bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of (Un)lockdown on COVID-19 transmission: A mathematical study of different phases in India
Authors: Kumar R. , Malik M. Z. , Shah S. R. 
Published: August 2020

SummaryThe novel coronavirus (SARS-CoV-2), identified in China at the end of the December 2019 is causing a potentially fatal respiratory syndrome (COVID-19), has meanwhile led to outbreak all over the globe. India has now become the third worst hit country globally with 16,38,870 confirmed cases and 35,747 confirmed deaths due to COVID-19 as of 31 July 2020. In this paper we have used mathematical modelling approach to study the effects of lockdowns and un-lockdowns on the pandemic evolution in India. This, study is based on SIDHARTHE model, which is an extension of classical SIR (Susceptible-Infected-Recovered) model. The SIDHARTHE model distinguish between the diagnosed and undiagnosed cases, which is very important because undiagnosed individuals are more likely to spread the virus than diagnosed individuals. We have stratified the lockdowns and un-lockdowns into seven phases and have computed the basic reproduction number R0for each phase. We have calibrated our model results with real data from 20 March 2020 to 31 July 2020. Our results demonstrate that different strategies implemented by GoI, have delayed the peak of pandemic by approximately 100 days. But due to underdiagnosis of the infected asymptomatic subpopulation, a sudden outbreak of cases can be observed in India.
Stromal Tumor Infiltrating Lymphocytes (sTILs) as a putative prognostic marker to identify a responsive subset of TNBC in an Indian Breast Cancer Cohort
Authors: Vaid Pooja M. , Puntambekar Anirudha K. , Banale Rituja A. , Reddy Ruhi R. , Unde Rohini R. , Namewar Namrata P. , Kelkar Devaki A. , Shashidhara LS , Koppiker Chaitanyanand B , Kulkarni Madhura 
Published: August 2020

AbstractObjectivesPrognostic significance of stromal tumor infiltrating lymphocytes (sTILs) is evaluated to identify a responsive subset of TNBC in an Indian cohort of breast cancer patients.MethodsA retrospective cohort of breast cancer patients from a single onco-surgeon breast cancer clinic treated with uniform treatment strategy across is evaluated for sTILs. FFPE tissue of primary tumor of invasive breast carcinoma are collected with ethical approvals. Tumor sections blinded for subtypes are stained with H&E and scored for sTILs by a pathologist following Immuno-Oncology TILs working group’s scoring guidelines.ResultsAnalysis of 144 primary breast tumors for sTILs scores re-enforces significantly higher infiltration in TNBC tumors than HER2+ and ER+ tumors. Higher sTILs scores co-relate with gradually incremental pathological response to therapy specifically in TNBC subset and with better disease-free survival outcomes. Within TNBC, older and post-menopausal patients harbor higher scores of sTILs.ConclusionDespite a small cohort of breast cancer patients, TNBC subtype reflected significantly higher scores of sTILs with better response to therapy and disease-free outcomes as compared to other breast cancer subtypes. A larger number of breast cancer patients from an Indian cohort will strengthen the findings to establish sTILs as a marker to identify a responsive subset of TNBC.Key pointsKey point 1This is a first attempt to understand the significance of stromal tumor-infiltrating lymphocytes in a breast cancer cohort from India, where higher recurrence and mortality rates are observed.Key point 2TNBC tumors show higher sTILs infiltration compared to non-TNBC patients. Higher sTILs scores within TNBC co-relates with better therapy response disease-free survival.Key point 3Higher sTILs scores in TNBC tumors in an Indian cohort showed a novel and unique association with old age and post-menopausal patients.
Large-scale transcriptome-wide profiling of microRNAs in human placenta and maternal plasma at early to mid gestation
Authors: Smith Melanie D. , Pillman Katherine , Jankovic-Karasoulos Tanja , McAninch Dale , Wan Qianhui , Bogias K. Justinian , McCullough Dylan , Bianco-Miotto Tina , Breen James , Roberts Claire T. 
Published: August 2020

AbstractBackgroundMicroRNAs (miRNAs) are increasingly seen as important regulators of placental development and opportunistic biomarker targets. Given the difficulty in obtaining samples from early gestation and subsequent paucity of the same, investigation of the role of miRNAs in early gestation human placenta has been limited. To address this, we generated miRNA profiles using 96 placentas from presumed normal pregnancies, across early gestation, in combination with matched profiles from maternal plasma. Placenta samples range from 6–23 weeks’ gestation, a time period that includes placenta from the early, relatively low but physiological (6–10 weeks’ gestation) oxygen environment, and later, physiologically normal oxygen environment (11–23 weeks’ gestation).ResultsWe identified 637 miRNAs with expression in 86 samples (after removing poor quality samples), showing a clear gestational age gradient from 6–23 weeks’ gestation. We identified 374 differentially expressed (DE) miRNAs between placentas from 6–10 weeks’ versus 11–23 weeks’ gestation. We see a clear gestational age group bias in miRNA clusters C19MC, C14MC, miR-17∼92 and paralogs, regions that also include many DE miRNAs. Proportional change in expression of placenta-specific miRNA clusters was reflected in maternal plasma.ConclusionThe presumed introduction of oxygenated maternal blood into the placenta (between ∼10–12 weeks’ gestation) changes the miRNA profile of the chorionic villus, particularly in placenta-specific miRNA clusters. Data presented here comprise a clinically important reference set for studying early placenta development and may underpin the generation of minimally invasive methods for monitoring placental health.
Joint associations of parental personality traits and socioeconomic position with trajectories of offspring depression: findings from up to 6925 families in a UK birth cohort
Authors: Cadman Tim , Kwong Alex S. F. , Moran Paul , O’Mahen Heather , Culpin Iryna , Lawlor Deborah A , Pearson Rebecca M. 
Published: August 2020

AbstractBackgroundParental personality may influence the course of offspring depression but this is unclear. It is also unknown whether the impact of parental personality on offspring depression is moderated by socioeconomic position (SEP). Our aims were to describe trajectories of depressive symptoms across adolescence for offspring of parents with and without maladaptive personality traits and to test for effect modification by SEP.MethodsA longitudinal study in the Avon Longitudinal Study of Parents and Children birth cohort (ALSPAC; ns = 3054 to 7046). Exposures were binary measures of maladaptive parental personality traits and the outcome was depressive symptoms ages 11 to 24 (SMFQ; range 0 – 26).ResultsOffspring of mothers with high maladaptive traits showed higher levels of depressive symptoms at all ages (SMFQ difference at age 10 = 0.66, CI 0.25 – 1.28, p = 0.02; age 22 = 1.00, CI 0.51 – 1.50, p < 0.001). There was weaker evidence of an association between paternal maladaptive personality traits and offspring depressive symptoms (SMFQ difference at age 10 = 0.21, CI –0.58 – 0.99, p = 0.60; age 22 = 0.02, CI –0.94, 0.90, p = 0.97). We found no consistent evidence of effect modification by SEP.ConclusionsOffspring of mothers with high levels of maladaptive personality traits show evidence of greater depressive symptoms throughout adolescence although the absolute increase in symptoms is small. Evidence for the effect of fathers’ personality was weaker. Socio-economic position and maladaptive personality traits appear to be independent risk factors.
Precision Colorectal Cancer Screening with Polygenic Risk Score
Authors: Tasa Tõnis , Puustusmaa Mikk , Tõnisson Neeme , Kolk Berit , Padrik Peeter 
Published: August 2020

AbstractColorectal cancer (CRC) is the second most common cancer in women and third most common cancer in men. Genome-wide association studies have identified numerous genetic variants (SNPs) independently associated with CRC. The effects of such SNPs can be combined into a single polygenic risk score (PRS). Stratification of individuals according to PRS could be introduced to primary and secondary prevention. Our aim was to combine risk stratification of a sex-specific PRS model with recommendations for individualized CRC screening.Previously published PRS models for predicting the risk of CRC were collected from the literature. These were validated on the UK Biobank (UKBB) consisting of a total of 458 696 quality-controlled genotypes with 1810 and 1348 prevalent male cases, and 2410 and 1810 incident male and female cases. The best performing sex-specific model was selected based on the AUC in prevalent data and independently validated in the incident dataset. Using Estonian CRC background information, we performed absolute risk simulations and examined the ability of PRS in risk stratifying individual screening recommendations. The best-performing model included 91 SNPs. The C-index of the best performing model in the dataset was 0.613 (SE = 0.007) and hazard ratio (HR) per unit of PRS was 1.53 (1.47 – 1.59) for males. Respective metrics for females were 0.617 (SE = 0.006) and 1.50 (1.44 – 1.58).PRS risk simulations showed that a genetically average 50-year-old female doubles her risk by age 58 (55 in males) and triples it by age 63 (59 in males). In addition, the best performing PRS model was able to identify individuals in one of seven groups proposed by Naber et al. for different coloscopy screening recommendation regimens.We have combined PRS-based recommendations for individual screening attendance. Our approach is easily adaptable to other nationalities by using population-specific background data of other genetically similar populations.
Disparities in COVID-19 Hospitalizations and Mortality among Black and Hispanic Patients: Cross-Sectional Analysis from the Greater Houston Metropolitan Area
Authors: Pan Alan P. , Khan Osman , Meeks Jennifer R. , Boom Marc L. , Masud Faisal N. , Andrieni Julia D. , Phillips Robert A. , Tiruneh Yordanos M. , Kash Bita A. , Vahidy Farhaan S. 
Published: August 2020

AbstractBackgroundDisparate racial and ethnic burdens of the Coronavirus Disease 2019 (COVID-19) pandemic may be attributable to higher susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or to factors such as differences in hospitalization and care provision.MethodsIn our cross-sectional analysis of lab-confirmed COVID-19 cases from a tertiary, eight-hospital healthcare system (Houston Methodist) across greater Houston, multivariable logistic regression models were fitted to evaluate the odds of hospitalization and mortality for non-Hispanic Blacks (NHBs) vs. non-Hispanic Whites (NHWs) and Hispanics vs. non-Hispanics.FindingsBetween March 3rd and July 18th, 2020, 70,496 individuals were tested for SARS-CoV-2; 12,084 (17·1%) tested positive, of whom 3,536 (29·3%) were hospitalized. Among positive cases, NHBs and Hispanics were significantly younger than NHWs and Hispanics, respectively (mean age NHBs vs. NHWs: 46.0 vs. 51.7 year and Hispanic vs. non-Hispanic: 44.0 vs. 48.7 years). Despite younger age, NHBs (vs. NHWs) had a higher prevalence of diabetes (25.2%), hypertension (47.7%), and chronic kidney disease (5.0%). Both minority groups resided in lower median income and higher population density areas. In fully adjusted models, NHBs and Hispanics had higher likelihoods of hospitalization, aOR (CI): 1·42 (1·24–1·63) and 1·61 (1·46–1·78), respectively. No differences were observed in intensive care unit (ICU) utilization or treatment parameters. Models adjusted for demographics, vital signs, laboratory parameters, hospital complications, and ICU admission demonstrated non-significantly lower likelihoods of in-hospital mortality among NHBs and Hispanics, aOR (CI): 0·65 (0·40–1·03) and 0·89 (0·59–1·31), respectively.InterpretationOur data did not demonstrate racial and ethnic differences in care provision and hospital outcomes. Higher susceptibility of racial and ethnic minorities to SARS-CoV-2 and subsequent hospitalization may be driven primarily by social determinants.
Healthcare workers’ knowledge, attitude and practices during the COVID-19 pandemic response in a tertiary care hospital of Nepal
Authors: K Limbu Dil , M Piryani Rano , K Sunny Avinash 
Published: August 2020

AbstractBackgroundTo control the spread of ongoing COVID-19 infection, extremely important measures need to be adopted. Healthcare worker’s adherence to prevention and control measures is affected by their knowledge, attitudes, and practices (KAP) towards COVID-19. In this study, we assessed the KAP among healthcare workers towards COVID-19 during the ongoing pandemic.MethodA self-developed piloted KAP questionnaire was used among the recruited healthcare workers working for the COVID-19 response in the Universal College of Medical Sciences Teaching Hospital (UCMSTH), in Bhairahawa, Nepal. The knowledge questionnaire consisted of questions regarding the clinical characteristics, prevention and management of COVID-19. Assessment on attitudes and practices towards COVID-19 included questions on behaviour and change in practices while working during this response. Knowledge scores were calculated and compared by demographic characteristics and their attitude and practices towards COVID-19. Data were analysed using bivariate statistics.ResultsA total of 103 healthcare workers participated in the study. The mean age of the participants was 28.24±6.11 years (range: 20-56); 60.2% were females; 61.2% were unmarried; 60.2% had medical degree and 39.8% were nursing staff. The mean knowledge score was 10.59±1.12 (range: 7-13) and it did not vary by demographic characteristics. Attitude was positive for 53.4% participants with a mean knowledge score of 10.35±1.19 and negative for 46.6% participants with a mean knowledge score of 10.88±0.98 (p = 0.02). Practice was good (≥3 score) for 81.5% participants with a mean knowledge score of 10.73±1.12 and practice was poor for 18.5% participants with a mean knowledge score of 10.46±1.13 (p = 0.24). The attitude of the participants improved with the increasing age of the participants (29.55±7.17, p = 0.02).ConclusionThere is comparably better knowledge regarding COVID-19 among healthcare workers along with appropriate practices, however attitude was less optimistic with better knowledge but more optimistic with higher age of the healthcare workers. Hence, protective measures for healthcare workers in order to improve their attitude is necessary during the pandemic response.
County and Demographic Differences in Drug Arrests and Controlled Substance Use in Maine
Authors: Hyde Trajan F. , Bekoe-Tabiri Amadea D. , Lopez Amalie K. Kropp , Devia Luis G. , Gutierrez Belsy D. , Lara Matthew C. , Soto Anthony R. , Kaufman Daniel E. , Simpson Kevin J. , Moran Matthew T. , Shah Dipam T. , Foster Michelle , Desrosiers Clare E. , Herbert John , Nichols Stephanie D. , McCall Kenneth L. , Piper Brian J. 
Published: August 2020

ABSTRACTIntroductionThe Diversion Alert Program (DAP) was established to curb the misuse of drugs and help identify people in need of substance use disorder (SUD) treatment. Law enforcement compiled arrest data into a database accessible by health care providers. The objectives of this investigation were to identify regional and demographic differences in drug use and misuse in Maine.MethodsAll arrests (N = 11,234) reported to the DAP from 2013 to 2018 were examined by county, arrestee demographics, and classified into families (opioids, stimulants, sedatives). The Automation of Reports and Consolidated Orders System (ARCOS) tracks the distribution of controlled pharmaceuticals (schedule I-V). Opioids were converted to oral morphine mg equivalents (MME). County and zip-code heat maps were constructed.ResultsThe counties with the most arrests per capita were Cumberland, Androscoggin, and Penobscot. Opioids were the most common drug class in arrests in all counties except Aroostook, where stimulants were most common. Medical distribution of opioids varied. With the exception of buprenorphine, which doubled, many prescription opioids like hydrocodone, fentanyl, and oxymorphone exhibited large (>50%) reductions. Methadone was the predominant opioid statewide (56.4% of the total MME) although there were sizeable differences (Presque Isle = 8.6%, Bangor = 78.9%) and this is likely impacted by use for SUD treatment. Amphetamine distribution increased by 67.9%. Conclusions: The DAP was useful to prevent information silos and enhance communication between law enforcement and health care providers. Maine’s DAP was a unique system to identify patients in need of additional treatment resources. The increase in prescription stimulants may warrant continued monitoring.
Pandemic Control in Econ-Epi Networks
Authors: Azzimonti Marina , Fogli Alessandra , Perri Fabrizio , Ponder Mark 
Published: August 2020

AbstractWe develop an ECON-EPI network model to evaluate policies designed to improve health and economic outcomes during a pandemic. Relative to the standard epidemiological SIR set-up, we explicitly model social contacts among individuals and allow for heterogeneity in their number and stability. In addition, we embed the network in a structural economic model describing how contacts generate economic activity. We calibrate it to the New York metro area during the 2020 COVID-19 crisis and show three main results. First, the ECON-EPI network implies patterns of infections that better match the data compared to the standard SIR. The switching during the early phase of the pandemic from unstable to stable contacts is crucial for this result. Second, the model suggests the design of smart policies that reduce infections and at the same time boost economic activity. Third, the model shows that reopening sectors characterized by numerous and unstable contacts (such as large events or schools) too early leads to fast growth of infections.
Seroprevalence of Coronavirus Disease 2019 (COVID-19) Among Health Care Workers from Three Pandemic Hospitals of Turkey
Authors: Alkurt Gizem , Murt Ahmet , Aydin Zeki , Tatli Ozge , Agaoglu Nihat Bugra , Irvem Arzu , Aydin Mehtap , Karaali Ridvan , Gunes Mustafa , Yesilyurt Batuhan , Turkez Hasan , Mardinoglu Adil , Doganay Mehmet , Basinoglu Filiz , Seyahi Nurhan , Dinler Doganay Gizem , Doganay Levent 
Published: August 2020

SUMMARYCOVID-19 is a global threat with an increasing number of infections. Research on IgG seroprevalence among health care workers (HCWs) is needed to re-evaluate health policies. This study was performed in three pandemic hospitals in Istanbul and Kocaeli. Different clusters of HCWs were screened for SARS-CoV-2 infection. Seropositivity rate among participants was evaluated by chemiluminescent microparticle immunoassay. We recruited 813 non-infected and 119 PCR-confirmed infected HCWs. Of the previously undiagnosed HCWs, 22 (2.7%) were seropositive. Seropositivity rates were highest for cleaning staff (6%), physicians (4%), nurses (2.2%) and radiology technicians (1%). Non-pandemic clinic (6.4%) and ICU (4.3%) had the highest prevalence. HCWs in “high risk group” had similar seropositivity rate with “no risk” group (2.9 vs 3.6p=0.7), indicating the efficient implementation of protection measures in the hospitals in Turkey. These findings might lead to the re-evaluation of infection control and transmission dynamics in hospitals.
Effective Reproduction Number and Dispersion under Contact Tracing and Lockdown on COVID-19 in Karnataka
Authors: Athreya Siva , Gadhiwala Nitya , Mishra Abhiti 
Published: August 2020

AbstractWe analyze the data provided in the Novel Coronavirus (COVID-19) media bulletins of the Govern-ment of Karnataka. We classify the patients of COVID-19 into clusters and study the Reproduction number and Dispersion for eight specific clusters. We find that it is uniformly less than one, indicating the benefits of contact tracing, lockdown and quarantine measures. However, the Dispersion is low indi-cating individual variation in secondary infections and the occurrence of Super-spreading events. Finally, we analyze the surge in infections after 27th June and find it unlikely that it was caused solely by the large Migration in May and June 2020.
Epidemic Analysis of COVID-19 in Egypt, Qatar and Saudi Arabia using the Generalized SEIR Model
Authors: Fahmy Ahmed E. , El-desouky Mohammed M. , Mohamed Ahmed S.A. 
Published: August 2020

AbstractBackgroundSince its emergence in late December 2019 and its declaration as a global pandemic by World Health Organization (WHO) on March 11, 2020, the novel coronavirus disease known as (COVID-19) has attracted global attention. The process of modeling and predicting the pandemic behavior became crucial as the different states needed accurate predictions to be able to adopt suitable policies to minimize the pressure on their health care systems. Researchers have employed modified variants of classical SIR/SEIR models to describe the dynamics of this pandemic. In this paper, after proven effective in numerous countries, a modified variant of SEIR is implemented to predict the behavior of COVID-19 in Egypt and other countries in the Middle East and North Africa region (MENA).MethodsWe built MATLAB simulations to fit the real data of COVID-19 Active, recovered and death Cases in Egypt, Qatar and Saudi Arabia to the modified SEIR model via Nelder-Mead algorithm to be able to estimate the future dynamics of the pandemic.FindingsWe estimate several characteristics of COVID-19 future dynamics in Egypt, Qatar and Saudi Arabia. We also estimate that the pandemic will resolve in the countries under investigation in February 2021, January 2021 and 28th August 2020 With total death cases of 9,742, 5,600, 185 and total cases of 187,600, 490,000, 120,000, respectively.
Reservoir population dynamics and pathogen epidemiology drive pathogen genetic diversity, spillover, and emergence
Authors: Remien Christopher H. , Nuismer Scott L. 
Published: August 2020

AbstractWhen several factors align, pathogens that normally infect wildlife can spill over into the human population. If pathogen transmission within the human population is self-sustaining, or rapidly evolves to be self sustaining, novel human pathogens can emerge. Although many factors influence the likelihood of spillover and emergence, the rate of contact between humans and wildlife is critical. Thus, for those pathogens inhabiting wildlife reservoirs with pronounced seasonal fluctuations in population density, it is broadly recognized that spillover risk also varies with season. What remains unknown, however, is the extent to which seasonal fluctuations in reservoir populations influence the evolutionary dynamics of pathogens in ways that affect the likelihood of emergence. Here, we use mathematical models and stochastic simulations to show that seasonal fluctuations in reservoir population densities lead to seasonal increases in genetic variation within pathogen populations and thus influence the waiting time for mutations capable of sustained human-to-human transmission. These seasonal increases in genetic variation also lead to elevated risk of emergence at predictable times of year.