#counterfactual-prediction News & Analysis

Benchmarking Counterfactual Prediction in Epidemic Time Series with Time-Varying Interventions

Researchers have developed a large-scale benchmark dataset for evaluating causal inference methods in epidemic time-series prediction under dynamic interventions. Using calibrated agent-based models grounded in real-world U.S. county data, the benchmark enables testing of causal inference techniques across static and time-varying treatment scenarios with verifiable counterfactual outcomes.