bluuebunny/crossref_metadata_2025 huggingface dataset:
Transmission dynamics of COVID-19 in household and community settings in the United Kingdom
Authors: Bernal Jamie Lopez , Panagiotopoulos Nikolaos , Byers Chloe , Garcia Vilaplana Tatiana , Boddington Nicki , Zhang Xu-Sheng , Charlett Andre , Elgohari Suzanne , Coughlan Laura , Whillock Rosie , Logan Sophie , Bolt Hikaru , Sinnathamby Mary , Letley Louise , MacDonald Pauline , Vivancos Roberto , Edeghere Oboaghe , Anderson Charlotte , Paranthaman Karthik , Cottrell Simon , McMenamin Jim , Zambon Maria , Dabrera Gavin , Ramsay Mary , Saliba Vanessa
Published: August 2020

Background

Households appear to be the highest risk setting for transmission of COVID-19. Large household transmission studies were reported in the early stages of the pandemic in Asia with secondary attack rates ranging from 5–30% but few large scale household transmission studies have been conducted outside of Asia.

Methods

A prospective case ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. Household secondary attack rates and serial intervals were estimated. Individual and household basic reproduction numbers were also estimated. The incubation period was estimated using known point source exposures that resulted in secondary cases.

Results

A total of 233 households with two or more people were included with a total of 472 contacts. The overall household SAR was 37% (95% CI 31–43%) with a mean serial interval of 4.67 days, an R0of 1.85 and a household reproduction number of 2.33. We find lower secondary attack rates in larger households. SARs were highest when the primary case was a child. We estimate a mean incubation period of around 4.5 days.

Conclusions

High rates of household transmission of COVID-19 were found in the UK emphasising the need for preventative measures in this setting. Careful monitoring of schools reopening is needed to monitor transmission from children.
Machine learning based clinical decision support system for early COVID-19 mortality prediction
Authors: Karthikeyan Akshaya , Garg Akshit , Vinod P. K. , Priyakumar U. Deva
Published: August 2020

The coronavirus disease 2019 (COVID-19) is an acute respiratory disease that has been classified as a pandemic by World Health Organization (WHO). The sudden spike in the number of infections and high mortality rates have put immense pressure on the public medical systems. Hence, it’s crucial to identify the key factors of mortality that yield high accuracy and consistency to optimize patient treatment strategy. This study uses machine learning methods to identify a powerful combination of five features that help predict mortality with 96% accuracy: neutrophils, lymphocytes, lactate dehydrogenase (LDH), high-sensitivity C-reactive protein (hs-CRP) and age. Various machine learning algorithms have been compared to achieve a consistent high accuracy across the days that span the disease. Robust testing with three cases confirm the strong predictive performance of the proposed model. The model predicts with an accuracy of 90% as early as 16 days before the outcome. This study would help accelerate the decision making process in healthcare systems for focused medical treatments early and accurately.
Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S.
Authors: Ray Evan L , Wattanachit Nutcha , Niemi Jarad , Kanji Abdul Hannan , House Katie , Cramer Estee Y , Bracher Johannes , Zheng Andrew , Yamana Teresa K , Xiong Xinyue , Woody Spencer , Wang Yuanjia , Wang Lily , Walraven Robert L , Tomar Vishal , Sherratt Katharine , Sheldon Daniel , Reiner Robert C , Prakash B. Aditya , Osthus Dave , Li Michael Lingzhi , Lee Elizabeth C , Koyluoglu Ugur , Keskinocak Pinar , Gu Youyang , Gu Quanquan , George Glover E. , España Guido , Corsetti Sabrina , Chhatwal Jagpreet , Cavany Sean , Biegel Hannah , Ben-Nun Michal , Walker Jo , Slayton Rachel , Lopez Velma , Biggerstaff Matthew , Johansson Michael A , Reich Nicholas G
Published: August 2020

Background

The COVID-19 pandemic has driven demand for forecasts to guide policy and planning. Previous research has suggested that combining forecasts from multiple models into a single “ensemble” forecast can increase the robustness of forecasts. Here we evaluate the real-time application of an open, collaborative ensemble to forecast deaths attributable to COVID-19 in the U.S.

Methods

Beginning on April 13, 2020, we collected and combined one- to four-week ahead forecasts of cumulative deaths for U.S. jurisdictions in standardized, probabilistic formats to generate real-time, publicly available ensemble forecasts. We evaluated the point prediction accuracy and calibration of these forecasts compared to reported deaths.

Results

Analysis of 2,512 ensemble forecasts made April 27 to July 20 with outcomes observed in the weeks ending May 23 through July 25, 2020 revealed precise short-term forecasts, with accuracy deteriorating at longer prediction horizons of up to four weeks. At all prediction horizons, the prediction intervals were well calibrated with 92-96% of observations falling within the rounded 95% prediction intervals.

Conclusions

This analysis demonstrates that real-time, publicly available ensemble forecasts issued in April-July 2020 provided robust short-term predictions of reported COVID-19 deaths in the United States. With the ongoing need for forecasts of impacts and resource needs for the COVID-19 response, the results underscore the importance of combining multiple probabilistic models and assessing forecast skill at different prediction horizons. Careful development, assessment, and communication of ensemble forecasts can provide reliable insight to public health decision makers.
Long-term anabolic androgenic steroid use is associated with deviant brain aging
Authors: Bjørnebekk Astrid , Kaufmann Tobias , Hauger Lisa E. , Westlye Lars T.
Published: August 2020

Background

High-dose long-term use of anabolic-androgenic steroids (AAS) may bring a range of health consequences, including brain and cognitive abnormalities. We performed age prediction based on brain scans to test whether prolonged AAS use is associated with accentuated brain aging.

Methods

T1-weighted brain MRI data were obtained from male weightlifters with a history of prolonged (n = 133) or no (n = 105) AAS use. We trained machine learning models on combinations of regional brain volumes, cortical thickness and surface area in an independent training set of 1838 healthy males aged 18–92 years and predicted brain age for each participant in our study. We used linear models to compare the gap between chronological age and predicted brain age (the brain age gap, BAG) between the two groups, and, in a subsample with longitudinal data (mean interval 3.5 years), tested for group differences in the change rate of BAG. Moreover, we tested for associations between apparent brain aging and AAS use duration, administration pattern and dependence.

Results

AAS users had higher BAG compared to weightlifting controls with strongest effects for frontal and insular regions. Higher BAG was associated with current AAS use, dependency, and longer history of AAS use. Group differences in BAG could not be explained by substance use, general cognitive abilities or depression. Longitudinal data revealed no group difference in the rate of BAG change.

Conclusions

The findings suggest that long-term high dose AAS use may have adverse effects on brain aging, potentially linked to current and exaggerated use of AAS.
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

The 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

Objectives

Prognostic significance of stromal tumor infiltrating lymphocytes (sTILs) is evaluated to identify a responsive subset of TNBC in an Indian cohort of breast cancer patients.

Methods

A 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.

Results

Analysis 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.

Conclusion

Despite 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 points

Key point 1

This 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 2

TNBC 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 3

Higher 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

Background

MicroRNAs (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).

Results

We 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.

Conclusion

The 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

Background

Parental 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.

Methods

A 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).

Results

Offspring 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.

Conclusions

Offspring 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.
It's not TB but what could it be? Abnormalities on chest X-rays taken during the Kenya National Tuberculosis Prevalence Survey
Authors: Mungai Brenda Nyambura , Joekes Elizabeth , Masini Enos , Obasi Angela , Manduku Veronica , Mugi Beatrice , Onǵanǵo Jane , Kirathe Dickson , Kiplimo Richard , Sitienei Joseph , Oronje Rose , Morton Ben , Squire Stephen Bertel , MacPherson Peter
Published: August 2020

Background:
The prevalence of diseases other than tuberculosis (TB) detected during chest X-ray (CXR) screening is unknown in sub-Saharan Africa. This represents a missed opportunity for identification and treatment of potentially significant disease. Our aim was to quantify and characterise non-TB abnormalities identified by TB-focused CXR screening during the 2016 Kenya National TB prevalence survey.

Methods:
We reviewed a random sample of 1140 adult (≥15 years) CXRs classified as "abnormal, suggestive of TB" or "abnormal other" during field interpretation from the TB Prevalence Survey. Each image was read (blinded to field classification and study radiologist read) by two expert radiologists, with images classified into one of four major anatomical categories and primary radiological diagnosis. A third reader resolved discrepancies. Prevalence and 95% confidence intervals of abnormalities diagnosis were estimated.

Findings:

Cardiomegaly was the most common non-TB abnormality at 259/1123 (23∙1%, 95% CI 20∙6%-25∙6%), while cardiomegaly with features of cardiac failure occurred in 17/1123 (1∙5 %, 95% CI 0.9%-2∙4%). We also identified chronic pulmonary pathology including suspected chronic obstructive pulmonary disease in 3∙2% (95% CI 2∙3%- 4∙4%) and non-specific patterns in 4∙6% (95% CI 3∙5%- 6∙0%). Prevalence of active-TB and severe post-TB lung changes was 3∙6% (95% CI 2∙6%- 4∙8%) and 1∙4% (95% CI 0∙8%- 2∙3%) respectively.

Interpretation:
Based on radiological diagnosis, we identified a wide variety of non-TB diagnoses during population-based TB screening. TB prevalence surveys and active case finding activities using mass CXR offer an opportunity to integrate disease screening efforts.

Funding
National Institute for Health Research (IMPALA-grant reference 16/136/35).
Precision Colorectal Cancer Screening with Polygenic Risk Score
Authors: Tasa Tõnis , Puustusmaa Mikk , Tõnisson Neeme , Kolk Berit , Padrik Peeter
Published: August 2020

Colorectal 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

Background

Disparate 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.

Methods

In 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.

Findings

Between 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.

Interpretation

Our 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

Background

To 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.

Method

A 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.

Results

A 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).

Conclusion

There 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

Introduction

The 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.

Methods

All 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.

Results

The 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

We 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

COVID-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

We 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

Background

Since 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).

Methods

We 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.

Findings

We 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

When 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.
Serum neopterin levels in relation to mild and severe COVID-19
Authors: Robertson Josefina , Gostner Johanna M , Nilsson Staffan , Andersson Lars-Magnus , Fuchs Dietmar , Gisslen Magnus
Published: August 2020

Background

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, is rapidly spreading worldwide. There is limited information about prognostic markers that could help clinicians to identify COVID-19 patients with a poor prognosis. Serum levels of the immune activation marker neopterin has shown to be of prognostic value in patients with SARS. The aim of this study was to investigate whether serum neopterin is associated with the severity of COVID-19.

Methods

We included 34 patients with confirmed COVID-19 between March 3 and March 30, 2020. Fifteen patients had mild disease and did not require hospitalization, whereas 19 patients developed severe COVID-19 requiring intensive care. Concentrations of serum neopterin, tryptophan, and kynurenine were measured at and repeatedly after inclusion.

Results

We found a more than two-fold higher mean concentration of neopterin in severely ill patients (mean value 42.0 nmol/L (SD 18.2)) compared to patients with mild symptoms (16.9 nmol/L (SD 11.0)). All of the severe cases had elevated neopterin concentrations (>9.1 nmol/L) at the initial sampling with values ranging from 17.2 to 86.7 nmol/L. In comparison, 10 of 15 patients with mild disease had neopterin levels above 9.1 nmol/L, with concentrations in the range from 4.9 to 31.6 nmol/L. Neopterin levels gradually decreased during the course of COVID-19, but severe cases maintained elevated levels for a longer period. Moreover, lower levels of tryptophan and higher levels of kynurenine, indicating an increased tryptophan catabolism, were seen in the group with severe cases.

Conclusions

In conclusion, we found that serum neopterin levels are associated with the severity of COVID-19. Our findings suggest that neopterin could be used as a prognostic marker, but further studies are needed to elucidate how it can be used in clinical praxis.
COVID19 epidemic growth rates have declined since early March in U.S. regions with active hospitalized case surveillance
Authors: Bhatia Rajiv
Published: August 2020

Introduction

Optimal pandemic monitoring and management requires unbiased and regionally specific estimates of disease incidence and epidemic growth.

Methods

I estimated growth rates and doubling times across a 22-week period of the SARS-COV-2 pandemic using hospital admissions incidence data collected through the US CDC COVID-NET surveillance program which operates in 98 U.S. counties located in 13 states. I cross validated the growth measures using mortality incidence data for the same regions and time periods.

Results

Between March 1 and August 8, 2020, two distinct waves of epidemic activity occurred. During the first wave in the COVID-NET monitoring regions, the harmonic mean of the maximum weekly growth rate was 534% (Median: 575; Range: 250 to 2250) and this maximum occurred in the second or third week of March in different regions. The harmonic mean of the minimum doubling time occurred with maximum growth rate and was 0.35 weeks (Median 0.36 weeks; Range: 0.22 to 0.55 weeks). The harmonic mean of the maximum incidence rate during the first wave of the epidemic was 8.5 hospital admissions per 100,000 people per week (Median: 9.2, Range: 4 to 40.5) and the peak of epidemic infection transmission associated with this maximum occurred on or before March 27, 2020 in eight of the 13 regions. Dividing the 22-week observed period into four intervals, the harmonic mean of the weekly hospitalization incidence rate was highest during the second interval (4.6 hospitalizations per week per 100,000), then fell during the third and fourth intervals. Growth rates declined from 101 percent per week in the first interval to 2.5 percent per week in the last. Doubling time have lengthened from 3/5th of a week in the first interval to 12.5 weeks in the last. Period by period, the cumulative incidence has grown primarily in a linear mode. The mean cumulative incidence of hospitalizations on Aug 8th, 2020 in the COVID-NET regions is 96 hospitalizations per 100,000. Regions which experienced the highest maximum weekly incidence rates or greatest cumulative incidence rates in the first wave, generally, but not uniformly, observed the lower incidence rates in the second wave. Growth measures calculated based on mortality incidence data corroborate these findings.

Conclusions

Declining epidemic growth rates of SARS-COV-2 infection appeared in early March in the first observations of nationwide hospital admissions surveillance program in multiple U.S. regions. A sizable fraction of the U.S. population may have been infected in a cryptic February epidemic acceleration phase. To more accurately monitor epidemic trends and inform pandemic mitigation planning going forward, the US CDC needs measures of epidemic disease incidence that better reflect clinical disease and account for large variations in case ascertainment strategies over time.
The Effects of Coronavirus Victimization Distress and Coronavirus Racial Bias on Mental Health Among AIAN, Asian, Black, and Latinx Young Adults
Authors: Fisher Celia B. , Tao Xiangyu , Yip Tiffany
Published: August 2020

Rationale

U.S. Racial/ethnic minorities have been disproportionately impacted by the COVID-19 pandemic in rates of infection and morbidity. Pre-pandemic racial discrimination has been associated with depression and general anxiety. However, the effect of Coronavirus specific forms of discrimination on mental health have not been examined. This study assessed the effect of previously identified social determinants of mental health and COVID-19 specific victimization and racial bias beliefs on depression and anxiety among young adults of color in the U.S.

Methods

A national online survey of 399 AIAN, Asian, Black, and Latinx adults (18 – 25 years) included demographic variables, COVID-19 health risks, and standardized measures of depression, anxiety, Coronavirus related victimization distress and perceptions of Coronavirus-related racial bias across a range of contexts.

Results

Employment, financial and prescription insecurity, COVID-19 health risks, Coronavirus victimization distress and Coronavirus racial bias beliefs were positively correlated with depression and anxiety. Scores on the Coronavirus racial bias scale were significantly higher among Asian and Black respondents. Structural equation modeling controlling for race/ethnicity and demographic variables indicated perceived Coronavirus racial bias mediated the effect of Coronavirus victimization distress on both mental health indices.

Conclusion

Results suggest the COVID-19 pandemic has created new pathways to mental health disparities among young adults of color by reversing formerly protective factors such as employment, and by exacerbating structural and societal inequities linked to race. Findings highlight the necessity of creating mental health services tailored to the specific needs of racial/ethnic minorities during the current and future health crises.
CLINICAL COURSE, RISK FACTORS FOR TRANSFER TO ICU AND MORTALITY IN PATIENTS WITH COVID-19 AFFECTED BY ACUTE RESPIRATORY FAILURE REFERRED TO A RESPIRATORY INTERMEDIATATE CARE UNIT
Authors: Buonamico Enrico , Quaranta Vitaliano Nicola , Boniello Esterina , Dimitri Michela , Majorano Marco , Labate Luciana , Pierucci Paola , Capozza Elena , Carpagnano Giovanna Elisiana , Resta Onofrio
Published: August 2020

Introduction

There are no clear guidelines as yet for the selection of patients affected by COVID-19 who can be treated in intermediate RICU, neither shared criteria for their intubation and transfer in ICU.

In the present study we described the clinical course and risk factors for transfer to ICU and mortality of SARS-Cov-2 positive patients affected by acute respiratory failure, hospitalized in a Respiratory Intermediate Care Unit in the south of Italy.

Methods

In this retrospective, observational single centre study we evaluated 96 laboratory confirmed COVID-19 patients affected by acute respiratory failure (ARF). We compared demographic data, laboratory data and clinical outcomes between deceased and survived patients, aiming to identify risk factors for transfer to ICU and mortality, and possible gender-related differences.

Results

Of 96 patients, 51 (53.1%) survived and 45 (46.9 %) died. Among those who died, 23 (51.1%) deceased in RICU. Twenty-nine (30.2%) were transferred to ICU, of whom 22 (75.9%) died in ICU. Patients affected by COPD have a higher mortality compared to patients without this comorbidity (p = 0.002). Lower baseline P/F ratio (p = 0,014) and neurologic comorbidities (p = 0,008) emerged as risk factors for death.

Male were younger than female patients (66 vs 80 y.o.; p = 0.042). In female patients, lower peripheral blood lymphocyte count (p = 0.007) is a risk factor for death, characteristic gender-related in our sample.

Female sex was a protective parameter against transfer to ICU (p = 0,036) and P/F ratio wasn’t a significant predictor of transfer to ICU (p = 0,227).

Only higher baseline CRP (p = 0,034) has shown a predictive role for transfer to ICU in our sample. Patients deceased after a transfer to ICU had younger age (p = 0,000), lower median comorbidity number (p = 0,000), lower D-dimer (p = 0,029) and lower prevalence of female sex (p = 0,029).

Discussion

Mortality in our study was similar to that found in other studies involving patients in non-invasive ventilation. In our study older age and comorbidities play as predictors of death in COVID-19 patients. COPD, despite presenting low prevalence, is a risk factor for death, both in men and women. In female patients chronic ischemic heart disease and congestive heart failure are death predictors. High CRP and lymphopenia, linked to inflammatory status, are predictors of transfer to ICU. Patients transferred to ICU higher mortality than the others, and patients who die in ICU are mostly men, younger and have less comorbidities. Baseline P/F ratio is not a good predictor of transfer to ICU, while in our sample is a sensible predictor of death. More studies need to be performed on COVID-19 patients, in the urgency of COVID-19 pandemic persistence.
No effect of resistance exercise on antibody responses to influenza vaccination in older adults: a randomized control trial
Authors: Elzayat Mahmoud T. , Markofski Melissa M. , Simpson Richard J. , Laughlin Mitzi , LaVoy Emily C.
Published: August 2020

Older adults are at elevated risk for morbidity and mortality caused by influenza. Vaccination is the primary means of prophylaxis, but protection is often compromised in older adults. As acute eccentric resistance exercise mobilizes immune cells into muscle, it may enhance vaccination response. PURPOSE: Compare antibody responses to influenza vaccination in older adults who performed resistance exercise prior to vaccination to those who did not exercise. METHODS: 29 resistance training-naive older adults (20 women, 73.9 ± 5.3 years) were randomized to 1 of 3 groups: vaccination in the same arm that exercised (Ex-S), vaccination in the opposite arm that exercised (Ex-OP), and seated rest (No-Ex). Exercise was unilateral and consisted of 10 sets of 5 eccentric repetitions at 80% of the pre-determined concentric one repetition maximum. Lateral raises were alternated with bicep curls. No-Ex sat quietly for 25 min. Following exercise or rest, all subjects received the 2018 quadrivalent influenza vaccine (Seqirus Afluria) in the non-dominant deltoid. Antibody titers against the four influenza vaccine strains were determined by hemagglutinin inhibition assays at baseline, 6-, and 24-weeks post-vaccination. Group differences in antibody titers by time were assessed by restricted maximum likelihood mixed models. Fold-changes in antibody titers 6- and 24-weeks from baseline were compared between groups by Kruskal-Wallis tests. RESULTS: No significant group x time effects were found for any strain. Groups did not differ in fold-increase of antibody titers 6- and 24-weeks post-vaccination. Although seroconversion rates remained low, only one subject (Ex-S) reported flu-like symptoms 18 weeks post-vaccination. CONCLUSION: Acute arm eccentric exercise did not influence antibody titers to the influenza vaccine delivered post-exercise in older adults. More strenuous exercise may be required for exercise to act as an adjuvant. http://ClinicalTrials.gov Identifier: NCT03736759 U.S. NIH Grant/Contract: R03AG052778
Defining movement instabilities in yips golfers using motion capture and muscle synergies
Authors: Revankar Gajanan S. , Ogasawara Issei , Hattori Noriaki , Kajiyama Yuta , Shimoda Shingo , Garcia Alvaro Costa , Uno Yuki , Nakano Tomohito , Gon Yasufumi , Kawamura Sadahito , Nakata Ken , Mochizuki Hideki
Published: August 2020

‘Yips’ is an involuntary movement disorder seen in some professional golfers. The diagnostic challenge in yips is to distinguish symptoms of task-specific dystonia from psychological ‘choking’. We evaluated 15 professional golfers with mild symptomatic yips via anxiety tests, motion-capture and surface electromyography during a ‘putting’ task. Movement instabilities were analyzed via temporal statistical methodologies (one-dimensional statistical parametric mapping). In a subset of golfers, we found significant differences in angular velocities of the putter-club rotation and altered synergy neural coefficients during the downswing phase. Our results showed that golfers with mild yips require sensitive motion-capture evaluations wherein movement instabilities become evident. Particularly the downswing is affected, and the ensuing perturbations in phasic muscle activity share dystonic features that are consistently identified as abnormal muscle synergy patterns. Despite a strong subjective feeling of yips that golfers complain of, movement analysis can reliably exclude those with ‘choking’ from those with task-specific dystonias.