Effects of working from home on lifestyle behaviors and mental health during the COVID-19 pandemic: A survey study.

The COVID-19 outbreak has led to relevant changes in everyday life worldwide. One of these changes has been a rapid transition to and an increasing implementation of working from home (WH) modality. This study aimed to evaluate the impact of mandatory WH during the COVID-19 pandemic on lifestyle behaviors, Mediterranean diet adherence, body weight, and depression. An online cross-sectional survey was conducted in the early 2022 at the National Research Council of Italy using ad hoc questions and validated scales collecting information on physical activity, sedentary behavior, hobbies/pastimes, dietary habits including adherence to the Mediterranean diet, body weight, and depression during WH compared with before WH. 748 respondents were included in the study. An increased sedentary lifetime was reported by 48% of respondents; however, the subsample of workers who previously performed moderate physical activity intensified this activity. Body weight gain during WH was self-reported in 39.9% of respondents. Mediterranean diet adherence increased (p≪0.001) during WH compared with before WH. The average level of mental health did not record an overall variation; however, the proportion of subjects with mild and moderate depression increased (p = 0.006), while workers who reported values indicative of depression before the transition declared an improvement. These findings highlight health-related impact of WH during the COVID-19 pandemic that may inform future strategies and policies to improve employees' health and well-being.

Caregiver and parent-child relationship during COVID-19: The mediator role of anxiety and life satisfaction.

AIM: This research was conducted to evaluate the mediation effect of anxiety and life satisfaction on the relationship between Care burden and Parent Child Relationship in Turkish parents during the COVID-19 epidemic. METHODS: The research was carried out with parents (221 women and 219 men) who have children between the ages of 6-18 living in Turkey. Data were collected in June-July 2021 using the demographic data form, "Care Burden Scale," "Pervasive Anxiety Disorder-7 Test," "Satisfaction with Life Scale," and "Parent Child Relationship Scale." Path analysis was used to analyse the relationships. In this study, structural equation modelling (SEM) was used to examine the path analysis. RESULTS: It was found that the burden of care and anxiety of the parents and the parent-child conflict relationship were positively correlated and negatively correlated with the life satisfaction and parent-child closeness relationship (p < 0.05). Path model analyses revealed that the burden of care had a direct effect on anxiety and life satisfaction, and an indirect effect on the parent-child relationship, respectively. CONCLUSIONS: It shows that parents' perceptions of how the COVID-19 pandemic is affecting their mental health have implications for parent and child well-being, with stronger relationships for low-income families. Anxiety and life satisfaction had a mediating effect between care burden and parent-child relationship. Given the demonstrable impact of COVID-19 on the parent-child relationship, this study may guide the planning of coping strategies and programmes focused on mental health.

Artificial Neural Network Prediction of COVID-19 Daily Infection Count.

This study addresses COVID-19 testing as a nonlinear sampling problem, aiming to uncover the dependence of the true infection count in the population on COVID-19 testing metrics such as testing volume and positivity rates. Employing an artificial neural network, we explore the relationship among daily confirmed case counts, testing data, population statistics, and the actual daily case count. The trained artificial neural network undergoes testing in in-sample, out-of-sample, and several hypothetical scenarios. A substantial focus of this paper lies in the estimation of the daily true case count, which serves as the output set of our training process. To achieve this, we implement a regularized backcasting technique that utilize death counts and the infection fatality ratio (IFR), as the death statistics and serological surveys (providing the IFR) as more reliable COVID-19 data sources. Addressing the impact of factors such as age distribution, vaccination, and emerging variants on the IFR time series is a pivotal aspect of our analysis. We expect our study to enhance our understanding of the genuine implications of the COVID-19 pandemic, subsequently benefiting mitigation strategies.

Prevalence and factors for anxiety and depression among secondary school teachers from Sfax city of Tunisia in times of the coronavirus disease 2019 pandemic: a cross-sectional study.

Introduction: teachers have to adapt during the coronavirus disease 2019 (COVID-19) pandemic to many changes that could potentially make them more vulnerable to psychological distress. We aimed to assess anxiety and depression in Tunisian secondary school teachers during the COVID-19 pandemic and to explore their associated factors. Methods: we conducted a cross-sectional survey concerning Tunisian secondary school teachers between May 1st, 2021, and June 30th, 2021, using an online survey platform via Google Forms. Participants were asked to fill in a form including two psychometric tests: the General Anxiety Disorder 7 (GAD-7) and the Patient Health Questionnaire 9 (PHQ-9). We performed both univariable and multivariable logistic regression analyses. Results: a total of 170 secondary school teachers were included, of whom 22.4% (n=38) were males and 77.6% (n=132) were females. The median age was 45.5 years (Q1=39, Q3=49). The overall anxiety prevalence was 34.7% (n=59) while it was 41.7% (n=71) for depression. In multivariable analysis, anxiety was strongly associated with sleep disturbances (aOR: 5.1; 95% CI: 1.80-14.45; p=0.002) and depression (aOR: 33.91; 95% CI: 12.32-93.33; p<0.001) while depression was strongly associated with dissatisfaction with working conditions (aOR: 3.99; 95% CI: 1.49-10.65; p=0.006), the irregular wearing of protective masks (aOR: 3.94; 95% CI: 1.33-11.66; p=0.013) and anxiety (aOR=51.63; 95% CI: 17.74-150.25; p<0.001). Conclusion: secondary school teachers in Tunisia are characterized by a high rate of anxiety and depressive disorders which are related to personal and professional factors on which we can act by supplying of educational institutions by protective masks, the implementation of programs for adjusting working conditions and the practice of non-pharmacological interventions for insomnia management.

Preparing correctional settings for the next pandemic: a modeling study of COVID-19 outbreaks in two high-income countries.

Introduction: Correctional facilities are high-priority settings for coordinated public health responses to the COVID-19 pandemic. These facilities are at high risk of disease transmission due to close contacts between people in prison and with the wider community. People in prison are also vulnerable to severe disease given their high burden of co-morbidities. Methods: We developed a mathematical model to evaluate the effect of various public health interventions, including vaccination, on the mitigation of COVID-19 outbreaks, applying it to prisons in Australia and Canada. Results: We found that, in the absence of any intervention, an outbreak would occur and infect almost 100% of people in prison within 20 days of the index case. However, the rapid rollout of vaccines with other non-pharmaceutical interventions would almost eliminate the risk of an outbreak. Discussion: Our study highlights that high vaccination coverage is required for variants with high transmission probability to completely mitigate the outbreak risk in prisons.

Solutions From Mexican-Descent Perinatal Women To Pandemic-Related Food, Mental Health, And Health And Safety Stressors.

Latina women in the US were disproportionately affected by the COVID-19 pandemic because of structural racism, including discrimination, reduced care access, and elevated risk for illness and death. Although several US policies were implemented to offset the economic toll of the pandemic, few addressed complex stressors, particularly those among Mexican-descent mothers. This qualitative study with thirty-eight perinatal women and mothers of young children who were of Mexican descent sought to identify pandemic-related stressors and solicit recommendations for addressing them during future large-scale crises. Identified stressors included food access issues, mental health needs, and health and safety concerns. The women's recommendations revealed feasible and actionable strategies, including increased access to behavioral and health care services and accessible information about food-related resources. The findings highlight the critical need for responsive policies and programs to ensure the well-being of Mexican-descent perinatal women and mothers of young children during large-scale crises.

The Impact on Working Conditions and Income Amongst Internists in Indonesia: Lesson Learned from the COVID-19 Pandemic.

Internists are at the forefront of providing care for COVID-19 patients. This situation adds more strain on already overburdened internists, particularly in Indonesia, where resources are scarce and unevenly distributed. The pandemic altered working conditions due to restrictions and regulatory changes. Multiple evidence exists for the effect of the COVID-19 pandemic on physicians' well-being, but less is known about its impact on their work dynamics and livelihoods. This study provides some lessons learned during the COVID-19 pandemic regarding the changes in working conditions and earnings experienced by Indonesian internists. There were 3,115 and 1,772 participants in the first and second survey, respectively. After one year, the proportion of internists handling COVID-19 cases, including critical COVID-19 cases, increased; with fewer internists over 60 years old involved. Working hours, number of patients, and monthly earnings decreased for the majority of internists. The increased workload was experienced by most participants one year of the pandemic, predominantly reported by female internists. The COVID-19 pandemic caused a considerable impact on working conditions and income amongst internists in Indonesia. These findings may provide information to institutions in formulating strategies and tools to improve the working conditions and livelihoods of internists in Indonesia amidst the pandemic and potential public health emergencies in the future.

Impacts of the COVID-19 Pandemic on the CODE ST-Segment Elevation Myocardial Infarction Program: A Quantitative and Qualitative Analysis.

BACKGROUND: The code ST-segment elevation myocardial infarction (STEMI) program is an operational standard of integrated service for STEMI patients carried out by Dr. Cipto Mangunkusumo Hospital. The emerging coronavirus disease 2019 (COVID-19) outbreak brought about many changes in the management of healthcare services, including the code STEMI program. This study aimed to evaluate the healthcare service quality of the Code STEMI program during the COVID-19 pandemic based on the Donabedian concept.  Methods: This was a mixed-methods study using quantitative and qualitative analyses. It was conducted at the Dr. Cipto Mangunkusumo Hospital, a national referral hospital in Indonesia. We compared the data of each patient, including response time, clinical outcomes, length of stay, and cost, from two years between 2018-2020 and 2020-2022 as the pre-COVID-19 code STEMI and COVID-19 Code STEMI periods, respectively. Interviews were conducted to determine the quality of services from the perspectives of stakeholders. RESULTS: A total of 195 patients participated in the study: 120 patients in pre-COVID-19 code STEMI and 75 patients in COVID-19 code STEMI. Our results showed that there was a significant increase in patient's length of stay during the COVID-19 pandemic (4 days vs. 6 days, p < 0.001). Meanwhile, MACE (13% vs. 11%, p = 0.581), the in-hospital mortality rate (8% vs. 5%, p = 0.706), door-to-wire crossing time (161 min vs. 173 min, p = 0.065), door-to-needle time (151 min vs. 143 min p = 0.953), and hospitalization cost (3,490 USD vs. 3,700 USD, p = 0.945) showed no significant changes. In terms of patient satisfaction, patients found code STEMI during COVID-19 to be responsive and excellent. CONCLUSION: The implementation of the code STEMI program during the COVID-19 pandemic revealed that modified pathways were required because of the COVID-19 screening process. According to the Donabedian model, during the pandemic, the code STEMI program's healthcare service quality decreased because of a reduction in efficacy, effectiveness, efficiency, and optimality. Despite these limitations attributed to the pandemic, the code STEMI program was able to provide good services for STEMI patients.

Factors that contributed to Ontario adults' mental health during the first 16 months of the COVID-19 pandemic: a decision tree analysis.

The COVID-19 pandemic has negatively impacted the mental health of individuals globally. However, less is known about the characteristics that contributed to some people having mental health problems during the pandemic, while others did not. Mental health problems can be understood on a continuum, ranging from acute (e.g., depression following a stressful event) to severe (e.g., chronic conditions that disrupt everyday functioning). Therefore, the purpose of this article was to generate profiles of adults who were more or less at risk for the development of mental health problems, in general, during the first 16-months of the COVID-19 pandemic in Ontario, Canada. Data were collected via online surveys at two time points: April-July 2020 and July-August 2021; 2,188 adults (Mage = 43.15 years; SD = 8.82) participated. Surveys included a demographic questionnaire and four previously validated tools to measure participants' mental health, subjective wellbeing, physical activity and sedentary behaviour, and sleep. A decision tree was generated at each time point for those with mental health problems, and those with no mental health problems. Results showed that subjective wellbeing was the biggest contributor to mental health status. Characteristics associated with no mental health problems among adults included having good wellbeing, being a good sleeper (quantity, quality, and patterns of sleep), and being over the age of 42. Characteristics associated with mental health problems included having poor wellbeing and being a poor sleeper. Findings revealed that specific characteristics interacted to contribute to adults' mental health status during the first 16 months of the COVID-19 pandemic. Given that wellbeing was the biggest contributor to mental health, researchers should focus on targeting adults' wellbeing to improve their mental health during future health crises.

An adaptive data-driven architecture for mental health care applications.

Background: In the current era of rapid technological innovation, our lives are becoming more closely intertwined with digital systems. Consequently, every human action generates a valuable repository of digital data. In this context, data-driven architectures are pivotal for organizing, manipulating, and presenting data to facilitate positive computing through ensemble machine learning models. Moreover, the COVID-19 pandemic underscored a substantial need for a flexible mental health care architecture. This architecture, inclusive of machine learning predictive models, has the potential to benefit a larger population by identifying individuals at a heightened risk of developing various mental disorders. Objective: Therefore, this research aims to create a flexible mental health care architecture that leverages data-driven methodologies and ensemble machine learning models. The objective is to proficiently structure, process, and present data for positive computing. The adaptive data-driven architecture facilitates customized interventions for diverse mental disorders, fostering positive computing. Consequently, improved mental health care outcomes and enhanced accessibility for individuals with varied mental health conditions are anticipated. Method: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the researchers conducted a systematic literature review in databases indexed in Web of Science to identify the existing strengths and limitations of software architecture relevant to our adaptive design. The systematic review was registered in PROSPERO (CRD42023444661). Additionally, a mapping process was employed to derive essential paradigms serving as the foundation for the research architectural design. To validate the architecture based on its features, professional experts utilized a Likert scale. Results: Through the review, the authors identified six fundamental paradigms crucial for designing architecture. Leveraging these paradigms, the authors crafted an adaptive data-driven architecture, subsequently validated by professional experts. The validation resulted in a mean score exceeding four for each evaluated feature, confirming the architecture's effectiveness. To further assess the architecture's practical application, a prototype architecture for predicting pandemic anxiety was developed.

Blood donation projections using hierarchical time series forecasting: the case of Zimbabwe's national blood bank.

BACKGROUND: The discrepancy between blood supply and demand requires accurate forecasts of the blood supply at any blood bank. Accurate blood donation forecasting gives blood managers empirical evidence in blood inventory management. The study aims to model and predict blood donations in Zimbabwe using hierarchical time series. The modelling technique allows one to identify, say, a declining donor category, and in that way, the method offers feasible and targeted solutions for blood managers to work on. METHODS: The monthly blood donation data covering the period 2007 to 2018, collected from the National Blood Service Zimbabwe (NBSZ) was used. The data was disaggregated by gender and blood groups types within each gender category. The model validation involved utilising actual blood donation data from 2019 and 2020. The model's performance was evaluated through the Mean Absolute Percentage Error (MAPE), uncovering expected and notable discrepancies during the Covid-19 pandemic period only. RESULTS: Blood group O had the highest monthly yield mean of 1507.85 and 1230.03 blood units for male and female donors, respectively. The top-down forecasting proportions (TDFP) under ARIMA, with a MAPE value of 11.30, was selected as the best approach and the model was then used to forecast future blood donations. The blood donation predictions for 2019 had a MAPE value of 14.80, suggesting alignment with previous years' donations. However, starting in April 2020, the Covid-19 pandemic disrupted blood collection, leading to a significant decrease in blood donation and hence a decrease in model accuracy. CONCLUSIONS: The gradual decrease in future blood donations exhibited by the predictions calls for blood authorities in Zimbabwe to develop interventions that encourage blood donor retention and regular donations. The impact of the Covid-19 pandemic distorted the blood donation patterns such that the developed model did not capture the significant drop in blood donations during the pandemic period. Other shocks such as, a surge in global pandemics and other disasters, will inevitably affect the blood donation system. Thus, forecasting future blood collections with a high degree of accuracy requires robust mathematical models which factor in, the impact of various shocks to the system, on short notice.

The experience of traumatic events, psychological distress, and social support: links to COVID-19 vaccine hesitancy and trends with age in a group of older Australians.

BACKGROUND: Vaccination is important to reduce disease-associated morbidity and mortality in an ageing global population. While older adults are more likely than younger adults to accept vaccines, some remain hesitant. We sought to understand how traumatic events, psychological distress and social support contribute to older adults' intention to receive a COVID-19 vaccine and whether these experiences change with age. METHODS: We analysed survey data collected as part of the Sax Institute's 45 and Up Study in a population of Australian adults aged 60 years and over. Data were derived from the COVID Insights study; a series of supplementary surveys about how participants experienced the COVID-19 pandemic. RESULTS: Higher intention to receive a COVID-19 vaccine was associated with greater social support (adjusted odds ratio (aOR):1.08; 95%CI:1.06-1.11; p <.001) while lower intention was associated with personally experiencing a serious illness, injury or assault in the last 12 months (aOR:0.79; 95% CI:0.64-0.98; p =.03). Social support and the experience of traumatic events increased significantly with age, while psychological distress decreased. CONCLUSIONS: There may be factors beyond disease-associated risks that play a role in vaccine acceptance with age. Older Australians on the younger end of the age spectrum may have specific needs to address their hesitancy that may be overlooked.

A qualitative exploration of the impacts of COVID-19 in two rural Southwestern Alaska communities.

This manuscript presents a qualitative exploration of the experiences of people in two Southwestern Alaska communities during the emergence of COVID-19 and subsequent pandemic response. The project used principles of community based participatory research and honoured Indigenous ways of knowing throughout the study design, data collection, analysis, and dissemination. Data was collected in 2022 through group and individual conversations with community members, exploring impacts of the COVID-19 pandemic. Participants included Elders, community health workers, Tribal council members, government employees, school personnel, and emergency response personnel. Notes and written responses were coded using thematic qualitative analysis. The most frequently identified themes were 1) feeling disconnected from family, friends, and other relationships, 2) death, 3) the Tribal councils did a good job, and 4) loss of celebrations and ceremonies. While the findings highlighted grief and a loss of social cohesion due to the pandemic, they also included indicators of resilience and thriving, such as appropriate and responsive local governance, revitalisation of traditional medicines, and coming together as a community to survive. This case study was conducted as part of an international collaboration to identify community-driven, evidence-based recommendations to inform pan-Arctic collaboration and decision making in public health during global emergencies.

Sex Differences in Clustering Unhealthy Lifestyles Among Survivors of COVID-19: Latent Class Analysis.

BACKGROUND: The COVID-19 pandemic has underscored the significance of adopting healthy lifestyles to mitigate the risk of severe outcomes and long-term consequences. OBJECTIVE: This study focuses on assessing the prevalence and clustering of 5 unhealthy lifestyle behaviors among Vietnamese adults after recovering from COVID-19, with a specific emphasis on sex differences. METHODS: The cross-sectional data of 5890 survivors of COVID-19 in Vietnam were analyzed from December 2021 to October 2022. To examine the sex differences in 5 unhealthy lifestyle behaviors (smoking, drinking, unhealthy diet, physical inactivity, and sedentary behavior), the percentages were plotted along with their corresponding 95% CI for each behavior. Latent class analysis was used to identify 2 distinct classes of individuals based on the clustering of these behaviors: the "less unhealthy" group and the "more unhealthy" group. We examined the sociodemographic characteristics associated with each identified class and used logistic regression to investigate the factors related to the "more unhealthy" group. RESULTS: The majority of individuals (male participants: 2432/2447, 99.4% and female participants: 3411/3443, 99.1%) exhibited at least 1 unhealthy behavior, with male participants being more susceptible to multiple unhealthy behaviors. The male-to-female ratio for having a single behavior was 1.003, but it escalated to 25 for individuals displaying all 5 behaviors. Male participants demonstrated a higher prevalence of combining alcohol intake with sedentary behavior (949/2447, 38.8%) or an unhealthy diet (861/2447, 35.2%), whereas female participants tended to exhibit physical inactivity combined with sedentary behavior (1305/3443, 37.9%) or an unhealthy diet (1260/3443, 36.6%). Married male participants had increased odds of falling into the "more unhealthy" group compared to their single counterparts (odds ratio [OR] 1.45, 95% CI 1.14-1.85), while female participants exhibited lower odds (OR 0.65, 95% CI 0.51-0.83). Female participants who are underweight showed a higher likelihood of belonging to the "more unhealthy" group (OR 1.11, 95% CI 0.89-1.39), but this was not observed among male participants (OR 0.6, 95% CI 0.41-0.89). In both sexes, older age, dependent employment, high education, and obesity were associated with higher odds of being in the "more unhealthy" group. CONCLUSIONS: The study identified notable sex differences in unhealthy lifestyle behaviors among survivors of COVID-19. Male survivors are more likely to engage in unhealthy behaviors compared to female survivors. These findings emphasize the importance of tailored public health interventions targeting sex-specific unhealthy behaviors. Specifically, addressing unhealthy habits is crucial for promoting post-COVID-19 health and well-being.

Association between the COVID-19 pandemic and mental health in very old people in Sweden.

BACKGROUND: During the COVID-19 pandemic, Sweden implemented social distancing measures to reduce infection rates. However, the recommendation meant to protect individuals particularly at risk may have had negative consequences. The aim of this study was to investigate the impact of the COVID-19 pandemic on very old Swedish peoples' mental health and factors associated with a decline in mental health. METHODS: We conducted a cross-sectional study among previous participants of the SilverMONICA (MONItoring of Trends and Determinants of CArdiovascular disease) study. Of 394 eligible participants, 257 (65.2%) agreed to participate. Of these, 250 individuals reported mental health impact from COVID-19. Structured telephone interviews were carried out during the spring of 2021. Data were analysed using the χ2 test, t-test, and binary logistic regression. RESULTS: Of 250 individuals (mean age: 85.5 ± 3.3 years, 54.0% women), 75 (30.0%) reported a negative impact on mental health, while 175 (70.0%) reported either a positive impact (n = 4) or no impact at all (n = 171). In the binary logistic regression model, factors associated with a decline in mental health included loneliness (odds ratio [95% confidence interval]) (3.87 [1.83-8.17]) and difficulty adhering to social distancing recommendations (5.10 [1.92-13.53]). High morale was associated with positive or no impact on mental health (0.37 [0.17-0.82]). CONCLUSIONS: A high percentage of very old people reported a negative impact on mental health from the COVID-19 pandemic, primarily from loneliness and difficulty adhering to social distancing measures, while high morale seemed to be a protective factor.

Network analysis of anxiety and depressive symptoms during the COVID-19 pandemic in older adults in the United Kingdom.

The health crisis caused by COVID-19 in the United Kingdom and the confinement measures that were subsequently implemented had unprecedented effects on the mental health of older adults, leading to the emergence and exacerbation of different comorbid symptoms including depression and anxiety. This study examined and compared depression and anxiety symptom networks in two specific quarantine periods (June-July and November-December) in the older adult population in the United Kingdom. We used the database of the English Longitudinal Study of Aging COVID-19 Substudy, consisting of 5797 participants in the first stage (54% women) and 6512 participants in the second stage (56% women), all over 50 years of age. The symptoms with the highest centrality in both times were: "Nervousness (A1)" and "Inability to relax (A4)" in expected influence and predictability, and "depressed mood (D1"; bridging expected influence). The latter measure along with "Irritability (A6)" overlapped in both depression and anxiety clusters in both networks. In addition, a the cross-lagged panel network model was examined in which a more significant influence on the direction of the symptom "Nervousness (A1)" by the depressive symptoms of "Anhedonia (D6)", "Hopelessness (D7)", and "Sleep problems (D3)" was observed; the latter measure has the highest predictive capability of the network. The results report which symptoms had a higher degree of centrality and transdiagnostic overlap in the cross-sectional networks (invariants) and the cross-lagged panel network model of anxious and depressive symptomatology.

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants may have different characteristics, e.g., in transmission, mortality, and the effectiveness of vaccines, indicating the importance of variant detection at the population level. Wastewater-based surveillance of SARS-CoV-2 RNA fragments has been shown to be an effective way to monitor the COVID-19 pandemic at the population level. Wastewater is a complex sample matrix affected by environmental factors and PCR inhibitors, causing insufficient coverage in sequencing, for example. Subsequently, results where part of the genome does not have sufficient coverage are not uncommon. To identify variants and their proportions in wastewater over time, we utilized next-generation sequencing with the ARTIC Network's primer set and bioinformatics pipeline to evaluate the presence of variants in partial genome data. Based on the wastewater data from November 2021 to February 2022, the Delta variant was dominant until mid-December in Helsinki, Finland's capital, and thereafter in late December 2022 Omicron became the most common variant. At the same time, the Omicron variant of SARS-CoV-2 outcompeted the previous Delta variant in Finland in new COVID-19 cases. The SARS-CoV-2 variant findings from wastewater are in agreement with the variant information obtained from the patient samples when visually comparing trends in the sewerage network area. This indicates that the sequencing of wastewater is an effective way to monitor temporal and spatial trends of SARS-CoV-2 variants at the population level.

LDA2Net Digging under the surface of COVID-19 scientific literature topics via a network-based approach.

During the COVID-19 pandemic, the scientific literature related to SARS-COV-2 has been growing dramatically. These literary items encompass a varied set of topics, ranging from vaccination to protective equipment efficacy as well as lockdown policy evaluations. As a result, the development of automatic methods that allow an in-depth exploration of this growing literature has become a relevant issue, both to identify the topical trends of COVID-related research and to zoom-in on its sub-themes. This work proposes a novel methodology, called LDA2Net, which combines topic modelling and network analysis, to investigate topics under their surface. More specifically, LDA2Net exploits the frequencies of consecutive words pairs (i.e. bigram) to build those network structures underlying the hidden topics extracted from large volumes of text by Latent Dirichlet Allocation (LDA). Results are promising and suggest that the topic model efficacy is magnified by the network-based representation. In particular, such enrichment is noticeable when it comes to displaying and exploring the topics at different levels of granularity.

ER-export and ARFRP1/AP-1-dependent delivery of SARS-CoV-2 Envelope to lysosomes controls late stages of viral replication.

The ß-coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the global COVID-19 pandemic. Coronaviral Envelope (E) proteins are pentameric viroporins that play essential roles in assembly, release, and pathogenesis. We developed a nondisruptive tagging strategy for SARS-CoV-2 E and find that, at steady state, it localizes to the Golgi and to lysosomes. We identify sequences in E, conserved across Coronaviridae, responsible for endoplasmic reticulum-to-Golgi export, and relate this activity to interaction with COP-II via SEC24. Using proximity biotinylation, we identify an ADP ribosylation factor 1/adaptor protein-1 (ARFRP1/AP-1)-dependent pathway allowing Golgi-to-lysosome trafficking of E. We identify sequences in E that bind AP-1, are conserved across ß-coronaviruses, and allow E to be trafficked from Golgi to lysosomes. We show that E acts to deacidify lysosomes and, by developing a trans-complementation assay for SARS-CoV-2 structural proteins, that lysosomal delivery of E and its viroporin activity is necessary for efficient viral replication and release.