Predictions

ID

Lang

Model name

Author

Repository

Description

3372

KAUST GeoHealth Model

pred_task1_ES.csv

3360

KAUST GeoHealth Model

pred_task3_RN.csv

3369

KAUST GeoHealth Model

pred_task3_DF.csv

3357

KAUST GeoHealth Model

pred_task1_DF.csv

3404

KAUST GeoHealth Model

pred_task1_MG.csv

3396

KAUST GeoHealth Model

pred_task2_RN.csv

2851

CNNLSTM_DengueForecast_Cases_Climate_Data_Driven_Ensemble

Validation test 2 in AL

3356

KAUST GeoHealth Model

pred_task1_RJ.csv

3395

KAUST GeoHealth Model

pred_task1_MA.csv

3386

KAUST GeoHealth Model

pred_task3_SP.csv

3411

KAUST GeoHealth Model

pred_task2_RJ.csv

3392

KAUST GeoHealth Model

pred_task3_MS.csv

3362

KAUST GeoHealth Model

pred_task3_RJ.csv

3342

KAUST GeoHealth Model

pred_task2_PI.csv

3349

KAUST GeoHealth Model

pred_task1_PA.csv

3389

KAUST GeoHealth Model

pred_task1_RS.csv

4699

Ensemble_top_5

2026 forecasts in CE

3401

KAUST GeoHealth Model

pred_task2_PR.csv

3409

KAUST GeoHealth Model

pred_task1_MS.csv

3365

KAUST GeoHealth Model

pred_task2_AC.csv

3407

KAUST GeoHealth Model

pred_task3_MA.csv

3368

KAUST GeoHealth Model

pred_task2_MA.csv

4745

Arima model (3 weeks ahead)

Prediction 3 weeks ahead using data up to epiweek 202527

4175

UERJ-SARIMAX-2025-2

Validation test 2 for UF=RR (UERJ-SARIMAX-2025-2)

2841

CNNLSTM_DengueForecast_Cases_Climate_Data_Driven_Ensemble

Validation test 1 in AL

3403

KAUST GeoHealth Model

pred_task1_MT.csv

3353

KAUST GeoHealth Model

pred_task3_ES.csv

3380

KAUST GeoHealth Model

pred_task1_PI.csv

3377

KAUST GeoHealth Model

pred_task2_CE.csv

186

Model 1 - Weekly and yearly (iid) components

The model is founded on a structural decomposition designed for modeling counting series, employing a Poisson distribution. The log intensity is defined by the sum of weekly and yearly components, where the first one is defined as a AR(1) process and the last one is assumed to be iid.