitative case study in a larger mixed-methods study design was used. Thirty-four interviews and four group discussions were conducted with relevant stakeholders in Malawi, Zambia and Zimbabwe. In Zambia, adolescents and young people were included and asked to describe their experience/perceptions of the impact of COVID-19 on their SRHR. Content and thematic analysis were used to analyze the data, Results: Priority shifts resulted in the focus of service provision to the COVID-19 response, shortages of already insufficient human resources due to infection and/or isolation, supply chain disruptions leading to shortages of important SRH-related commodities and supplies, compromised quality of services such as counselling for HIV and overall limited AYP’s access to SRH information. Suggestions for interventions to improve SRH services include the need for a disaster preparedness strategy, increased funding for ASRHR, the use of community health workers and community-based ASRHR strategies, and the use of technology and social media platforms such as mhealth. Conclusion:Disruption of SRH services for AYP due to pandemic related-restrictions, and diversion of resources/funding has had a ripple effect that may have long-term consequences for AYP throughout the East and Southern African region. This calls for further investment in AYP’s access to SRHR services as progress made may have been deterred.

N-protein vaccine Convacell(R) is effective against COVID-19: phase 3, randomized, double-blind, placebo-controlled clinical trial (preprint)

We have developed a Convacell(R), a COVID-19 vaccine based on the conservative viral nucleocapsid (N) protein. The N protein is evolutionary conservative and is abundantly expressed on the surface of infected cells, allowing anti-N immune response generated by Convacell(R) to rapidly clear infected cells and provide long-lasting protection against COVID-19. Convacell(R) has been demonstrated to be safe and highly immunogenic, creating immune responses lasting over a year, in phase I/II and IIb clinical trials. Phase IIb clinical trial has also demonstrated that a single dose vaccination regimen with Convacell(R) is sufficient to provide an immune response. Here we report the finding of the phase III clinical trial of Convacell(R). Two groups of volunteers from Russia have been either vaccinated with a single dose of Convacell(R) or injected with placebo, and then monitored for incidence of COVID-19 and adverse effects. Anti-N antibody titers at admission were also analyzed, to take into account for potential effects of previous virus encounters. Disease incidence over 6 months results indicate an overall vaccine efficacy of 85.2% (95% confidence interval: 67.4-93.3%). Additionally, Convacell(R) has shown a good safety profile. Overall, Convacell(R) demonstrated highly desirable qualities and good performance as a vaccine and can be considered as valuable COVID-19 preventative measure.

Gender Bias in Emerging New Research Topics: The Impact of COVID-19 on Women in Science (preprint)

We investigate the impact of new research opportunities on the long-standing under-representation of women in medical and academic leadership by assessing the impact of the emergence of COVID-19 as a new research topic in the life sciences on women's authorship. After collecting publication data from 2019 and 2020 on biomedical publications, where the position of first and last author is most important for future career development, we use the major Medical Subject Heading (MeSH) terms to identify the main research area of each publication and measure the relation of each paper to COVID-19. Using a Difference-in-Difference approach, we find that although the general female authorship trend is upwards, papers in areas related to COVID-19 are less likely to have a woman as first or last author compared to research areas not related to COVID-19. Conversely, new publication opportunities in the COVID-19 research field increase the proportion of women in middle, less-relevant, author positions. Stay-at-home mandates, journal importance, and access to new funds do not fully explain the drop in women's outcomes. The decline in female first authorship is related to the increase of teams in which both lead authors have no prior experience in the COVID-related research field. In addition, pre-existing publishing teams show reduced bias in female key authorship with respect to new teams specifically formed for COVID-related research. This suggests that opportunistic teams, transitioning into research areas with emerging interests, possess greater flexibility in choosing the primary and final authors, potentially reducing uncertainties associated with engaging in productions divergent from their past scientific experiences by excluding women scientists from key authorship positions.

Similarities between long COVID and cognitive impairment and potential implications; Results from the 2022 BRFSS (preprint)

BackgroundCOVID has been linked to cognitive issues with brain fog a common complaint among adults reporting long COVID (symptoms lasting 3 or more months). ObjectiveTo study similarities and differences between cognitive impairment (CI) (the cognitive disability measure) and long COVID. MethodsUsing 2022 BRFSS data from 50 states and 169,894 respondents in 29 states with COVID vaccine data, respondents with CI and long COVID were compared in unadjusted analysis and logistic regression. Apparent vaccine effectiveness was compared in the 29 states. ResultsPrevalence of long COVID was 7.4% (95% CI 7.3-7.6) and CI was 13.4% (13.2-13.6) with both rates higher among women, ages 18-64 years, Hispanics, American Indians, ever smokers, those with depression, e-cigarette users, and those with more of the co-morbidities of diabetes, asthma, COPD, and obesity. The strong association between long COVID and CI was confirmed. Apparent vaccine effectiveness of 3 or more doses vs <3 was 38% for long COVID and 35% for CI, in both cases reducing rates for 3 or more doses to those comparable to adults with 0 comorbidities and showing dose response gradients. For CI, apparent vaccine effectiveness was similar for respondents with or without long COVID. Logistic regression confirmed most results except the magnitude of vaccine effectiveness on CI was reduced in some models while vaccine effectiveness for long COVID was confirmed. ConclusionsMore research is needed to understand the apparent effectiveness of COVID vaccines on CI but, if confirmed, results could expand the list of non-infectious outcomes for which mRNA vaccines can be effective.

Increased fibrinaloid microclot counts in platelet-poor plasma are associated with Long COVID (preprint)

Outcomes following SARS-CoV-2 infection are variable; whilst the majority of patients recover without serious complications, a subset of patients develop prolonged illness termed Long COVID or post-acute sequelae of SARS-CoV-2 infection (PASC). The pathophysiology underlying Long COVID remains unclear but appears to involve multiple mechanisms including persistent inflammation, coagulopathy, autoimmunity, and organ damage. Studies suggest that microclots, also known as fibrinaloids, play a role in Long COVID. In this context, we developed a method to quantify microclots and investigated the relationship between microclot counts and Long COVID. We show that as a cohort, platelet-poor plasma from Long COVID samples had a higher microclot count compared to control groups but retained a wide distribution of counts. Recent COVID-19 infections were also seen to be associated with microclot counts higher than the control groups and equivalent to the Long COVID cohort, with a subsequent time-dependent reduction of counts. Our findings suggest that microclots could be a potential biomarker of disease and/or a treatment target in some Long COVID patients.

The Aftermath of COVID-19: Exploring Long-Term Effects on the Organ Systems (preprint)

Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) is a complicated disease that affects millions of people all over the world. Previous studies have shown that PASC impacts 10% of SARS-CoV-2 infected patients of which 50-70% are hospitalized. It has also been shown that 10-12% of those vaccinated against COVID-19 were affected with PASC and its complications. The severity and the later development of PASC symptoms is positively associated with the early intensity of the infection. Results: The generated health complications caused by PASC involve a vast variety of organ systems. Patients affected by PASC have been diagnosed with neuropsychiatric and neurological symptoms. Cardiovascular system also has been involved and several diseases such as myocarditis, pericarditis, and coronary artery diseases were reported. Chronic hematological problems such as thrombotic endothelialitis and hypercoagulability were described as a condition that could increase the risk of clotting disorders and coagulopathy in PASC patients. Chest pain, breathlessness, and cough in PASC patients were associated with respiratory system in long COVID-19 causing respiratory distress syndrome. The observed immune complications were notable, involving several diseases. Renal system also was impacted and result in raising the risk of diseases such as thrombotic issues, fibrosis, and sepsis. Endocrine gland malfunction can lead to diabetes, thyroiditis, and male infertility. Symptoms such as diarrhea, nausea, loss of appetite and taste were also among reported observations due to several gastrointestinal disorders. Skin abnormalities might be an indication of infection and long-term implications such as persistent cutaneous complaints were linked to PASC. Conclusions: Long COVID is a multidimensional syndrome with considerable public health implications, affecting several physiological systems and demanding thorough medical therapy as well as more study to address its underlying causes and long-term effects.

Respiratory viral infection promotes the awakening and outgrowth of dormant metastatic breast cancer cells in lungs (preprint)

Breast cancer is the second most common cancer globally. Most deaths from breast cancer are due to metastatic disease which often follows long periods of clinical dormancy1. Understanding the mechanisms that disrupt the quiescence of dormant disseminated cancer cells (DCC) is crucial for addressing metastatic progression. Infection with respiratory viruses (e.g. influenza or SARS-CoV-2) is common and triggers an inflammatory response locally and systemically2,3. Here we show that influenza virus infection leads to loss of the pro-dormancy mesenchymal phenotype in breast DCC in the lung, causing DCC proliferation within days of infection, and a greater than 100-fold expansion of carcinoma cells into metastatic lesions within two weeks. Such DCC phenotypic change and expansion is interleukin-6 (IL-6)-dependent. We further show that CD4 T cells are required for the maintenance of pulmonary metastatic burden post-influenza virus infection, in part through attenuation of CD8 cell responses in the lungs. Single-cell RNA-seq analyses reveal DCC-dependent impairment of T-cell activation in the lungs of infected mice. SARS-CoV-2 infected mice also showed increased breast DCC expansion in lungs post-infection. Expanding our findings to human observational data, we observed that cancer survivors contracting a SARS-CoV-2 infection have substantially increased risks of lung metastatic progression and cancer-related death compared to cancer survivors who did not. These discoveries underscore the significant impact of respiratory viral infections on the resurgence of metastatic cancer, offering novel insights into the interconnection between infectious diseases and cancer metastasis.

SARS-CoV-2 disrupts host gene networks: unveiling key hub genes as potential therapeutic targets for COVID-19 management (preprint)

Background Although the end of COVID-19 as a public health emergency was declared on May 2023, still new cases of the infection are reported and the risk remains of new variants emerging that may cause new surges in cases and deaths. While clinical symptoms have been rapidly defined worldwide, the basic body responses and pathogenetic mechanisms acting in patients with SARS-CoV-2 infection over time until recovery or death require further investigation. The understanding of the molecular mechanisms underlying the development and course of the disease is essential in designing effective preventive and therapeutic approaches, and ultimately reducing mortality and disease spreading.Methods The current investigation aimed to identify the key genes engaged in SARS-CoV-2 infection and uncover their molecular implication in disease severity. To achieve this goal high-throughput RNA sequencing of peripheral blood samples collected from healthy donors and COVID-19 patients was performed. The resulting sequence data were processed using a wide range of bioinformatics tools to obtain detailed modifications within five transcriptomic phenomena: expression of genes and long non-coding RNAs, alternative splicing, allel-specific expression and circRNA production. The in silico procedure was completed with a functional analysis of the identified alterations.Results The transcriptomic analysis revealed that SARS-CoV-2 has a significant impact on multiple genes encoding ribosomal proteins (RPs). Results show that these genes differ not only in terms of expression but also manifest biases in alternative splicing and ASE ratios. The integrated functional analysis exposed that RPs mostly affected pathways and processes related to infection—COVID-19 and NOD-like receptor signaling pathway, SARS-CoV-2-host interactions and response to the virus. Furthermore, our results linked the multiple intronic ASE variants and exonic circular RNA differentiations with SARS-CoV-2 infection, suggesting that these molecular events play a crucial role in mRNA maturation and transcription during COVID-19 disease.Conclusions By elucidating the genetic mechanisms induced by the virus, the current research provides significant information that can be employed to create new targeted therapeutic strategies for future research and treatment related to COVID-19. Moreover, the findings highlight potentially promising therapeutic biomarkers for early risk assessment of critically ill patients.

Loneliness during the last phase of the COVID-19 pandemic in China: Trajectories, predictors, and impact on adolescent mental health (preprint)

Background Little is known about the long-term courses of loneliness, associated risk factors and effect on mental health in adolescents during the COVID-19 pandemic. This study aimed to explore the trajectories of loneliness among Chinese adolescents during the last phase of the pandemic. We also aimed to identify risk factors in each loneliness course and the impact of loneliness on emotional problems, peer problems, hyperactivity and conduct problems. Methods  We conducted longitudinal analyses using four waves of data from 2347 Chinese adolescents covering a period of 20 months (October 2021 – May 2023). Loneliness was assessed using the UCLA 3-Item Loneliness Scale. The self-reported version of the Strengths and Difficulties Questionnaire was utilized to evaluate participants’ mental health outcomes. Growth mixture modelling was employed to identify latent classes of loneliness trajectories. Associated risk factors were investigated using multinomial logistic regression model. Mixed-effects logistic regression models were constructed to examine the long-term impact of loneliness classes on mental health outcomes. Results Three courses of loneliness were identified: Decreasing Low Loneliness (58.71%), Increasing Medium Loneliness (36.52%), and Increasing High Loneliness (4.77%). Risk factors for poorer loneliness trajectories included lack of physical exercise habits, poorer mental health literacy, medium or low perceived social support, having study difficulties, being female, higher grades, and lower economic status. Loneliness courses were associated with the severity and variability of emotional problems, peer problems, hyperactivity and conduct problems. Individuals in the higher loneliness classes experienced a significant increase in these mental health problems over time. Conclusions  During the last phase of the pandemic, a large proportion of adolescents in our study endured medium to high levels of loneliness with no signs of improvement. Both unfavorable loneliness trajectories adversely affected internalizing and externalizing problems and displayed an upward trend in these difficulties. Results highlight the importance of considering how to tackle loneliness both within the context of COVID-19 and more generally.

Life changes and mental health among Chinese children and adolescents during the pandemic: a combination of cross-sectional, longitudinal and clustering studies (preprint)

The measures to prevent COVID-19 pandemic had caused significant life changes, which could be distressing for mental health among children and adolescents. We aimed to evaluate the short- and long-term effects of life changes on children’s mental health in a large Chinese cohort. Survey-based life changes during COVID-19 lockdown were measured among 7,829 Chinese students at Grade 1–9, including social contacts, lifestyles and family financial status. Clustering analysis was applied to identify potential patterns of these changes. Depressive and anxiety symptoms were measured using the Center for Epidemiologic Studies Depression Scale and Screen for Child Anxiety Related Emotional Disorders. Logistic regression models were used to investigate the associations between these changes, their patterns and the presence of depression/anxiety symptoms using both cross-sectional and longitudinal designs. We found that the prevalence of depression and anxiety symptoms decreased during pandemic (34.6–32.6%). However, during and shortly after lockdown, students who reported negative impacts on their study, social and outside activities and diet, and decreased electronic time and sugar-sweetened consumption, as well as family income decline and unemployment had increased risks of depressive/anxiety symptoms, and students with changed sleep time had increased depressive symptoms. These associations attenuated or disappeared one year later. Similar patterns were observed in clustering analysis, while only the group with severe impact on family financial status showed a sustained increase in depression symptoms. In summary, restrictive measures that changed children and adolescents’ daily life during COVID-19 lockdown showed negative effects on their mental health, with some commonalities and distinctions patterns in the manifestation of depression and anxiety symptoms.

A Bayesian Regression Approach for Estimating the Impact of COVID-19 on Consumer Behavior in the Restaurant Industry (preprint)

The COVID-19 pandemic has had a long-term impact on industries worldwide, with the hospitality and food industry facing significant challenges, leading to the permanent closure of many restaurants and the loss of jobs. In this study, we developed an innovative analytical framework using Hamiltonian Monte Carlo for predictive modeling with Bayesian regression, aiming to estimate the change point in consumer behavior towards different types of restaurants due to COVID-19. Our approach emphasizes a novel method in computational analysis, providing insights into customer behavior changes before and after the pandemic. This research contributes to understanding the effects of COVID-19 on the restaurant industry and is valuable for restaurant owners and policymakers.