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Institution

National Research University – Higher School of Economics

EducationMoscow, Russia
About: National Research University – Higher School of Economics is a education organization based out in Moscow, Russia. It is known for research contribution in the topics: Population & Computer science. The organization has 12873 authors who have published 23376 publications receiving 256396 citations.


Papers
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Journal ArticleDOI
Julio S. Solís Arce, Shana S. Warren1, Niccolo F. Meriggi, Alexandra Scacco, Nina McMurry, Maarten Voors2, Georgiy Syunyaev3, Georgiy Syunyaev4, Amyn A. Malik5, Samya Aboutajdine, Opeyemi Adeojo6, Deborah Anigo, Alex Armand7, Alex Armand8, Saher Asad9, Martin Atyera1, Britta Augsburg7, Manisha Awasthi, Gloria Eden Ayesiga1, Antonella Bancalari7, Antonella Bancalari10, Martina Björkman Nyqvist11, Ekaterina Borisova3, Ekaterina Borisova12, Constantin Manuel Bosancianu, Magarita Rosa Cabra García1, Ali Cheema13, Ali Cheema9, Elliott Collins1, Filippo Cuccaro1, Ahsan Zia Farooqi13, Tatheer Fatima, Mattia Fracchia8, Mery Len Galindo Soria1, Andrea Guariso14, Ali Hasanain9, Sofía Jaramillo1, Sellu Kallon2, Sellu Kallon15, Anthony Kamwesigye1, Arjun Kharel16, Sarah E. Kreps17, Madison Levine2, Rebecca Littman18, Mohammad Malik13, Gisele Manirabaruta1, Jean Léodomir Habarimana Mfura1, Fatoma Momoh1, Alberto Mucauque, Imamo Mussa, Jean Aime Nsabimana1, Isaac Obara, María Juliana Otálora1, Béchir Wendemi Ouédraogo1, Touba Bakary Pare1, Melina R. Platas19, Laura Polanco1, Javaeria A. Qureshi18, Mariam Raheem, Vasudha Ramakrishna5, Ismail Rendrá, Taimur Shah, Sarene Eyla Shaked1, Jacob N. Shapiro20, Jakob Svensson21, Ahsan Tariq13, Achille Mignondo Tchibozo1, Hamid Ali Tiwana13, Bhartendu Trivedi, Corey Vernot5, Pedro C. Vicente8, Laurin Weissinger22, Basit Zafar23, Baobao Zhang17, Dean Karlan1, Dean Karlan24, Michael Callen25, Matthieu Teachout, Macartan Humphreys4, Ahmed Mushfiq Mobarak5, Saad B. Omer5 
TL;DR: In this article, the authors analyzed COVID-19 vaccine acceptance across 15 survey samples covering 10 low and middle-income countries (LMICs) in Asia, Africa and South America, Russia (an upper-middle-income country) and the United States, including a total of 44,260 individuals.
Abstract: Widespread acceptance of COVID-19 vaccines is crucial for achieving sufficient immunization coverage to end the global pandemic, yet few studies have investigated COVID-19 vaccination attitudes in lower-income countries, where large-scale vaccination is just beginning. We analyze COVID-19 vaccine acceptance across 15 survey samples covering 10 low- and middle-income countries (LMICs) in Asia, Africa and South America, Russia (an upper-middle-income country) and the United States, including a total of 44,260 individuals. We find considerably higher willingness to take a COVID-19 vaccine in our LMIC samples (mean 80.3%; median 78%; range 30.1 percentage points) compared with the United States (mean 64.6%) and Russia (mean 30.4%). Vaccine acceptance in LMICs is primarily explained by an interest in personal protection against COVID-19, while concern about side effects is the most common reason for hesitancy. Health workers are the most trusted sources of guidance about COVID-19 vaccines. Evidence from this sample of LMICs suggests that prioritizing vaccine distribution to the Global South should yield high returns in advancing global immunization coverage. Vaccination campaigns should focus on translating the high levels of stated acceptance into actual uptake. Messages highlighting vaccine efficacy and safety, delivered by healthcare workers, could be effective for addressing any remaining hesitancy in the analyzed LMICs.

536 citations

Journal ArticleDOI
TL;DR: In this paper, the structural equivalence of the Zimbardo Time Perspective Inventory (ZTPI) across 26 samples from 24 countries (N = 12,200) was assessed.
Abstract: In this article, we assess the structural equivalence of the Zimbardo Time Perspective Inventory (ZTPI) across 26 samples from 24 countries (N = 12,200). The ZTPI is proven to be a valid and reliable index of individual differences in time perspective across five temporal categories: Past Negative, Past Positive, Present Fatalistic, Present Hedonistic, and Future. We obtained evidence for invariance of 36 items (out of 56) and also the five-factor structure of ZTPI across 23 countries. The short ZTPI scales are reliable for country-level analysis, whereas we recommend the use of the full scales for individual-level analysis. The short version of ZTPI will further promote integration of research in the time perspective domain in relation to many different psycho-social processes.

525 citations

Journal ArticleDOI
Haidong Wang1, Timothy M. Wolock1, Austin Carter1, Grant Nguyen1  +497 moreInstitutions (214)
TL;DR: This report provides national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015.

522 citations

Proceedings Article
07 Feb 2019
TL;DR: In this article, the authors proposed SWA-Gaussian (SWAG) approach for uncertainty representation and calibration in deep learning, where the first moment of stochastic gradient descent (SGD) is computed using a modified learning rate schedule.
Abstract: We propose SWA-Gaussian (SWAG), a simple, scalable, and general purpose approach for uncertainty representation and calibration in deep learning. Stochastic Weight Averaging (SWA), which computes the first moment of stochastic gradient descent (SGD) iterates with a modified learning rate schedule, has recently been shown to improve generalization in deep learning. With SWAG, we fit a Gaussian using the SWA solution as the first moment and a low rank plus diagonal covariance also derived from the SGD iterates, forming an approximate posterior distribution over neural network weights; we then sample from this Gaussian distribution to perform Bayesian model averaging. We empirically find that SWAG approximates the shape of the true posterior, in accordance with results describing the stationary distribution of SGD iterates. Moreover, we demonstrate that SWAG performs well on a wide variety of tasks, including out of sample detection, calibration, and transfer learning, in comparison to many popular alternatives including variational inference, MC dropout, KFAC Laplace, and temperature scaling.

493 citations

Journal ArticleDOI
Hmwe H Kyu1, Christine Pinho1, Joseph Wagner1, Jonathan C Brown1  +199 moreInstitutions (118)
TL;DR: Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies and give guidance to policy makers in countries where more attention is needed.
Abstract: Importance The literature focuses on mortality among children younger than 5 years. Comparable information on nonfatal health outcomes among these children and the fatal and nonfatal burden of diseases and injuries among older children and adolescents is scarce. Objective To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged Evidence Review Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14 244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35 620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIV infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR 2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates. Findings Of the 7.7 (95% uncertainty interval [UI], 7.4-8.1) million deaths among children and adolescents globally in 2013, 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections among younger children (905 059 deaths; 95% UI, 810 304-998 125), diarrheal diseases among older children (38 325 deaths; 95% UI, 30 365-47 678), and road injuries among adolescents (115 186 deaths; 95% UI, 105 185-124 870). Iron deficiency anemia was the leading cause of years lived with disability among children and adolescents, affecting 619 (95% UI, 618-621) million in 2013. Large between-country variations exist in mortality from leading causes among children and adolescents. Countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in most leading causes of death, whereas countries with the slowest declines had stagnant or increasing trends in the leading causes of death. In 2013, Nigeria had a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria. India had 33% of the world’s deaths from neonatal encephalopathy. Half of the world’s diarrheal deaths among children and adolescents occurred in just 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia. Conclusions and Relevance Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an impact. Proven interventions exist to prevent or treat the leading causes of unnecessary death and disability among children and adolescents. The findings presented here show that these are underused and give guidance to policy makers in countries where more attention is needed.

486 citations


Authors

Showing all 13307 results

NameH-indexPapersCitations
Rasmus Nielsen13555684898
Matthew Jones125116196909
Fedor Ratnikov123110467091
Kenneth J. Arrow113411111221
Wil M. P. van der Aalst10872542429
Peter Schmidt10563861822
Roel Aaij98107144234
John W. Berry9735152470
Federico Alessio96105442300
Denis Derkach96118445772
Marco Adinolfi9583140777
Michael Alexander9588138749
Alexey Boldyrev9443932000
Shalom H. Schwartz9422067609
Richard Blundell9348761730
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023129
2022586
20212,478
20203,025
20192,590
20182,259