index.json

[{"authors":["harrison-zhu"],"categories":null,"content":"I am an Assistant Professor at the Department of Public Health, University of Copenhagen. Before joining the University of Copenhagen, I first obtained my integrated masters’ (MSci; 2015-2019) in Mathematics from Imperial College London. I then obtained my PhD (2019-2023) from Imperial College London, as part of the EPSRC Centre of Doctoral Training in Modern Statistics and Statistical Machine Learning at Imperial and Oxford. I had the privilege of being supervised by Seth Flaxman and Yingzhen Li. My research interests are in developing probabilistic machine learning and deep learning methods to understand complex patterns in public health. Some particular topics that I am interested in are: phylogenetics, infectious diseases modeling and Bayesian deep learning.\n","date":1664582400,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1666269699,"objectID":"1442b5ad98bfae1cd9dea196ed5acf51","permalink":"https://mlglobalhealth.github.io/author/harrison-zhu/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/harrison-zhu/","section":"authors","summary":"I am an Assistant Professor at the Department of Public Health, University of Copenhagen. Before joining the University of Copenhagen, I first obtained my integrated masters’ (MSci; 2015-2019) in Mathematics from Imperial College London.","tags":null,"title":"Harrison Zhu","type":"authors"},{"authors":["samir-bhatt"],"categories":null,"content":"Dr. Samir Bhatt is a Professor at the University of Copenhagen and Imperial College London, where his research team works at the interface of mathematics, biology and computer science. While undertaking a MPhil at the University of Cambridge and a DPhil at the University of Oxford, he developed methods to estimate the rate of molecular adaptation in viruses, and conducted the first study investigating the origins of the 2009 Swine Flu pandemic. Subsequent research explored spatial epidemiology, including the first study to quantify the global distribution and burden of Dengue disease and a study measuring the effect of interventions (such as bednets) on malaria prevalence and incidence across Sub-Saharan Africa. At Imperial College London, Dr. Bhatt expanded his research to include studying housing quality in sub-Saharan Africa, developing network infection models for malaria, mapping travel accessibility, large scale geostatistical methods, and outbreak methodology. Recently, Dr. Bhatt has been involved in research and advising on the COVID-19 pandemic. His group now focuses on mathematical, statistical and computer science tools to answer questions on human health and biology in general.\n","date":1664582400,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1666269699,"objectID":"f5a7233193af5e1fc50f651cb9be7deb","permalink":"https://mlglobalhealth.github.io/author/samir-bhatt/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/samir-bhatt/","section":"authors","summary":"Dr. Samir Bhatt is a Professor at the University of Copenhagen and Imperial College London, where his research team works at the interface of mathematics, biology and computer science. While undertaking a MPhil at the University of Cambridge and a DPhil at the University of Oxford, he developed methods to estimate the rate of molecular adaptation in viruses, and conducted the first study investigating the origins of the 2009 Swine Flu pandemic.","tags":null,"title":"Samir Bhatt","type":"authors"},{"authors":["seth-flaxman"],"categories":null,"content":"I am an associate professor at the University of Oxford in the Department of Computer Science and a tutorial fellow of Jesus College. My research is on scalable methods and flexible models for spatiotemporal statistics and Bayesian machine learning, applied to public policy and social science. I’ve worked on application areas that include public health, orphanhood, deep learning from satellite and street-level imagery, crime, voting patterns, filter bubbles / echo chambers in media, the big data paradox, the regulation of machine learning algorithms, and emotion.\nI am working with colleagues from University of Oxford, Imperial College London, and University of Copenhagen to model the spread of COVID-19.\n","date":1664582400,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1666269699,"objectID":"e81bbd5cebac798ec0b7cab21c7a5c36","permalink":"https://mlglobalhealth.github.io/author/seth-flaxman/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/seth-flaxman/","section":"authors","summary":"I am an associate professor at the University of Oxford in the Department of Computer Science and a tutorial fellow of Jesus College. My research is on scalable methods and flexible models for spatiotemporal statistics and Bayesian machine learning, applied to public policy and social science.","tags":null,"title":"Seth Flaxman","type":"authors"},{"authors":["swapnil-mishra"],"categories":null,"content":"I am an Assistant Professor at National University of Singapore (NUS), where I am primarily working at intersection of public health, machine learning and Bayesian modelling. I am part of Machine Learning \u0026amp; Global Health Network, which is a multi-country and multi-organisation network focused on doing fundamental research in machine learning and problems related to global health.\nMy research focuses on applying and developing statistical machine learning techniques for the broader and messier world of science and public policy, especially global health. I develop flexible and scalable models for understanding various spatiotemporal data, for example, epidemics (COVID-19, Malaria, HIV) and crime. For my doctorate, I built models for understanding the evolution of popularity in social media. My work focused on algorithms to model point processes with classical machine learning techniques as well as using modern deep learning networks, mainly recurrent networks.\n","date":1664582400,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1666269699,"objectID":"1f281055ad3ae7959f21334517f032b1","permalink":"https://mlglobalhealth.github.io/author/swapnil-mishra/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/swapnil-mishra/","section":"authors","summary":"I am an Assistant Professor at National University of Singapore (NUS), where I am primarily working at intersection of public health, machine learning and Bayesian modelling. I am part of Machine Learning \u0026 Global Health Network, which is a multi-country and multi-organisation network focused on doing fundamental research in machine learning and problems related to global health.","tags":null,"title":"Swapnil Mishra","type":"authors"},{"authors":["adam-howes"],"categories":null,"content":"I completed my PhD in Modern Statistics and Statistical Machine Learning at Imperial College London with Seth Flaxman and Jeffrey Imai-Eaton in 2023. See my personal website for information about my current activities.\n","date":1654041600,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822705,"objectID":"ee424fe4f523508df09029e01c38ea04","permalink":"https://mlglobalhealth.github.io/author/adam-howes/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/adam-howes/","section":"authors","summary":"I completed my PhD in Modern Statistics and Statistical Machine Learning at Imperial College London with Seth Flaxman and Jeffrey Imai-Eaton in 2023. See my personal website for information about my current activities.","tags":null,"title":"Adam Howes","type":"authors"},{"authors":null,"categories":null,"content":"My background is in Bayesian modelling of spatiotemporal disease surveillance and environmental data, including point pattern data analysis and detection of hotspots on gridded surfaces. Currently, I am interested in using deep generative modelling to power MCMC inference in classical spatial statistics, as well as adaptive survey design.\n","date":1654041600,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822709,"objectID":"baeebe274e456f89b6182f139d65b460","permalink":"https://mlglobalhealth.github.io/author/elizaveta-semenova/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/elizaveta-semenova/","section":"authors","summary":"My background is in Bayesian modelling of spatiotemporal disease surveillance and environmental data, including point pattern data analysis and detection of hotspots on gridded surfaces. Currently, I am interested in using deep generative modelling to power MCMC inference in classical spatial statistics, as well as adaptive survey design.","tags":null,"title":"Elizaveta Semenova","type":"authors"},{"authors":["alexandra-blenkinsop"],"categories":null,"content":"I am a Research Associate based in the statistics section at Imperial College London. My research uses viral sequence data, clinical and epidemiological patient data to characterise HIV transmission at population-level, which can be used to guide public health interventions. I have also been involved in research relating to COVID-19, with a focus on children losing parents and caregivers. More broadly, I am interested in studying health inequalities, to inform policy seeking to close these gaps.\nI have collaborated with numerous partners including the HIV Transmission Elimination Team (H-TEAM), the Amsterdam Institute of Global Health and Development, the Phylogenetics And Networks for Generalised Epidemics in Africa (PANGEA) HIV consortium, the Botswana-Havard AIDS Institute Partnership and the United States Centers for Disease Control and Prevention (CDC).\n","date":1651363200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822704,"objectID":"226affe5f2cff6d1f3a4cc3a9e149f9d","permalink":"https://mlglobalhealth.github.io/author/alexandra-blenkinsop/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/alexandra-blenkinsop/","section":"authors","summary":"I am a Research Associate based in the statistics section at Imperial College London. My research uses viral sequence data, clinical and epidemiological patient data to characterise HIV transmission at population-level, which can be used to guide public health interventions.","tags":null,"title":"Alexandra Blenkinsop","type":"authors"},{"authors":["andrea-brizzi"],"categories":null,"content":"I am a PhD student at Imperial College London, part of the StatML program. My research lies at the intersection of Bayesian modelling and phylogenetics, and tries to describe changes in the Sub-Saharan HIV epidemic. Further, I am interested in the estimation of HIV infection dates based on viral sequencing data.\n","date":1651363200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822692,"objectID":"c5fdb63aa0a1180a8e91484777fb3f4e","permalink":"https://mlglobalhealth.github.io/author/andrea-brizzi/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/andrea-brizzi/","section":"authors","summary":"I am a PhD student at Imperial College London, part of the StatML program. My research lies at the intersection of Bayesian modelling and phylogenetics, and tries to describe changes in the Sub-Saharan HIV epidemic.","tags":null,"title":"Andrea Brizzi","type":"authors"},{"authors":["charles-whittaker"],"categories":null,"content":"My work involves modelling infectious disease transmission dynamics, across a range of different systems that to date have included malaria, loiasis, ebola and COVID-19. Broader research interests include include disease ecology, the dynamics of emerging infectious diseases, surveillance system design and mitigating globally catastrophic biological risks.\n","date":1651363200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822705,"objectID":"9f89f0769657edf22485bf668898c1a6","permalink":"https://mlglobalhealth.github.io/author/charles-whittaker/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/charles-whittaker/","section":"authors","summary":"My work involves modelling infectious disease transmission dynamics, across a range of different systems that to date have included malaria, loiasis, ebola and COVID-19. Broader research interests include include disease ecology, the dynamics of emerging infectious diseases, surveillance system design and mitigating globally catastrophic biological risks.","tags":null,"title":"Charles Whittaker","type":"authors"},{"authors":["iwona-hawryluk"],"categories":null,"content":"My work at Imperial College London focused on applications of modern probabilistic machine learning methods to modelling infectious disease dynamics. In my PhD project I looked at developing statistical methods for characterising the severity of emerging pathogens. I was also involved in modelling the Covid-19 epidemic in Brazil.\nSee my personal website for the current role and activities.\n","date":1651363200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822693,"objectID":"21cac473763dd816506d79cb0b738171","permalink":"https://mlglobalhealth.github.io/author/iwona-hawryluk/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/iwona-hawryluk/","section":"authors","summary":"My work at Imperial College London focused on applications of modern probabilistic machine learning methods to modelling infectious disease dynamics. In my PhD project I looked at developing statistical methods for characterising the severity of emerging pathogens.","tags":null,"title":"Iwona Hawryluk","type":"authors"},{"authors":["oliver-ratmann"],"categories":null,"content":"I develop bespoke statistical methods for public good. My group and I are particularly interested in novel Bayesian methods that harness information in viral deep sequence data, mobile phone mobility data, and time-resolved patient data to characterise the spread of infectious diseases, and to guide public health interventions.\nWe are involved in a number of multinational data-driven public health projects. I co-lead the Phylogenetics and Networks of Generalised HIV epidemics in Africa, and my group develops statistical methods to analyse HIV deep sequence data. I am a member of the Global Reference Group for children affected by COVID-19 and help develop methods to quantify the number of children who lost their parents or caregivers to COVID-19. My group works closely with Emodo Inc. to harness global mobile phone device data for public good. I am the lead statistician of the LONGVIEW study at the Rakai Health Sciences Program. We are affiliated with the HIV transmission elimination initiative Amsterdam and have joined forces for a future with no new HIV infections.\n","date":1651363200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822705,"objectID":"3a29df51d610441067bad4042c14a0f4","permalink":"https://mlglobalhealth.github.io/author/oliver-ratmann/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/oliver-ratmann/","section":"authors","summary":"I develop bespoke statistical methods for public good. My group and I are particularly interested in novel Bayesian methods that harness information in viral deep sequence data, mobile phone mobility data, and time-resolved patient data to characterise the spread of infectious diseases, and to guide public health interventions.","tags":null,"title":"Oliver Ratmann","type":"authors"},{"authors":["xenia-miscouridou"],"categories":null,"content":"My research intersts lie in the broad area of statistical machine learning with broader goal to build methods that combine the strengths of statistics and computation aspiring to answer scientific questions with impact in real life.\nMy phd focus was on Bayesian non parametric modelling for random graphs, complex networks, time interaction data and on practical Bayesian non parametric methods and theory for a variety of applications.\nMy research to date includes more broadly Bayesian methods, deep generative models, unsupervised learning techniques, point processes and stochastic processes with applications in social science, epidemiology and finance.\n","date":1651363200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822705,"objectID":"a065249bac0a9e550aca5e0e2e112fad","permalink":"https://mlglobalhealth.github.io/author/xenia-miscouridou/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/xenia-miscouridou/","section":"authors","summary":"My research intersts lie in the broad area of statistical machine learning with broader goal to build methods that combine the strengths of statistics and computation aspiring to answer scientific questions with impact in real life.","tags":null,"title":"Xenia Miscouridou","type":"authors"},{"authors":null,"categories":null,"content":"I am a Lecturer in Statistical Science in the School of Mathematics at the University of Bristol. I am interested in developing and applying novel methods for infectious disease outbreak analysis to help inform policy makers in real time. My current research focuses on developing spatial temporal renewal based transmission models alongside estimating the number of children affected by COVID-19 and crises.\n","date":1648771200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822694,"objectID":"53342ccd77a9854701ca01fe4d232b16","permalink":"https://mlglobalhealth.github.io/author/juliette-unwin/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/juliette-unwin/","section":"authors","summary":"I am a Lecturer in Statistical Science in the School of Mathematics at the University of Bristol. I am interested in developing and applying novel methods for infectious disease outbreak analysis to help inform policy makers in real time.","tags":null,"title":"Juliette Unwin","type":"authors"},{"authors":["dino-sejdinovic"],"categories":null,"content":"Dino Sejdinovic is a Professor of Statistical Machine Learning at the School of Computer and Mathematical Sciences, University of Adelaide, affiliated with the Australian Institute for Machine Learning (AIML). He was previously a Lecturer and an Associate Professor at the Department of Statistics, University of Oxford (2014-2022), a Fellow of Mansfield College, Oxford, and a Turing Faculty Fellow of the Alan Turing Institute. He held postdoctoral positions at the Gatsby Computational Neuroscience Unit, University College London (2011-2014) and at the Institute for Statistical Science, University of Bristol (2009-2011). He received a PhD in Electrical and Electronic Engineering from the University of Bristol (2009) and a Diplom in Mathematics and Theoretical Computer Science from the University of Sarajevo (2006). His research spans a wide variety of topics at the interface between machine learning and statistical methodology, including large-scale nonparametric and kernel methods, robust and trustworthy machine learning, causal inference, and uncertainty quantification.\n","date":1638316800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822698,"objectID":"e5d3a5ada1568d00ec1e7f8dd3418381","permalink":"https://mlglobalhealth.github.io/author/dino-sejdinovic/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/dino-sejdinovic/","section":"authors","summary":"Dino Sejdinovic is a Professor of Statistical Machine Learning at the School of Computer and Mathematical Sciences, University of Adelaide, affiliated with the Australian Institute for Machine Learning (AIML). He was previously a Lecturer and an Associate Professor at the Department of Statistics, University of Oxford (2014-2022), a Fellow of Mansfield College, Oxford, and a Turing Faculty Fellow of the Alan Turing Institute.","tags":null,"title":"Dino Sejdinovic","type":"authors"},{"authors":["yu-chen"],"categories":null,"content":"","date":1625097600,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822693,"objectID":"8ede28e39e96e0f0a7c669197a1a6ac0","permalink":"https://mlglobalhealth.github.io/author/yu-chen/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/yu-chen/","section":"authors","summary":"","tags":null,"title":"Yu Chen","type":"authors"},{"authors":["nuno-faria"],"categories":null,"content":"My research programme is focused on studying the evolution and epidemiology of rapidly evolving viruses that circulate in human and animal populations, such as SARS-CoV-2, yellow fever, chikungunya, Zika and dengue. Current research topics include: epidemiology, evolution and phylodynamics of viral epidemics; local and regional genomic capacity and outbreak preparedness; and implementation of One Health approaches in hotspots of emerging infectious diseases.\nI coordinate the Brazil-UK CADDE Centre (Centre for Arbovirus Discovery, Diagnostics, Genomics and Epidemiology) with Prof. Ester Sabino from the University of São Paulo. In February 2020, CADDE led the initiative that resulted in the generation, analysis and report of the first SARS-CoV-2 genomes from Latin America in \u0026lt;48 hours. Our team then provided early insights into the epidemiology and genetic diversity of SARS-CoV-2 in Brazil and uncovered a three-quarters attack rate of SARS-CoV-2 in the Amazon region by October 2020. In January 2021, our team discovered the first cases of the SARS-CoV-2 Gamma variant of concern in Manaus. I also lead the ArboSPREAD project, a network for surveillance of arbovirus spread and persistence across corridors of ecological suitability between Angola and Brazil that characterised a Zika outbreak caused by Asian genotype lineage in Angola. I have previously co-led the ZiBRA project in northeast Brazil for real-time genome sequencing of Zika virus in Brazil.\n","date":1612137600,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822701,"objectID":"740737236fbbb0b8ee95c77dc2962e0c","permalink":"https://mlglobalhealth.github.io/author/nuno-faria/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/nuno-faria/","section":"authors","summary":"My research programme is focused on studying the evolution and epidemiology of rapidly evolving viruses that circulate in human and animal populations, such as SARS-CoV-2, yellow fever, chikungunya, Zika and dengue.","tags":null,"title":"Nuno Faria","type":"authors"},{"authors":["helen-coupland"],"categories":null,"content":"In my research I use machine learning to explore risk factors and their temporal relationships in large longitudinal cohort health data.\n","date":1609459200,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822698,"objectID":"60d17f564f8f757d4aa9924b82b57d5f","permalink":"https://mlglobalhealth.github.io/author/helen-coupland/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/helen-coupland/","section":"authors","summary":"In my research I use machine learning to explore risk factors and their temporal relationships in large longitudinal cohort health data.","tags":null,"title":"Helen Coupland","type":"authors"},{"authors":"daniel-laydon","categories":null,"content":"I am a postdoctoral researcher at the MRC Centre for Global Infectious Disease Analysis, based at the Department of Infectious Disease Epidemiology. My research is focussed on the transmission, prevention and alleviation of infectious disease. I use a combination of mathematical, statistical and computational models to study a variety of viruses, including dengue, Middle Eastern Respiratory Syndrome (MERS), and in recent years COVID-19. Since the pandemic, I have been especially interested in pandemic preparedness and emerging threats to human health.\n","date":1593561600,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1655822698,"objectID":"46af9d384b574a85bc10e18a97b5a6b3","permalink":"https://mlglobalhealth.github.io/author/daniel-laydon/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/daniel-laydon/","section":"authors","summary":"I am a postdoctoral researcher at the MRC Centre for Global Infectious Disease Analysis, based at the Department of Infectious Disease Epidemiology. My research is focussed on the transmission, prevention and alleviation of infectious disease.","tags":null,"title":"Daniel Laydon","type":"authors"},{"authors":["alexandros-katsiferis"],"categories":null,"content":"My main research is focused on prediction modelling of adverse outcomes in vulnerable individuals challenged by life-stressors. My primary interest lies in the use of longitudinal, time-series data, their properties and dynamics in classic and machine learning prognostic models. I am also fascinated by the implementation, understanding, and utility of various sources of data that capture further layers of the complexity of human health. My PhD project is placed in the intersection of epidemiology, statistics and machine learning.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"cb62d11ef2274aed3ed4f20e95d66bf5","permalink":"https://mlglobalhealth.github.io/author/alexandros-katsiferis/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/alexandros-katsiferis/","section":"authors","summary":"My main research is focused on prediction modelling of adverse outcomes in vulnerable individuals challenged by life-stressors. My primary interest lies in the use of longitudinal, time-series data, their properties and dynamics in classic and machine learning prognostic models.","tags":null,"title":"Alexandros Katsiferis","type":"authors"},{"authors":["andre-amaral"],"categories":null,"content":"My main research interests include Bayesian methods of inference and spatio-temporal modeling with applications in epidemiology.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"670df1c7763c9c14d4cd2acdf9cd0e87","permalink":"https://mlglobalhealth.github.io/author/andre-victor-ribeiro-amaral/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/andre-victor-ribeiro-amaral/","section":"authors","summary":"My main research interests include Bayesian methods of inference and spatio-temporal modeling with applications in epidemiology.","tags":null,"title":"André Victor Ribeiro Amaral","type":"authors"},{"authors":["david-duchene"],"categories":null,"content":"Dr David Duchene is an Associate Professor at the University of Copenhagen, co-leading the Computational and Mathematical Global Health group at the Department of Public Health. Originally trained as an evolutionary biologist, his research traverses various fields including evolutionary modelling, comparative analysis, biogeography, epidemiology (phylodynamics), and most recently machine learning in public health. His past work has largely focused on explaining how and why molecules evolve (these molecules being the genes of animals or pathogens), using a broad diversity of statistical approaches. In collaboration with genome-sequencing consortia, his work connects processes at the ‘macro’ scale (macroevolution, macroecology, phylogeography) with those at ‘micro’ scales (molecular evolution). One broad question being: how and why do novel living beings and pathogens emerge? Another current focus of his research the challenge of identifying infection in livestock and wildlife using techniques from computer vision. The link between animal movement (neuroscience), infection (epidemiology), and genomics is an exciting budding field that will requre a truly interdisciplinary team.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"cabacdfbf0dce7751e58d4a7d0fd9774","permalink":"https://mlglobalhealth.github.io/author/david-a.-duchene/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/david-a.-duchene/","section":"authors","summary":"Dr David Duchene is an Associate Professor at the University of Copenhagen, co-leading the Computational and Mathematical Global Health group at the Department of Public Health. Originally trained as an evolutionary biologist, his research traverses various fields including evolutionary modelling, comparative analysis, biogeography, epidemiology (phylodynamics), and most recently machine learning in public health.","tags":null,"title":"David A. Duchene","type":"authors"},{"authors":["david-selby"],"categories":null,"content":"I am a senior researcher in the Data Science and its Applications department at the German Research Centre for Artificial Intelligence (DFKI), based in Kaiserslautern. My work touches on a number of areas in the application of data science to health research, including use of smartphones for patient self-reporting of symptoms. I am also interested in meta-level questions such as reproducibility, synthetic data generation, data science ethics and the influence of bibliometrics on research funding, the latter being the subject of my PhD.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"7cb0637716616c399edfe9fac1d3bf50","permalink":"https://mlglobalhealth.github.io/author/david-selby/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/david-selby/","section":"authors","summary":"I am a senior researcher in the Data Science and its Applications department at the German Research Centre for Artificial Intelligence (DFKI), based in Kaiserslautern. My work touches on a number of areas in the application of data science to health research, including use of smartphones for patient self-reporting of symptoms.","tags":null,"title":"David Selby","type":"authors"},{"authors":["giovanni-charles"],"categories":null,"content":"I work on math models of disease transmission and ML-based surrogates for inference and optimisation, my areas of interest include: time-series prediction, transformers for time-series, Approximate Bayesian Inference, differential equations, differentiable agent based models, optimal control and JAX development.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"acc2838f9d60af3ea67835e583999b15","permalink":"https://mlglobalhealth.github.io/author/giovanni-charles/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/giovanni-charles/","section":"authors","summary":"I work on math models of disease transmission and ML-based surrogates for inference and optimisation, my areas of interest include: time-series prediction, transformers for time-series, Approximate Bayesian Inference, differential equations, differentiable agent based models, optimal control and JAX development.","tags":null,"title":"Giovanni Charles","type":"authors"},{"authors":["jingyan-huang"],"categories":null,"content":"I am a Posdoctoral Researcher at National University of Singapore (NUS), where I am primarily working at Bayesian modelling, public health, change-point detection and sequential testing.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bc24f8b6f3fda292be67cab62383cb28","permalink":"https://mlglobalhealth.github.io/author/jingyan-huang/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/jingyan-huang/","section":"authors","summary":"I am a Posdoctoral Researcher at National University of Singapore (NUS), where I am primarily working at Bayesian modelling, public health, change-point detection and sequential testing.","tags":null,"title":"Jingyan Huang","type":"authors"},{"authors":["johannes-hruza"],"categories":null,"content":"I am a PhD student at the University of Copenhagen supervised by Samir Bhatt (Section of Epidemiology) and Erin Gabriel (Section of Biostatistics). My PhD focuses on causal and statistical methods that can be applied to health data.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"a6c61d5f71f1e62aa10780bb5e590e26","permalink":"https://mlglobalhealth.github.io/author/johannes-hruza/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/johannes-hruza/","section":"authors","summary":"I am a PhD student at the University of Copenhagen supervised by Samir Bhatt (Section of Epidemiology) and Erin Gabriel (Section of Biostatistics). My PhD focuses on causal and statistical methods that can be applied to health data.","tags":null,"title":"Johannes Hruza","type":"authors"},{"authors":["kaustubh-chakradeo"],"categories":null,"content":"I am a PhD candidate at the Section of Epidemiology of the University of Copenhagen. My PhD is based on deep learning based medical imaging analysis, focusing on infectious diseases like malaria. My primary interest is using artificial intelligence with medical imaging modalities, for infectious diseases. I am also interested in the law and ethics of AI technologies, with a focus on their use for minority groups.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"4ac7fd1875debf6a0ca111d50a37d688","permalink":"https://mlglobalhealth.github.io/author/kaustubh-chakradeo/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/kaustubh-chakradeo/","section":"authors","summary":"I am a PhD candidate at the Section of Epidemiology of the University of Copenhagen. My PhD is based on deep learning based medical imaging analysis, focusing on infectious diseases like malaria.","tags":null,"title":"Kaustubh Chakradeo","type":"authors"},{"authors":["mark-khurana"],"categories":null,"content":"I am a medical doctor and epidemiologist currently working in phylogenetics and mathematical modeling of infectious diseases as a PhD student under Samir Bhatt.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"6ba86e3d163905bcdab8659a48969374","permalink":"https://mlglobalhealth.github.io/author/mark-khurana/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/mark-khurana/","section":"authors","summary":"I am a medical doctor and epidemiologist currently working in phylogenetics and mathematical modeling of infectious diseases as a PhD student under Samir Bhatt.","tags":null,"title":"Mark Khurana","type":"authors"},{"authors":["mathilde-marie-brunnich-sloth"],"categories":null,"content":"I am a PhD student at the University of Copenhagen in the research group ‘Computational and Mathematical Global Health Group’ at the Section of Health Data Science and AI. I am also affiliated with the research group ‘Social Epidemiology’ at the Section of Social Medicine, UCPH. My PhD supervisors on the project are Professor Samir Bhatt and Associate Professor Terese Sara Høj Jørgensen. My work evolves around life course epidemiology and social inequality in health.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"c9a9150c97ab14f02c36475f49a239f7","permalink":"https://mlglobalhealth.github.io/author/mathilde-marie-brunnich-sloth/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/mathilde-marie-brunnich-sloth/","section":"authors","summary":"I am a PhD student at the University of Copenhagen in the research group ‘Computational and Mathematical Global Health Group’ at the Section of Health Data Science and AI. I am also affiliated with the research group ‘Social Epidemiology’ at the Section of Social Medicine, UCPH.","tags":null,"title":"Mathilde Marie Brünnich Sloth","type":"authors"},{"authors":["mengyan-zhang"],"categories":null,"content":"I am a postdoctoral research associate at the University of Oxford, under the supervision of Dr. Seth Flaxman. Before that, I did my PhD at the Australian National University and Data61, CSIRO (awarded 2023.02), under the supervision of Dr. Cheng Soon Ong, Prof. Lexing Xie and Prof. Eduardo Eyras. My research interests are online experimental design in machine learning, including multi-armed bandits and active learning. I work on both theoretical and practical views of experimental design with two goals: (I) Designing adaptive strategies for imperfect feedback. Understanding the concentration of measures and adaptive strategies involved. (II) Designing the pipeline and recommendation strategies from a practical point of view, including applications in survey design, global health and biology.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"e9431e604ad165ff057534461e27489b","permalink":"https://mlglobalhealth.github.io/author/mengyan-zhang/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/mengyan-zhang/","section":"authors","summary":"I am a postdoctoral research associate at the University of Oxford, under the supervision of Dr. Seth Flaxman. Before that, I did my PhD at the Australian National University and Data61, CSIRO (awarded 2023.","tags":null,"title":"Mengyan Zhang","type":"authors"},{"authors":["moritz-kraemer"],"categories":null,"content":"I am an associate professor at the University of Oxford in the Department of Biology, Reuben College, and the Pandemic Sciences Institute. My research is on scalable interdisciplinary methods applied to the most important questions in human health research. I lead multiple global initiatives on building federated, privacy first global health infrastructure. My background is in statistical learning applied to large and biased datasets.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bfa110c3cc5faf86e02e66bcd9317d45","permalink":"https://mlglobalhealth.github.io/author/moritz-kraemer/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/moritz-kraemer/","section":"authors","summary":"I am an associate professor at the University of Oxford in the Department of Biology, Reuben College, and the Pandemic Sciences Institute. My research is on scalable interdisciplinary methods applied to the most important questions in human health research.","tags":null,"title":"Moritz Kraemer","type":"authors"},{"authors":["mousumi-roy"],"categories":null,"content":"I am working as a Research Fellow at National University of Singapore (NUS). My primary work focuses on developing a Bayesian framework to model spatio-temporal disease propagation. In this process, I am interested in exploring the effect of human mobility on the disease spread.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"8c11aee2bd199522647e26c6618fa3c4","permalink":"https://mlglobalhealth.github.io/author/mousumi-roy/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/mousumi-roy/","section":"authors","summary":"I am working as a Research Fellow at National University of Singapore (NUS). My primary work focuses on developing a Bayesian framework to model spatio-temporal disease propagation. In this process, I am interested in exploring the effect of human mobility on the disease spread.","tags":null,"title":"Mousumi Roy","type":"authors"},{"authors":["neil-scheidwasser"],"categories":null,"content":"I am a PhD student at the Section of Epidemiology of the University of Copenhagen. While my PhD focuses on phylogenetics, epidemiology, and machine learning, I am also interested in computational neuroscience and deep learning-based representations of speech and audio.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"f07089d1f45f0b06bfd3ea13cd0ad3f2","permalink":"https://mlglobalhealth.github.io/author/neil-scheidwasser/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/neil-scheidwasser/","section":"authors","summary":"I am a PhD student at the Section of Epidemiology of the University of Copenhagen. While my PhD focuses on phylogenetics, epidemiology, and machine learning, I am also interested in computational neuroscience and deep learning-based representations of speech and audio.","tags":null,"title":"Neil Scheidwasser","type":"authors"},{"authors":["nicolas-banholzer"],"categories":null,"content":"My work involves modelling of transmissions risks of respiratory infectious diseases (primarily SARS-CoV-2 and Mycobacterium tuberculosis), and the effectiveness of non-pharmaceutical interventions and infection control measures. I am generally interested in Bayesian modelling, in particular Bayesian hierarchical and latent variable models.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"cefb5189923392d0f28ea5290f79efde","permalink":"https://mlglobalhealth.github.io/author/nicolas-banholzer/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/nicolas-banholzer/","section":"authors","summary":"My work involves modelling of transmissions risks of respiratory infectious diseases (primarily SARS-CoV-2 and Mycobacterium tuberculosis), and the effectiveness of non-pharmaceutical interventions and infection control measures. I am generally interested in Bayesian modelling, in particular Bayesian hierarchical and latent variable models.","tags":null,"title":"Nicolas Banholzer","type":"authors"},{"authors":["paolo-andrich"],"categories":null,"content":"Paolo joined the MLGH Network as a postdoctoral researcher in the Fall of 2024. Working under the direction of Prof. Seth Flaxman at the University of Oxford, he focuses on the development of probabilistic epidemiological models with the goal of equipping healthcare providers and decision-makers with tools to better prepare for future emergencies.\nPrior to this appointment, Paolo worked for several years as a physics researcher investigating the quantum mechanical properties of nanomaterials, before shifting to a data science career. Most recently, he was part of a team at the World Food Programme supporting the humanitarian crisis preparedness efforts of UN agencies and international NGOs. He is particularly interested in the application of Bayesian statistical approaches and causal reasoning to inform social and public policy.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"56da9f8e3678e260bb49592b09478641","permalink":"https://mlglobalhealth.github.io/author/paolo-andrich/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/paolo-andrich/","section":"authors","summary":"Paolo joined the MLGH Network as a postdoctoral researcher in the Fall of 2024. Working under the direction of Prof. Seth Flaxman at the University of Oxford, he focuses on the development of probabilistic epidemiological models with the goal of equipping healthcare providers and decision-makers with tools to better prepare for future emergencies.","tags":null,"title":"Paolo Andrich","type":"authors"},{"authors":["prakhar-verma"],"categories":null,"content":"I am a machine learning Ph.D. student with Arno Solin’s research group at Aalto University, Finland. I am broadly interested in probabilistic modelling and efficient inference techniques. For my master’s thesis, I researched on developing variational inference techniques for non-linear SDEs. Recently, my work has focused on sequential decision-making models that need computationally efficient and well-calibrated uncertainty.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"fff0ce258d5ff1a32a5cf7d84f3dff84","permalink":"https://mlglobalhealth.github.io/author/prakhar-verma/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/prakhar-verma/","section":"authors","summary":"I am a machine learning Ph.D. student with Arno Solin’s research group at Aalto University, Finland. I am broadly interested in probabilistic modelling and efficient inference techniques. For my master’s thesis, I researched on developing variational inference techniques for non-linear SDEs.","tags":null,"title":"Prakhar Verma","type":"authors"},{"authors":null,"categories":null,"content":"I am an Assistant Professor at National University of Singapore (NUS), where I am primarily working at intersection of public health, machine learning and Bayesian modelling. I am part of Machine Learning \u0026amp; Global Health Network, which is a multi-country and multi-organisation network focused on doing fundamental research in machine learning and problems related to global health.\nMy research focuses on applying and developing statistical machine learning techniques for the broader and messier world of science and public policy, especially global health. I develop flexible and scalable models for understanding various spatiotemporal data, for example, epidemics (COVID-19, Malaria, HIV) and crime. For my doctorate, I built models for understanding the evolution of popularity in social media. My work focused on algorithms to model point processes with classical machine learning techniques as well as using modern deep learning networks, mainly recurrent networks.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"2525497d367e79493fd32b198b28f040","permalink":"https://mlglobalhealth.github.io/author/s-mishra/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/s-mishra/","section":"authors","summary":"I am an Assistant Professor at National University of Singapore (NUS), where I am primarily working at intersection of public health, machine learning and Bayesian modelling. I am part of Machine Learning \u0026 Global Health Network, which is a multi-country and multi-organisation network focused on doing fundamental research in machine learning and problems related to global health.","tags":null,"title":"S Mishra","type":"authors"},{"authors":["sahoko-ishida"],"categories":null,"content":" I am a post-doc at Professor Seth Flaxman’s lab at Department of Computer Science, University of Oxford. I completed my PhD degree in Statistics at London School of Economics (LSE), supervised by Professor Wicher Bergsma. My research interests include: Gaussian process regression, kernel methods, spatio-temporal analysis, statistical modelling, Bayesian inference and efficient and interpretable statistical learning. I am particularly interested in applications to the areas of environmental studies, and epidemiology. Prior to starting my PhD study, I was working as a statistician at the pharmaceutical industry. I completed my Master’s degree in Statistics at LSE, and my Bachelor’s in Economics and Political Science at Waseda University in Tokyo. See my personal website.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"80ab393851613ad650c5d281de3c2271","permalink":"https://mlglobalhealth.github.io/author/sahoko-ishida/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sahoko-ishida/","section":"authors","summary":"I am a post-doc at Professor Seth Flaxman’s lab at Department of Computer Science, University of Oxford. I completed my PhD degree in Statistics at London School of Economics (LSE), supervised by Professor Wicher Bergsma.","tags":null,"title":"Sahoko Ishida","type":"authors"},{"authors":["sebastian-vollmer"],"categories":null,"content":"I am a professor of applications of machine learning at the Technical University of Kaiserslautern and the German Center for Artificial Intelligence. I am also an associate professor in statistics and mathematics in the Mathematics Insitute and the department of statistics at the University of Warwick. I used be the director of data study groups at the Alan Turing Institute. As well as a Co-Director health and medical sciences research programme. My research interests lie at the interface of computational statistics and machine learning, with a particular focus on real-world applications. I’ve worked in application areas ranging from transport, energy, and in particular health and well-being.\nBefore joining the University of Warwick, I was a lecturer in Statistics at the University of Oxford. Prior to this I undertook postdoctoral research with Arnaud Doucet (Oxford) and Yee Whye Teh (Oxford). I completed my PhD in September 2013 in Mathematics at the University of Warwick supervised by Andrew Stuart and Martin Hairer.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"7c4f7048ed56acd55882ee2a75c50a72","permalink":"https://mlglobalhealth.github.io/author/sebastian-vollmer/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/sebastian-vollmer/","section":"authors","summary":"I am a professor of applications of machine learning at the Technical University of Kaiserslautern and the German Center for Artificial Intelligence. I am also an associate professor in statistics and mathematics in the Mathematics Insitute and the department of statistics at the University of Warwick.","tags":null,"title":"Sebastian Vollmer","type":"authors"},{"authors":["shozen-dan"],"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"778deb2fdd54acc0d1a2ab0f3c707244","permalink":"https://mlglobalhealth.github.io/author/shozen-dan/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/shozen-dan/","section":"authors","summary":"","tags":null,"title":"Shozen Dan","type":"authors"},{"authors":["siyi-sun"],"categories":null,"content":"Siyi is pursuing her DPhil degree in Computer Science at Oxford. Shr received her master degree in Computer Science at New York University, New York, NY 10003 USA. She obtained her B.S. degree in Information and Computational Science at University of Science and Technology Beijing, Beijing, China.\nHer previous work focused on machine learning, infectious disease modeling and fuzzy inference systems. Currently, her research interests are centered on time series prediction with deep learning and its applications in public health and finance.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"3112f7b40b2995ded39cc1d3672813c8","permalink":"https://mlglobalhealth.github.io/author/siyi-sun/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/siyi-sun/","section":"authors","summary":"Siyi is pursuing her DPhil degree in Computer Science at Oxford. Shr received her master degree in Computer Science at New York University, New York, NY 10003 USA. She obtained her B.","tags":null,"title":"Siyi Sun","type":"authors"},{"authors":["tristan-naidoo"],"categories":null,"content":"I am interested in the intersection of Natural Language Processing and Public Health. In line with this interest, the focus of my PhD is to investigate how Twitter data can be used to quantify adherence to protective behaviours over the COVID-19 pandemic.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"bae9d2884384c7cc978b3c1b1538ea6c","permalink":"https://mlglobalhealth.github.io/author/tristan-naidoo/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/tristan-naidoo/","section":"authors","summary":"I am interested in the intersection of Natural Language Processing and Public Health. In line with this interest, the focus of my PhD is to investigate how Twitter data can be used to quantify adherence to protective behaviours over the COVID-19 pandemic.","tags":null,"title":"Tristan Naidoo","type":"authors"},{"authors":["victoria-cox"],"categories":null,"content":"I am interested in the seasonality and heterogeneity of infectious disease transmission across space and time, and the interplay between environment, land use, human behaviour, zoonotic animal reservoirs and vector populations which drives this. During my PhD my research focused on the impact of climate and environmental factors on the spread of arboviruses such as dengue, chikungunya, Zika, and West Nile virus. As part of the Modelling Translational Hub at Imperial, which provides academic modelling outputs to global health agencies and other stakeholders, my research interests centre around pandemic preparedness.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":-62135596800,"objectID":"e76a9d385fec9dfcdcf4f72d7bf6e2a3","permalink":"https://mlglobalhealth.github.io/author/victoria-cox/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/victoria-cox/","section":"authors","summary":"I am interested in the seasonality and heterogeneity of infectious disease transmission across space and time, and the interplay between environment, land use, human behaviour, zoonotic animal reservoirs and vector populations which drives this.","tags":null,"title":"Victoria Cox","type":"authors"},{"authors":null,"categories":null,"content":" When: 24th - 28th March 2025 Where: AIMS, Cape Town, South Africa\nImperial College London and AIMS South Africa are pleased to offer a new 1 week short course in Modern Statistics and Global Health. This course is targeted at Masters level students and above with a background in statistics and/or data science, who are interested in modern statistical methods with applications in global population health.\nAttendees will learn how to:\nWrite their own models in the probabilistic programming language Stan, carry out full Bayesian inference and assess model convergence, Implement advanced statistical models including mixed effects models for hierarchical data, non-parametric gaussian process regression models and computationally scalable approximations, Implement compartmental models for infectious disease epidemiology, Implement a full phylogenetic analysis pipeline for the analysis of pathogen genomic data, Interpret results and present findings Attendees will learn on the course through a blended mix of lectures, hands-on computer practicals and guided tutorials, group work and presenting to their peers.\nPre-requisites: Good knowledge of Python and git\nDeadline to apply: 31 January 2025\nMore information Apply ","date":1731888e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1731888e3,"objectID":"d58e47c046f31f437fe8a7fefc86b3bd","permalink":"https://mlglobalhealth.github.io/short_courses/upcoming/aimsximperial2025/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/short_courses/upcoming/aimsximperial2025/","section":"short_courses","summary":"Imperial College London and the Machine Learning and Global Health Network will host a course from March 24–28, 2025, at AIMS in Cape Town. This one-week, hands-on course is designed for students and researchers working at the intersection of statistics and public health. Participants will learn how to integrate modern statistical techniques with the Stan probabilistic programming language to address a wide range of applications, including epidemiological, genomic, and spatial data.","tags":null,"title":"Modern Statistics and Machine Learning for Population Health in Africa","type":"short_courses"},{"authors":null,"categories":[],"content":" In February 2024, 4 members of the Machine Learning and Global Health Network visited AIMS Rwanda to deliver a 3-day workshop on modern methods at the intersection of epidemiology, statistical modelling and computer science, including probabilistic programming using Stan, computationally efficient non-parametric Bayesian inference, statistical techniques for infectious disease modelling and public health, and phylogenetics. Course Contents Thursday February 22 Lecture 1: Introductions (9.00-9.30) Bayesian Inference Lecture 2: Introduction to Stan for applied Bayesian analyses (9.30-10.00) Practical 1: Stan basics (10.00-11.30) Lecture 3: Scalable Gaussian process regression models (11.45-12.30) Practical 2: Scalable GP regression models (12.30-13.00) Practical 2: Scalable GP regression models continued (14.00-16.00) Friday February 23 Infectious Disease Modelling Lecture 4: Introduction to Infectious Disease Modelling (09.00-10:00) Lecture 5: Introduction to phylogenetics (10:00-10:40) Lecture 6: (11.00-13:00) Four remote research talks from the Machine Learning and Global Health Network (Oliver Ratmann, Seth Flaxman, Samir Bhatt, Liza Semenova)\nPractical 3: Running a phylogenetic pipeline (14:00-15:00) Lecture 6: SIR models (15:00-16:00) Saturday February 24 Practical 4: Deriving SIR type models (09:00-10:30) Lecture 7: Introduction to Fitting an SIR model practical (10:45-11:00) Practical 5: Fitting an SIR model in Stan (11.00-13.00) Course material All course material is freely available from https://github.com/MLGlobalHealth/aims_rwanda_2024\nCourse testimonials and 📸 A few quotes from the course:\n“The course is very important. In this era of AI and Machine learning, it may be the time to train more youngsters and senior researchers to explore more about the use of AI in the field of modelling and treating communicable diseases.”\n“I have been enjoying the content and learning Modern Statistics and Machine Learning for Global Health, methodology used was really valuable.”\n","date":170856e4,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1714480064,"objectID":"674b0c48947b076a640acc2d51a12cbc","permalink":"https://mlglobalhealth.github.io/ms_ml_short_course/past_short_courses/aimsximperial2024/","publishdate":"2024-02-22T14:27:44+02:00","relpermalink":"/ms_ml_short_course/past_short_courses/aimsximperial2024/","section":"ms_ml_short_course","summary":"In February 2024, 4 members of the Machine Learning and Global Health Network visited AIMS Rwanda to deliver a 3-day workshop on modern methods at the intersection of epidemiology, statistical modelling and computer science, including probabilistic programming using Stan, computationally efficient non-parametric Bayesian inference, statistical techniques for infectious disease modelling and public health, and phylogenetics.","tags":[],"title":"AIMS-Imperial Rwanda 2024: Modern Statistics and Machine Learning for Global Health","type":"ms_ml_short_course"},{"authors":null,"categories":null,"content":" First thing is to fork the website repository Clone the fork on your local machine. Let us assume the directory you have cloned is named base_dir Next is to install hugo for local development. You can find instructions at this page. You may skip this page if you are not looking to have a local version, this will just not let you preview how you changes would look on the website. Now go to the base_dir using the shell of you r choice on your local computer. Mac OS Sheel after cloning the repo. To add a new user run the following command hugo new content/authors/firstname-lastname . Remember to change first and last names as the name you want for yourself (surely you can be Swapnil and want to be known as Samir/Seth that can be benefecial :P ) This will create a new folder firstname-lastname inside content/authors/ Now you can open the whole folder in a text editor of your choice and navigate to the file content/authors/firstname-lastname/_index.md Please fill in the details in this file as per your requirement. most of the stuff is self explanatory. In case of any issues raise a concern on zulip Only thing to know is that in area with user_groups the allowed values are: Principal Investigators Researchers Grad Students Administration Visitors Alumni Delete avatar.jpg in your folder and replace with a file with pic you want to be displayed. Remember you need to have the name of the file as avatar.jpg/avatar.png. This is how it look on vscode for reference VSCODE view of the repo and added new folder. Now go back to terminal and to the base_dir and run hugo serve View of the terminal after running hugo serve. This will display you changes on a localhost as informed on the terminal. Open that local host to see your changes Your changes on the local host. If you are happy then press ctrl+c to stop Now delete the the public directory. The command for unix systems is rm -rf public Commit your changes and push it to your fork Now submit a PR to the MLGH repository when happy If you want to add other content than authors you can have a more detailed look at Wowchemy Documentation for Hugo themes. Nothing more sophisticated than adding appropriate markdown files. ","date":1685664e3,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1685664e3,"objectID":"662fa4fc161cd37701d7cd73056e7a14","permalink":"https://mlglobalhealth.github.io/add-profile/","publishdate":"2023-06-02T00:00:00Z","relpermalink":"/add-profile/","section":"","summary":"Instruction to add an user on the mlgh webpage","tags":null,"title":"Adding your profile","type":"page"},{"authors":["Swapnil Mishra","Seth Flaxman","Tresnia Berah","Harrison Zhu","Mikko Pakkanen","Samir Bhatt"],"categories":[],"content":"","date":1664582400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1666269699,"objectID":"51e26a534cd41e33ce321bd5eb715404","permalink":"https://mlglobalhealth.github.io/publication/mishra-2022-oct/","publishdate":"2022-10-20T12:41:39.069971Z","relpermalink":"/publication/mishra-2022-oct/","section":"publication","summary":"","tags":[],"title":"πVAE: a stochastic process prior for Bayesian deep learning with MCMC","type":"publication"},{"authors":["Susan Hillis","Joel-Pascal Ntwali N’konzi","William Msemburi","Lucie Cluver","Andrés Villaveces","Seth Flaxman","H. Juliette T. Unwin"],"categories":[],"content":"","date":1661990400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1666268864,"objectID":"ee7342c40906f87d09776e504107c540","permalink":"https://mlglobalhealth.github.io/publication/10-1001-jamapediatrics-2022-3157/","publishdate":"2022-10-20T12:29:23.658815Z","relpermalink":"/publication/10-1001-jamapediatrics-2022-3157/","section":"publication","summary":"The availability of new excess mortality data enables us to update global minimum estimates of COVID-19 orphanhood and caregiver death among children. Consequences for children can be devastating, including institutionalization, abuse, traumatic grief, mental health problems, adolescent pregnancy, poor educational outcomes, and chronic and infectious diseases. Global totals and country comparisons were previously hampered by inconsistencies in COVID-19 testing and incomplete death reporting. The new orphanhood estimates derived here based on excess deaths provide a comprehensive measure of COVID-19’s long-term impact on orphanhood and caregiver loss.","tags":[],"title":"Orphanhood and Caregiver Loss Among Children Based on New Global Excess COVID-19 Death Estimates","type":"publication"},{"authors":["Elizaveta Semenova","Yidan Xu","Adam Howes","Theo Rashid","Samir Bhatt","Swapnil Mishra","Seth Flaxman"],"categories":[],"content":"","date":1654041600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822692,"objectID":"f934857f89d5549bb703fa1d4cdb3f84","permalink":"https://mlglobalhealth.github.io/publication/semenova-2022-jun/","publishdate":"2022-10-20T12:29:16.209448Z","relpermalink":"/publication/semenova-2022-jun/","section":"publication","summary":"","tags":[],"title":"PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation","type":"publication"},{"authors":["Andrea Brizzi","Charles Whittaker","Luciana M. S. Servo","Iwona Hawryluk","Carlos A. Prete","William M. de Souza","Renato S. Aguiar","Leonardo J. T. Araujo","Leonardo S. Bastos","Alexandra Blenkinsop","Lewis F. Buss","Darlan Candido","Marcia C. Castro","Silvia F. Costa","Julio Croda","Andreza Aruska de Souza Santos","Christopher Dye","Seth Flaxman","Paula L. C. Fonseca","Victor E. V. Geddes","Bernardo Gutierrez","Philippe Lemey","Anna S. Levin","Thomas Mellan","Diego M. Bonfim","Xenia Miscouridou","Swapnil Mishra","Mélodie Monod","Filipe R. R. Moreira","Bruce Nelson","Rafael H. M. Pereira","Otavio Ranzani","Ricardo P. Schnekenberg","Elizaveta Semenova","Raphael Sonnabend","Renan P. Souza","Xiaoyue Xi","Ester C. Sabino","Nuno R. Faria","Samir Bhatt","Oliver Ratmann"],"categories":[],"content":"","date":1651363200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822692,"objectID":"8fbc6a9dab990a5faf68c4e7ff35aafa","permalink":"https://mlglobalhealth.github.io/publication/brizzi-2022-may/","publishdate":"2022-10-20T12:29:16.328505Z","relpermalink":"/publication/brizzi-2022-may/","section":"publication","summary":"","tags":[],"title":"Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals","type":"publication"},{"authors":["Charles Whittaker","Peter Winskill","Marianne Sinka","Samuel Pironon","Claire Massey","Daniel J. Weiss","Michele Nguyen","Peter W. Gething","Ashwani Kumar","Azra Ghani","Samir Bhatt"],"categories":[],"content":"","date":1648771200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822692,"objectID":"72c19045954439108567bdfd7e74bf34","permalink":"https://mlglobalhealth.github.io/publication/whittaker-2022-apr/","publishdate":"2022-10-20T12:29:16.45409Z","relpermalink":"/publication/whittaker-2022-apr/","section":"publication","summary":"","tags":[],"title":"A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations","type":"publication"},{"authors":["Juliette Unwin","Susan Hillis","Lucie Cluver","Seth Flaxman","Philip S. Goldman","Alexander Butchart","Gretchen Bachman","Laura Rawlings","Christl A. Donnelly","Oliver Ratmann","Phil Green","Charles A. Nelson","Alexandra Blenkinsop","Samir Bhatt","Chris Desmond","Andrés Villaveces","Lorraine Sherr"],"categories":[],"content":"","date":1648771200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822692,"objectID":"92b6d2d4bd942d891cf601d7ac27c210","permalink":"https://mlglobalhealth.github.io/publication/unwin-2022-apr/","publishdate":"2022-10-20T12:29:16.565355Z","relpermalink":"/publication/unwin-2022-apr/","section":"publication","summary":"","tags":[],"title":"Global, regional, and national minimum estimates of children affected by COVID-19-associated orphanhood and caregiver death, by age and family circumstance up to Oct 31, 2021: an updated modelling study","type":"publication"},{"authors":["Seth Flaxman","Charles Whittaker","Elizaveta Semenova","Theo Rashid","Robbie Parks","Alexandra Blenkinsop","H Juliette T Unwin","Swapnil Mishra","Samir Bhatt","Deepti Gurdasani"," others"],"categories":[],"content":"","date":1640995200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822704,"objectID":"97821929692f61fe883ad374f436c08e","permalink":"https://mlglobalhealth.github.io/publication/flaxman-2022-covid/","publishdate":"2022-10-20T12:29:22.144162Z","relpermalink":"/publication/flaxman-2022-covid/","section":"publication","summary":"","tags":[],"title":"Covid-19 is a leading cause of death in children and young people ages 0-19 years in the United States","type":"publication"},{"authors":["James W Firman","Mark TD Cronin","Philip H Rowe","Elizaveta Semenova","John E Doe"],"categories":[],"content":"","date":1640995200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822704,"objectID":"4780d80b47175d844b7b271ebf061d7a","permalink":"https://mlglobalhealth.github.io/publication/firman-2022-use/","publishdate":"2022-10-20T12:29:22.263812Z","relpermalink":"/publication/firman-2022-use/","section":"publication","summary":"","tags":[],"title":"The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity","type":"publication"},{"authors":["Iwona Hawryluk","Henrique Hoeltgebaum","Swapnil Mishra","Xenia Miscouridou","Ricardo P. Schnekenberg","Charles Whittaker","Michaela Vollmer","Seth Flaxman","Samir Bhatt","Thomas A. Mellan"],"categories":[],"content":"","date":1638316800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822693,"objectID":"e85ac8c7bb9f94470484809df3b9407b","permalink":"https://mlglobalhealth.github.io/publication/hawryluk-2021-dec/","publishdate":"2022-10-20T12:29:16.679759Z","relpermalink":"/publication/hawryluk-2021-dec/","section":"publication","summary":"","tags":[],"title":"Gaussian process nowcasting: application to COVID-19 mortality reporting","type":"publication"},{"authors":["Valerie C. Bradley","Shiro Kuriwaki","Michael Isakov","Dino Sejdinovic","Xiao-Li Meng","Seth Flaxman"],"categories":[],"content":"","date":1638316800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822697,"objectID":"2fff244a4c975e8a7401a5839f32cdb9","permalink":"https://mlglobalhealth.github.io/publication/bradley-2021-dec/","publishdate":"2022-10-20T12:29:19.108251Z","relpermalink":"/publication/bradley-2021-dec/","section":"publication","summary":"","tags":[],"title":"Unrepresentative big surveys significantly overestimated US vaccine uptake","type":"publication"},{"authors":["Charles Whittaker","Patrick G. T. Walker","Mervat Alhaffar","Arran Hamlet","Bimandra A. Djaafara","Azra Ghani","Neil Ferguson","Maysoon Dahab","Francesco Checchi","Oliver J. Watson"],"categories":[],"content":"","date":1633046400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822699,"objectID":"27fc7eaa2991ce22721ec8ca71a95c00","permalink":"https://mlglobalhealth.github.io/publication/whittaker-2021-oct/","publishdate":"2022-10-20T12:29:20.126079Z","relpermalink":"/publication/whittaker-2021-oct/","section":"publication","summary":"","tags":[],"title":"Under-reporting of deaths limits our understanding of true burden of covid-19","type":"publication"},{"authors":["Mrinank Sharma","Sören Mindermann","Charlie Rogers-Smith","Gavin Leech","Benedict Snodin","Janvi Ahuja","Jonas B Sandbrink","Joshua Teperowski Monrad","George Altman","Gurpreet Dhaliwal","Lukas Finnveden","Alexander John Norman","Sebastian B Oehm","Julia Fabienne Sandkühler","Laurence Aitchison","Tomá ̌s Gavenčiak","Thomas Mellan","Jan Kulveit","Leonid Chindelevitch","Seth Flaxman","Yarin Gal","Swapnil Mishra","Samir Bhatt","Jan Markus Brauner"],"categories":[],"content":"","date":1633046400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822690,"objectID":"0d265c1bb7fd46823df9773d2afd95aa","permalink":"https://mlglobalhealth.github.io/publication/sharma-2021-xj/","publishdate":"2022-10-20T12:29:14.848607Z","relpermalink":"/publication/sharma-2021-xj/","section":"publication","summary":"European governments use non-pharmaceutical interventions (NPIs) to control resurging waves of COVID-19. However, they only have outdated estimates for how effective individual NPIs were in the first wave. We estimate the effectiveness of 17 NPIs in Europe's second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe. Business closures, educational institution closures, and gathering bans reduced transmission, but reduced it less than they did in the first wave. This difference is likely due to organisational safety measures and individual protective behaviours-such as distancing-which made various areas of public life safer and thereby reduced the effect of closing them. Specifically, we find smaller effects for closing educational institutions, suggesting that stringent safety measures made schools safer compared to the first wave. Second-wave estimates outperform previous estimates at predicting transmission in Europe's third wave.","tags":[],"title":"Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe","type":"publication"},{"authors":["Susan D. Hillis","H. Juliette T. Unwin","Yu Chen","Lucie Cluver","Lorraine Sherr","Philip S. Goldman","Oliver Ratmann","Christl A. Donnelly","Samir Bhatt","Andrés Villaveces","Alexander Butchart","Gretchen Bachman","Laura Rawlings","Phil Green","Charles A. Nelson","Seth Flaxman"],"categories":[],"content":"","date":1625097600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822693,"objectID":"3c2ce18b4518ea383a73bb444bb60a16","permalink":"https://mlglobalhealth.github.io/publication/hillis-2021-jul/","publishdate":"2022-10-20T12:29:16.792377Z","relpermalink":"/publication/hillis-2021-jul/","section":"publication","summary":"","tags":[],"title":"Global minimum estimates of children affected by COVID-19-associated orphanhood and deaths of caregivers: a modelling study","type":"publication"},{"authors":["P. Smith Thomas","Flaxman Seth","S. Gallinat Amanda","P. Kinosian Sylvia","Stemkovski Michael","T. Unwin H. Juliette","J. Watson Oliver","Whittaker Charles","Cattarino Lorenzo","Dorigatti Ilaria","Tristem Michael","D. Pearse William"],"categories":[],"content":"","date":1622505600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822696,"objectID":"81c6b88dfb174363a55f990f09e45659","permalink":"https://mlglobalhealth.github.io/publication/smith-thomas-2021-jun/","publishdate":"2022-10-20T12:29:18.99721Z","relpermalink":"/publication/smith-thomas-2021-jun/","section":"publication","summary":"","tags":[],"title":"Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions","type":"publication"},{"authors":["Juliette Unwin","Isobel Routledge","Seth Flaxman","Marian-Andrei Rizoiu","Shengjie Lai","Justin Cohen","Daniel J. Weiss","Swapnil Mishra","Samir Bhatt"],"categories":[],"content":"","date":1617235200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822693,"objectID":"cad4566663e758e85157cb74f12f1336","permalink":"https://mlglobalhealth.github.io/publication/unwin-2021-apr/","publishdate":"2022-10-20T12:29:17.144138Z","relpermalink":"/publication/unwin-2021-apr/","section":"publication","summary":"","tags":[],"title":"Using Hawkes Processes to model imported and local malaria cases in near-elimination settings","type":"publication"},{"authors":["Erik Volz","Swapnil Mishra","Meera Chand","Jeffrey C. Barrett","Robert Johnson","Lily Geidelberg","Wes R. Hinsley","Daniel J. Laydon","Gavin Dabrera","ıfmmode\\acuteA\\elseÁ\\fiine O′Toole","Roberto Amato","Manon Ragonnet-Cronin","Ian Harrison","Ben Jackson","Cristina V. Ariani","Olivia Boyd","Nicholas J. Loman","John T. McCrone","Sıfmmode\\acuteo\\elseó\\finia Gonıfmmode\\mboxç\\elseç\\fialves","David Jorgensen","Richard Myers","Verity Hill","David K. Jackson","Katy Gaythorpe","Natalie Groves","John Sillitoe","Dominic P. Kwiatkowski","Seth Flaxman","Oliver Ratmann","Samir Bhatt","Susan Hopkins","Axel Gandy","Andrew Rambaut","Neil M. Ferguson","The COVID-19 Genomics UK (COG-UK) consortium"],"categories":[],"content":"","date":1614556800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822690,"objectID":"e7aee861bbdd80dcbd1ce5b0176d875f","permalink":"https://mlglobalhealth.github.io/publication/volz-2021-mar/","publishdate":"2022-06-21T14:44:50.280033Z","relpermalink":"/publication/volz-2021-mar/","section":"publication","summary":"","tags":[],"title":"Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England","type":"publication"},{"authors":["Louis du Plessis","John T. McCrone","Alexander E. Zarebski","Verity Hill","Christopher Ruis","Bernardo Gutierrez","Jayna Raghwani","Jordan Ashworth","Rachel Colquhoun","Thomas R. Connor","Nuno R. Faria","Ben Jackson","Nicholas J. Loman","ıfmmode\\acuteA\\elseÁ\\fiine O′Toole","Samuel M. Nicholls","Kris V. Parag","Emily Scher","Tetyana I. Vasylyeva","Erik M. Volz","Alexander Watts","Isaac I. Bogoch","Kamran Khan","Covid-19 Genomics Uk (cog-Uk) Consortiumıfmmode\\dag\\else†\\fi","David M. Aanensen","Moritz U. G. Kraemer","Andrew Rambaut","Oliver G. Pybus"],"categories":[],"content":"","date":1612137600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822699,"objectID":"4ba2dab73bb7666e2a591775e66e067b","permalink":"https://mlglobalhealth.github.io/publication/du-plessis-2021-feb/","publishdate":"2022-10-20T12:29:20.24868Z","relpermalink":"/publication/du-plessis-2021-feb/","section":"publication","summary":"","tags":[],"title":"Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK","type":"publication"},{"authors":["Ester C. Sabino","Lewis F. Buss","Maria P. S. Carvalho","Carlos A. Prete","Myuki A. E. Crispim","Nelson A. Fraiji","Rafael H. M. Pereira","Kris V. Parag","Pedro da Silva Peixoto","Moritz U. G. Kraemer","Marcio K. Oikawa","Tassila Salomon","Zulma M. Cucunuba","Mıfmmode\\acutea\\elseá\\fircia C. Castro","Andreza Aruska de Souza Santos","Vıfmmode\\acuteımath\\elseí\\fitor H. Nascimento","Henrique S. Pereira","Neil M. Ferguson","Oliver G. Pybus","Adam Kucharski","Michael P. Busch","Christopher Dye","Nuno Faria"],"categories":[],"content":"","date":1612137600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822699,"objectID":"b8f54fe208f8dd9eb54fc2690c7c8c8f","permalink":"https://mlglobalhealth.github.io/publication/sabino-2021-feb/","publishdate":"2022-10-20T12:29:20.364186Z","relpermalink":"/publication/sabino-2021-feb/","section":"publication","summary":"","tags":[],"title":"Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence","type":"publication"},{"authors":["Mélodie Monod","Alexandra Blenkinsop","Xiaoyue Xi","Daniel Hebert","Sivan Bershan","Simon Tietze","Marc Baguelin","Valerie C. Bradley","Yu Chen","Helen Coupland","Sarah Filippi","Jonathan Ish-Horowicz","Martin McManus","Thomas Mellan","Axel Gandy","Michael Hutchinson","Juliette Unwin","Sabine L. van Elsland","Michaela A. C. Vollmer","Sebastian Weber","Harrison Zhu","Anne Bezancon","Neil M. Ferguson","Swapnil Mishra","Seth Flaxman","Samir Bhatt","Oliver Ratmann"," "],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822690,"objectID":"9eed792a6e21d8b6f19bc63996b67be8","permalink":"https://mlglobalhealth.github.io/publication/monodeabe-8372/","publishdate":"2022-10-20T12:29:15.00626Z","relpermalink":"/publication/monodeabe-8372/","section":"publication","summary":"Following initial declines, in mid 2020 a resurgence in transmission of novel coronavirus disease (COVID-19) occurred in the US and Europe. As COVID19 disease control efforts are re-intensified, understanding the age demographics driving transmission and how these affect the loosening of interventions is crucial. We analyze aggregated, age-specific mobility trends from more than 10 million individuals in the US and link these mechanistically to age-specific COVID-19 mortality data. We estimate that as of October 2020, individuals aged 20-49 are the only age groups sustaining resurgent SARS-CoV-2 transmission with reproduction numbers well above one, and that at least 65 of 100 COVID-19 infections originate from individuals aged 20-49 in the US. Targeting interventions – including transmission-blocking vaccines – to adults aged 20-49 is an important consideration in halting resurgent epidemics and preventing COVID-19-attributable deaths.","tags":[],"title":"Age groups that sustain resurging COVID-19 epidemics in the United States","type":"publication"},{"authors":["PA Vel’misov","Yu A Tamarova","EP Semenova"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822709,"objectID":"6780b72bf360c60a06c603afcc165f61","permalink":"https://mlglobalhealth.github.io/publication/vel-2021-asymptotic/","publishdate":"2022-10-20T12:29:23.423473Z","relpermalink":"/publication/vel-2021-asymptotic/","section":"publication","summary":"","tags":[],"title":"Asymptotic Equations of Gas Dynamics: Qualitative Analysis, Construction of Solutions, and Applications","type":"publication"},{"authors":["Léo Grinsztajn","Elizaveta Semenova","Charles C Margossian","Julien Riou"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822706,"objectID":"4a5a4ea251a14ee86d1760b7366fe99e","permalink":"https://mlglobalhealth.github.io/publication/grinsztajn-2021-bayesian/","publishdate":"2022-10-20T12:29:22.834268Z","relpermalink":"/publication/grinsztajn-2021-bayesian/","section":"publication","summary":"","tags":[],"title":"Bayesian workflow for disease transmission modeling in Stan","type":"publication"},{"authors":["Swapnil Mishra","Sören Mindermann","Mrinank Sharma","Charles Whittaker","Thomas A Mellan","Thomas Wilton","Dimitra Klapsa","Ryan Mate","Martin Fritzsche","Maria Zambon","Janvi Ahuja","Adam Howes","Xenia Miscouridou","Guy P Nason","Oliver Ratmann","Elizaveta Semenova","Gavin Leech","Julia Fabienne Sandkühler","Charlie Rogers-Smith","Michaela Vollmer","H Juliette T Unwin","Yarin Gal","Meera Chand","Axel Gandy","Javier Martin","Erik Volz","Neil M Ferguson","Samir Bhatt","Jan M Brauner","Seth Flaxman","The COVID-19 Genomics UK (COG-UK) Consortium"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822705,"objectID":"937d95fbf76151496cd2855deca90022","permalink":"https://mlglobalhealth.github.io/publication/mishra-2021-changing/","publishdate":"2022-10-20T12:29:22.607055Z","relpermalink":"/publication/mishra-2021-changing/","section":"publication","summary":"","tags":[],"title":"Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England","type":"publication"},{"authors":["Elizaveta Semenova$^\\dagger$","Maria Luisa Guerriero","Bairu Zhang","Andreas Hock","Philip Hopcroft","Ganesh Kadamur","Avid M Afzal","Stanley E Lazic"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822705,"objectID":"36c6a137f500e2319fec27005a2ed649","permalink":"https://mlglobalhealth.github.io/publication/semenova-2021-flexible/","publishdate":"2022-10-20T12:29:22.493709Z","relpermalink":"/publication/semenova-2021-flexible/","section":"publication","summary":"","tags":[],"title":"Flexible fitting of PROTAC concentration-response curves with changepoint Gaussian Processes","type":"publication"},{"authors":["AF Brito$^*$","E Semenova$^*$","G Dudas$^*$","GW Hassler","CC Kalinich","MUG Kraemer","SC Hill","OG Pybus","C Dye","S Bhatt"," others"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822704,"objectID":"0b22d05b908decf10eea49058efb930d","permalink":"https://mlglobalhealth.github.io/publication/brito-2021-global/","publishdate":"2022-10-20T12:29:22.382147Z","relpermalink":"/publication/brito-2021-global/","section":"publication","summary":"","tags":[],"title":"Global disparities in SARS-CoV-2 genomic surveillance","type":"publication"},{"authors":["Lewis F. Buss","Carlos A. PreteJr.","Claudia M. M. Abrahim","Alfredo MendroneJr.","Tassila Salomon","Cesar de Almeida-Neto","Rafael F. O. Franıfmmode\\mboxç\\elseç\\fia","Maria C. Belotti","Maria P. S. S. Carvalho","Allyson G. Costa","Myuki A. E. Crispim","Suzete C. Ferreira","Nelson A. Fraiji","Susie Gurzenda","Charles Whittaker","Leonardo T. Kamaura","Pedro L. Takecian","Pedro da Silva Peixoto","Marcio K. Oikawa","Anna S. Nishiya","Vanderson Rocha","Nanci A. Salles","Andreza Aruska de Souza Santos","Martirene A. da Silva","Brian Custer","Kris V. Parag","Manoel Barral-Netto","Moritz U. G. Kraemer","Rafael H. M. Pereira","Oliver G. Pybus","Michael P. Busch","Mıfmmode\\acutea\\elseá\\fircia C. Castro","Christopher Dye","Vıfmmode\\acuteımath\\elseí\\fitor H. Nascimento","Nuno Faria","Ester C. Sabino"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822700,"objectID":"18a5fa46b2ca9d3d7a028ac442f9635c","permalink":"https://mlglobalhealth.github.io/publication/buss-2021-jan/","publishdate":"2022-10-20T12:29:20.477823Z","relpermalink":"/publication/buss-2021-jan/","section":"publication","summary":"","tags":[],"title":"Three-quarters attack rate of SARS-CoV-2 in the Brazilian Amazon during a largely unmitigated epidemic","type":"publication"},{"authors":["Lesley Scott","Nei-Yuan Hsiao","Sikhuline Moyo","Lavanya Singh","Houriiyah Tegally","Graeme Dor","Piet Maes","Oliver G Pybus","Moritz UG Kraemer","Elizaveta Semenova"," others"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822706,"objectID":"465e21f8154a470abe9add3d5512c78e","permalink":"https://mlglobalhealth.github.io/publication/scott-2021-track/","publishdate":"2022-10-20T12:29:22.721112Z","relpermalink":"/publication/scott-2021-track/","section":"publication","summary":"","tags":[],"title":"Track Omicron’s spread with molecular data","type":"publication"},{"authors":["Lewis H Mervin","Simon Johansson","Elizaveta Semenova","Kathryn A Giblin","Ola Engkvist"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822707,"objectID":"45649d39ad72a1f1a65ebd4a80d98bbe","permalink":"https://mlglobalhealth.github.io/publication/mervin-2021-uncertainty/","publishdate":"2022-10-20T12:29:22.94698Z","relpermalink":"/publication/mervin-2021-uncertainty/","section":"publication","summary":"","tags":[],"title":"Uncertainty quantification in drug design","type":"publication"},{"authors":["Mikko S Pakkanen","Xenia Miscouridou","T Berah","Swapnil Mishra","TA Mellan","Samir Bhatt"],"categories":[],"content":"","date":1609459200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822693,"objectID":"3f938f7307adbc0ac127d6ae8d68065b","permalink":"https://mlglobalhealth.github.io/publication/pakkanen-2021-unifying/","publishdate":"2022-10-20T12:29:16.908272Z","relpermalink":"/publication/pakkanen-2021-unifying/","section":"publication","summary":"","tags":[],"title":"Unifying incidence and prevalence under a time-varying general branching process","type":"publication"},{"authors":["Juliette Unwin","Swapnil Mishra","Valerie C. Bradley","Axel Gandy","Thomas A. Mellan","Helen Coupland","Jonathan Ish-Horowicz","Michaela A. C. Vollmer","Charles Whittaker","Sarah L. Filippi","Xiaoyue Xi","Mélodie Monod","Oliver Ratmann","Michael Hutchinson","Fabian Valka","Harrison Zhu","Iwona Hawryluk","Philip Milton","Kylie E. C. Ainslie","Marc Baguelin","Adhiratha Boonyasiri","Nick F. Brazeau","Lorenzo Cattarino","Zulma Cucunuba","Gina Cuomo-Dannenburg","Ilaria Dorigatti","Oliver D. Eales","Jeffrey W. Eaton","Sabine L. van Elsland","Richard G. FitzJohn","Katy A. M. Gaythorpe","William Green","Wes Hinsley","Benjamin Jeffrey","Edward Knock","Daniel J. Laydon","John Lees","Gemma Nedjati-Gilani","Pierre Nouvellet","Lucy Okell","Kris V. Parag","Igor Siveroni","Hayley A. Thompson","Patrick Walker","Caroline E. Walters","Oliver J. Watson","Lilith K. Whittles","Azra C. Ghani","Neil M. Ferguson","Steven Riley","Christl A. Donnelly","Samir Bhatt","Seth Flaxman"],"categories":[],"content":"","date":1606780800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822690,"objectID":"ca3376aa1200064dd201a37ce1173e87","permalink":"https://mlglobalhealth.github.io/publication/unwin-2020-dec/","publishdate":"2022-10-20T12:29:15.124195Z","relpermalink":"/publication/unwin-2020-dec/","section":"publication","summary":"","tags":[],"title":"State-level tracking of COVID-19 in the United States","type":"publication"},{"authors":["Darlan S. Candido","Ingra M. Claro","Jaqueline G. de Jesus","William M. Souza","Filipe R. R. Moreira","Simon Dellicour","Thomas A. Mellan","Louis du Plessis","Rafael H. M. Pereira","Flavia C. S. Sales","Erika R. Manuli","Julien Thıfmmode\\acutee\\elseé\\fizıfmmode\\acutee\\elseé\\fi","Luiz Almeida","Mariane T. Menezes","Carolina M. Voloch","Marcilio J. Fumagalli","Thaıfmmode\\acuteımath\\elseí\\fis M. Coletti","Camila A. M. da Silva","Mariana S. Ramundo","Mariene R. Amorim","Henrique H. Hoeltgebaum","Swapnil Mishra","Mandev S. Gill","Luiz M. Carvalho","Lewis F. Buss","Carlos A. PreteJr.","Jordan Ashworth","Helder I. Nakaya","Pedro S. Peixoto","Oliver J. Brady","Samuel M. Nicholls","Amilcar Tanuri","ıfmmode\\acuteA\\elseÁ\\fitila D. Rossi","Carlos K. V. Braga","Alexandra L. Gerber","Ana Paula de C. Guimarıfmmode\\tildea\\elseã\\fies","Nelson GaburoJr.","Cecila Salete Alencar","Alessandro C. S. Ferreira","Cristiano X. Lima","Josıfmmode\\acutee\\elseé\\fi Eduardo Levi","Celso Granato","Giulia M. Ferreira","Ronaldo S. FranciscoJr.","Fabiana Granja","Marcia T. Garcia","Maria Luiza Moretti","Mauricio W. PerroudJr.","Terezinha M. P. P. Castiıfmmode\\tilden\\elseñ\\fieiras","Carolina S. Lazari","Sarah C. Hill","Andreza Aruska de Souza Santos","Camila L. Simeoni","Julia Forato","Andrei C. Sposito","Angelica Z. Schreiber","Magnun N. N. Santos","Camila Zolini de Sıfmmode\\acutea\\elseá\\fi","Renan P. Souza","Luciana C. Resende-Moreira","Mauro M. Teixeira","Josy Hubner","Patricia A. F. Leme","Rennan G. Moreira","Maurıfmmode\\acuteımath\\elseí\\ficio L. Nogueira","Diagnosis Brazil-Uk Centre for Arbovirus Discovery","Neil M. Ferguson","Silvia F. Costa","Josıfmmode\\acutee\\elseé\\fi Luiz Proenca-Modena","Ana Tereza R. Vasconcelos","Samir Bhatt","Philippe Lemey","Chieh-Hsi Wu","Andrew Rambaut","Nick J. Loman","Renato S. Aguiar","Oliver G. Pybus","Ester C. Sabino","Nuno Rodrigues Faria"],"categories":[],"content":"","date":1598918400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822693,"objectID":"de8f807676bbb4b37cc0405a056a1981","permalink":"https://mlglobalhealth.github.io/publication/candido-2020-sep/","publishdate":"2022-10-20T12:29:17.025097Z","relpermalink":"/publication/candido-2020-sep/","section":"publication","summary":"","tags":[],"title":"Evolution and epidemic spread of SARS-CoV-2 in Brazil","type":"publication"},{"authors":["Alexandra B. Hogan","Britta L. Jewell","Ellie Sherrard-Smith","Juan F. Vesga","Oliver J. Watson","Charles Whittaker","Arran Hamlet","Jennifer A. Smith","Peter Winskill","Robert Verity","Marc Baguelin","John A. Lees","Lilith K. Whittles","Kylie E. C. Ainslie","Samir Bhatt","Adhiratha Boonyasiri","Nicholas F. Brazeau","Lorenzo Cattarino","Laura V. Cooper","Helen Coupland","Gina Cuomo-Dannenburg","Amy Dighe","Bimandra A. Djaafara","Christl A. Donnelly","Jeff W. Eaton","Sabine L. van Elsland","Richard G. FitzJohn","Han Fu","Katy A. M. Gaythorpe","William Green","David J. Haw","Sarah Hayes","Wes Hinsley","Natsuko Imai","Daniel J. Laydon","Tara D. Mangal","Thomas A. Mellan","Swapnil Mishra","Gemma Nedjati-Gilani","Kris V. Parag","Hayley A. Thompson","H. Juliette T. Unwin","Michaela A. C. Vollmer","Caroline E. Walters","Haowei Wang","Yuanrong Wang","Xiaoyue Xi","Neil M. Ferguson","Lucy C. Okell","Thomas S. Churcher","Nimalan Arinaminpathy","Azra C. Ghani","Patrick G. T. Walker","Timothy B. Hallett"],"categories":[],"content":"","date":1598918400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822698,"objectID":"2949b5ae9ec8e62b5eeddfcc2d0fde2b","permalink":"https://mlglobalhealth.github.io/publication/hogan-2020-sep/","publishdate":"2022-10-20T12:29:19.784388Z","relpermalink":"/publication/hogan-2020-sep/","section":"publication","summary":"","tags":[],"title":"Potential impact of the COVID-19 pandemic on HIV, tuberculosis, and malaria in low-income and middle-income countries: a modelling study","type":"publication"},{"authors":["Ellie Sherrard-Smith","Alexandra B. Hogan","Arran Hamlet","Oliver J. Watson","Charlie Whittaker","Peter Winskill","Fatima Ali","Audu B. Mohammad","Perpetua Uhomoibhi","Ibrahim Maikore","Nnenna Ogbulafor","Jamilu Nikau","Mara D. Kont","Joseph D. Challenger","Robert Verity","Ben Lambert","Matthew Cairns","Bhargavi Rao","Marc Baguelin","Lilith K. Whittles","John A. Lees","Sangeeta Bhatia","Edward S. Knock","Lucy Okell","Hannah C. Slater","Azra C. Ghani","Patrick G. T. Walker","Okefu Oyale Okoko","Thomas S. Churcher"],"categories":[],"content":"","date":1598918400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822699,"objectID":"084fafd93443f15a304118cf631c8d37","permalink":"https://mlglobalhealth.github.io/publication/sherrard-smith-2020-sep/","publishdate":"2022-10-20T12:29:20.01116Z","relpermalink":"/publication/sherrard-smith-2020-sep/","section":"publication","summary":"","tags":[],"title":"The potential public health consequences of COVID-19 on malaria in Africa","type":"publication"},{"authors":["William Marciel de Souza","Lewis Fletcher Buss","Darlan da Silva Candido","Jean-Paul Carrera","Sabrina Li","Alexander E. Zarebski","Rafael Henrique Moraes Pereira","Carlos A. Prete","Andreza Aruska de Souza-Santos","Kris V. Parag","Maria Carolina T. D. Belotti","Maria F. Vincenti-Gonzalez","Janey Messina","Flavia Cristina da Silva Sales","Pamela dos Santos Andrade","Vıfmmode\\acuteımath\\elseí\\fitor Heloiz Nascimento","Fabio Ghilardi","Leandro Abade","Bernardo Gutierrez","Moritz U. G. Kraemer","Carlos K. V. Braga","Renato Santana Aguiar","Neal Alexander","Philippe Mayaud","Oliver J. Brady","Izabel Marcilio","Nelson Gouveia","Guangdi Li","Adriana Tami","Silvano Barbosa de Oliveira","Victor Bertollo Gomes Porto","Fabiana Ganem","Walquiria Aparecida Ferreira de Almeida","Francieli Fontana Sutile Tardetti Fantinato","Eduardo Marques Macıfmmode\\acutea\\elseá\\firio","Wanderson Kleber de Oliveira","Mauricio L. Nogueira","Oliver G. Pybus","Chieh-Hsi Wu","Julio Croda","Ester C. Sabino","Nuno Faria"],"categories":[],"content":"","date":159624e4,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822700,"objectID":"98561c8777cda50c2e92692088e48133","permalink":"https://mlglobalhealth.github.io/publication/de-souza-2020-aug/","publishdate":"2022-10-20T12:29:20.594775Z","relpermalink":"/publication/de-souza-2020-aug/","section":"publication","summary":"","tags":[],"title":"Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil","type":"publication"},{"authors":["Patrick G. T. Walker","Charles Whittaker","Oliver J. Watson","Marc Baguelin","Peter Winskill","Arran Hamlet","Bimandra A. Djafaara","Zulma Cucunubıfmmode\\acutea\\elseá\\fi","Daniela Olivera Mesa","Will Green","Hayley Thompson","Shevanthi Nayagam","Kylie E. C. Ainslie","Sangeeta Bhatia","Samir Bhatt","Adhiratha Boonyasiri","Olivia Boyd","Nicholas F. Brazeau","Lorenzo Cattarino","Gina Cuomo-Dannenburg","Amy Dighe","Christl A. Donnelly","Ilaria Dorigatti","Sabine L. van Elsland","Rich FitzJohn","Han Fu","Katy A. M. Gaythorpe","Lily Geidelberg","Nicholas Grassly","David Haw","Sarah Hayes","Wes Hinsley","Natsuko Imai","David Jorgensen","Edward Knock","Daniel Laydon","Swapnil Mishra","Gemma Nedjati-Gilani","Lucy C. Okell","H. Juliette Unwin","Robert Verity","Michaela Vollmer","Caroline E. Walters","Haowei Wang","Yuanrong Wang","Xiaoyue Xi","David G. Lalloo","Neil M. Ferguson","Azra C. Ghani"],"categories":[],"content":"","date":1593561600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822698,"objectID":"5f6e0b776956d6a62bb7a4b7851e8eb5","permalink":"https://mlglobalhealth.github.io/publication/walker-2020-jul/","publishdate":"2022-10-20T12:29:19.668936Z","relpermalink":"/publication/walker-2020-jul/","section":"publication","summary":"","tags":[],"title":"The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries","type":"publication"},{"authors":["Robert Verity","Lucy C. Okell","Ilaria Dorigatti","Peter Winskill","Charles Whittaker","Natsuko Imai","Gina Cuomo-Dannenburg","Hayley Thompson","Patrick G. T. Walker","Han Fu","Amy Dighe","Jamie T. Griffin","Marc Baguelin","Sangeeta Bhatia","Adhiratha Boonyasiri","Anne Cori","Zulma Cucunubıfmmode\\acutea\\elseá\\fi","Rich FitzJohn","Katy Gaythorpe","Will Green","Arran Hamlet","Wes Hinsley","Daniel Laydon","Gemma Nedjati-Gilani","Steven Riley","Sabine van Elsland","Erik Volz","Haowei Wang","Yuanrong Wang","Xiaoyue Xi","Christl A. Donnelly","Azra C. Ghani","Neil M. Ferguson"],"categories":[],"content":"","date":1590969600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822694,"objectID":"ca3a1ac00aaf5817e3e18e48d8835d21","permalink":"https://mlglobalhealth.github.io/publication/verity-2020-jun/","publishdate":"2022-10-20T12:29:17.498623Z","relpermalink":"/publication/verity-2020-jun/","section":"publication","summary":"","tags":[],"title":"Estimates of the severity of coronavirus disease 2019: a model-based analysis","type":"publication"},{"authors":["Seth Flaxman","Swapnil Mishra","Axel Gandy","Juliette Unwin","Thomas A. Mellan","Helen Coupland","Charles Whittaker","Harrison Zhu","Tresnia Berah","Jeffrey W. Eaton","Mélodie Monod","Pablo N. Perez-Guzman","Nora Schmit","Lucia Cilloni","Kylie E. C. Ainslie","Marc Baguelin","Adhiratha Boonyasiri","Olivia Boyd","Lorenzo Cattarino","Laura V. Cooper","Zulma Cucunubá","Gina Cuomo-Dannenburg","Amy Dighe","Bimandra Djaafara","Ilaria Dorigatti","Sabine L. van Elsland","Richard G. FitzJohn","Katy A. M. Gaythorpe","Lily Geidelberg","Nicholas C. Grassly","William D. Green","Timothy Hallett","Arran Hamlet","Wes Hinsley","Ben Jeffrey","Edward Knock","Daniel J. Laydon","Gemma Nedjati-Gilani","Pierre Nouvellet","Kris V. Parag","Igor Siveroni","Hayley A. Thompson","Robert Verity","Erik Volz","Caroline E. Walters","Haowei Wang","Yuanrong Wang","Oliver J. Watson","Peter Winskill","Xiaoyue Xi","Patrick GT Walker","Azra C. Ghani","Christl A. Donnelly","Steven M. Riley","Michaela A. C. Vollmer","Neil M. Ferguson","Lucy C. Okell","Samir Bhatt","Imperial College COVID-19 Response Team"],"categories":[],"content":"","date":1590969600,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822690,"objectID":"733f44fa23293c0a43ce78da25a5be3b","permalink":"https://mlglobalhealth.github.io/publication/flaxman-2020/","publishdate":"2022-10-20T12:29:15.241372Z","relpermalink":"/publication/flaxman-2020/","section":"publication","summary":"Following the emergence of a novel coronavirus1 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lockdowns. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates. Our model relies on fixed estimates of some epidemiological parameters such as the infection fatality rate, does not include importation or subnational variation and assumes that changes in the reproduction number are an immediate response to interventions rather than gradual changes in behavior. Amidst the ongoing pandemic, we rely on death data that is incomplete, with systematic biases in reporting, and subject to future consolidation. We estimate that, for all the countries we consider, current interventions have been sufficient to drive the reproduction number $$R_t$$Rt below 1 (probability $$R_tbackslash,$$Rt\u003c 1.0 is 99.9%) and achieve epidemic control. We estimate that, across all 11 countries, between 12 and 15 million individuals have been infected with SARS-CoV-2 up to 4th May, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions and lockdown in particular have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.","tags":[],"title":"Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe","type":"publication"},{"authors":["Adrien Todeschini","Xenia Miscouridou","François Caron"],"categories":[],"content":"","date":1585699200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655822703,"objectID":"a2c4bc8b6286ca8977a4486a3f095c7c","permalink":"https://mlglobalhealth.github.io/publication/todeschini-2020-apr/","publishdate":"2022-10-20T12:29:21.912801Z","relpermalink":"/publication/todeschini-2020-apr/","section":"publication","summary":"","tags":[],"title":"Exchangeable random measures for sparse and modular graphs with overlapping communities","type":"publication"},{"authors":["Oliver Ratmann","Joseph Kagaayi","Matthew Hall","Tanya Golubchick","Godfrey Kigozi","Xiaoyue Xi","Chris Wymant","Gertrude Nakigozi","Lucie Abeler-Dıfmmode\\ddoto\\elseö\\firner","David Bonsall","Astrid Gall","Anne Hoppe","Paul Kellam","Jeremiah Bazaale","Sarah Kalibbala","Oliver Laeyendecker","Justin Lessler","Fred Nalugoda","Larry W. Chang","Tulio de Oliveira","Deenan Pillay","Thomas C. Quinn","Steven J. Reynolds","Simon E. F. Spencer","Robert Ssekubugu","David Serwadda","Maria J. Wawer","Ronald H. Gray","Christophe Fraser","M. Kate Grabowski","Helen Ayles","Rory Bowden","Vincent Calvez","Myron Cohen","Anne Dennis","Max Essex","Sarah Fidler","Dan Frampton","Richard Hayes","Josh Herbeck","Pontiano Kaleebu","Cissy Kityo","Jairam Lingappa","Vladimir Novitsky","Nick Paton","Andrew Rambaut","Janet Seeley","Deogratius Ssemwanga","Frank Tanser","Tom Lutalo","Ronald Galiwango","Fred Makumbi","Nelson K. Sewankambo","Dorean Nabukalu","Anthony Ndyanabo","Joseph Ssekasanvu","Hadijja Nakawooya","Jessica Nakukumba","Grace N. Kigozi","Betty S. Nantume","Nampijja Resty","Jedidah Kambasu","Margaret Nalugemwa","Regina Nakabuye","Lawrence Ssebanobe","Justine Nankinga","Adrian Kayiira","Gorreth Nanfuka","Ruth Ahimbisibwe","Stephen Tomusange","Ronald M. Galiwango","Margaret Nakalanzi","Joseph O. Otobi","Denis Ankunda","Joseph L. 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