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The overlapping burden of the three leading causes of disability and death in sub-Saharan African children

Nature Communications 2022年第1期13卷 1-14页

作者： Reiner, Robert C. Welgan, Catherine A. Troeger, Christopher E. Baumann, Mathew M. Weiss, Daniel J. Deshpande, Aniruddha Blacker, Brigette F. Miller-Petrie, Molly K. Earl, Lucas Bhatt, Samir Abolhassani, Hassan Abosetugn, Akine Eshete Abu-Gharbieh, Eman Adekanmbi, Victor Adetokunboh, Olatunji O. Aghaali, Mohammad Aji, Budi Alahdab, Fares Al-Aly, Ziyad Alhassan, Robert Kaba Ali, Saqib Alizade, Hesam Aljunid, Syed Mohamed Almasi-Hashiani, Amir Al-Mekhlafi, Hesham M. Altirkawi, Khalid A. Alvis-Guzman, Nelson Amare, Azmeraw T. Amini, Saeed Amugsi, Dickson A. Ancuceanu, Robert Andrei, Catalina Liliana Ansari, Fereshteh Anvari, Davood Appiah, Seth Christopher Yaw Arabloo, Jalal Aremu, Olatunde Atout, Maha Moh’d Wahbi Ausloos, Marcel Ausloos, Floriane Ayanore, Martin Amogre Aynalem, Yared Asmare Azene, Zelalem Nigussie Badawi, Alaa Baig, Atif Amin Banach, Maciej Bedi, Neeraj Bhagavathula, Akshaya Srikanth Bhandari, Dinesh Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bijani, Ali Birhanu, Tesega Tesega Mengistu Bitew, Zebenay Workneh Boloor, Archith Brady, Oliver J. Butt, Zahid A. Car, Josip Carvalho, Felix Casey, Daniel C. Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Coelho, Camila H. Cook, Aubrey J. Damiani, Giovanni Daoud, Farah Gela, Jiregna Darega Darwish, Amira Hamed Daryani, Ahmad Das, Jai K. Davis Weaver, Nicole Deribe, Kebede Desalew, Assefa Dharmaratne, Samath Dhamminda Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Dorostkar, Fariba Dubljanin, Eleonora Duko, Bereket Dwyer-Lindgren, Laura Effiong, Andem El Sayed Zaki, Maysaa El Tantawi, Maha Enany, Shymaa Fattahi, Nazir Feigin, Valery L. Fernandes, Eduarda Ferrara, Pietro Fischer, Florian Foigt, Nataliya A. Folayan, Morenike Oluwatoyin Foroutan, Masoud Frostad, Joseph Jon Fukumoto, Takeshi Gaidhane, Abhay Motiramji Gebrekrstos, Hailemikael Gebrekidan G. K. Gebremeskel, Leake Gebreslassie, Assefa Ayalew Gething, Peter W. Gezae, Kebede Embaye Ghadiri, Keyghobad Ghashghaee, Ahmad Golechha, Mahaveer Gubar Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Malaria Atlas Project University of Oxford Oxford United Kingdom Imperial College London London United Kingdom Department of Laboratory Medicine Karolinska University Hospital Huddinge Sweden Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Debre Berhan University Debre Berhan Ethiopia Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Population Health Sciences King’s College London London United Kingdom Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Stellenbosch South Africa Department of Global Health Stellenbosch University Cape Town South Africa Department of Epidemiology and Biostatistics Qom University of Medical Sciences Qom Iran Faculty of Medicine and Public Health Jenderal Soedirman University Purwokerto Indonesia Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center Department of Veterans Affairs St Louis MO United States Institute of Health Research University of Health and Allied Sciences Ho Ghana Department of Information Systems College of Economics and Political Science Sultan Qaboos University Muscat Oman Infectious and Tropical Disease Research Center Hormozgan University of Medical Sciences Bandar Abbas Iran Department of Health Policy and Management Kuwait University Safat Kuwait International Centre for Casemix and Clinical Coding National University of Malaysia Bandar Tun Razak Malaysia Department of Epidemiology Arak University of Medical Sciences Arak Iran Medical Research Center

Despite substantial declines since 2000, lower respiratory infections (LRIs), diarrhoeal diseases, and malaria remain among the leading causes of nonfatal and fatal disease burden for children under 5 years of age (under 5), primarily in sub-Saharan Africa (SSA). The spatial burden of each of these diseases has been estimated subnationally across SSA, yet no prior analyses have examined the pattern of their combined burden. Here we synthesise subnational estimates of the burden of LRIs, diarrhoea, and malaria in children under-5 from 2000 to 2017 for 43 sub-Saharan countries. Some units faced a relatively equal burden from each of the three diseases, while others had one or two dominant sources of unit-level burden, with no consistent pattern geographically across the entire subcontinent. Using a subnational counterfactual analysis, we show that nearly 300 million DALYs could have been averted since 2000 by raising all units to their national average. Our findings are directly relevant for decision-makers in determining which and targeting where the most appropriate interventions are for increasing child survival. © 2022, The Author(s).

关键词： Biogeography Epidemiology Infectious diseases Malaria

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Burdens of type 2 diabetes and cardiovascular disease attributable to sugar-sweetened beverages in 184 countries (06 Jan, 10.1038/s41591-024-03345-4, 2025)

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NATURE MEDICINE 2025年第2期31卷 696-696页

作者： Lara-Castor, Laura O'Hearn, Meghan Cudhea, Frederick Miller, Victoria Shi, Peilin Zhang, Jianyi Sharib, Julia R. Cash, Sean B. Barquera, Simon Micha, Renata Mozaffarian, Dariush Food Is Medicine Institute Friedman School of Nutrition Science and Policy Tufts University Boston MA USA Institute of Health Metrics and Evaluation University of Washington Seattle WA USA Food Systems for the Future Institute Chicago IL USA Department of Medicine McMaster University Hamilton Ontario Canada Population Health Research Institute Hamilton Ontario Canada University of Thessaly Volos Greece Tufts University School of Medicine Boston MA USA Department of Medicine Tufts Medical Center Boston MA USA Center for Surgery and Public Health Brigham and Women’s Hospital Boston MA USA Friedman School of Nutrition Science and Policy Tufts University Boston MA USA Research Center on Nutrition and Health National Institute of Public Health Cuernavaca Mexico National Institute of Public Health (INSP) Cuernavaca Mexico Academy of Athens Athens Greece Acibadem University Istanbul Turkey Addis Ababa University Addis Ababa Ethiopia Aga Khan Foundation Geneva Switzerland All India Institute of Medical Sciences New Delhi India American University of Beirut Beirut Lebanon Amrita School of Dentistry Eranakulum India Andalas University Padang Indonesia Arab Center for Nutrition Manama Bahrain Ardabil University of Medical Sciences Ardabil Iran Bacha Khan University Charsadda Pakistan Biodiversity International Nairobi Kenya Brighton and Sussex Medical School Brighton UK Center for Studies of Sensory Impairment Aging and Metabolism (CeSSIAM) Guatemala City Guatemala Centre For Media Studies New Delhi India Centro de Atencion Nutricional Antimano (CANIA) Miami FL USA Centro de Estudios sobre Nutrición Infantil (CESNI) Buenos Aires Argentina Child Growth and Development Research Center Isfahan University of Medical Sciences Isfahan Iran College of Applied Sciences Department of Food Science and Applied Nutrition Addis Ababa Science and Technology University Addis Ababa Ethiopia Consultative Group on International Agricultural Research (CGIAR) M

The consumption of sugar-sweetened beverages (SSBs) is associated with type 2 diabetes (T2D) and cardiovascular diseases (CVD). However, an updated and comprehensive assessment of the global burden attributable to SSBs remains scarce. Here we estimated SSB-attributable T2D and CVD burdens across 184 countries in 1990 and 2020 globally, regionally and nationally, incorporating data from the Global Dietary Database, jointly stratified by age, sex, educational attainment and urbanicity. In 2020, 2.2 million (95% uncertainty interval 2.0–2.3) new T2D cases and 1.2 million (95% uncertainty interval 1.1–1.3) new CVD cases were attributable to SSBs worldwide, representing 9.8% and 3.1%, respectively, of all incident cases. Globally, proportional SSB-attributable burdens were higher among men versus women, younger versus older adults, higher- versus lower-educated adults, and adults in urban versus rural areas. By world region, the highest SSB-attributable percentage burdens were in Latin America and the Caribbean (T2D: 24.4%; CVD: 11.3%) and sub-Saharan Africa (T2D: 21.5%; CVD: 10.5%). From 1990 to 2020, the largest proportional increases in SSB-attributable incident T2D and CVD cases were in sub-Saharan Africa (+8.8% and +4.4%, respectively). Our study highlights the countries and subpopulations most affected by cardiometabolic disease associated with SSB consumption, assisting in shaping effective policies and interventions to reduce these burdens globally.

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Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment

arXiv

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arXiv 2017年

作者： Lu, Yan-Feng Jia, Li-Hao Qaio, Hong Li, Yi Research Center for Brain-inspired Intelligence Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai China School of Information Engineering Nanchang University Nanchang China

Biologically inspired model (BIM) for image recognition is a robust computational architecture, which has attracted widespread attention. BIM can be described as a four-layer structure based on the mechanisms of the visual cortex. Although the performance of BIM for image recognition is robust, it takes the randomly selected ways for the patch selection, which is sightless, and results in heavy computing burden. To address this issue, we propose a novel patch selection method with oriented Gaussian-Hermite moment (PSGHM), and we enhanced the BIM based on the proposed PSGHM, named as PBIM. In contrast to the conventional BIM which adopts the random method to select patches within the feature representation layers processed by multi-scale Gabor filter banks, the proposed PBIM takes the PSGHM way to extract a small number of representation features while offering promising distinctiveness. To show the effectiveness of the proposed PBIM, experimental studies on object categorization are conducted on the CalTech05, TU Darmstadt (TUD), and GRAZ01 databases. Experimental results demonstrate that the performance of PBIM is a significant improvement on that of the conventional BIM. Copyright © 2017, The Authors. All rights reserved.

关键词： Image enhancement

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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A fast and compact saliency score regression network based on fully convolutional network

arXiv

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arXiv 2017年

作者： Xi, Xuanyang Luo, Yongkang Li, Fengfu Wang, Peng Qiao, Hong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing100190 China LSEC Institute of Applied Mathematics AMSS Chinese Academy of Sciences Beijing100190 China

Visual saliency detection aims at identifying the most visually distinctive parts in an image, and serves as a pre-processing step for a variety of computer vision and image processing tasks. To this end, the saliency detection procedure must be as fast and compact as possible and optimally processes input images in a real time manner. It is an essential application requirement for the saliency detection task. However, contemporary detection methods often utilize some complicated procedures to pursue feeble improvements on the detection precession, which always take hundreds of milliseconds and make them not easy to be applied practically. In this paper, we tackle this problem by proposing a fast and compact saliency score regression network which employs fully convolutional network, a special deep convolutional neural network, to estimate the saliency of objects in images. It is an extremely simplified end-to-end deep neural network without any pre-processings and post-processings. When given an image, the network can directly predict a dense full-resolution saliency map (image-to-image prediction). It works like a compact pipeline which effectively simplifies the detection procedure. Our method is evaluated on six public datasets, and experimental results show that it can achieve comparable or better precision performance than the state-of-the-art methods while get a significant improvement in detection speed (35 FPS, processing in real time). Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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Numerical solution of time-dependent diffusion equations with nonlocal boundary conditions via a fast matrix approach

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Journal of the Egyptian Mathematical Society 2016年第1期24卷 86-91页

作者： Emran Tohidi Faezeh Toutounian Department of Applied Mathematics School of Mathematical Sciences Ferdowsi University of Mashhad Mashhad Iran The Center of Excellence on Modelling and Control Systems Ferdowsi University of Mashhad Mashhad Iran

This article contributes a matrix approach by using Taylor approximation to obtain the numerical solution of one-dimensional time-dependent parabolic partial differential equations (PDEs) subject to nonlocal boundary integral conditions. We first impose the initial and boundary conditions to the main problems and then reach to the associated integro-PDEs. By using operational matrices and also the completeness of the monomials basis, the obtained integro-PDEs will be reduced to the generalized Sylvester equations. For solving these algebraic systems, we apply a famous technique in Krylov subspace iterative methods. A numerical example is considered to show the efficiency of the proposed idea.

关键词： One-dimensional parabolic equation Nonlocal boundary conditions Taylor approximation Operational matrices Krylov subspace iterative methods Restarted GMRES 65M70 35R10 41A58

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Approaches and solutions for Martian spacesuit design 68

Approaches and solutions for Martian spacesuit design

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68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017

作者： Lousada, J. Kamaletdinova, G.R. Patel, D. Lakmal, Y. Oluwafemi, F.A. De La Torre, A. Heshani, U. Onevsky, M.P. Skvortsov, S.A. DLR [German Aerospace Center Germany Scientific laboratory of design and modelling of complex engineering systems Tambov State Technical University 106 Sovetskaya street Tambov392000 Russia 400 Kent Street SydneyNSW2000 Australia C/o European Space Policy Institute Schwarzenbergplatz 6 Vienna1030 Austria Km 17 Airport Road Abuja437 Nigeria C/o European Space Policy Institute Schwarzenbergplatz 6 Vienna1030 Austria C/o European Space Policy Institute Schwarzenbergplatz 6 Vienna1030 Austria Department of Information processes and control Tambov State Technical University 106 Sovetskaya street Tambov392000 Russia Department of Information processes and control Tambov State Technical University 106 Sovetskaya street Tambov392000 Russia

ISBN: (纸本)9781510855373

The Human exploration of Mars is often seen as the next step in human exploration of the Solar System. Decades of scientific explorations related to Mars recorded data on the environment of the planet, including geological aspects, atmospheric composition, life aspects, and helped to create a foundation defining main hazards and security risk assessment. Based on data from decades of observation and robotic missions to Mars, many agencies and organizations around the world started planning the first human mission to Mars. Extravehicular Activities (EVAs) will play a crucial role in any mission either long or short term as human participation is an essential step in the future. Short term mission EVAs will allow to collect additional data about the planet and its environment, to run external experiments, and to work on setting up a part of future habitats if needed. Long term mission EVAs will help to run maintenance activities supporting the whole operation of the habitat or station and continue all needed scientific activities. Previous studies were dedicated to the analysis of possible hazards for the habitat, station and spacesuit. The most relevant hazards for the spacesuit design were defined including structural failures, power, thermal control and life support systems off-nominal situations (ONS), communication problems, loss in data management and problems related with humans in the crew. Previous works related to the logical and physical level of model of knowledge database for automated control system of the "artificial lungs" equipment helped to define basic conditions of human in this mission, dependence on psychophysiological state and needed level of preliminary testing. Potential solutions for listed ONS will be discussed in this paper in greater details. This paper will examine past experience in spacesuit design and its restrictions including aspects of mobility and operability, the conditions they are created to work in and its applicability in Mar

关键词： Fracture mechanics

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Some derivative-free solvers for numerical solution of SODEs

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SeMA Journal 2015年第1期68卷 17-27页

作者： Soheili, Ali R. Soleymani, F. The Center of Excellence on Modelling and Control Systems Ferdowsi University of Mashhad Mashhad Iran Department of Applied Mathematics School of Mathematical Sciences Ferdowsi University of Mashhad Mashhad Iran

In this paper, some variants of stochastic solvers free from derivatives for Ito ^ stochastic ordinary differential equations (SODEs) are given. The derived strong variants are convergent and explicit. Then, some implicit solvers are also proposed. Numerical results are reported for confirming convergence properties and for comparing the behavior of these methods for pathwise approximation of SODEs. © 2015, Sociedad Española de Matemática Aplicada.

关键词： Heuristic derivation Numerical solution Stochastic differential equations Stochastic Runge–Kutta methods Strong sense

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Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18: a modelling study

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The Lancet HIV 2021年第6期8卷 e363-e375页

作者： Sartorius, Benn VanderHeide, John D. Yang, Mingyou Goosmann, Erik A. Hon, Julia Haeuser, Emily Cork, Michael A. Perkins, Samantha Jahagirdar, Deepa Schaeffer, Lauren E. Serfes, Audrey L. LeGrand, Kate E. Abbastabar, Hedayat Abebo, Zeleke Hailemariam Abosetugn, Akine Eshete Abu-Gharbieh, Eman Accrombessi, Manfred Mario Kokou Adebayo, Oladimeji M. Adegbosin, Adeyinka Emmanuel Adekanmbi, Victor Adetokunboh, Olatunji O. Adeyinka, Daniel Adedayo Ahinkorah, Bright Opoku Ahmadi, Keivan Ahmed, Muktar Beshir Akalu, Yonas Akinyemi, Oluwaseun Oladapo Akinyemi, Rufus Olusola Aklilu, Addis Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Noore Alamneh, Alehegn Aderaw Alanzi, Turki M. Alemu, Biresaw Wassihun Alhassan, Robert Kaba Ali, Tilahun Alipour, Vahid Amini, Saeed Ancuceanu, Robert Ansari, Fereshteh Anteneh, Zelalem Alamrew Anvari, Davood Anwer, Razique Appiah, Seth Christopher Yaw Arabloo, Jalal Asemahagn, Mulusew A. Asghari Jafarabadi, Mohammad Asmare, Wondwossen Niguse Atnafu, Desta Debalkie Atout, Maha Moh'd Wahbi Atreya, Alok Ausloos, Marcel Awedew, Atalel Fentahun Ayala Quintanilla, Beatriz Paulina Ayanore, Martin Amogre Aynalem, Yared Asmare Ayza, Muluken Altaye Azari, Samad Azene, Zelalem Nigussie Babar, Zaheer-Ud-Din Baig, Atif Amin Balakrishnan, Senthilkumar Banach, Maciej Bärnighausen, Till Winfried Basu, Sanjay Bayati, Mohsen Bedi, Neeraj Bekuma, Tariku Tesfaye Bezabhe, Woldesellassie M. Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bibi, Sadia Bikbov, Boris Birhan, Tsegaye Adane Bitew, Zebenay Workneh Bockarie, Moses John Boloor, Archith Brady, Oliver J. Bragazzi, Nicola Luigi Briko, Andrey Nikolaevich Briko, Nikolay Ivanovich Burugina Nagaraja, Sharath Butt, Zahid A. Cárdenas, Rosario Carvalho, Felix Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Cook, Aubrey J. Cormier, Natalie Maria Cowden, Richard G. Culquichicon, Carlos Dagnew, Baye Dahlawi, Saad M.A. D Centre for Tropical Medicine and Global Health Nuffield Department of Medicine University of Oxford Oxford United Kingdom Malaria Atlas Project University of Oxford Oxford United Kingdom The George Institute for Global Health University of Oxford Oxford United Kingdom Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Insights Program Bill and Melinda Gates Foundation Seattle WA United States Global Programs Medical Teams International Seattle WA United States Department of Pediatric Newborn Medicine Brigham and Women's Hospital Boston MA United States Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Pediatric Chronic Kidney Disease Research Center Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Arba Minch University Arba Minch Ethiopia Department of Medical Laboratory Sciences Arba Minch University Arba Minch Ethiopia College of Medicine and Health Science Arba Minch University Arba Minch Ethiopia Department of Nursing Arba Minch University Arba Minch Ethiopia Department of Biomedical Sciences Arba Minch University Arba Minch Ethiopia Department of Public Health Debre Berhan University Debre Brehan

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique,

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Corrigendum to “A pathway-based network analysis of hypertension-related genes” [Physica A 444 (2016) 928–939]

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Physica A: Statistical Mechanics and its Applications 2016年 447卷 569-570页

作者： Huan Wang Jing-Bo Hu Chuan-Yun Xu De-Hai Zhang Qian Yan Ming Xu Ke-Fei Cao Xu-Sheng Zhang School of Computer Science and Technology Baoji University of Arts and Sciences Baoji Shaanxi 721016 China Center for Nonlinear Complex Systems Department of Physics School of Physics Science and Technology Yunnan University Kunming Yunnan 650091 China School of Electronic and Electrical Engineering Baoji University of Arts and Sciences Baoji Shaanxi 721016 China School of Software Yunnan University Kunming Yunnan 650091 China School of Physics and Electronic Science Chuxiong Normal University Chuxiong Yunnan 675000 China School of Mathematical Sciences Kaili University Kaili Guizhou 556011 China Modelling and Economics Unit Centre for Infectious Disease Surveillance and Control Public Health England 61 Colindale Avenue London NW9 5EQ UK Medical Research Council Centre for Outbreak Analysis and Modelling Department of Infectious Disease Epidemiology School of Public Health Imperial College London Norfolk Place London W2 1PG UK

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