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Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Information Theory, Inference, and Learning Algorithms
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Bias correction in species distribution models: pooling survey and collection data for multiple species
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A practical guide to structured expert elicitation using the IDEA protocol
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A guide to eliciting and using expert knowledge in Bayesian ecological models
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The ‘Heuristics and Biases’ Bias in Expert Elicitation
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Particle Markov Chain Monte Carlo Methods
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SMC2: An Efficient Algorithm for Sequential Analysis of State Space Models
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Eliciting Expert Knowledge in Conservation Science
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Bayesian Model Choice: Asymptotics and Exact Calculations
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The Bernstein-Von-Mises theorem under misspecification
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Exceptional Paper—Probability Encoding in Decision Analysis
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Flexible Modeling of Epidemics with an Empirical Bayes Framework
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Revealing the True Incidence of Pandemic A(H1N1)pdm09 Influenza in Finland during the First Two Seasons — An Analysis Based on a Dynamic Transmission Model
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Bayesian reconstruction of transmission within outbreaks using genomic variants
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Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions
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Community Mitigation Guidelines to Prevent Pandemic Influenza — United States, 2017
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THE POWER OF EXPERT OPINION IN ECOLOGICAL MODELS USING BAYESIAN METHODS: IMPACT OF GRAZING ON BIRDS
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Online Flutracking Survey of Influenza-like Illness during Pandemic (H1N1) 2009, Australia
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Modeling Influenza Virus Infection: A Roadmap for Influenza Research
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Ebola virus disease in the Democratic Republic of the Congo, 1976-2014
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The Prior Can Often Only Be Understood in the Context of the Likelihood
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