Cover Image

Leveraging Synthetic and Genetic Data to Improve Epidemic Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Osthus, Dave, Murph, Alexander C., Goldberg, Emma E., Beesley, Lauren J., Fischer, William M., Parikh, Nidhi K., Castro, Lauren A.
Format:	Preprint
Published:	2026
Subjects:	Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Transfer Learning using 66 Diseases for Disease Forecasting Applications
by: Beesley, Lauren J, et al.
Published: (2026)

Mapping Incidence and Prevalence Peak Data for SIR Forecasting Applications
by: Murph, Alexander C., et al.
Published: (2024)

EpiFFORMA: Disease-Agnostic Ensemble Weighting for Forecasting Emerging Epidemic Time Series without Historical Data
by: Murph, Alexander C., et al.
Published: (2025)

Code for the publication "Beyond Equal Weights: A Disease-agnostic Approach to Ensemble Learning for Infectious Disease Forecasting"
by: Murph, Alexander C., et al.
Published: (2025)

Bayesian Statistical Inversion for High-Dimensional Computer Model Output and Spatially Distributed Counts
by: Barnett, Steven D., et al.
Published: (2025)

Moving Towards Automated Interstellar Boundary Explorer Data Selection with LOTUS
by: Stricklin, Madeline A., et al.
Published: (2024)

Improving Outbreak Forecasts Through Model Augmentation
by: Gibson, Graham C., et al.
Published: (2025)

Statistical methods for partitioning ribbon and globally-distributed flux using data from the Interstellar Boundary Explorer
by: Beesley, Lauren J., et al.
Published: (2023)

Does Spatial Information Improve Influenza Forecasting?
by: Thivierge, Gabrielle, et al.
Published: (2024)

Inferring Epidemics from Multiple Dependent Data via Pseudo-Marginal Methods
by: Corbella, Alice, et al.
Published: (2022)

Monotonic warpings for additive and deep Gaussian processes
by: Barnett, Steven D., et al.
Published: (2024)

Data (in)equities in data science: Dissecting systemic and systematic biases in pulse oximetry
by: Rountree, Lillian, et al.
Published: (2026)

Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations
by: Murph, Alexander C., et al.
Published: (2023)

Modelling Under-Reported Data: Pitfalls of Naïve Approaches and a New Statistical Framework for Epidemic Curve Reconstruction
by: Slater, Justin J., et al.
Published: (2025)

A Machine Learning Framework for Constructing Heterogeneous Contact Networks: Implications for Epidemic Modelling
by: Kearney, Luke Murray, et al.
Published: (2026)

Just add water: A simple floral bud injection method for stable Agrobacterium ‐mediated transformation in two ecotypes of Mimulus guttatus
by: Lauren E. Stanley, et al.
Published: (2025)

Estimating Time-Varying Epidemic Severity Rates with Adaptive Deconvolution
by: Goldwasser, Jeremy, et al.
Published: (2025)

Zombie Epidemic -- on Modeling the Effect of Interventions
by: Ek, Kaisa, et al.
Published: (2024)

Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo
by: Fadikar, Arindam, et al.
Published: (2024)

Investigating the HIV Epidemic in Miami Using a Novel Approach for Bayesian Inference on Partially Observed Networks
by: Goyal, Ravi, et al.
Published: (2024)

Are they two seeds in a pod? Comparing seed rain recovery in grasslands using artificial grass carpets versus sticky traps
by: Lauren L. Sullivan, et al.
Published: (2026)

How dependent are quantitative volcanic ash concentration and along‐flight dosage forecasts to model structural choices?
by: Lauren A. James, et al.
Published: (2024)

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2025)

Evidence of Fine‐Scale Genetic Structure in Tiger Sharks (Galeocerdo cuvier) Highlights the Importance of Stratified Sampling Regimes
by: Jessica J. Fish, et al.
Published: (2025)

Movement of insurgent gangs: A Bayesian kernel density model for incomplete temporal data
by: Sriram, Karthik, et al.
Published: (2024)

Automated Image Color Mapping for a Historic Photographic Collection
by: Arnold, Taylor, et al.
Published: (2024)

Semi-Markov Models with Particle-Based Bayesian Inference for Epidemics
by: Aschermayr, Patrick, et al.
Published: (2026)

Towards Enhancing Data Equity in Public Health Data Science
by: Wang, Yiran, et al.
Published: (2025)

Exploring the Potential Role of Generative AI in the TRAPD Procedure for Survey Translation
by: Metheney, Erica Ann, et al.
Published: (2024)

Generative AI as a Safety Net for Survey Question Refinement
by: Metheney, Erica Ann, et al.
Published: (2025)

Evaluating the Use of Large Language Models as Synthetic Social Agents in Social Science Research
by: Madden, Emma Rose
Published: (2025)

Causal Inference Using Augmented Epidemic Models
by: Bong, Heejong, et al.
Published: (2024)

Forecasting Tangency Portfolios and Investing in the Minimum Euclidean Distance Portfolio to Maximize Out-of-Sample Sharpe Ratios
by: Alexander, Nolan, et al.
Published: (2026)

Chimeric Forecasting: Blending Human Judgment and Computational Methods for Improved, Real-time Forecasts of Influenza Hospitalizations
by: McAndrew, Thomas, et al.
Published: (2024)

Tracking the Spatiotemporal Spread of the Ohio Overdose Epidemic with Topological Data Analysis
by: Bermingham, Nicholas, et al.
Published: (2025)

When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
by: Kuh, Swen, et al.
Published: (2026)

Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes
by: Liu, Xueqing, et al.
Published: (2023)

Leveraging Large Language Models to Improve Precision in Randomized Controlled Trials
by: Lowe, Jaylin, et al.
Published: (2026)

A web-based user interface for Fam3PRO, a multi-gene, multi-cancer risk prediction model for families with cancer history
by: Chen, Xueying, et al.
Published: (2025)

Frequentist Inference for Semi-mechanistic Epidemic Models with Interventions
by: Bong, Heejong, et al.
Published: (2023)