Search

Your search keyword '"Flaxman, Seth"' showing total 652 results
Start Over Author "Flaxman, Seth"
652 results on '"Flaxman, Seth"'

51. Orphanhood and Caregiver Loss Among Children Based on New Global Excess COVID-19 Death Estimates

Author

Hillis, Susan, Ntwali N'konzi, Joel-Pascal, Msemburi, William, Cluver, Lucie, Villaveces, Andres, Flaxman, Seth, and Unwin, H. Juliette T.

Subjects
Epidemics -- Social aspects -- United States, Child welfare -- Management, Orphans -- Statistics -- Health aspects, Pediatric research, Company business management, Health
Abstract

The availability of new excess mortality data enables us to update global minimum estimates of COVID-19 orphanhood and caregiver death among children (The Economist, 2021; Unwin et al., 2022; Wang, [...]

Published
2022

53. A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe

Author

Altman, George, Ahuja, Janvi, Monrad, Joshua Teperowski, Dhaliwal, Gurpreet, Rogers-Smith, Charlie, Leech, Gavin, Snodin, Benedict, Sandbrink, Jonas B., Finnveden, Lukas, Norman, Alexander John, Oehm, Sebastian B., Sandkühler, Julia Fabienne, Kulveit, Jan, Flaxman, Seth, Gal, Yarin, Mishra, Swapnil, Bhatt, Samir, Sharma, Mrinank, Mindermann, Sören, and Brauner, Jan Markus

Published
2022
Full Text
View/download PDF

55. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study

Author

Nyberg, Tommy, Ferguson, Neil M, Nash, Sophie G, Webster, Harriet H, Flaxman, Seth, Andrews, Nick, Hinsley, Wes, Lopez Bernal, Jamie, Kall, Meaghan, Bhatt, Samir, Blomquist, Paula, Zaidi, Asad, Volz, Erik, Abdul Aziz, Nurin, Harman, Katie, Funk, Sebastian, Abbott, Sam, Hope, Russell, Charlett, Andre, Chand, Meera, Ghani, Azra C, Seaman, Shaun R, Dabrera, Gavin, De Angelis, Daniela, Presanis, Anne M, Thelwall, Simon, Bernal, Jamie Lopez, and Aziz, Nurin Abdul

Published
2022
Full Text
View/download PDF

56. Bayesian Approaches to Distribution Regression

Author

Law, Ho Chung Leon, Sutherland, Danica J., Sejdinovic, Dino, and Flaxman, Seth

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

Distribution regression has recently attracted much interest as a generic solution to the problem of supervised learning where labels are available at the group level, rather than at the individual level. Current approaches, however, do not propagate the uncertainty in observations due to sampling variability in the groups. This effectively assumes that small and large groups are estimated equally well, and should have equal weight in the final regression. We account for this uncertainty with a Bayesian distribution regression formalism, improving the robustness and performance of the model when group sizes vary. We frame our models in a neural network style, allowing for simple MAP inference using backpropagation to learn the parameters, as well as MCMC-based inference which can fully propagate uncertainty. We demonstrate our approach on illustrative toy datasets, as well as on a challenging problem of predicting age from images.

Published
2017

57. Detecting causal associations in large nonlinear time series datasets

Author

Runge, Jakob, Nowack, Peer, Kretschmer, Marlene, Flaxman, Seth, and Sejdinovic, Dino

Subjects
Statistics - Methodology, Physics - Atmospheric and Oceanic Physics, Statistics - Applications
Abstract

Identifying causal relationships from observational time series data is a key problem in disciplines such as climate science or neuroscience, where experiments are often not possible. Data-driven causal inference is challenging since datasets are often high-dimensional and nonlinear with limited sample sizes. Here we introduce a novel method that flexibly combines linear or nonlinear conditional independence tests with a causal discovery algorithm that allows to reconstruct causal networks from large-scale time series datasets. We validate the method on a well-established climatic teleconnection connecting the tropical Pacific with extra-tropical temperatures and using large-scale synthetic datasets mimicking the typical properties of real data. The experiments demonstrate that our method outperforms alternative techniques in detection power from small to large-scale datasets and opens up entirely new possibilities to discover causal networks from time series across a range of research fields., Comment: 46 pages, 19 figures

Published
2017
Full Text
View/download PDF

58. Improved prediction accuracy for disease risk mapping using Gaussian Process stacked generalisation

Author

Bhatt, Samir, Cameron, Ewan, Flaxman, Seth R, Weiss, Daniel J, Smith, David L, and Gething, Peter W

Subjects
Statistics - Applications, Statistics - Machine Learning
Abstract

Maps of infectious disease---charting spatial variations in the force of infection, degree of endemicity, and the burden on human health---provide an essential evidence base to support planning towards global health targets. Contemporary disease mapping efforts have embraced statistical modelling approaches to properly acknowledge uncertainties in both the available measurements and their spatial interpolation. The most common such approach is that of Gaussian process regression, a mathematical framework comprised of two components: a mean function harnessing the predictive power of multiple independent variables, and a covariance function yielding spatio-temporal shrinkage against residual variation from the mean. Though many techniques have been developed to improve the flexibility and fitting of the covariance function, models for the mean function have typically been restricted to simple linear terms. For infectious diseases, known to be driven by complex interactions between environmental and socio-economic factors, improved modelling of the mean function can greatly boost predictive power. Here we present an ensemble approach based on stacked generalisation that allows for multiple, non-linear algorithmic mean functions to be jointly embedded within the Gaussian process framework. We apply this method to mapping Plasmodium falciparum prevalence data in Sub-Saharan Africa and show that the generalised ensemble approach markedly out-performs any individual method., Comment: Under Submission

Published
2016

59. Is Gun Violence Contagious?

Author

Loeffler, Charles and Flaxman, Seth

Subjects
Statistics - Applications
Abstract

Existing theories of gun violence predict stable spatial concentrations and contagious diffusion of gun violence into surrounding areas. Recent empirical studies have reported confirmatory evidence of such spatiotemporal diffusion of gun violence. However, existing tests cannot readily distinguish spatiotemporal clustering from spatiotemporal diffusion. This leaves as an open question whether gun violence actually is contagious or merely clusters in space and time. Compounding this problem, gun violence is subject to considerable measurement error with many nonfatal shootings going unreported to police. Using point process data from an acoustical gunshot locator system and a combination of Bayesian spatiotemporal point process modeling and space/time interaction tests, this paper demonstrates that contemporary urban gun violence does diffuse, but only slightly, suggesting that a disease model for infectious spread of gun violence is a poor fit for the geographically stable and temporally stochastic process observed.

Published
2016

60. Understanding the 2016 US Presidential Election using ecological inference and distribution regression with census microdata

Author

Flaxman, Seth, Sutherland, Danica J., Wang, Yu-Xiang, and Teh, Yee Whye

Subjects
Statistics - Applications, Statistics - Machine Learning
Abstract

We combine fine-grained spatially referenced census data with the vote outcomes from the 2016 US presidential election. Using this dataset, we perform ecological inference using distribution regression (Flaxman et al, KDD 2015) with a multinomial-logit regression so as to model the vote outcome Trump, Clinton, Other / Didn't vote as a function of demographic and socioeconomic features. Ecological inference allows us to estimate "exit poll" style results like what was Trump's support among white women, but for entirely novel categories. We also perform exploratory data analysis to understand which census variables are predictive of voting for Trump, voting for Clinton, or not voting for either. All of our methods are implemented in Python and R, and are available online for replication.

Published
2016

61. Orphanhood and caregiver death among children in the United States due to all-cause mortality 2000-2021: A Modeling Study

Author

Villaveces, Andrés, primary, Chen, Yu, additional, Tucker, Sydney, additional, Blenkinsop, Alexandra, additional, Cluver, Lucie, additional, Sherr, Lorraine, additional, Losby, Jan L., additional, Graves, Linden, additional, Noonan, Rita, additional, Annor, Francis, additional, Kojey-Merle, Victor, additional, Wang, Douhan, additional, Massetti, Greta, additional, Rawlins, Laura, additional, Nelson, Charles A., additional, Unwin, H Juliette T, additional, Flaxman, Seth, additional, Hillis, Susan, additional, and Ratmann, Oliver, additional

Published
2024
Full Text
View/download PDF

63. Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England

Author

Mishra, Swapnil, Mindermann, Sören, Sharma, Mrinank, Whittaker, Charles, Mellan, Thomas A, Wilton, Thomas, Klapsa, Dimitra, Mate, Ryan, Fritzsche, Martin, Zambon, Maria, Ahuja, Janvi, Howes, Adam, Miscouridou, Xenia, Nason, Guy P, Ratmann, Oliver, Semenova, Elizaveta, Leech, Gavin, Sandkühler, Julia Fabienne, Rogers-Smith, Charlie, Vollmer, Michaela, Unwin, H Juliette T, Gal, Yarin, Chand, Meera, Gandy, Axel, Martin, Javier, Volz, Erik, Ferguson, Neil M, Bhatt, Samir, Brauner, Jan M, and Flaxman, Seth

Published
2021
Full Text
View/download PDF

64. Poisson intensity estimation with reproducing kernels

Author

Flaxman, Seth, Teh, Yee Whye, and Sejdinovic, Dino

Subjects
Statistics - Machine Learning
Abstract

Despite the fundamental nature of the inhomogeneous Poisson process in the theory and application of stochastic processes, and its attractive generalizations (e.g. Cox process), few tractable nonparametric modeling approaches of intensity functions exist, especially when observed points lie in a high-dimensional space. In this paper we develop a new, computationally tractable Reproducing Kernel Hilbert Space (RKHS) formulation for the inhomogeneous Poisson process. We model the square root of the intensity as an RKHS function. Whereas RKHS models used in supervised learning rely on the so-called representer theorem, the form of the inhomogeneous Poisson process likelihood means that the representer theorem does not apply. However, we prove that the representer theorem does hold in an appropriately transformed RKHS, guaranteeing that the optimization of the penalized likelihood can be cast as a tractable finite-dimensional problem. The resulting approach is simple to implement, and readily scales to high dimensions and large-scale datasets., Comment: AISTATS 2017

Published
2016

65. European Union regulations on algorithmic decision-making and a 'right to explanation'

Author

Goodman, Bryce and Flaxman, Seth

Subjects
Statistics - Machine Learning, Computer Science - Computers and Society, Computer Science - Learning
Abstract

We summarize the potential impact that the European Union's new General Data Protection Regulation will have on the routine use of machine learning algorithms. Slated to take effect as law across the EU in 2018, it will restrict automated individual decision-making (that is, algorithms that make decisions based on user-level predictors) which "significantly affect" users. The law will also effectively create a "right to explanation," whereby a user can ask for an explanation of an algorithmic decision that was made about them. We argue that while this law will pose large challenges for industry, it highlights opportunities for computer scientists to take the lead in designing algorithms and evaluation frameworks which avoid discrimination and enable explanation., Comment: presented at 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016), New York, NY

Published
2016
Full Text
View/download PDF

66. Collaborative Filtering with Side Information: a Gaussian Process Perspective

Author

Kim, Hyunjik, Lu, Xiaoyu, Flaxman, Seth, and Teh, Yee Whye

Subjects
Statistics - Machine Learning, Computer Science - Information Retrieval, Computer Science - Learning
Abstract

We tackle the problem of collaborative filtering (CF) with side information, through the lens of Gaussian Process (GP) regression. Driven by the idea of using the kernel to explicitly model user-item similarities, we formulate the GP in a way that allows the incorporation of low-rank matrix factorisation, arriving at our model, the Tucker Gaussian Process (TGP). Consequently, TGP generalises classical Bayesian matrix factorisation models, and goes beyond them to give a natural and elegant method for incorporating side information, giving enhanced predictive performance for CF problems. Moreover we show that it is a novel model for regression, especially well-suited to grid-structured data and problems where the dependence on covariates is close to being separable.

Published
2016

67. Bayesian Learning of Kernel Embeddings

Author

Flaxman, Seth, Sejdinovic, Dino, Cunningham, John P., and Filippi, Sarah

Subjects
Statistics - Machine Learning
Abstract

Kernel methods are one of the mainstays of machine learning, but the problem of kernel learning remains challenging, with only a few heuristics and very little theory. This is of particular importance in methods based on estimation of kernel mean embeddings of probability measures. For characteristic kernels, which include most commonly used ones, the kernel mean embedding uniquely determines its probability measure, so it can be used to design a powerful statistical testing framework, which includes nonparametric two-sample and independence tests. In practice, however, the performance of these tests can be very sensitive to the choice of kernel and its lengthscale parameters. To address this central issue, we propose a new probabilistic model for kernel mean embeddings, the Bayesian Kernel Embedding model, combining a Gaussian process prior over the Reproducing Kernel Hilbert Space containing the mean embedding with a conjugate likelihood function, thus yielding a closed form posterior over the mean embedding. The posterior mean of our model is closely related to recently proposed shrinkage estimators for kernel mean embeddings, while the posterior uncertainty is a new, interesting feature with various possible applications. Critically for the purposes of kernel learning, our model gives a simple, closed form marginal pseudolikelihood of the observed data given the kernel hyperparameters. This marginal pseudolikelihood can either be optimized to inform the hyperparameter choice or fully Bayesian inference can be used., Comment: Conference paper appearing in UAI 2016, including Appendix

Published
2016

69. Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces

Author

Herlands, William, Wilson, Andrew, Nickisch, Hannes, Flaxman, Seth, Neill, Daniel, van Panhuis, Wilbert, and Xing, Eric

Subjects
Statistics - Machine Learning
Abstract

We present a scalable Gaussian process model for identifying and characterizing smooth multidimensional changepoints, and automatically learning changes in expressive covariance structure. We use Random Kitchen Sink features to flexibly define a change surface in combination with expressive spectral mixture kernels to capture the complex statistical structure. Finally, through the use of novel methods for additive non-separable kernels, we can scale the model to large datasets. We demonstrate the model on numerical and real world data, including a large spatio-temporal disease dataset where we identify previously unknown heterogeneous changes in space and time., Comment: 18 pages, 8 figures

Published
2015

73. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study

Author

Steinmetz, Jaimie D, Bourne, Rupert R A, Briant, Paul Svitil, Flaxman, Seth R, Taylor, Hugh R B, Jonas, Jost B, Abdoli, Amir Aberhe, Abrha, Woldu Aberhe, Abualhasan, Ahmed, Abu-Gharbieh, Eman Girum, Adal, Tadele Girum, Afshin, Ashkan, Ahmadieh, Hamid, Alemayehu, Wondu, Alemzadeh, Sayyed Amirpooya Samir, Alfaar, Ahmed Samir, Alipour, Vahid, Androudi, Sofia, Arabloo, Jalal, Arditi, Aries Berhe, Aregawi, Brhane Berhe, Arrigo, Alessandro, Ashbaugh, Charlie, Ashrafi, Elham Debalkie, Atnafu, Desta Debalkie, Bagli, Eleni Amin, Baig, Atif Amin Winfried, Bärnighausen, Till Winfried, Battaglia Parodi, Maurizio, Beheshti, Mahya Srikanth, Bhagavathula, Akshaya Srikanth, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhattacharyya, Krittika, Bijani, Ali, Bikbov, Mukharram, Bottone, Michele, Braithwaite, Tasanee M, Bron, Alain M, Burugina Nagaraja, Sharath A, Butt, Zahid A, Caetano dos Santos, Florentino Luciano L, Carneiro, Vera L James, Casson, Robert James, Cheng, Ching-Yu Jasmine, Choi, Jee-Young Jasmine, Chu, Dinh-Toi, Cicinelli, Maria Vittoria M, Coelho, João M G, Congdon, Nathan G A, Couto, Rosa A A, Cromwell, Elizabeth A M, Dahlawi, Saad M, Dai, Xiaochen, Dana, Reza, Dandona, Lalit, Dandona, Rakhi A, Del Monte, Monte A, Derbew Molla, Meseret, Dervenis, Nikolaos Alemayehu, Desta, Abebaw Alemayehu P, Deva, Jenny P, Diaz, Daniel, Djalalinia, Shirin E, Ehrlich, Joshua R, Elayedath, Rajesh Rashad, Elhabashy, Hala Rashad B, Ellwein, Leon B, Emamian, Mohammad Hassan, Eskandarieh, Sharareh, Farzadfar, Farshad G, Fernandes, Arthur G, Fischer, Florian S, Friedman, David S M, Furtado, João M, Gaidhane, Shilpa, Gazzard, Gus, Gebremichael, Berhe, George, Ronnie, Ghashghaee, Ahmad, Gilani, Syed Amir, Golechha, Mahaveer, Hamidi, Samer Randall, Hammond, Billy Randall R, Hartnett, Mary Elizabeth R Kusuma, Hartono, Risky Kusuma, Hashi, Abdiwahab I, Hay, Simon I, Hayat, Khezar, Heidari, Golnaz, Ho, Hung Chak, Holla, Ramesh, Househ, Mowafa J, Huang, John J Emmanuel, Ibitoye, Segun Emmanuel M, Ilic, Irena M D, Ilic, Milena D D, Ingram, April D Naghibi, Irvani, Seyed Sina Naghibi, Islam, Sheikh Mohammed Shariful, Itumalla, Ramaiah, Jayaram, Shubha Prakash, Jha, Ravi Prakash, Kahloun, Rim, Kalhor, Rohollah, Kandel, Himal, Kasa, Ayele Semachew, Kavetskyy, Taras A, Kayode, Gbenga A H, Kempen, John H, Khairallah, Moncef, Khalilov, Rovshan Ahmad, Khan, Ejaz Ahmad C, Khanna, Rohit C, Khatib, Mahalaqua Nazli Ahmed, Khoja, Tawfik Ahmed E, Kim, Judy E, Kim, Yun Jin, Kim, Gyu Ri, Kisa, Sezer, Kisa, Adnan, Kosen, Soewarta, Koyanagi, Ai, Kucuk Bicer, Burcu, Kulkarni, Vaman P, Kurmi, Om P, Landires, Iván Charles, Lansingh, Van Charles L, Leasher, Janet L E, LeGrand, Kate E, Leveziel, Nicolas, Limburg, Hans, Liu, Xuefeng, Madhava Kunjathur, Shilpashree, Maleki, Shokofeh, Manafi, Navid, Mansouri, Kaweh, McAlinden, Colm Gebremichael, Meles, Gebrekiros Gebremichael M, Mersha, Abera M, Michalek, Irmina Maria R, Miller, Ted R, Misra, Sanjeev, Mohammad, Yousef, Mohammadi, Seyed Farzad Abdu, Mohammed, Jemal Abdu H, Mokdad, Ali H, Moni, Mohammad Ali Al, Montasir, Ahmed Al R, Morse, Alan R Fentaw, Mulaw, Getahun Fentaw C, Naderi, Mehdi, Naderifar, Homa S, Naidoo, Kovin S, Naimzada, Mukhammad David, Nangia, Vinay, Narasimha Swamy, Sreenivas Muhammad, Naveed, Dr Muhammad, Negash, Hadush Lan, Nguyen, Huong Lan, Nunez-Samudio, Virginia Akpojene, Ogbo, Felix Akpojene, Ogundimu, Kolawole T, Olagunju, Andrew T E, Onwujekwe, Obinna E, Otstavnov, Nikita O, Owolabi, Mayowa O, Pakshir, Keyvan, Panda-Jonas, Songhomitra, Parekh, Utsav, Park, Eun-Cheol, Pasovic, Maja, Pawar, Shrikant, Pesudovs, Konrad, Peto, Tunde Quang, Pham, Hai Quang, Pinheiro, Marina, Podder, Vivek, Rahimi-Movaghar, Vafa, Rahman, Mohammad Hifz Ur Y, Ramulu, Pradeep Y, Rathi, Priya, Rawaf, Salman Laith, Rawaf, David Laith, Rawal, Lal, Reinig, Nickolas M, Renzaho, Andre M, Rezapour, Aziz L, Robin, Alan L, Rossetti, Luca, Sabour, Siamak, Safi, Sare, Sahebkar, Amirhossein, Sahraian, Mohammad Ali M, Samy, Abdallah M, Sathian, Brijesh, Saya, Ganesh Kumar, Saylan, Mete A, Shaheen, Amira A Ali, Shaikh, Masood Ali T, Shen, Tueng T, Shibuya, Kenji Shibabaw, Shiferaw, Wondimeneh Shibabaw, Shigematsu, Mika, Shin, Jae Il, Silva, Juan Carlos, Silvester, Alexander A, Singh, Jasvinder A, Singhal, Deepika S, Sitorus, Rita S, Skiadaresi, Eirini Yurievich, Skryabin, Valentin Yurievich Aleksandrovna, Skryabina, Anna Aleksandrovna, Soheili, Amin Bekele, Sorrie, Muluken Bekele A R C, Sousa, Raúl A R C T, Sreeramareddy, Chandrashekhar T, Stambolian, Dwight Girma, Tadesse, Eyayou Girma, Tahhan, Nina Ismail, Tareque, Md Ismail, Topouzis, Fotis Xuan, Tran, Bach Xuan, Tsegaye, Gebiyaw K, Tsilimbaris, Miltiadis K, Varma, Rohit, Virgili, Gianni, Vongpradith, Avina Thu, Vu, Giang Thu, Wang, Ya Xing, Wang, Ningli Hailay, Weldemariam, Abrha Hailay K, West, Sheila K Gebeyehu, Wondmeneh, Temesgen Gebeyehu Y, Wong, Tien Y, Yaseri, Mehdi, Yonemoto, Naohiro, Yu, Chuanhua Sergeevich, Zastrozhin, Mikhail Sergeevich, Zhang, Zhi-Jiang R, Zimsen, Stephanie R, Resnikoff, Serge, and Vos, Theo

Published
2021
Full Text
View/download PDF

74. Trends in prevalence of blindness and distance and near vision impairment over 30 years: an analysis for the Global Burden of Disease Study

Author

Bourne, Rupert, Steinmetz, Jaimie D, Flaxman, Seth, Briant, Paul Svitil, Taylor, Hugh R, Resnikoff, Serge, Casson, Robert James, Abdoli, Amir, Abu-Gharbieh, Eman, Afshin, Ashkan, Ahmadieh, Hamid, Akalu, Yonas, Alamneh, Alehegn Aderaw, Alemayehu, Wondu, Alfaar, Ahmed Samir, Alipour, Vahid, Anbesu, Etsay Woldu, Androudi, Sofia, Arabloo, Jalal, Arditi, Aries, Asaad, Malke, Bagli, Eleni, Baig, Atif Amin, Bärnighausen, Till Winfried, Battaglia Parodi, Maurizio, Bhagavathula, Akshaya Srikanth, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhattacharyya, Krittika, Bijani, Ali, Bikbov, Mukharram, Bottone, Michele, Braithwaite, Tasanee, Bron, Alain M, Butt, Zahid A, Cheng, Ching-Yu, Chu, Dinh-Toi, Cicinelli, Maria Vittoria, Coelho, João M, Dagnew, Baye, Dai, Xiaochen, Dana, Reza, Dandona, Lalit, Dandona, Rakhi, Del Monte, Monte A, Deva, Jenny P, Diaz, Daniel, Djalalinia, Shirin, Dreer, Laura E, Ehrlich, Joshua R, Ellwein, Leon B, Emamian, Mohammad Hassan, Fernandes, Arthur G, Fischer, Florian, Friedman, David S, Furtado, João M, Gaidhane, Abhay Motiramji, Gaidhane, Shilpa, Gazzard, Gus, Gebremichael, Berhe, George, Ronnie, Ghashghaee, Ahmad, Golechha, Mahaveer, Hamidi, Samer, Hammond, Billy Randall, Hartnett, Mary Elizabeth R, Hartono, Risky Kusuma, Hay, Simon I, Heidari, Golnaz, Ho, Hung Chak, Hoang, Chi Linh, Househ, Mowafa, Ibitoye, Segun Emmanuel, Ilic, Irena M, Ilic, Milena D, Ingram, April D, Irvani, Seyed Sina Naghibi, Jha, Ravi Prakash, Kahloun, Rim, Kandel, Himal, Kasa, Ayele Semachew, Kempen, John H, Keramati, Maryam, Khairallah, Moncef, Khan, Ejaz Ahmad, Khanna, Rohit C, Khatib, Mahalaqua Nazli, Kim, Judy E, Kim, Yun Jin, Kisa, Sezer, Kisa, Adnan, Koyanagi, Ai, Kurmi, Om P, Lansingh, Van Charles, Leasher, Janet L, Leveziel, Nicolas, Limburg, Hans, Majdan, Marek, Manafi, Navid, Mansouri, Kaweh, McAlinden, Colm, Mohammadi, Seyed Farzad, Mohammadian-Hafshejani, Abdollah, Mohammadpourhodki, Reza, Mokdad, Ali H, Moosavi, Delaram, Morse, Alan R, Naderi, Mehdi, Naidoo, Kovin S, Nangia, Vinay, Nguyen, Cuong Tat, Nguyen, Huong Lan Thi, Ogundimu, Kolawole, Olagunju, Andrew T, Ostroff, Samuel M, Panda-Jonas, Songhomitra, Pesudovs, Konrad, Peto, Tunde, Quazi Syed, Zahiruddin, Rahman, Mohammad Hifz Ur, Ramulu, Pradeep Y, Rawaf, Salman, Rawaf, David Laith, Reinig, Nickolas, Robin, Alan L, Rossetti, Luca, Safi, Sare, Sahebkar, Amirhossein, Samy, Abdallah M, Saxena, Deepak, Serle, Janet B, Shaikh, Masood Ali, Shen, Tueng T, Shibuya, Kenji, Shin, Jae Il, Silva, Juan Carlos, Silvester, Alexander, Singh, Jasvinder A, Singhal, Deepika, Sitorus, Rita S, Skiadaresi, Eirini, Skirbekk, Vegard, Soheili, Amin, Sousa, Raúl A R C, Spurlock, Emma Elizabeth, Stambolian, Dwight, Taddele, Biruk Wogayehu, Tadesse, Eyayou Girma, Tahhan, Nina, Tareque, Md Ismail, Topouzis, Fotis, Tran, Bach Xuan, Travillian, Ravensara S, Tsilimbaris, Miltiadis K, Varma, Rohit, Virgili, Gianni, Wang, Ya Xing, Wang, Ningli, West, Sheila K, Wong, Tien Y, Zaidi, Zoubida, Zewdie, Kaleab Alemayehu, Jonas, Jost B, and Vos, Theo

Published
2021
Full Text
View/download PDF

75. Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China

Author

Fu, Han, Wang, Haowei, Xi, Xiaoyue, Boonyasiri, Adhiratha, Wang, Yuanrong, Hinsley, Wes, Fraser, Keith J., McCabe, Ruth, Olivera Mesa, Daniela, Skarp, Janetta, Ledda, Alice, Dewé, Tamsin, Dighe, Amy, Winskill, Peter, van Elsland, Sabine L., Ainslie, Kylie E.C., Baguelin, Marc, Bhatt, Samir, Boyd, Olivia, Brazeau, Nicholas F., Cattarino, Lorenzo, Charles, Giovanni, Coupland, Helen, Cucunuba, Zulma M., Cuomo-Dannenburg, Gina, Donnelly, Christl A., Dorigatti, Ilaria, Eales, Oliver D., FitzJohn, Richard G., Flaxman, Seth, Gaythorpe, Katy A.M., Ghani, Azra C., Green, William D., Hamlet, Arran, Hauck, Katharina, Haw, David J., Jeffrey, Benjamin, Laydon, Daniel J., Lees, John A., Mellan, Thomas, Mishra, Swapnil, Nedjati-Gilani, Gemma, Nouvellet, Pierre, Okell, Lucy, Parag, Kris V., Ragonnet-Cronin, Manon, Riley, Steven, Schmit, Nora, Thompson, Hayley A., Unwin, H.Juliette T., Verity, Robert, Vollmer, Michaela A.C., Volz, Erik, Walker, Patrick G.T., Walters, Caroline E., Watson, Oliver J., Whittaker, Charles, Whittles, Lilith K., Imai, Natsuko, Bhatia, Sangeeta, and Ferguson, Neil M.

Published
2021
Full Text
View/download PDF

76. Global estimates on the number of people blind or visually impaired by cataract:a meta-analysis from 2000 to 2020

Author

Fernandes, Arthur G, Cicinelli, Maria V, Arrigo, Alessandro, Leveziel, Nicolas, Briant, Paul Svitil, Vos, Theo, Resnikoff, Serge, Taylor, Hugh R, Sedighi, Tabassom, Flaxman, Seth, Steinmetz, Jaimie, Bourne, Rupert, Fernandes, Arthur G, Cicinelli, Maria V, Arrigo, Alessandro, Leveziel, Nicolas, Briant, Paul Svitil, Vos, Theo, Resnikoff, Serge, Taylor, Hugh R, Sedighi, Tabassom, Flaxman, Seth, Steinmetz, Jaimie, and Bourne, Rupert

Abstract

BACKGROUND: To estimate global and regional trends from 2000 to 2020 of the number of persons visually impaired by cataract and their proportion of the total number of vision-impaired individuals.METHODS: A systematic review and meta-analysis of published population studies and gray literature from 2000 to 2020 was carried out to estimate global and regional trends. We developed prevalence estimates based on modeled distance visual impairment and blindness due to cataract, producing location-, year-, age-, and sex-specific estimates of moderate to severe vision impairment (MSVI presenting visual acuity <6/18, ≥3/60) and blindness (presenting visual acuity <3/60). Estimates are age-standardized using the GBD standard population.RESULTS: In 2020, among overall (all ages) 43.3 million blind and 295 million with MSVI, 17.0 million (39.6%) people were blind and 83.5 million (28.3%) had MSVI due to cataract blind 60% female, MSVI 59% female. From 1990 to 2020, the count of persons blind (MSVI) due to cataract increased by 29.7%(93.1%) whereas the age-standardized global prevalence of cataract-related blindness improved by -27.5% and MSVI increased by 7.2%. The contribution of cataract to the age-standardized prevalence of blindness exceeded the global figure only in South Asia (62.9%) and Southeast Asia and Oceania (47.9%).CONCLUSIONS: The number of people blind and with MSVI due to cataract has risen over the past 30 years, despite a decrease in the age-standardized prevalence of cataract. This indicates that cataract treatment programs have been beneficial, but population growth and aging have outpaced their impact. Growing numbers of cataract blind indicate that more, better-directed, resources are needed to increase global capacity for cataract surgery.

Published
2024

77. Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study

Author

Ainslie, Kylie, Baguelin, Marc, Bhatt, Samir, Boonyasiri, Adhiratha, Brazeau, Nick, Cattarino, Lorenzo, Coupland, Helen, Cucunuba, Zulma, Cuomo-Dannenburg, Gina, Dighe, Amy, Donnelly, Christl, van Elsland, Sabine L, FitzJohn, Richard, Flaxman, Seth, Fraser, Keith, Gaythorpe, Katy, Green, Will, Hamlet, Arran, Hinsley, Wes, Imai, Natsuko, Knock, Edward, Laydon, Daniel, Mellan, Thomas, Mishra, Swapnil, Nedjati-Gilani, Gemma, Nouvellet, Pierre, Okell, Lucy, Ragonnet-Cronin, Manon, Thompson, Hayley A, Unwin, H. Juliette T, Vollmer, Michaela, Volz, Erik, Walters, Caroline, Wang, Yuanrong, Watson, Oliver J, Whittaker, Charles, Whittles, Lilith, Xi, Xiaoyue, Grassly, Nicholas C, Pons-Salort, Margarita, Parker, Edward P K, White, Peter J, and Ferguson, Neil M

Published
2020
Full Text
View/download PDF

78. The Effectiveness of Hope Groups, a Mental Health, Parenting Support, and Violence Prevention Program for Families Affected by the War in Ukraine: Findings from a Pre-Post Study

Author

Hillis, Susan, primary, Tucker, Sydney Faith, additional, Baldonado, Nicole, additional, Taradaika, Evgenia, additional, Bryn, Lyudmyla, additional, Kharchenko, Svitlana, additional, Machabelii, Tetiana, additional, Taylor, Roisin, additional, Green, Phil, additional, Goldman, Philip, additional, Awah, Isang, additional, Baldonado, Joshua, additional, Gomez, Praveen, additional, Flaxman, Seth, additional, Ratmann, Oliver, additional, Lachman, Jamie, additional, Sherr, Lorraine, additional, and Cluver, Lucie, additional

Published
2024
Full Text
View/download PDF

79. Reply to: The effect of interventions on COVID-19

Author

Flaxman, Seth, Mishra, Swapnil, Scott, James, Ferguson, Neil, Gandy, Axel, and Bhatt, Samir

Subjects
Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Seth Flaxman [sup.1] , Swapnil Mishra [sup.2] , James Scott [sup.1] , Neil Ferguson [sup.2] , Axel Gandy [sup.1] , Samir Bhatt [sup.2] Author Affiliations: (1) Department of Mathematics, [...]

Published
2020
Full Text
View/download PDF

85. Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe

Author

Sharma, Mrinank, Mindermann, Sören, Rogers-Smith, Charlie, Leech, Gavin, Snodin, Benedict, Ahuja, Janvi, Sandbrink, Jonas B., Monrad, Joshua Teperowski, Altman, George, Dhaliwal, Gurpreet, Finnveden, Lukas, Norman, Alexander John, Oehm, Sebastian B., Sandkühler, Julia Fabienne, Aitchison, Laurence, Gavenčiak, Tomáš, Mellan, Thomas, Kulveit, Jan, Chindelevitch, Leonid, Flaxman, Seth, Gal, Yarin, Mishra, Swapnil, Bhatt, Samir, and Brauner, Jan Markus

Published
2021
Full Text
View/download PDF

87. Author Correction: Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Author

Brizzi, Andrea, Whittaker, Charles, Servo, Luciana M. S., Hawryluk, Iwona, Prete, Jr, Carlos A., de Souza, William M., Aguiar, Renato S., Araujo, Leonardo J. T., Bastos, Leonardo S., Blenkinsop, Alexandra, Buss, Lewis F., Candido, Darlan, Castro, Marcia C., Costa, Silvia F., Croda, Julio, de Souza Santos, Andreza Aruska, Dye, Christopher, Flaxman, Seth, Fonseca, Paula L. C., Geddes, Victor E. V., Gutierrez, Bernardo, Lemey, Philippe, Levin, Anna S., Mellan, Thomas, Bonfim, Diego M., Miscouridou, Xenia, Mishra, Swapnil, Monod, Mélodie, Moreira, Filipe R. R., Nelson, Bruce, Pereira, Rafael H. M., Ranzani, Otavio, Schnekenberg, Ricardo P., Semenova, Elizaveta, Sonabend, Raphael, Souza, Renan P., Xi, Xiaoyue, Sabino, Ester C., Faria, Nuno R., Bhatt, Samir, and Ratmann, Oliver

Published
2022
Full Text
View/download PDF

92. Mapping changes in housing in sub-Saharan Africa from 2000 to 2015

Author

Tusting, Lucy S., Bisanzio, Donal, Alabaster, Graham, Cameron, Ewan, Cibulskis, Richard, Davies, Michael, and Flaxman, Seth

Subjects
Sub-Saharan Africa -- Economic aspects, Housing development -- Planning -- Economic aspects -- Reports, Africans, Nutrition, Housing, Water resource management, Human rights, Urban population, Water, Sustainable development, Geostatistics, Metropolitan areas, Company business planning, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Access to adequate housing is a fundamental human right, essential to human security, nutrition and health, and a core objective of the United Nations Sustainable Development Goals.sup.1,2. Globally, the housing need is most acute in Africa, where the population will more than double by 2050. However, existing data on housing quality across Africa are limited primarily to urban areas and are mostly recorded at the national level. Here we quantify changes in housing in sub-Saharan Africa from 2000 to 2015 by combining national survey data within a geostatistical framework. We show a marked transformation of housing in urban and rural sub-Saharan Africa between 2000 and 2015, with the prevalence of improved housing (with improved water and sanitation, sufficient living area and durable construction) doubling from 11% (95% confidence interval, 10-12%) to 23% (21-25%). However, 53 (50-57) million urban Africans (47% (44-50%) of the urban population analysed) were living in unimproved housing in 2015. We provide high-resolution, standardized estimates of housing conditions across sub-Saharan Africa. Our maps provide a baseline for measuring change and a mechanism to guide interventions during the era of the Sustainable Development Goals. The prevalence of improved housing (with improved drinking water and sanitation, sufficient living area and durable construction) in urban and rural sub-Saharan Africa doubled between 2000 and 2015., Author(s): Lucy S. Tusting [sup.1] , Donal Bisanzio [sup.2] [sup.3] , Graham Alabaster [sup.4] , Ewan Cameron [sup.5] , Richard Cibulskis [sup.6] , Michael Davies [sup.7] , Seth Flaxman [sup.8] [...]

Published
2019
Full Text
View/download PDF

93. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

Author

Lim, Stephen S, Vos, Theo, Flaxman, Abraham D, Danaei, Goodarz, Shibuya, Kenji, Adair-Rohani, Heather, AlMazroa, Mohammad A, Amann, Markus, Anderson, H Ross, Andrews, Kathryn G, Aryee, Martin, Atkinson, Charles, Bacchus, Loraine J, Bahalim, Adil N, Balakrishnan, Kalpana, Balmes, John, Barker-Collo, Suzanne, Baxter, Amanda, Bell, Michelle L, Blore, Jed D, Blyth, Fiona, Bonner, Carissa, Borges, Guilherme, Bourne, Rupert, Boussinesq, Michel, Brauer, Michael, Brooks, Peter, Bruce, Nigel G, Brunekreef, Bert, Bryan-Hancock, Claire, Bucello, Chiara, Buchbinder, Rachelle, Bull, Fiona, Burnett, Richard T, Byers, Tim E, Calabria, Bianca, Carapetis, Jonathan, Carnahan, Emily, Chafe, Zoe, Charlson, Fiona, Chen, Honglei, Chen, Jian Shen, Cheng, Andrew Tai-Ann, Child, Jennifer Christine, Cohen, Aaron, Colson, K Ellicott, Cowie, Benjamin C, Darby, Sarah, Darling, Susan, Davis, Adrian, Degenhardt, Louisa, Dentener, Frank, Jarlais, Don C Des, Devries, Karen, Dherani, Mukesh, Ding, Eric L, Dorsey, E Ray, Driscoll, Tim, Edmond, Karen, Ali, Suad Eltahir, Engell, Rebecca E, Erwin, Patricia J, Fahimi, Saman, Falder, Gail, Farzadfar, Farshad, Ferrari, Alize, Finucane, Mariel M, Flaxman, Seth, Fowkes, Francis Gerry R, Freedman, Greg, Freeman, Michael K, Gakidou, Emmanuela, Ghosh, Santu, Giovannucci, Edward, Gmel, Gerhard, Graham, Kathryn, Grainger, Rebecca, Grant, Bridget, Gunnell, David, Gutierrez, Hialy R, Hall, Wayne, Hoek, Hans W, Hogan, Anthony, Hosgood, H Dean, Hoy, Damian, Hu, Howard, Hubbell, Bryan J, Hutchings, Sally J, Ibeanusi, Sydney E, Jacklyn, Gemma L, Jasrasaria, Rashmi, Jonas, Jost B, Kan, Haidong, Kanis, John A, Kassebaum, Nicholas, Kawakami, Norito, Khang, Young-Ho, Khatibzadeh, Shahab, Khoo, Jon-Paul, and Kok, Cindy

Subjects
Tobacco Smoke and Health, Prevention, Tobacco, Burden of Illness, Nutrition, Pediatric, 2.2 Factors relating to the physical environment, 2.3 Psychological, social and economic factors, Aetiology, Respiratory, Cardiovascular, Good Health and Well Being, Clean Water and Sanitation, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Global Health, Humans, Infant, Infant, Newborn, Male, Middle Aged, Mortality, Quality-Adjusted Life Years, Risk Assessment, Risk Factors, Sex Factors, Young Adult, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundQuantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time.MethodsWe estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden.FindingsIn 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2-7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5-7·0]), and alcohol use (5·5% [5·0-5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8-9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6-8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4-6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2-10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4-1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania.InterpretationWorldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children.FundingBill & Melinda Gates Foundation.

Published
2012

94. State-level tracking of COVID-19 in the United States

Author

Unwin, H. Juliette T., Mishra, Swapnil, Bradley, Valerie C., Gandy, Axel, Mellan, Thomas A., Coupland, Helen, Ish-Horowicz, Jonathan, Vollmer, Michaela A. C., Whittaker, Charles, Filippi, Sarah L., Xi, Xiaoyue, Monod, Mélodie, Ratmann, Oliver, Hutchinson, Michael, Valka, Fabian, Zhu, Harrison, Hawryluk, Iwona, Milton, Philip, Ainslie, Kylie E. C., Baguelin, Marc, Boonyasiri, Adhiratha, Brazeau, Nick F., Cattarino, Lorenzo, Cucunuba, Zulma, Cuomo-Dannenburg, Gina, Dorigatti, Ilaria, Eales, Oliver D., Eaton, Jeffrey W., van Elsland, Sabine L., FitzJohn, Richard G., Gaythorpe, Katy A. M., Green, William, Hinsley, Wes, Jeffrey, Benjamin, Knock, Edward, Laydon, Daniel J., Lees, John, Nedjati-Gilani, Gemma, Nouvellet, Pierre, Okell, Lucy, Parag, Kris V., Siveroni, Igor, Thompson, Hayley A., Walker, Patrick, Walters, Caroline E., Watson, Oliver J., Whittles, Lilith K., Ghani, Azra C., Ferguson, Neil M., Riley, Steven, Donnelly, Christl A., Bhatt, Samir, and Flaxman, Seth

Published
2020
Full Text
View/download PDF

95. Global causes of blindness and distance vision impairment 1990–2020: a systematic review and meta-analysis

Author

Bourne, Rupert, Ackland, Peter, Arditi, Aries, Barkana, Yaniv, Bozkurt, Banu, Braithwaite, Tasanee, Bron, Alain, Budenz, Donald, Cai, Feng, Casson, Robert, Chakravarthy, Usha, Choi, Jaewan, Cicinelli, Maria Vittoria, Congdon, Nathan, Dana, Reza, Dandona, Rakhi, Dandona, Lalit, Das, Aditi, Dekaris, Iva, Del Monte, Monte, deva, Jenny, Dreer, Laura, Ellwein, Leon, Frazier, Marcela, Frick, Kevin, Friedman, David, Furtado, Joao, Gao, Hua, Gazzard, Gus, George, Ronnie, Gichuhi, Stephen, Gonzalez, Victor, Hammond, Billy, Hartnett, Mary Elizabeth, He, Minguang, Hejtmancik, James, Hirai, Flavio, Huang, John, Ingram, April, Javitt, Jonathan, Jonas, Jost, Joslin, Charlotte, Keeffe, Jill, Kempen, John, Khairallah, Moncef, Khanna, Rohit, Kim, Judy, Lambrou, George, Lansingh, Van Charles, Lanzetta, Paolo, Leasher, Janet, Lim, Jennifer, LIMBURG, Hans, Mansouri, Kaweh, Mathew, Anu, Morse, Alan, Munoz, Beatriz, Musch, David, Naidoo, Kovin, Nangia, Vinay, Palaiou, Maria, Parodi, Maurizio Battaglia, Pena, Fernando Yaacov, Pesudovs, Konrad, Peto, Tunde, Quigley, Harry, Raju, Murugesan, Ramulu, Pradeep, Rankin, Zane, Resnikoff, Serge, Reza, Dana, Robin, Alan, Rossetti, Luca, Saaddine, Jinan, Sandar, Mya, Serle, Janet, Shen, Tueng, Shetty, Rajesh, Sieving, Pamela, Silva, Juan Carlos, Silvester, Alex, Sitorus, Rita S., Stambolian, Dwight, Stevens, Gretchen, Taylor, Hugh, Tejedor, Jaime, Tielsch, James, Tsilimbaris, Miltiadis, van Meurs, Jan, Varma, Rohit, Virgili, Gianni, Wang, Ya Xing, Wang, Ning-Li, West, Sheila, Wiedemann, Peter, Wong, Tien, Wormald, Richard, Zheng, Yingfeng, Flaxman, Seth R, Bourne, Rupert R A, Cicinelli, Maria V, Jonas, Jost B, Kempen, John H, Limburg, Hans, Stevens, Gretchen A, Tahhan, Nina, Wong, Tien Y, and Taylor, Hugh R

Published
2017
Full Text
View/download PDF

97. List child dependents on death certificates

Author

Flaxman, Seth, primary, Kasonka, Lackson, additional, Cluver, Lucie, additional, Souza, Andrea Santos, additional, Nelson, Charles A, additional, Blenkinsop, Alexandra, additional, Unwin, H. Juliette T., additional, and Hillis, Susan, additional

Published
2023
Full Text
View/download PDF

98. Magnitude, temporal trends, and projections of the global prevalence of blindness and distance and near vision impairment: a systematic review and meta-analysis

Author

Bourne, Rupert, Ackland, Peter, Arditi, Aries, Barkana, Yaniv, Bozkurt, Banu, BRAITHWAITE, TASANEE, Bron, Alain, Budenz, Donald, Cai, Feng, Casson, Robert, Chakravarthy, Usha, Choi, Jaewan, Cicinelli, Maria Vittoria, Congdon, Nathan, Dana, Reza, Dandona, Rakhi, Dandona, Lalit, Das, Aditi, Dekaris, Iva, Del Monte, Monte, Deva, Jenny, Dreer, Laura, Ellwein, Leon, Frazier, Marcela, Frick, Kevin, Friedman, David, Furtado, Joao, Gao, Hua, Gazzard, Gus, George, Ronnie, Gichuhi, Stephen, Gonzalez, Victor, Hammond, Billy, Hartnett, Mary Elizabeth, He, Minguang, Hejtmancik, James, Hirai, Flavio, Huang, John, Ingram, April, Javitt, Jonathan, Jonas, Jost, Joslin, Charlotte, Keeffe, Jill, Kempen, John, Khairallah, Moncef, Khanna, Rohit, Kim, Judy, Lambrou, George, Lansingh, Van Charles, Lanzetta, Paolo, Leasher, Janet, Lim, Jennifer, LIMBURG, Hans, Mansouri, Kaweh, Mathew, Anu, Morse, Alan, Munoz, Beatriz, Musch, David, Naidoo, Kovin, Nangia, Vinay, PALAIOU, MARIA, Parodi, Maurizio Battaglia, Pena, Fernando Yaacov, Pesudovs, Konrad, Peto, Tunde, Quigley, Harry, Raju, Murugesan, Ramulu, Pradeep, Resnikoff, Serge, Robin, Alan, Rossetti, Luca, Saaddine, Jinan, SANDAR, MYA, Serle, Janet, Shen, Tueng, Shetty, Rajesh, Sieving, Pamela, Silva, Juan Carlos, Silvester, Alex, Sitorus, Rita S, Stambolian, Dwight, Stevens, Gretchen, Taylor, Hugh, Tejedor, Jaime, Tielsch, James, Tsilimbaris, Miltiadis, van Meurs, Jan, Varma, Rohit, Virgili, Gianni, Volmink, Jimmy, Wang, Ya Xing, Wang, Ning-Li, West, Sheila, Wiedemann, Peter, Wong, Tien, Wormald, Richard, Zheng, Yingfeng, Bourne, Rupert R A, Flaxman, Seth R, Braithwaite, Tasanee, Cicinelli, Maria V, Jonas, Jost B, Kempen, John H, Limburg, Hans, Stevens, Gretchen A, Tahhan, Nina, Wong, Tien Y, and Taylor, Hugh R

Published
2017
Full Text
View/download PDF

99. Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa

Author

Howes, Adam, primary, Risher, Kathryn A., additional, Nguyen, Van Kính, additional, Stevens, Oliver, additional, Jia, Katherine M., additional, Wolock, Timothy M., additional, Esra, Rachel T., additional, Zembe, Lycias, additional, Wanyeki, Ian, additional, Mahy, Mary, additional, Benedikt, Clemens, additional, Flaxman, Seth R., additional, and Eaton, Jeffrey W., additional

Published
2023
Full Text
View/download PDF

100. Changes in life expectancy and house prices in London from 2002 to 2019: hyper-resolution spatiotemporal analysis of death registration and real estate data

Author

Bennett, James E., primary, Rashid, Theo, additional, Zolfaghari, Alireza, additional, Doyle, Yvonne, additional, Suel, Esra, additional, Pearson-Stuttard, Jonathan, additional, Davies, Bethan, additional, Fecht, Daniela, additional, Muller, Emily S., additional, Nathvani, Ricky S., additional, Sportiche, Noemie, additional, Daby, Hima Iyathooray, additional, Johnson, Eric, additional, Li, Guangquan, additional, Flaxman, Seth, additional, Toledano, Mireille B., additional, Asaria, Miqdad, additional, and Ezzati, Majid, additional

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results