Review
Computer Science, Interdisciplinary Applications
Patrick Blonigan, Jaideep Ray, Cosmin Safta
Summary: A simple Bayesian method is presented for inferring and forecasting multiwave outbreaks of COVID-19, using timely epidemiological data to provide short-term forecasts for medical resource planning. The method postulates one- and multiwave infection models, estimates parameters with Markov chain Monte Carlo sampling, and selects between competing disease models using information-theoretic criteria. Demonstrated on COVID-19 outbreaks in California, New Mexico, and Florida, the method is robust to noise, provides useful forecasts with uncertainty bounds, and reliably detects transitions from single-wave to successive surge outbreaks.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2021)
Article
Computer Science, Theory & Methods
Joshua J. Bon, Anthony Lee, Christopher Drovandi
Summary: Delayed-acceptance technique reduces computational effort for Bayesian models with expensive likelihoods by using surrogate likelihoods to avoid evaluating expensive ones. It adaptsively tunes surrogate likelihoods within the sequential Monte Carlo framework to yield better approximations, increasing computational efficiency while avoiding particle degeneracy. This novel algorithm is applied to static Bayesian models for computational efficiency demonstrations on toy and real examples.
STATISTICS AND COMPUTING
(2021)
Article
Agriculture, Dairy & Animal Science
M. A. Stephen, C. R. Burke, N. Steele, J. E. Pryce, S. Meier, P. R. Amer, C. V. C. Phyn, D. J. Garrick
Summary: In this study, the genetic and phenotypic relationships between anogenital distance (AGD) and body stature and fertility traits in dairy cattle were characterized. The results showed that AGD is a moderately heritable trait and is associated with reproductive success in lactating cows.
JOURNAL OF DAIRY SCIENCE
(2023)
Article
Infectious Diseases
Tianyi Luo, Jiaojiao Wang, Quanyi Wang, Xiaoli Wang, Pengfei Zhao, Daniel Dajun Zeng, Qingpeng Zhang, Zhidong Cao
Summary: The study aims to reconstruct the complete transmission chain of the COVID-19 outbreak in Beijing's Xinfadi Market using epidemiological investigation data, contributing to understanding transmission dynamics and risk factors. Results show that the transmission rate of COVID-19 within households is 9.2%, and older people are more susceptible. The accuracy of the reconstructed transmission chain is 67.26%. In the Beef and Mutton Trading Hall of Xinfadi market, most transmission occurs within 20 meters, with an average transmission distance of 13.00 meters and the deepest transmission generation being the 9th.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2022)
Article
Computer Science, Theory & Methods
Alix Marie d'Avigneau, Sumeetpal S. Singh, Lawrence M. Murray
Summary: Efficient MCMC algorithms are crucial in Bayesian inference, especially in the context of parallel tempering. This study addresses the issue of randomly varying local move completion times in multi-processor parallel tempering by imposing real-time deadlines on the parallel local moves and performing exchanges at these deadlines without any processor idling. The methodology of exchanges at real-time deadlines is shown to lead to significant performance enhancements without introducing bias, with potential applications in ABC algorithms for parameter estimation.
STATISTICS AND COMPUTING
(2021)
Article
Mathematics, Interdisciplinary Applications
Evgeny Levi, Radu Craiu
Summary: Scientists utilize large datasets to tackle complex problems and use approximate methods like Approximate Bayesian Computation (ABC) or Bayesian Synthetic Likelihood (BSL) to accelerate computation. However, the number of simulations required remains a limiting factor.
Article
Biochemical Research Methods
Lucille Lopez-Delisle, Jean-Baptiste Delisle
Summary: This study introduces a new tool called baredSC, which uses a Gaussian mixture model to infer the intrinsic expression distribution in scRNA-seq data. The tool can be used to obtain the expression distribution of individual genes and pairs of genes, as well as estimate the correlation between the expressions of two genes. The effectiveness of baredSC is demonstrated through application on simulated data and real biological datasets.
BMC BIOINFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Arpit Kapoor, Eshwar Nukala, Rohitash Chandra
Summary: The major challenge in Bayesian neural networks is to develop effective sampling methods for addressing deep neural networks and big data-related problems. This paper proposes a synergy of neuroevolution and Bayesian neural networks, utilizing particle swarm optimization as efficient proposal distributions in tempered MCMC sampling. The results demonstrate improved prediction accuracy and reduced computational time compared to traditional methods for time-series and pattern classification problems.
APPLIED SOFT COMPUTING
(2022)
Article
Statistics & Probability
Yves Atchade, Liwei Wang
Summary: This paper proposes a fast approximate Markov chain Monte Carlo sampling framework for a large class of sparse Bayesian inference problems. The computational cost per iteration in several regression models is of order O(n(s+J)), which can be further reduced by data sub-sampling. The algorithm is an extension of the asynchronous Gibbs sampler and can be viewed as a form of Bayesian iterated sure independent screening.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
(2023)
Article
Mathematics, Interdisciplinary Applications
Aliaksandr Hubin, Georg Heinze, Riccardo De Bin
Summary: This paper proposes a framework for fitting multivariable fractional polynomial models as special cases of Bayesian generalized nonlinear models. By applying an adapted version of the genetically modified mode jumping Markov chain Monte Carlo algorithm, the Bayesian version of fractional polynomials can be used in any supervised learning task.
FRACTAL AND FRACTIONAL
(2023)
Article
Multidisciplinary Sciences
Melodie 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, H. Juliette T. 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
Summary: Research shows that in the United States, individuals aged 20 to 49 are the main source of COVID-19 transmission, playing a crucial role in the spread of the virus. Therefore, targeting interventions towards this age group is crucial in halting the resurgence of the epidemic and preventing COVID-19 deaths.
Article
Automation & Control Systems
Liam Hodgkinson, Robert Salomone, Fred Roosta
Summary: Implicit integrators from theta-method discretization of overdamped Langevin diffusion SDE were studied for sampling from a log-concave density. The resulting sampling methods were analyzed for theta in [0,1] and various step sizes. Generalizing and extending prior works, geometric ergodicity and stability were proven for theta >= 1/2 across all step sizes. Subsequent sample generation was shown to involve solving a strongly-convex optimization problem, feasible with existing methods, supported by numerical examples.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Automation & Control Systems
Lorenzo Pacchiardi, Ritabrata Dutta
Summary: Bayesian Likelihood-Free Inference (LFI) approaches use model simulations to obtain posterior distributions for stochastic models with intractable likelihood. Approximate Bayesian Computation (ABC) is a popular LFI method that reduces data dimensionality using summary statistics. This work introduces a new way to learn ABC statistics by generating parameter-simulation pairs independently and using Score Matching to train a neural conditional exponential family for likelihood approximation. The likelihood approximation is then used in an MCMC for doubly intractable distributions to draw posterior samples.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Ziwen An, Leah F. South, Christopher Drovandi
Summary: Bayesian synthetic likelihood (BSL) is a method for estimating the posterior distribution of parameters for complex statistical models and stochastic processes. It approximates the likelihood function through model simulation and density estimation, requiring less tuning and simulations compared to other methods.
JOURNAL OF STATISTICAL SOFTWARE
(2022)
Article
Multidisciplinary Sciences
Karen Larson, Georgios Arampatzis, Clark Bowman, Zhizhong Chen, Panagiotis Hadjidoukas, Costas Papadimitriou, Petros Koumoutsakos, Anastasios Matzavinos
Summary: This study introduces a Bayesian uncertainty quantification framework to infer model parameters for disease spreading on networks, showing its potential for robust model fitting and effective identification of disease origins. The results demonstrate the practical relevance of the proposed framework for epidemic prediction and management, as disease-related data become increasingly available.
ROYAL SOCIETY OPEN SCIENCE
(2021)
Article
Microbiology
Sadaf Rasheed Mughal, Sadia Ambreen Niazi, Thuy Do, Steven C. Gilbert, Xavier Didelot, David R. Radford, David Beighton
Summary: The aim of this study was to use high-throughput sequencing techniques to investigate the taxonomy of Actinomyces naeslundii and its closely related species. The strains were classified as A. naeslundii and A. oris based on MLST data analysis. Whole genome sequencing was performed on selected strains of A. oris and A. naeslundii, and comparative genomic analysis was carried out. The results showed that A. oris forms six distinct groups, while A. naeslundii forms three. The correct designation of isolates will help in the identification of clinical Actinomyces isolates found in dental plaque and accelerate further research on the biochemical characterization and pathogenesis of this group of microorganisms.
Article
Veterinary Sciences
Mostafa Y. Abdel-Glil, Helmut Hotzel, Herbert Tomaso, Xavier Didelot, Christian Brandt, Christian Seyboldt, Joerg Linde, Stefan Schwarz, Heinrich Neubauer, Hosny El-Adawy
Summary: Campylobacter fetus subsp. venerealis (Cfv) is the cause of bovine genital campylobacteriosis (BGC), which is a trade-relevant disease listed by the World Organization for Animal Health (WOAH). This study aimed to investigate the genomic diversity of German Cfv strains isolated from different federal states in Germany. Whole-genome sequencing and phylogenetic analysis were conducted on 63 Cfv strains collected between 1985 and 2015, and compared with international Cfv isolates. The results showed a genetically conserved Cfv population in Germany, with a lineage that emerged in the nineteenth century and diversified over time. The control interventions in Germany have been successful, as no outbreaks have been reported since 2015.
FRONTIERS IN VETERINARY SCIENCE
(2023)
Article
Microbiology
Kate E. Dingle, Jane Freeman, Xavier Didelot, T. Phuong Quan, David W. Eyre, Jeremy Swann, William D. Spittal, Emma V. Clark, Keith A. Jolley, A. Sarah Walker, Mark H. Wilcox, Derrick W. Crook
Summary: Clostridioides difficile is a significant cause of healthcare-associated infections, with multidrug-resistant strains causing high-mortality outbreaks. Cephalosporin treatment is a known risk factor, and antimicrobial stewardship is important for control. This study investigated the correlation between cephalosporin MICs, amino acid substitutions in penicillin binding proteins, and fluoroquinolone resistance in C. difficile.
Article
Multidisciplinary Sciences
Michelle Kendall, Daphne Tsallis, Chris Wymant, Andrea Di Francia, Yakubu Balogun, Xavier Didelot, Luca Ferretti, Christophe Fraser
Summary: The NHS COVID-19 app, launched in England and Wales in September 2020, had a Bluetooth-based contact tracing functionality to reduce the transmission of SARS-CoV-2. The study shows that user engagement and the app's impact on the epidemic varied based on social and epidemic characteristics. The authors also discuss the interaction and complementarity of manual and digital contact tracing approaches.
NATURE COMMUNICATIONS
(2023)
Article
Infectious Diseases
Sangeeta Bhatia, Jack Wardle, Rebecca K. Nash, Pierre Nouvellet, Anne Cori
Summary: The evolution of SARS-CoV-2 indicates that emerging variants can hinder the global COVID-19 response. A novel method is presented to estimate the transmission advantage of new variants compared to a reference variant by combining information from multiple locations and over time. Extensive simulation studies demonstrate the effectiveness of the method and provide guidance on its optimal use and interpretation. The method's open-source software implementation allows for rapid exploration of spatial and temporal variations in estimated transmission advantage, with estimations provided for the Alpha and Delta variants.
Review
Infectious Diseases
Jack Wardle, Sangeeta Bhatia, Moritz U. G. Kraemer, Pierre Nouvellet, Anne Cori
Summary: Reliable estimation of human mobility is crucial for understanding the spatial spread of infectious diseases and effectively controlling them. However, data on human mobility at an appropriate temporal or spatial resolution are often unavailable, leading to the use of model-derived mobility proxies. This study reviewed data sources and mobility models used to characterize human movement in Africa and conducted simulation studies to assess the impact of using mobility proxies on predicting disease spread. The findings showed limited empirical measures of human mobility in Africa with significant implications for epidemic dynamics.
Editorial Material
Infectious Diseases
Anne Cori, Britta Lassmann, Pierre Nouvellet
Article
Infectious Diseases
Luis Roger Esquivel Gomez, Cyril Savin, Voahangy Andrianaivoarimanana, Soloandry Rahajandraibe, Lovasoa Nomena Randriantseheno, Zhemin Zhou, Arthur Kocher, Xavier Didelot, Minoarisoa Rajerison, Denise Kuehnert
Summary: Plague reappeared in the city of Mahajanga, Madagascar in 1991 after a plague-free period of over 60 years. This study used a phylogeographic model to analyze the genome sequences of Yersinia pestis and identified two migrations from the Central Highlands that caused the outbreaks in the 1990s. The pathogen likely survived in wild reservoirs before spillover to humans.
PLOS NEGLECTED TROPICAL DISEASES
(2023)
Article
Public, Environmental & Occupational Health
Natsuko Imai, Thomas Rawson, Edward S. Knock, Raphael Sonabend, Yasin Elmaci, Pablo N. Perez-Guzman, Lilith K. Whittles, Divya Thekke Kanapram, Katy A. M. Gaythorpe, Wes Hinsley, Bimandra A. Djaafara, Haowei Wang, Keith Fraser, Richard G. FitzJohn, Alexandra B. Hogan, Patrick Doohan, Azra C. Ghani, Neil M. Ferguson, Marc Baguelin, Anne Cori
Summary: The UK's strategy of delaying the second dose of the COVID-19 vaccine by 12 weeks and providing single-dose protection to a larger population has been effective in reducing hospitalizations and deaths.
LANCET PUBLIC HEALTH
(2023)
Article
Multidisciplinary Sciences
Sangeeta Bhatia, Kris V. Parag, Jack Wardle, Rebecca K. Nash, Natsuko Imai, Sabine L. Van Elsland, Britta Lassmann, John S. Brownstein, Angel Desai, Mark Herringer, Kara Sewalk, Sarah Claire Loeb, John Ramatowski, Gina Cuomo-Dannenburg, Elita Jauneikaite, H. Juliette T. Unwin, Steven Riley, Neil Ferguson, Christl A. Donnelly, Anne Cori, Pierre Nouvellet
Summary: This study retrospectively evaluated COVID-19 forecasts produced for 81 countries between March 8th and November 29th, 2020. The results showed that both short- and medium-term forecasts accurately captured the epidemic trajectory across different waves of COVID-19 infections. Simple transmission models calibrated with routine disease surveillance data reliably predicted the epidemic situation in multiple countries.
Article
Multidisciplinary Sciences
Pablo N. N. Perez-Guzman, Edward Knock, Natsuko Imai, Thomas Rawson, Yasin Elmaci, Joana Alcada, Lilith K. K. Whittles, Divya Thekke Kanapram, Raphael Sonabend, Katy A. M. Gaythorpe, Wes Hinsley, Richard G. G. FitzJohn, Erik Volz, Robert Verity, Neil M. M. Ferguson, Anne Cori, Marc Baguelin
Summary: In this study, the epidemiological properties of different SARS-CoV-2 variants in England until early 2022 were examined using mathematical modeling. The impact of control measures, including non-pharmaceutical interventions, therapeutics, and vaccination, on virus transmission and severity was quantified. Each successive variant had a higher transmissibility, with Omicron being the most transmissible. NPIs played a crucial role in controlling virus transmission. Immune escape properties of Omicron reduced population immunity. Alpha had the highest infection fatality ratio, followed by Delta, Wildtype, and Omicron. Continued surveillance and long-term strategies for maintaining effective immunity are important to manage future variants.
NATURE COMMUNICATIONS
(2023)
Correction
Infectious Diseases
Sangeeta Bhatia, Natsuko Imai, Oliver J. Watson, Auss Abbood, Philip Abdelmalik, Thijs Cornelissen, Stephane Ghozzi, Britta Lassmann, Radhika Nagesh, Manon L. Ragonnet-Cronin, Johannes Christof Schnitzler, Moritz Ug Kraemer, Simon Cauchemez, Pierre Nouvellet, Anne Cori
LANCET INFECTIOUS DISEASES
(2023)
Article
Multidisciplinary Sciences
David Helekal, Matt Keeling, Yonatan H. Grad, Xavier Didelot
Summary: Increasing levels of antibiotic resistance pose a major threat to public health. Understanding the costs and benefits of resistance can lead to better use of antibiotics and prevent the spread of resistance.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2023)
Article
Virology
Xavier Didelot, Vinicius Franceschi, Simon D. W. Frost, Ann Dennis, Erik M. Volz
Summary: Inference of effective population size from genomic data can provide insights into demographic history and epidemiological dynamics. A nonparametric approach based on latent process models is developed to estimate the population size dynamics, optimizing parameters using out-of-sample prediction accuracy. The methodology is demonstrated using simulation experiments and applied to HIV-1 and SARS-CoV-2 datasets to estimate the impact of interventions on epidemic dynamics.
Article
Biochemical Research Methods
Xavier Didelot, David Helekal, Michelle Kendall, Paolo Ribeca
Summary: The ability to distinguish imported cases from locally acquired cases is important for selecting public health control strategies. This study proposes an alternative approach using genomic data from a specific location to detect imported cases by comparing them with previous cases from the same location.
