Epidemic Forecasting

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Epidemic forecasting estimates how disease cases, outbreaks, and healthcare demand will change across places and time horizons, helping public-health teams plan surveillance and response. Methods range from seasonal statistics and neural time-series models to spatial graph learning, mechanistic simulations, and hybrids that combine learned components with epidemic dynamics; some also use wastewater, mobility, or text signals. Work spans diseases such as influenza, COVID-19, dengue, and malaria, with benchmarks increasingly testing rolling, multi-horizon forecasts, uncertainty intervals, and transfer across regions or diseases. Despite promising results from multimodal and hybrid models, simple seasonal or last-value baselines can remain difficult to beat, while shifting transmission, sparse data, uncertain spatial links, and calibrated uncertainty remain major challenges.

Latest papers

36 papers7 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Asymmetric Bidirectional Predictive Dynamics in Google Search and COVID-19 Time Series: A Multi-Horizon Forecast-Error Analysis
Oct 20, 2026Andrei Velichko, Imen MahmoudTime Series Forecasting Epidemic Forecasting
Institute of Physics and Technology, Petrozavodsk State University, 33 Lenina Prospekt, Petrozavodsk 185910, Republic of Karelia, Russia · University of Mannouba, Tunisia · Laboratory of Research in Innovative and Management, Risk, Accounting and Finance
Learning and Forecasting Multiscale Spatiotemporal Epidemic Dynamics with Lagrangian-Eulerian Graph Neural ODEs
Oct 15, 2026Jinyi Duan, Qian Li, Biao TangEpidemic Forecasting Spatial Epidemic Modeling
School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China . · School of Mathematics and Statistics, Xi’an University of Technology, Xi’an, 710054, People’s Republic of China . · Center for Intersection of Mathematics and Life Sciences, Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China .
EpiGuard: An Autonomous Infectious-Disease Early Warning Agent Platform
Oct 14, 2026Tonglong Wei, Zheng Yuan, Lingshuai Lin +3Early Warning Detection Epidemic Forecasting
Shanghai Artificial Intelligence Laboratory
Beyond Single-Pathogen Forecasts: Predicting Shared Respiratory Hospital Burden from Influenza, COVID-19, and RSV
Oct 12, 2026Gaurob Saha, MinJae Woo, Lior RennertEpidemic Forecasting Healthcare
Department of Public Health Sciences and Center for Public Health Modeling and Response, Clemson University, Clemson, SC 29601, USA
Planetary Geospatial Foundation Models: A New Paradigm for Global Public Health
Oct 5, 2026Arbaaz Muslim, Aviv Slobodkin, Katherine Wheeler-Martin +35Epidemic Forecasting Geospatial Foundation Models
Google, Mountain View, CA, USA · Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA · Center for Child Health Services Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA +14
EpiWorld: Grounding LLM Policy Agents in Epidemiological World Models
Oct 2, 2026Zeeshan Memon, Yiqi Su, Kai Shu +2Action-Conditioned World Models Epidemic Forecasting
Department of Computer Science, Emory University, Atlanta, GA, USA · Department of Computer Science, Virginia Tech, Alexandria, VA, USA
Hybrid epidemic simulation framework coupling equation-based and individual-based models
Sep 28, 2026Jaeyoung Kwak, Michael H. Lees, Chin Chun Ooi +1Epidemic Forecasting Agent-Based Modeling
College of Computing and Data Science, Nanyang Technological University, Singapore · Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands · Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore
TERN: A Delta-rule Memory with a Seasonal Reference and Online Adaptation for Epidemic Forecasting
Sep 16, 2026Shunya Nagashima, Yuta FunayamaEpidemic Forecasting Time Series Forecasting
LTS, Inc., Japan
Integrating adaptive human behavior into epidemic models with large language models
Aug 30, 2026Yicheng Mao, Haoyang Li, Rob Deardon +1Epidemic Forecasting Large Language Model-Based Social Simulation
Department of Mathematics and Statistics, University of Calgary, University Drive NW, Calgary, T2N 1N4, Canada · Department of Systems & Information Engineering, University of Virginia, Charlottesville, VA, USA · Faculty of Veterinary Medicine, University of Calgary, University Drive NW, Calgary, T2N 1N4, Canada
Modalities Should Talk to Each Other: Dual-Stream Multimodal Learning for Long-Horizon Influenza Forecasting
Aug 24, 2026Seyed Mohammad Hossein Hashemi, Mohsen Hooshmand, Parvin RazzaghiEpidemic Forecasting Long-Term Time Series Forecasting
Department of Computer Science & Information Technology, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study
Aug 7, 2026Yushu Zou, Ye Li, Johra Moosa +3Epidemic Forecasting Gradient-Boosted Decision Trees
Public Health Ontario, Toronto, Canada · Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Canada · Department of Laboratory Medicine and Pathobiology, University of Toronto, Canada +1
EpiFlow: A framework for improving the utility of wastewater signals for disease forecasting
Aug 7, 2026Aniruddha Adiga, Jingyuan Chou, Gursharn Kaur +8Epidemic Forecasting Probabilistic Forecasting
Biocomplexity Institute, University of Virginia · Department of Computer Science, University of Virginia · Virginia Department of Health +3
TREA-Net: A Transferable Residual Epidemiological Adaptation Network for Dengue Incidence Forecasting
Jul 29, 2026Inesh Shukla, Madhurima Panja, Tanujit Chakraborty +1Epidemic Forecasting Residual Learning
International Institute of Information Technology Hyderabad, India · SAFIR, Sorbonne University Abu Dhabi, United Arab Emirates · Sorbonne Center for Artificial Intelligence, Sorbonne Universit´e, Paris, France
GeoID-PINN: Identifiability-Aware Regional Epidemic Inference with Geographic Coupling
Jul 28, 2026Weixiong Hua, Fan BuEpidemic Forecasting Parameter Identifiability
Department of Biostatistics · University of Michigan · Ann Arbor, Michigan, USA
Long-Memory Reservoir Computing for Data-Scarce Dengue Forecasting
Jul 13, 2026Rahul Goswami, Shinjini Paul, Palash Ghosh +1Epidemic Forecasting Reservoir Computing
Department of Mathematics, Indian Institute of Technology Guwahati, India · SAFIR, Sorbonne University Abu Dhabi, United Arab Emirates · Leiden University, Leiden, South Holland, Netherlands +1
Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning
Jun 20, 2026Diana Guadalupe Gomez, Chenwei Wu, Zhiyi Wang +2Epidemic Forecasting Spatiotemporal Reasoning
University of Michigan Ann Arbor, MI, USA
Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting
Jun 17, 2026Alireza Jafari, Judy Fox, Geoffrey C. Fox +2Epidemic Forecasting LLM-Based Time Series Forecasting
Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904 USA · School of Data Science, University of Virginia, Charlottesville, VA 22904 USA · Biocomplexity Institute and the Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904 USA +1
Evidence Acquisition and Stopping via Lattice Distillation
Jun 8, 2026Yixuan Zhang, Yang Song, Jiayi Zhang +4Epidemic Forecasting Selective Prediction
Section of Health Data Science and AI, Department of Public Health, University of Copenhagen, Copenhagen, Denmark · Section of Health Data Science & AI, Department of Public Health, University of Copenhagen, Copenhagen, Denmark · Rutgers University, New Brunswick, NJ, USA +1
EpiEvolve: Self-Evolving Agents for Streaming Pandemic Forecasting under Regime Shifts
Jun 3, 2026Yiming Lu, Sihang Zeng, Zhengxu Tang +3Online Time Series Forecasting Epidemic Forecasting
Emory University · University of Washington
Hybrid Probabilistic Forecasting of Under-Five Malaria Admissions in Ghana: A Gaussian Process Regression with Holt-Winters Smoothing
May 30, 2026T. Ansah-Narh, Y. Asare Afrane, J. Bremang TandohEpidemic Forecasting Time Series Forecasting
Bayesian Inference of Nonlinear Malaria Dynamics in Ghana via an Ensemble Markov Chain Monte Carlo Sampler
May 30, 2026T. Ansah-Narh, Y. Asare Afrane, J. Bremang TandohEpidemic Forecasting Bayesian Inference
Ghana Space Science and Technology Institute, Ghana Atomic Energy Commission, P. O. Box LG 80, Legon, Accra, Ghana · Department of Medical Microbiology, University of Ghana Medical School, University of Ghana, Accra, Ghana
Spatio-temporal stochastic graph-based learning for infectious disease forecasting
May 28, 2026Luz Stefani Sotomayor Valenzuela, Susanna Cramb, Darren WraithEpidemic Forecasting Probabilistic Forecasting
School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia · QUT Centre for Data Science, Queensland University of Technology, Brisbane, Australia
Transfer Learning using 66 Diseases for Disease Forecasting Applications
May 26, 2026Lauren J Beesley, Alexander C Murph, Dave Osthus +1Multivariate Time Series Forecasting Epidemic Forecasting
Statistics, Los Alamos National Laboratory · Computational Intelligence & Modeling, Los Alamos National Laboratory
SL-BiLEM: Structured Learnable Behavior-in-the-Loop Epidemic Modeling for Forecasting and Policy Evaluation
May 26, 2026Haochun Wang, Sendong Zhao, Jingbo Wang +3Epidemic Forecasting Distribution Shift
Faculty of Computing, Harbin Institute of Technology, Harbin, China
Prospective multi-pathogen disease forecasting using autonomous LLM-guided tree search
May 15, 2026Sarah Martinson, Michael P. Brenner, Martyna Plomecka +3Epidemic Forecasting Language Model-Guided Search Heuristics
Google Research · School of Engineering and Applied Sciences, Harvard University · Google Deepmind +1
EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting
May 12, 2026Madhurima Panja, Danny D'Agostino, Huitao Li +2Multivariate Time Series Forecasting Epidemic Forecasting
Sorbonne University Abu Dhabi · Duke-NUS Medical School, Singapore
SpatialEpiBench: Benchmarking Spatial Information and Epidemic Priors in Forecasting
May 7, 2026Ruiqi Lyu, Alistair Turcan, Bryan WilderEpidemic Forecasting Forecasting Benchmarks
1Carnegie Mellon University
Koopman Representations for Early Outbreak Warning and Minimal Counterfactual Intervention in Multi-Agent Epidemic Simulations
May 3, 2026Florin LeonEpidemic Forecasting Agent-Based Modeling
Department of Computers Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iași, Romania
Generative diffusion models for spatiotemporal influenza forecasting
Apr 27, 2026Joseph Lemaitre, Justin LesslerEpidemic Forecasting Spatiotemporal Forecasting
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA · Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA · Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
IDOBE: Infectious Disease Outbreak forecasting Benchmark Ecosystem
Apr 20, 2026Aniruddha Adiga, Jingyuan Chou, Anshul Chiranth +7Epidemic Forecasting Forecasting Benchmarks
Biocomplexity Institute, University of Virginia, Charlottesville, Virginia, USA · Department of Public and Ecosystem Health Cornell University College of Veterinary Medicine, Ithaca, New York, USA · Johns Hopkins University, Baltimore, Maryland, USA +2

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Asymmetric Bidirectional Predictive Dynamics in Google Search and COVID-19 Time Series: A Multi-Horizon Forecast-Error Analysis

Andrei Velichko, Imen Mahmoud

Institute of Physics and Technology, Petrozavodsk State University, 33 Lenina Prospekt, Petrozavodsk 185910, Republic of Karelia, Russia · University of Mannouba, Tunisia · Laboratory of Research in Innovative and Management, Risk, Accounting and Finance

Time Series Forecasting Epidemic Forecasting Time Series Forecasting with Covariates

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Online search activity is widely used as a digital trace of information seeking during epidemics, but its predictive value is often reduced to correlation, a selected lag, or a single forecast-error score. We examine eight pre-specified Google Trends-COVID-19 pairs in both directions using matched LightGBM forecasts over rolling 400-day windows and horizons of 1-14 days. Log-RMSE gain is combined with forecast-error distribution entropy (FEDE), which captures horizon-dependent changes in the signed error distribution. The resulting directional predictive signature comprises response class, RMSE effect, FEDE endpoint and early-slope responses, persistence across rolling regimes, and horizon profile. For screening candidate directions, we also introduce a relative persistence-weighted directional predictive response strength (DPRS) on a within-study 0-100 scale; 100 denotes the strongest observed response in the comparison set, not an absolute coupling maximum. The pairs show concordant, RMSE-only, FEDE-only, and mixed responses. "loss of smell" -> reported cases is accuracy-dominant, with mean log-RMSE gain 0.104 (about 9.9% equivalent RMSE reduction) and DPRS 100, whereas the reverse direction is FEDE-dominant (D_FEDE=0.048; DPRS=42). "covid test" -> positive rate is FEDE-dominant (D_FEDE=0.039; positive in 72% of windows; DPRS=98) despite negative RMSE gain, while "lockdown" -> stringency is the clearest concordant case (DPRS=78). World-level symptom/case pairs are less persistent. Thus, forecast accuracy and error-distribution dynamics are complementary, predictive effects can be direction- and metric-dependent, and forecast horizon is part of the relationship. Aggregated regime-level patterns should not be extrapolated to individual time points or interpreted as evidence of causality.