Predictions
ID
Lang
Model name
Repository
Description
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202531
Model 2 - Weekly and yearly (rw1) 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 follows a RW(1) process.
UERJ-SARIMAX-2025-2
Validation test 2 for UF=AC (UERJ-SARIMAX-2025-2)
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.
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202539
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202534
LSTM-RF model
LSTM-RF predictions for Mosqlimate Sprint 2025
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202525
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202524
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202533
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202535
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202538
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202536
LSTM model for Infodengue Sprint
Predictions for 2024 in AM using the comb_att_n architecture
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202530
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202541
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202532
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state AL.
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202537
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202544
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202528
LNCC-CLiDENGO-2025-1
Validation test 3 for UF=RR (LNCC-CLiDENGO model)
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202529
Cornell PEH - NegBinom Baseline model
Validation 2 (NegBinom Baseline model)
Arima model (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202510
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.
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202540
LSTM model with climate covariates (3 weeks ahead)
Prediction 3 weeks ahead using data up to epiweek 202543
3054 predictions
https://api.mosqlimate.org/api/registry/predictions/?page=6&per_page=30&
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