+Updated 2024/11/20 14:50 +
+The US RSV Forecast Hub is as a collaborative forecasting effort to +produce weekly short-term forecasts of weekly laboratory-confirmed RSV +hospital admissions for the US and individual states. Each week, +participants are asked to provide national- and jurisdiction-specific +probabilistic forecasts of the weekly number of confirmed RSV +hospitalizations for the following four weeks. The US RSV Forecast Hub +is open to any team willing to provide projections at the right temporal +and spatial scales. We only require that participating teams share point +estimates and uncertainty bounds, along with a short model description +and answers to a list of key questions about design.
+Those interested in participating, please see the README file in the +Github +repository.
+If you are interested in longer-term scenario projections of RSV in +the US, please take a look at the US RSV Scenario Modeling +Hub.
+RSV hospital admission forecast for the United States +(national-level) for all age groups (0-130yr), weekly incident +admissions:
+ + +Note: The dashed red line represents the peak of national RSV +hospitalizations during the 2023-24 season.
+
State-level forecasts
+ + +National-level forecasts by Age
+ + + + +
Evaluation will begin 4 weeks after the first model submissions.
+
Previous weeks’ forecasts are available in the archive and can be +accessed in the links below. These forecasts are not updated with +updated ground truth data, thus the ground truth data may differ between +them as data are back-filled.
+
The Respiratory Syncytial Virus Hospitalization Surveillance Network +(RSV-NET) is a network that conducts active, population-based +surveillance for laboratory-confirmed RSV-associated hospitalizations in +children younger than 18 years of age and adults. The network currently +includes 58 counties in 12 states that participate in the Emerging +Infections Program (California, Colorado, Connecticut, Georgia, +Maryland, Minnesota, New Mexico, New York, Oregon, and Tennessee) or the +Influenza Hospitalization Surveillance Program (Michigan and Utah). Age- +and state-specific data on laboratory-confirmed RSV hospitalization +rates are available for 12 states and the US from RSV-NET spanning +2017-18 to present (RSV-NET CDC +Webpage). Age-specific weekly rates per 100,000 population are +reported in this system.
+The data has been standardized and posted on the rsv-forecast-hub +GitHub target-data/ +folder and is updated weekly. The target in this data is the weekly +number of hospitalizations in each given state (inc_hosp variable), for +all ages and for each age group. To obtain counts, we have converted +RSV-NET weekly rates based on state population sizes. This method +assumes that RSV-NET hospitals are representative of the whole state. To +obtain national US counts, we have used the rates provided for the +“overall RSV-NET network”. The data covers 2017-present. Reported age +groups include: [0-6 months], [6-12 months], [1-2 yr], [2-4 yr], [5-17 +yr], [18-49 yr], [50-64 yr], and 65+ years. The standardized dataset +includes week-, state-, and age-specific RSV counts (the target), rates, +and population sizes.
+
| Team | +Model | +Brief Description | +
|---|---|---|
| CEPH Lab at Indiana University | +Rtrend RSV | +A renewal equation method based on Bayesian +estimation of Rt from past hospitalization data. | +
| Columbia University | +RSV_SVIRS | +Age-structured SVIRS model coupled with Ensemble +Adjustment Kalman Filter. Inputs CDC RSV-NET, POLYMOD contact matrix, +and seasonal absolute humidity | +
| The Center for Systems Science and Engineering at Johns +Hopkins University | +CSSE Multi-pathogen Model for RSV | +A data-driven multipathogen modeling approach to +forecast RSV hospitalizations | +
| Predictive Science Inc. | +Package for Respiratory Disease Open-source +Forecasting | +We fit and extrapolate an age-stratified SIR +compartmental model with four levels of natural immunity as well as +infant/elder vaccination. | +
| UGA_flucast | +INFLAenza | +A spatial time-series model that uses the R-INLA +package for estimating forecast posterior distributions. | +
| University of Michigan, Computer Science and +Engineering | +DeepOutbreak | +Deep neural network model with conformal +predictions. | +
+Updated 2024/12/04 18:07 +
+The US RSV Forecast Hub is as a collaborative forecasting effort to +produce weekly short-term forecasts of weekly laboratory-confirmed RSV +hospital admissions for the US and individual states. Each week, +participants are asked to provide national- and jurisdiction-specific +probabilistic forecasts of the weekly number of confirmed RSV +hospitalizations for the following four weeks. The US RSV Forecast Hub +is open to any team willing to provide projections at the right temporal +and spatial scales. We only require that participating teams share point +estimates and uncertainty bounds, along with a short model description +and answers to a list of key questions about design.
+Those interested in participating, please see the README file in the +Github +repository.
+If you are interested in longer-term scenario projections of RSV in +the US, please take a look at the US RSV Scenario Modeling +Hub.
+RSV hospital admission forecast for the United States +(national-level) for all age groups (0-130yr), weekly incident +admissions:
+ + +Note: The dashed red line represents the peak of national RSV +hospitalizations during the 2023-24 season.
+
Previous weeks’ forecasts are available in the archive and can be +accessed in the links below. These forecasts are not updated with +updated ground truth data, thus the ground truth data may differ between +them as data are back-filled.
+
The Respiratory Syncytial Virus Hospitalization Surveillance Network +(RSV-NET) is a network that conducts active, population-based +surveillance for laboratory-confirmed RSV-associated hospitalizations in +children younger than 18 years of age and adults. The network currently +includes 58 counties in 12 states that participate in the Emerging +Infections Program (California, Colorado, Connecticut, Georgia, +Maryland, Minnesota, New Mexico, New York, Oregon, and Tennessee) or the +Influenza Hospitalization Surveillance Program (Michigan and Utah). Age- +and state-specific data on laboratory-confirmed RSV hospitalization +rates are available for 12 states and the US from RSV-NET spanning +2017-18 to present (RSV-NET CDC +Webpage). Age-specific weekly rates per 100,000 population are +reported in this system.
+The data has been standardized and posted on the rsv-forecast-hub +GitHub target-data/ +folder and is updated weekly. The target in this data is the weekly +number of hospitalizations in each given state (inc_hosp variable), for +all ages and for each age group. To obtain counts, we have converted +RSV-NET weekly rates based on state population sizes. This method +assumes that RSV-NET hospitals are representative of the whole state. To +obtain national US counts, we have used the rates provided for the +“overall RSV-NET network”. The data covers 2017-present. Reported age +groups include: [0-6 months], [6-12 months], [1-2 yr], [2-4 yr], [5-17 +yr], [18-49 yr], [50-64 yr], and 65+ years. The standardized dataset +includes week-, state-, and age-specific RSV counts (the target), rates, +and population sizes.
+
| Team | +Model | +Brief Description | +
|---|---|---|
| CEPH Lab at Indiana University | +Rtrend RSV | +A renewal equation method based on Bayesian +estimation of Rt from past hospitalization data. | +
| Columbia University | +RSV_SVIRS | +Age-structured SVIRS model coupled with Ensemble +Adjustment Kalman Filter. Inputs CDC RSV-NET, POLYMOD contact matrix, +and seasonal absolute humidity | +
| The Center for Systems Science and Engineering at Johns +Hopkins University | +CSSE Multi-pathogen Model for RSV | +A data-driven multipathogen modeling approach to +forecast RSV hospitalizations | +
| Metaculus | +Metaculus Community Prediction | +A recency-weighted average of predictions made by +forecasters on the Metaculus prediction platform. Missing forecasts are +linearly interpolated. | +
| Predictive Science Inc. | +Package for Respiratory Disease Open-source +Forecasting | +We fit and extrapolate an age-stratified SIR +compartmental model with four levels of natural immunity as well as +infant/elder vaccination. | +
| UGA_flucast | +INFLAenza | +A spatial time-series model that uses the R-INLA +package for estimating forecast posterior distributions. | +
-Updated 2024/12/04 18:07 +Updated 2024/12/05 19:19
RSV hospital admission forecast for the United States (national-level) for all age groups (0-130yr), weekly incident admissions:
- - + +Note: The dashed red line represents the peak of national RSV hospitalizations during the 2023-24 season.
State-level forecasts
+ + +National-level forecasts by Age
+ +
Previous weeks’ forecasts are available in the archive and can be @@ -3743,6 +3634,10 @@