Predictions


ID

Lang

Model name

Author

Repository

Predict date Type Model ID

Description

268

Model 2 - Weekly and yearly (rw1) components

2024-08-15 Model 28

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 follows a RW(1) process.

Dengue oracle - M2

2025-09-08 Model 156

2026 forecasts in PA

GHR Model 2025

2025-07-31 Model 135

GHR Model 2025 Validation Test 3 - PR

252

Model 1 - Weekly and yearly (iid) components

2024-08-15 Model 27

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.

KAUST GeoHealth Model

2025-08-07 Model 141

pred_task2_RS.csv

Cornell PEH - NegBinom Baseline model

2025-07-29 Model 139

Validation 3 (NegBinom Baseline model)

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202501

ISI_Dengue_Model

2025-08-21 Model 134

2024-25 Dengue Forecast for Roraima

42

Deep learning model using BI-LSTM Layers

2023-09-12 Model 6

Forecast de novos casos para o geocode 2408102 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode e das cidades clusterizadas com ele

977

2025 sprint test - Sarima

2025-07-22 Model 108

2025 - Sarima - Preditores da picada

GHR Model 2025

2025-07-31 Model 135

GHR Model 2025 Validation Test 1 - SP

Cornell PEH - NegBinom Baseline model

2025-07-29 Model 139

Validation 3 (NegBinom Baseline model)

193

Model 1 - Weekly and yearly (iid) components

2024-08-15 Model 27

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.

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202521

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202530

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202542

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202531

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202526

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202519

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202536

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202514

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202508

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202531

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202527

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202522

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202516

LSTM model with climate covariates (3 weeks ahead)

2025-11-10 Model 161

Prediction 3 weeks ahead using data up to epiweek 202503

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202542

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202536

Arima model (3 weeks ahead)

2025-11-11 Model 160

Prediction 3 weeks ahead using data up to epiweek 202506

3054 predictions

https://api.mosqlimate.org/api/registry/predictions/?page=1&per_page=30&


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