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Merge pull request cdcepi#17 from cdcepi/main
merge latest model forecasts
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‎.github/workflows/update_target_data.yml‎

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use-public-rspm: true
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- name: Install dependencies
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run: |
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install.packages(c("dplyr", "lubridate", "RSocrata"))
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install.packages("RSocrata", repos = c("https://chicago.r-universe.dev", "https://cloud.r-project.org"))
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install.packages(c("dplyr", "lubridate"))
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shell: Rscript {0}
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- name: Generate target csv files
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run: Rscript target-data/get_target_data.R

‎auxiliary-data/target-data-archive/target-hospital-admissions_2025-03-22.csv‎

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‎auxiliary-data/target-data-archive/target-hospital-admissions_2025-03-29.csv‎

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‎auxiliary-data/target-data-archive/target-hospital-admissions_2025-04-05.csv‎

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‎auxiliary-data/target-data-archive/target-hospital-admissions_2025-04-12.csv‎

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‎auxiliary-data/target-data-archive/target-hospital-admissions_2025-04-19.csv‎

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‎model-metadata/CADPH-FluCAT_Ensemble.yml‎

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@@ -22,6 +22,6 @@ methods_long: "An ensemble of several time series forecasts including; (1) autor
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ensemble_of_models: true
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ensemble_of_hub_models: false
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model_version: "1.1"
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website_url: "https://calcat.covid19.ca.gov/cacovidmodels/"
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website_url: "http://calcat.cdph.ca.gov/"
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team_funding: "The views and opinions expressed by the authors are their own and do not necessarily represent the views and opinions of the California Department of Public Health or the California Health and Human Services Agency."
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‎model-metadata/UVAFluX-OptimWISE.yml‎

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team_name: "UVAFluX"
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team_abbr: "UVAFluX"
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model_name: "OptimWISE: ensemble forecasting model that learns optimal weights for combining probabilistic forecasts from multiple models by minimizing a regularized Weighted Interval Score (WIS)."
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model_abbr: "OptimWISE"
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model_version: "1.0"
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model_contributors: [
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{
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"name": "Nibir Chandra Mandal",
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"affiliation": "UVA",
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"email": "wyr6fx@virginia.edu"
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},
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{
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"name": "Gursharn Kaur",
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"affiliation": "UVA",
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"email": "gursharn@virginia.edu"
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},
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{
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"name": "Aniruddha Adiga",
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"affiliation": "UVA",
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"email": "aniruddha@virginia.edu"
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},
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{
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"name": "Bryan Lewis",
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"affiliation": "UVA",
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"email": "bl4zc@virginia.edu"
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},
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{
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"name": "Madhav Marathe",
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"affiliation": "UVA",
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"email": "marathe@virginia.edu"
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},
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{
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"name": "Srinivasan Venkatramanan",
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"affiliation": "UVA",
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"email": "srini@virginia.edu"
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}
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]
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website_url: "https://biocomplexity.virginia.edu/institute/divisions/network-systems-science-and-advanced-computing"
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license: "CC-BY-4.0"
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citation: "citation"
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team_funding: "funding"
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designated_model: False
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methods: "Ensemble model aggregating forecasts from five models: lstm, ARIMA, ENKF, Phase-Informed, ES_LO"
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data_inputs: "Weekly incident flu hospitalizations from HHS"
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methods_long: "Optim-WISE is an ensemble forecasting model that learns optimal weights for combining quantile forecasts from five models by minimizing the Weighted Interval Score (WIS) over recent training weeks (upto 4 weeks). It uses optimization with regularization to ensure stable weights, producing a final probabilistic forecast tailored to each location and forecast horizon."
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ensemble_of_models: True
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ensemble_of_hub_models: false

‎model-output/CADPH-FluCAT_Ensemble/2025-03-29-CADPH-FluCAT_Ensemble.csv‎

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"reference_date","target","horizon","target_end_date","location","output_type","output_type_id","value"
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‎model-output/CADPH-FluCAT_Ensemble/2025-04-05-CADPH-FluCAT_Ensemble.csv‎

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"reference_date","target","horizon","target_end_date","location","output_type","output_type_id","value"
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54+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.25,222.060153703265
55+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.3,239.571507661811
56+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.35,257.559483596127
57+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.4,276.028709871705
58+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.45,295.139317832658
59+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.5,316.699486193259
60+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.55,337.555374136497
61+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.6,361.005332600727
62+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.65,387.806612186222
63+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.7,418.071682361574
64+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.75,453.659206761434
65+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.8,497.004395974988
66+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.85,552.771901871541
67+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.9,634.888633050642
68+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.95,779.677595706191
69+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.975,930.58276827436
70+
2025-04-05,"wk inc flu hosp",2,2025-04-19,"06","quantile",0.99,1144.23457943167
71+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.01,77.2648953732098
72+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.025,93.4727806218262
73+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.05,110.813313066224
74+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.1,134.826600538819
75+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.15,154.62622482752
76+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.2,173.220834168825
77+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.25,190.97998971465
78+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.3,209.347208743662
79+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.35,227.715974336195
80+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.4,247.114282973466
81+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.45,267.401830629175
82+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.5,288.975285232462
83+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.55,312.013478739821
84+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.6,338.166980835606
85+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.65,367.779031022749
86+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.7,401.954597578458
87+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.75,442.579189058986
88+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.8,494.139881357708
89+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.85,561.813808520648
90+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.9,662.297613692062
91+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.95,847.106884096244
92+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.975,1052.32193126653
93+
2025-04-05,"wk inc flu hosp",3,2025-04-26,"06","quantile",0.99,1357.6584596711

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