Balancing Flexibility and Compliance in Response to Long-Tailed Business Process Changes (preprint)

The resilience of process-aware information systems (PAIS) is vital for enterprises' competitiveness in the ever-changing world. Enterprises need continuously maintain business processes in PAIS against uncertainty, resulting in the constant research topic of change management in business process management (BPM). However, previous efforts have left some gaps in dealing with uncertainties in change requirements, either due to high costs or technical incapability. Among these gaps, long-tailed change (LTC), characterized as the urgent and customizable maintenance needs in response to the residual uncertainty, has been largely undeveloped. COVID-19 and some emergent events in 2022 call for more effective solutions to such problems, to mitigate the business loss and to seek emerging opportunities. LTC challenges come from the contention between the degree of flexibility and compliance with business regulations in the context of rapid adaptation. In this paper, we develop a systematic approach to deal with these issues. First, we formulate the problem as a cooperation of multiple participants in the business by leveraging the separation of concerns principle to clarify the division of labor contributing to agility and fine-tuning capability of the approach, and to provide a controllable mechanism to balance operational resilience and dependable adaptation for PAIS. According to the framework, we develop a domain-specific language (DSL) and corresponding techniques to support business people in customizing business processes' behavior to meet circumstances. At the same time, business stakeholders can enforce core functions and service-level agreement (SLA) constraints on the whole business process. We validate our framework through two scenarios, one for design-time model adaptation and the other for run-time instance adaptation. These experiments reveal promising potentials of the framework in adapting to LTC and resolving the contention between agility/flexibility in change and compliance with business regulations, which significantly improves PAIS's resilience to wide-spectrum, low-frequent, sporadic, and transitory events.

Prevalence and Characterization of Long Covid-19 Symptoms in Health Care Professionals- A Need of the Hour (preprint)

Background: With the global advent of Covid-19, Healthcare workers (HCW) were under a lot of physical and psychological pressure. Information on persistent symptoms post Covid-19 Infection in HCWs is lacking.  Objectives: This Study is aimed at assessing the impact of the post Covid-19 syndrome in HCWs.  Materials and Methods: A Questionnaire was prepared as google form and shared with the HCWs through WhatsApp enquiring regarding the health conditions that are still persistent post recovery from Covid-19 infection.  Results: A total of 328 Health Care Professionals participated in the present survey (18-65 yrs). The gender distribution revealed 67.7% were females and 32.3% were males. 60.3% of the participants were infected with COVID-19 before taking the first dose of vaccination which is reduced to 17.5% after vaccination. The post COVID complications observed from the study were hair loss (35.4%), easy fatigability (25%), mood swings (22.9%), anxiety (18.8%), insomnia/sleeplessness (13.9%), depression (12.5%) and joint pains/arthritis (11.8%). The other complications observed were loss of taste (9%), lightheadedness/postural hypotension (8.3%), amnesia/loss of memory and anosmia/loss of smell (7.6%), gastritis (6.3%), palpitations, hypersomnia and pulmonary complications (5.6%) and chest pain (4.9%). Unpaired t-test and One-Way ANNOVA resulted in a significant value (p values of >0.05).  Discussion: Despite the fact that females experienced more post-Covid-19 symptoms (15 out of 17), males experienced more chest pain and anxiety symptoms. According to our findings, 57 of 100 Covid-19 health care workers have post-Covid complications. The participants presented with non-specific symptoms such as easy fatigability, mood swings, light headedness, anxiety but most of the participants quoted more specific symptoms such as depression, pulmonary complications, hair loss, joint pains, gastritis, chest pain, palpitations, loss of taste, amnesia, hyperglycemia, insomnia, hypersomnia and anosmia. However, non-specific symptoms such as fatigue, mood swings, lightheadedness, and anxiety were also mentioned. The symptoms of post-acute COVID-19 syndrome vary greatly. Early detection requires a unified definition of long COVID and characterization of its manifestation. Furthermore, more research should be conducted to identify risk factors and the precise mechanisms that lead to the development of long COVID syndrome. Such knowledge may aid future research aimed at preventing such a complication.

The era of our lives: The memory of Korsakoff patients for the first Covid-19 pandemic lockdown in the Netherlands.

Memories for worldwide and emotional events (such as 9/11) are more vividly relived and recalled than memories for everyday events. Previous studies have shown that flashbulb memories of a single event enhanced the memory strength in severe amnesia. It is currently unknown whether macro-events that stretch out over longer periods of time (weeks, months) strengthen memory even further. Our aim was therefore to investigate to what extent patients with severe amnesia, due to Korsakoff's syndrome (KS), were able to relive the first Covid-19 lockdown in the Netherlands, and whether experienced emotions enhanced reliving of the participants. We included 22 KS patients and 24 age-, education-, and gender-matched healthy controls. Covid-19 related memories were assessed by measures of autobiographical memory specificity, phenomenological reliving, emotional intensity and semantic-and episodic knowledge about the first lockdown in March 2020 - May 2020 in the Netherlands. Although amnesia patients remembered significantly fewer autobiographical details regarding the Covid-19 lockdown than healthy controls, one fourth of the KS patients recalled specific events. Amnesia patients reported levels of emotional intensity equivalent to those in the control group. Stronger autobiographical reliving was associated with higher emotional intensity. Both amnesia patients and healthy controls had higher recall of episodic than semantic lockdown related information. In conclusion, results demonstrate that information for macro-events can still be memorized and relived, most specifically when emotional valence is high, even by highly amnestic patients.

Dissociative experiences among Lebanese university students: Association with mental health issues, the economic crisis, the COVID-19 pandemic, and the Beirut port explosion.

BACKGROUND: Dissociative experiences are psychological manifestations characterized by a loss of connection and continuity between thoughts, emotions, environment, behavior, and identity. Lebanon has been facing indescribable events in the last few years, including the COVID-19 pandemic, the Beirut explosion, a crushing economic crisis with the highest inflation rate the country has known in over three decades. The aim of this study was to evaluate the correlation between dissociative experiences and post-traumatic stress symptoms from the economic crisis, the Beirut blast, the COVID-19 pandemic, and other mental health issues in a sample of Lebanese university students. METHODS: This cross-sectional study enrolled 419 active university students (18-35 years) from all over Lebanon (May and August 2021). The respondents received the online soft copy of a survey by a snowball sampling technique through social media and messaging apps. The questionnaire included sociodemographic data, the Dissociative Experience Scale (DES-II), the PTSD Checklist Specific Version (PCL-S), the Financial Wellbeing Scale, the Beirut Distress Scale, the Lebanese Anxiety Scale, the Patient Health Questionnaire. RESULTS: The two-factor model of the DES fitted best according to CFI, RMSEA and χ2/df values, but modestly according to TLI. The two factors were absorption and amnesia/depersonalization. Higher stress (Beta = 0.95) and more PTSD from the Beirut blast (Beta = 0.29) and from the economic crisis (Beta = 0.23) were significantly associated with more absorption. A personal history of depression (Beta = 6.03), higher stress (Beta = 0.36) and more PTSD from the Beirut blast (Beta = 0.27) and from the COVID-19 pandemic (Beta = 0.16) were significantly associated with more amnesia/depersonalization. CONCLUSION: Significant rates of dissociative experiences and their sub-manifestations (amnesia/depersonalization and absorption) were found among Lebanese university students, with remarkable co-occurrence of a traumatic/stressful pattern, whether on an individual (history of PTSD) or a collective level (Post-traumatic manifestations from Beirut blast, COVID-19 pandemic and/or economic crisis), or whether correlated to an acute single event or to certain chronic stressors, or even to a personal history of depression. Such findings must raise the attention to serious mental and psychosocial alteration in the Lebanese national identity.

Human Mobility Modeling During the COVID-19 Pandemic via Deep Graph Diffusion Infomax (preprint)

Non-Pharmaceutical Interventions (NPIs), such as social gathering restrictions, have shown effectiveness to slow the transmission of COVID-19 by reducing the contact of people. To support policy-makers, multiple studies have first modeled human mobility via macro indicators (e.g., average daily travel distance) and then studied the effectiveness of NPIs. In this work, we focus on mobility modeling and, from a micro perspective, aim to predict locations that will be visited by COVID-19 cases. Since NPIs generally cause economic and societal loss, such a micro perspective prediction benefits governments when they design and evaluate them. However, in real-world situations, strict privacy data protection regulations result in severe data sparsity problems (i.e., limited case and location information). To address these challenges, we formulate the micro perspective mobility modeling into computing the relevance score between a diffusion and a location, conditional on a geometric graph. we propose a model named Deep Graph Diffusion Infomax (DGDI), which jointly models variables including a geometric graph, a set of diffusions and a set of locations.To facilitate the research of COVID-19 prediction, we present two benchmarks that contain geometric graphs and location histories of COVID-19 cases. Extensive experiments on the two benchmarks show that DGDI significantly outperforms other competing methods.

Might first-hand experience of ill-health and economic hardship during the COVID-19 pandemic strengthen public support for vaccination and the reallocation of health sector funding towards health emergency preparedness in South Africa? (preprint)

AimsWe examined whether first-hand experience of ill-health and economic hardship during the COVID-19 pandemic might strengthen public support for vaccination, and for the reallocation of health sector funding towards health emergency preparedness in South Africa - a country in which high rates of vaccine hesitancy go hand in hand with widespread discontent regarding public service delivery. MethodsUsing data from 1,600 South African respondents who were surveyed during 2021 for the Eighth Round of Afrobarometer (AB-R8), discrete measures of household- and individual-level sociodemographic and economic factors were generated to permit confounder-adjusted analyses of probabilistic causal relationships between self-reported measures of: personal/household COVID-19 illness and job/income/business loss as a result of COVID-19; and the likelihood that respondents would accept a (government-approved) COVID-19 vaccine, or support the reallocation of health sector funding towards health emergency preparedness. FindingsThere was little evidence that personal/household experience of COVID-19 illness was associated with the likelihood that respondents would (or would not) accept a (government-approved) COVID-19 vaccine (OR: 0.96; 95%CI: 0.72,1.28); or that these respondents would (or would not) support the reallocation of health sector funding towards health emergency preparedness (OR: 0.95; 95%CI: 0.71,1.26), even after adjustment for individual- or household-level sociodemographic and economic covariates considered likely confounders. There was similarly little evidence that personal/household experience of job/income/business loss as a result of the COVID-19 pandemic was associated with support for the reallocation of health sector resources for emergency preparedness (OR: 1.02; 95%CI: 0.80,1.30); again, even after adjustment for potential confounders. However, respondents who reported that they or someone in their household had lost their job/income/or business as a result of the COVID-19 pandemic had only around half the odds of reporting that they would accept a (government-approved) COVID-19 vaccine (OR: 0.60; 95%CI: 0.47,0.77) - and this finding, like the others in these analyses, was largely unaffected by the inclusion/exclusion of covariates considered susceptible to change following the onset of the COVID-19 pandemic (i.e. those covariates potentially operating as colliders rather than genuine confounders). ConclusionsThese findings suggest that - despite the postulated experiential dividend of COVID-19 illness (i.e. its expected impact on vaccine hesitancy and support for the reallocation of health sector resources for health emergency preparedness) - no such dividend was observed in this broadly representative sample of South African adults. Indeed, job/income/business loss (and associated economic hardship) also had little effect on support for the reallocation of health sector resources for health emergency preparedness; yet this was somewhat paradoxically associated with a much lower odds of vaccine acceptance - paradoxically, since vaccination has been widely viewed as a pragmatic (if somewhat neoliberal) intervention to protect economic activity. However, these findings might simply reflect inadequate confounder adjustment for preceding and entrenched attitudes towards vaccination amongst those South Africans who are also most vulnerable to job/income/business loss as a result of the COVID-19 pandemic. Protecting the livelihood and health of such individuals and households is likely to remain a substantial challenge and key priority for future emergencies in which economic activity is compromised. AimThe aim of the present study was to examine whether first-hand experience of ill-health and economic hardship during the COVID-19 pandemic might have strengthened public support for vaccination, and for the reallocation of health sector funding towards health emergency preparedness in South Africa - a country in which high rates of vaccine hesitancy go hand in hand with widespread discontent regarding public service delivery. To this end we drew on data generated by the eighth round of household surveys undertaken by Afrobarometer (AB-R8) which interviewed 1,600 respondents across South Africa during 2021 - more than a year after the countrys first confirmed case of COVID-19 on 5 March 2020.

From loss to recovery: how to effectively assess chemosensory impairments during COVID-19 pandemic (preprint)

Chemosensory impairments have been established as a specific indicator of COVID-19. They affect most patients and may persist long past the resolution of respiratory symptoms, representing an unprecedented medical challenge. Since the SARS-CoV-2 pandemic started, we now know much more about smell, taste, and chemesthesis loss associated with COVID-19. However, the temporal dynamics and characteristics of recovery are still unknown. Here, capitalizing on data from the Global Consortium for Chemosensory Research (GCCR) crowdsourced survey, we assessed chemosensory abilities after the resolution of respiratory symptoms in participants diagnosed with COVID-19 during the first wave of the pandemic in Italy. This analysis led to the identification of two patterns of chemosensory recovery, limited (partial) and substantial, which were found to be associated with differential age, degrees of chemosensory loss, and regional patterns. Uncovering the self-reported phenomenology of recovery from smell, taste, and chemesthetic disorders is the first, yet essential step, to provide healthcare professionals with the tools to take purposeful and targeted action to address chemosensory disorders and its severe discomfort.

SARS-CoV-2 infection and risk of clinical sequelae during the post-acute phase: a retrospective cohort study (preprint)

Objective: Clinical sequelae have not been well characterized during the post-acute phase of SARS-CoV-2 among adults 18 to 65 years old, and this study sought to fill that gap by evaluating excess risk and relative hazards for developing incident clinical sequelae during the post-acute phase. Design: Retrospective cohort study including three propensity-matched groups. Setting: This study merged three data sources from a large United States health plan: a large national administrative claims database, an outpatient lab testing database, and an inpatient hospital admissions database. Participants: Individuals 18 to 65 years old with continuous health plan enrollment from January 2019 to date of SARS-CoV-2 diagnosis. Three comparator groups were identified and propensity-score matched to individuals infected with SARS-CoV-2: a 2020 comparator group, a historical 2019 comparator group and a historical comparator group with viral lower respiratory tract illness (vLRTI). Main outcome measures: Over 50 clinical sequelae during the post-acute phase (index date + 21 days) were ascertained using ICD-10 codes. Excess risk due to SARS-CoV-2 during the 4 months following the acute phase of illness and hazard ratios with 95% Bonferroni-corrected confidence intervals were calculated. Results: This study found 14% of adults [≤]65 years of age who were infected with SARS-CoV-2 (n=193113) had at least one new clinical sequelae that required medical attention during the post-acute phase of illness. When considering risk for specific sequelae attributable to SARS-Cov-2 infection during the post-acute phase, clinical outcomes including chronic respiratory failure, cardiac arrythmia, hypercoagulability, encephalopathy, peripheral neuropathy, amnesia (memory difficulty), diabetes, liver test abnormalities, myocarditis, anxiety and fatigue were significantly elevated compared to the three propensity-matched comparator groups (2020, 2019, vLRTI). Significant risk differences due to SARS-CoV-2 infection ranged from 0.02 to 2.26 per 100 people and hazard ratios ranged from 1.24 to 25.65 when compared to the 2020 comparator group. Conclusions: Our results confirm excess risk for developing clinical sequelae due to SARS-CoV-2 during the post-acute phase, including specific types of sequelae less commonly seen among other viral illnesses. Although individuals who were older, had pre-existing conditions, and were hospitalized due to COVID-19 were at greatest excess risk, younger adults ([≤]50 years), adults who did not have pre-existing conditions or adults who were not hospitalized due to COVID-19 were still at elevated risk for developing new clinical sequelae. The elevated risk for incident sequelae during the post-acute phase is relevant for healthcare planning.

Describing the impact of the COVID-19 pandemic on alcohol-induced blackout tweets.

INTRODUCTION AND AIMS: COVID-19, considered a pandemic by the World Health Organization, overwhelmed hospitals in the USA. In parallel to the growing pandemic, alcohol sales grew in the USA, with people stockpiling alcohol. Alcohol-induced blackouts are one particularly concerning consequence of heavy drinking, and the extent to which blackout prevalence may change in the context of a pandemic is unknown. The purpose of the current study is to describe the prevalence of publicly available tweets in the USA referencing alcohol-induced blackouts prior to and during the COVID-19 outbreak. DESIGN AND METHODS: We used Crimson Hexagon's ForSight tool to access all original English tweets written in the USA that referenced alcohol-related blackouts in 2019 and 2020. Using infoveillance methods, we tracked changes in the number and proportion of tweets about blackouts. RESULTS: More alcohol-related blackout tweets were written between 13 March and 24 April in 2020 than 2019. In addition, a greater proportion of all tweets referenced blackouts in 2020 than in 2019. In the period prior to the 'stay at home' orders (January to mid-March), the proportion of blackout tweets were higher in 2020 than 2019. DISCUSSION AND CONCLUSION: Our findings demonstrate that references to high-risk drinking persist during the pandemic despite restrictions on large social gatherings. Given that the internet is a common source of information for COVID-19, the frequent posting about blackouts during this period might normalise the behaviour. This is concerning because alcohol use increases susceptibility to COVID-19, and alcohol-related mortality can further tax hospital resources.

The Effect of Tax Incentives Practices on Sustainability of Micro, Small and Medium Enterprises in Ethiopia During the Outbreak of Corona Virus Pandemic (preprint)

Purpose: The aim of this study was to identify the effect of tax incentive practise on sustainability of MSMEs during outbreak of corona virus pandemic in Ethiopia. Design/methodology/approach: In order to achieve this objective, the researchers have employed quantitative research approach with explanatory research design in which six hypotheses have been tested. The primary data was collected from 300 respondents using structured questionnaires. Multiple regression model was employed to identify the effect of tax incentives on sustainability of MSMEs in Ethiopia. Findings: According to the regression analysis, this study revealed that tax holiday, tax allowance, reduction in tax rate, accelerated depreciation, loss carry forward and tax exemption have positive and statistically significant effect on the sustainability of the MSMEs. Based on the finding of the study was concluded that the existence of tax incentive practice has positive contribution to sustainability of the micro, small and medium sized enterprise.Research limitations/implications: The current study was geographically focus on Ethiopia by considering the micro, small and medium sized enterprises sector. The subject wise was focused on the effect of the tax incentives:(tax holiday, tax allowance, tax exemption, and accelerated depreciation, reduction in tax rate, and loss carry forward) and on the sustainability of MSMEs. The study used primary data which is limited to a year of  2020. It might be improved in the future if other researchers incorporate large firms in the country and uses secondary data for analysis. Practical implications: To survive, micro, small and medium scale enterprises need the support from the government in the form of tax incentives. The role of tax incentives in enhancing the growth of micro, small and medium sized enterprises is very significant on the sustainability of MSMEs as well as the economy as a whole. Hence, the findings and recommendations of the current study might serve as an ingredient and be informative to the policy makers on MSMEs sector. It might also give a general insight to the policy makers, academician and professional groups of society and the public at large with regard to the role of effect of tax incentives on the sustainability and growth of MSMEs during outbreak of coronavirus.Originality/value: This study contributes to empirical evidence about the effect of tax incentives practices on sustainability of micro, small and medium enterprises in Ethiopia by considering tax incentive practice in terms of tax holiday, tax allowance, reduction in tax rate, accelerated depreciation, loss carry forward and tax exemption. As tax incentives theories supported the findings of this study, we have concluded that tax incentive practices provided by government have positive contribution for the sustainability and growth of micro, small and medium sized enterprises in Ethiopia

Use of Alcohol and Addictive Drugs During the COVID-19 Outbreak: Associations with Mental Health and Pandemic-Related Problems (preprint)

The outbreak of COVID-19 has had a major impact on people’s daily life. This study aimed to examine use of alcohol and addictive drugs during the COVID-19 outbreak and examine their association with mental health problems and problems related to the pandemic. A sample of 4527 persons responded to the survey. Use of alcohol and addictive drugs were cross-tabulated with sociodemographic variables, mental health problems and problems related to COVID-19. Logistic regression analyses were used to examine the strength of the associations. Daily use of alcohol was associated with depression and expecting financial loss in relation to the COVID-19 outbreak. Use of cannabis was associated with expecting financial loss in relation to COVID-19. Use of sedatives was associated with anxiety, depression, and insomnia. Use of painkillers was associated with insomnia and self-reported risk of complications if contracting the coronavirus. We conclude that the occurrence of mental health problems is more important for an understanding of the use of alcohol and addictive drugs during the COVID-19 outbreak compared to specific pandemic-related worries.

A One-Minute Blood Test to Monitor Immune Responses in COVID-19 Patients and Predict Clinical Risks of Developing Moderate to Severe Symptoms (preprint)

Coronavirus disease 2019 (COVID-19) has brought enormous loss and interruption to human life and the global economy since the first outbreak reported in China between late 2019 to early 2020, and will likely remain a public health threat in the months and years to come. Upon infection with SARS-CoV-2, the virus that causes COVID-19, most people will develop no or mild symptoms, however, a small percentage of the population will become severely ill, require hospitalization, intensive care, and some succumb to death. The current knowledge of COVID-19 disease progression with worsening symptom complex implicates the critical importance of identifying patients with high clinical risk compared to those who would be at lower risk for disease control and patient management with better therapeutic output. Currently no clinical test is available that can predict risk factors and immune status change at different severity scales. The immune system plays a critical role in the defense against infectious diseases. Extensive research has found that COVID-19 patients with poor clinical outcomes differ significantly in their immune responses to the virus from those who exhibit milder symptoms. We previously developed a nanoparticle-enabled blood test that can detect the humoral immune status change in animals. In this study, we applied this new test to analyze the immune response in relation to disease severity in COVID-19 patients. From the testing of 153 COVID-19 patient samples and 142 negative controls, we detected statistically significant differences between COVID-19 patients with no or mild symptoms from those who developed moderate to severe symptoms. Mechanistic study suggests that these differences are associated with type 1 versus type 2 immune responses. We conclude that this new rapid test could potentially become a valuable clinical tool for COVID-19 patient risk stratification and management.

Single-cell analysis reveals the function of lung progenitor cells in COVID-19 patients (preprint)

The high mortality of severe 2019 novel coronavirus disease (COVID-19) cases is mainly caused by acute respiratory distress syndrome (ARDS), which is characterized by increased permeability of the alveolar epithelial barriers, pulmonary edema and consequently inflammatory tissue damage. Some but not all patients showed full functional recovery after the devastating lung damage, and so far there is little knowledge about the lung repair process1. Here by analyzing the bronchoalveolar lavage fluid (BALF) of COVID-19 patients through single cell RNA-sequencing (scRNA-Seq), we found that in severe (or critical) cases, there is remarkable expansion of TM4SF1+ and KRT5+ lung progenitor cells. The two distinct populations of progenitor cells could play crucial roles in alveolar cell regeneration and epithelial barrier re-establishment, respectively. In order to understand the function of KRT5+ progenitors in vivo, we transplanted a single KRT5+ cell-derived cell population into damaged mouse lung. Time-course single-cell transcriptomic analysis showed that the transplanted KRT5+ progenitors could long-term engrafted into host lung and differentiate into HOPX+ OCLN+ alveolar barrier cell which restored the epithelial barrier and efficiently prevented inflammatory cell infiltration. Similar barrier cells were also identified in some COVID-19 patients with massive leukocyte infiltration. Altogether this work uncovered the mechanism that how various lung progenitor cells work in concert to prevent and replenish alveoli loss post severe SARS-CoV-2 infection.

Detection of Fraud Transactions Using Recurrent Neural Network during COVID-19 (preprint)

Online transactions are becoming more popular in present situation where the globe is facing an unknown disease COVID-19. Now authorities of Countries requested peoples to use cashless transaction as far as possible. Practically it is not always possible to use it in all transactions. Since number of such cashless transactions have been increasing during lockdown period due to COVID-19, fraudulent transactions are also increasing in a rapid way. Fraud can be analysed by viewing a series of customer transactions data that was done in his/her previous transactions. Normally banks or other transaction authorities warned their customers about the transaction If any deviation is noticed by them from available patterns. These authorities think that it is possibly of fraudulent transaction. For detection of fraud during COVID-19, banks and credit card companies are applying various methods such as data mining , decision tree, rule based mining, neural network, fuzzy clustering approach and machine learning methods. These approaches is try to find out normal usage pattern of customers based on their past activities. The objective of this paper is to find out such fraud transactions during such unmanageable situation.Digital payment schemes are often threatened by fraudulent activities. Detecting fraud transaction in during money transfer may save customers from financial loss. Mobile based money transactions are focused in this paper for fraud detection. A Deep Learning (DL) framework is suggested in this paper that monitors and detects fraudulent activities. Implementing and applying recurrent neural network on PaySim generated synthetic financial dataset, deceptive transactions are identified. The proposed method is capable to detect deceptive transactions with an accuracy of 99.87%, F1-Score of 0.99 and MSE of 0.01.

Unemployment and health-related quality of life in melanoma patients during the COVID-19 pandemic: A web-based cross-sectional study (preprint)

Background The outbreak of coronavirus disease-2019 (COVID-19) ineluctably caused social distancing and unemployment, which may bring additional health risks for patients with cancer. To investigate the association of the pandemic-related impacts with the health-related quality of life (HRQoL) among patients with melanoma during the COVID-19 pandemic, we conducted a cross-sectional study among Chinese patients with melanoma.Methods A self-administered online questionnaire was distributed to melanoma patients through social media. Demographic and clinical data, and pandemic-related impacts (unemployment and income loss) were collected. HRQoL was determined by the Functional Assessment of Cancer Therapy-General (FACT-G) and its disease-specific module (the melanoma subscale, MS).Results A total of 70 patients with melanoma completed the study. The mean age of the patients was 55.2 ± 14.8 years, 45.7% (32/70) were male, and 21.4% (15/70) were unemployed since the epidemic. Unemployment of the patients and their family members and income loss were significantly associated with a lower FACT-G score, while the MS score was associated with the unemployment of the patients’ family members.Conclusions Our findings suggested that unemployment is associated with impaired HRQoL in melanoma patients during the COVID-19 epidemic.