bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of SARS-CoV-2 transmission fear and COVID-19 pandemic on the mental health of patients with primary immunodeficiency disorders, severe asthma, and other high-risk groups
Authors: Çölkesen Fatih , Kılınçel Oğuzhan , Sözen Mehmet , Yıldız Eray , Beyaz Şengül , Çölkesen Fatma , Aytekin Gökhan , Koçak Mehmet Zahid , Alsancak Yakup , Araz Murat , Arslan Şevket 
Published: June 2020

AbstractBackgroundThe adverse effects of COVID-19 pandemic on the mental health of high-risk group patients for morbidity and mortality and its impact on public health in the long term have not been clearly determined.ObjectiveTo determine the level of COVID-19 related transmission fear and anxiety in healthcare workers and patients with primary immunodeficiency disorder (PID), severe asthma, and the ones with other comorbidities.MethodsThe healthcare workers and patients with PID, severe asthma (all patients receiving biological agent treatment), malignancy, cardiovascular disease, hypertension (90% of patients receiving ACEI or ARB therapy), diabetes mellitus (42 % of patients receiving DPP-4 inhibitor therapy) were included in the study. A total of 560 participants, 80 individuals in each group, were provided. The hospital anxiety and depression scale (HADS) and Fear of illness and virus evaluation (FIVE) scales were applied to the groups with face to face interview methods.ResultsThe mean age was 49.30 ± 13.74 years and 306 (55 %) were female. The FIVE Scale and HADS-A scale scores of health care workers were significantly higher than other groups scores (p = 0.001 and 0.006). The second-highest scores belonged to patients with PID. There was no significant difference between the groups for the HADS-D score (p=0.07). The lowest score in all scales was observed in patients with hypertension.ConclusionsThis study demonstrated that in the pandemic process, patients with primary immunodeficiency, asthma patients, and other comorbid patients, especially healthcare workers, should be referred to the centers for the detection and treatment of mental health conditions.
The impact of the COVID-19 pandemic on quality of life, physical and psychosocial wellbeing in breast cancer patients and survivors – a prospective, multicenter cohort study
Authors: Bargon CA Claudia A , Batenburg Marilot CT , van Stam Lilianne E , van der Molen Dieuwke R Mink , van Dam Iris E , van der Leij Femke , Baas Inge O , Ernst Miranda F , Maarse Wiesje , Vermulst Nieke , Schoenmaeckers Ernst JP , van Dalen Thijs , Bijlsma Rhodé M , Young-Afat Danny A , Doeksen Annemiek , Verkooijen Helena M ,   UMBRELLA study group
Published: June 2020

ABSTRACTPurposeThe COVID-19 pandemic and the resulting social distancing and lockdown measures are having a substantial impact on daily life and medical management of people with breast cancer. We evaluated to what extent these changes have affected quality of life and physical, and psychosocial wellbeing of people (being) treated for breast cancer.MethodsThis study was conducted within the prospective Utrecht cohort for Multiple BREast cancer intervention studies and Long-term evaluation (UMBRELLA). Shortly after the implementation of COVID-19 measures, extra questionnaires were sent to 1595 cohort participants, including standard UMBRELLA quality of life (EORTC) questionnaires. Patient-reported outcomes (PROs) were compared to the most recent PROs collected within UMBRELLA before COVID-19. The impact of COVID-19 on PROs was evaluated using mixed models analysis.ResultsIn total, 1051 patients (66%) completed the questionnaires. One third (n = 327, 31%) reported a higher threshold to contact their general practitioner due to COVID-19. A significant deterioration in emotional functioning was observed (82·6 to 77·9, p < 0.001) and 505 (48%, 95% CI 45-51) patients reported moderate to severe loneliness. Small significant improvements were observed in QoL, physical-, social- and role functioning scores. In the subgroup of 51 patients under active treatment, there was a strong deterioration in social functioning (69·8 to 5·0, p = 0·03).ConclusionDue to COVID-19, patients (being) treated for breast cancer are less likely to contact physicians, and experience a deterioration in emotional functioning. Patients undergoing active treatment report a strong drop in social functioning. One in two patients reports (severe) loneliness. Online applications facilitating peer contact and e-mental health interventions could support mental health and social interaction times of total lockdown or social distancing.
Early identification of postpartum depression using demographic, clinical, and digital phenotyping
Authors: Hahn Lisa , Eickhoff Simon B. , Habel Ute , Stickeler Elmar , Schnakenberg Patricia , Goecke Tamme W. , Stickel Susanne , Franz Matthias , Dukart Juergen , Chechko Natalia 
Published: June 2020

AbstractBackgroundPostpartum depression (PPD) and adjustment disorder (AD) affect up to 25% of women after childbirth. However, there are no accurate screening tools for either disorder to identify at-risk mothers and enable them to benefit from early intervention.AimsTo evaluate combinations of anamnestic, clinical and remote assessments for an early and accurate identification of PPD and AD.MethodTwo cohorts of mothers giving birth were included in the study (N=308 and N=193). At baseline, participants underwent a detailed anamnestic and clinical interview. Remote assessments were collected over twelve weeks comprising mood and stress levels as well as depression and attachment scores. At twelve weeks postpartum, an experienced clinician assigned the participants to three distinct groups: women with PPD, women with AD, and healthy controls (HC). Combinations of these assessments were assessed for an early an accurate detection of PPD and AD in the first cohort and, after pre-registration, prospectively validated in the second cohort.ResultsCombinations of postnatal depression, attachment (for AD) and mood scores at week 3 achieved balanced accuracies of 93% and 79% for differentiation of PPD and AD from HC in the prospective validation cohort. Differentiation between AD and PPD, with a balanced accuracy of 73 % was possible at week 6 based on mood levels only.ConclusionsCombinations of in clinic and remote self-assessments allowed for early and accurate detection of PPD and AD as early as three weeks postpartum, enabling early intervention to the benefit of both mothers and children.
Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil
Authors: Jorge Daniel C. P. , Rodrigues Moreno S. , Silva Mateus S. , Cardim Luciana L. , da Silva Nívea B. , Silveira Ismael H. , Silva Vivian A. F. , Pereira Felipe A. C. , de Azevedo Arthur R. , Amad Alan A. S. , Pinho Suani T.R. , Andrade Roberto F. S. , Ramos Pablo I. P. , Oliveira Juliane F. 
Published: June 2020

AbstractCOVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or vaccines, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 707 published governmental interventions, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR (Susceptible, Exposed, Infected and Removed) model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. We analyze the effect of both the extent of enforced measures across Brazilian states and population movement on the changes in the TR and effective reproduction number. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions and represents a major challenge to the control of COVID-19 in low- and middle-income countries.
Predicting the Trajectory of Any COVID19 Epidemic From the Best Straight Line
Authors: Levitt Michael , Scaiewicz Andrea , Zonta Francesco 
Published: June 2020

ABSTRACTA pipeline involving data acquisition, curation, carefully chosen graphs and mathematical models, allows analysis of COVID-19 outbreaks at 3,546 locations world-wide (all countries plus smaller administrative divisions with data available). Comparison of locations with over 50 deaths shows all outbreaks have a common feature: H(t) defined as loge(X(t)/X(t-1)) decreases linearly on a log scale, where X(t) is the total number of Cases or Deaths on day, t (we use ln for loge). The downward slopes vary by about a factor of three with time constants (1/slope) of between 1 and 3 weeks; this suggests it may be possible to predict when an outbreak will end. Is it possible to go beyond this and perform early prediction of the outcome in terms of the eventual plateau number of total confirmed cases or deaths?We test this hypothesis by showing that the trajectory of cases or deaths in any outbreak can be converted into a straight line. Specifically Y(t) ≡ −ln(ln(N / X (t)), is a straight line for the correct plateau value N, which is determined by a new method, Best-Line Fitting (BLF). BLF involves a straight-line facilitation extrapolation needed for prediction; it is blindingly fast and amenable to optimization. We find that in some locations that entire trajectory can be predicted early, whereas others take longer to follow this simple functional form. Fortunately, BLF distinguishes predictions that are likely to be correct in that they show a stable plateau of total cases or death (N value). We apply BLF to locations that seem close to a stable predicted N value and then forecast the outcome at some locations that are still growing wildly. Our accompanying web-site will be updated frequently and provide all graphs and data described here.
Forecasting COVID-19 Dynamics and Endpoint in Bangladesh: A Data-driven Approach
Authors: Hridoy Al-Ekram Elahee , Naim Mohammad , Emon Nazim Uddin , Tipo Imrul Hasan , Alam Safayet , Al Mamun Abdullah , Islam Mohammad Safiqul 
Published: June 2020

AbstractOn December 31, 2019, the World Health Organization (WHO) was informed that atypical pneumonia-like cases have emerged in Wuhan City, Hubei province, China. WHO identified it as a novel coronavirus and declared a global pandemic on March 11th, 2020. At the time of writing this, the COVID-19 claimed more than 440 thousand lives worldwide and led to the global economy and social life into an abyss edge in the living memory. As of now, the confirmed cases in Bangladesh have surpassed 100 thousand and more than 1343 deaths putting startling concern on the policymakers and health professionals; thus, prediction models are necessary to forecast a possible number of cases in the future. To shed light on it, in this paper, we presented data-driven estimation methods, the Long Short-Term Memory (LSTM) networks, and Logistic Curve methods to predict the possible number of COVID-19 cases in Bangladesh for the upcoming months. The results using Logistic Curve suggests that Bangladesh has passed the inflection point on around 28-30 May 2020, a plausible end date to be on the 2nd of January 2021 and it is expected that the total number of infected people to be between 187 thousand to 193 thousand with the assumption that stringent policies are in place. The logistic curve also suggested that Bangladesh would reach peak COVID-19 cases at the end of August with more than 185 thousand total confirmed cases, and around 6000 thousand daily new cases may observe. Our findings recommend that the containment strategies should immediately implement to reduce transmission and epidemic rate of COVID-19 in upcoming days.HighlightsAccording to the Logistic curve fitting analysis, the inflection point of the COVID-19 pandemic has recently passed, which was approximately between May 28, 2020, to May 30, 2020.It is estimated that the total number of confirmed cases will be around 187-193 thousand at the end of the epidemic. We expect that the actual number will most likely to in between these two values, under the assumption that the current transmission is stable and improved stringent policies will be in place to contain the spread of COVID-19.The estimated total death toll will be around 3600-4000 at the end of the epidemic.The epidemic of COVID-19 in Bangladesh will be mostly under control by the 2nd of January 2021 if stringent measures are taken immediately.
Cost effectiveness of interventions for Post-Traumatic Stress Disorders following major incidents including terrorism and pandemics
Authors: Hogan Nicole , Knapp Martin , McDaid David , Davies Mark , Brewin Chris R. 
Published: June 2020

AbstractBackgroundPost-traumatic stress disorder (PTSD) is commonly experienced in the aftermath of major incidents such as terrorism and pandemics. Well-established principles of response include effective and scalable treatment for individuals affected by PTSD. In England, such responses have combined proactive outreach, screening, and evidence-based interventions (a “screen-and-treat” approach), but little is known about the cost-effectiveness of this approach.MethodsA decision modelling analysis was undertaken to estimate the costs per quality adjusted life year (QALY) gained from a screen-and-treat approach compared to treatment-as-usual. Model input variables were drawn from relevant empirical studies in the context of terrorism and the unit costs of health and social care in England. The model was run over a five-year time horizon for a hypothetical cohort of 1,000 exposed adults from the perspective of the National Health Service and Personal Social Services in England.ResultsThe incremental cost per QALY gained was £8,297. This would be considered cost-effective 95% of the time at a willingness-to-pay threshold of £20,000 per QALY gained, the threshold associated with NICE. Sensitivity analysis confirmed this result was robust.ConclusionsA screen-and-treat approach for identifying and treating PTSD in adults following major incidents appears cost-effective in England compared to treatment-as-usual through conventional primary care routes. This finding was in the context of terrorism but can be translatable into other major-incident related scenarios including the current COVID-19 pandemic in lieu of data on the impact of this pandemic.Competing interest statementThe authors have declared no competing interest.Funding statementNo additional funding was provided for this studyAuthor DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.Yes
Analyses and Forecast for COVID-19 epidemic in India
Authors: Banerjee Rudra , Bhattacharjee Srijit , Varadwaj Pritish Kumar 
Published: June 2020

AbstractCOVID-19 is a highly infectious disease that is causing havoc to the entire world due to the newly discovered coronavirus SARS-CoV-2. In this study, the dynamics of COVID-19 for India and a few selected states with different demographic structures have been analyzed using a SEIRD epidemiological model. A systematic estimation of the basic reproductive ratio R0 is made for India and for each of the selected states. The study has analysed and predicted the dynamics of the temporal progression of the disease in Indian and the selected eight states: Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh. For India, the most optimistic scenario with respect to duration of the epidemic shows, the peak of infection will appear before mid September with the estimated R0 = 1.917, from the SEIRD model. Further, we show, a Gaussian fit of the daily incidences also indicates the peak will appear around middle of August this year. Our analyses suggest, the earliest dates when the epidemic will start to decline in most states are between Jun-August. For India, the number of infected people at the time of peak will be around 1.6 million including asymptomatic people. If the community transmission is prohibited, then the epidemic will infect not more than 3.1 million people in India. We also compared India’s position in containing the disease with two countries with higher and lower number of infections than India and show the early imposition of lockdown has reduced the number of infected cases significantly.
Adjusting confirmed COVID-19 case counts for testing volume
Authors: Favero Nathan 
Published: June 2020

AbstractWhen assessing the relative prevalence of the novel coronavirus (COVID-19), observers often point to the number of COVID-19 cases that have been confirmed through viral testing. However, comparisons based on confirmed case counts alone can be misleading since a higher case count may reflect either a higher disease prevalence or a better rate of disease detection. Using weekly records of viral test results for each state in the US, I demonstrate how confirmed case counts can be adjusted based on the percentage of COVID-19 tests that come back positive. A regression analysis indicates that case counts track better with future hospitalizations and deaths when employing this simple adjustment for testing coverage. Viral testing results can be used as a leading indicator of COVID-19 prevalence, but data reporting standards should be improved, and care should be taken to account for testing coverage when comparing confirmed case counts.
Innate immune genes distinguish the immune microenvironment of early onset colorectal cancer
Authors: Gardner Ivy H. , Siddharthan Ragavan , Watson Katherine , Dewey Elizabeth , Ruhl Rebecca , Guan Xiangnan , Xia Zheng , Tsikitis Liana V. , Anand Sudarshan 
Published: June 2020

AbstractDespite a decrease in the incidence of colorectal cancer (CRC) over the last 40 years, the incidence of CRC in people under 50 years old is increasing around the globe. Early onset (≤50 years old) and late onset (≥65 years old) CRC appear to have differences in their clinicopathological and genetic features, but it is unclear if there are differences in the tumor microenvironment. We hypothesized that the immune microenvironment of early onset CRC is distinct from late onset CRC and promotes tumor progression. We used Nanostring immune profiling to analyze mRNA expression of immune genes in FFPE surgical specimens from patients with early (N=40) and late onset (N=39) CRC. We found three genes, SAA1, C7, and CFD, have increased expression in early onset colorectal cancer and distinct immune signatures based on the tumor location. After adjusting for clinicopathological features, increased expression of CFD and SAA1 were associated with worse progression free survival and increased expression of C7 was associated with worse overall survival. Our data demonstrate that the immune microenvironment in early onset CRC is unique, location dependent, and associated with worse outcomes.
Social media and smartphone app use predicts maintenance of physical activity during Covid-19 enforced isolation in psychiatric outpatients
Authors: Norbury Agnes , Liu Shelley H , Campaña-Montes Juan José , Romero-Medrano Lorena , Barrigon Maria L. , Smith Emma ,   MEmind Study Group, Artes Antonio , Baca-Garcia Enrique , Perez-Rodriguez M. Mercedes 
Published: June 2020

AbstractPublic health professionals have raised concerns that the social and physical distancing measures implemented in response to the Covid-19 pandemic may negatively impact health in other areas, via both decreased physical activity and increased social isolation. Here, we investigated whether increased engagement with digital social tools may help mitigate effects of enforced isolation on physical activity and mood, in a naturalistic study of at-risk individuals. Passively sensed smartphone app use and actigraphy data, collected from a sample of psychiatric outpatients both before and during imposition of strict lockdown conditions (N=163), were analysed using Gaussian graphical models: a form of network analysis which gives insight into the predictive relationships between measures across timepoints. Within-individuals, we found evidence of a positive predictive path between digital social engagement, general smartphone use, and physical activity – selectively under lockdown conditions. Further, we observed a positive relationship between social media use and total daily steps across individuals during (but not prior to) lockdown. We interpret these findings in terms of individuals using these digital tools to harness online social support structures, which may help guard against negative effects of in-person social deprivation and other pandemic-related stress. Monitoring of these measures is low burden and unintrusive and therefore, given appropriate consent, could potentially help identify individuals who are failing to engage this mechanism, providing a route to early intervention in this and other vulnerable populations.
Association study of DNAJC13, UCHL1, HTRA2, GIGYF2 and EIF4G1 with Parkinson’s disease
Authors: Saini Prabhjyot , Rudakou Uladzislau , Yu Eric , Ruskey Jennifer A. , Asayesh Farnaz , Laurent Sandra B. , Spiegelman Dan , Fahn Stanley , Waters Cheryl , Monchi Oury , Dauvilliers Yves , Dupré Nicolas , Greenbaum Lior , Hassin-Baer Sharon , Espay Alberto J. , Rouleau Guy A. , Alcalay Roy N. , Fon Edward A. , Postuma Ronald B. , Gan-Or Ziv 
Published: June 2020

AbstractRare mutations in genes originally discovered in multi-generational families have been associated with increased risk of Parkinson’s Disease (PD). The involvement of rare variants in DNAJC13, UCHL1, HTRA2, GIGYF2 and EIF4G1 loci have been poorly studied or produced conflicting results across cohorts. However, they are still being often referred to as “PD-genes” and used in different models. To further elucidate the role of these five genes in PD, we fully sequenced them using molecular inversion probes in 2,408 PD patients and 3,444 controls from 3 different cohorts. A total of 788 rare variants were identified across the five genes and three cohorts. Burden analyses and optimized sequence Kernel association tests revealed no significant association between any of the genes and PD after correction for multiple comparisons. Our results do not support an association of the five tested genes with PD. Combined with previous studies, it is unlikely that any of these genes plays an important role in PD. Their designation as “PARK” genes should be reconsidered.