2024-10-23 ECDC models - SARIMA & SOCA simplex

model-metadata/ECDC-SARIMA.yml

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+team_name: European Centre for Disease Prevention and Control
+model_name: ARIMA model with seasonality
+team_abbr: ECDC
+model_abbr: SARIMA
+model_contributors:
+  - name: ECDC Mathematical Modelling Team 
+    affiliation: European Centre for Disease Prevention and Control
+    email: [email protected]
+team_model_designation: primary
+data_inputs: ECDC ERVISS
+methods: A simple ARIMA model with seasonality

model-metadata/ECDC-soca_simplex.yml

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+team_name: European Centre for Disease Prevention and Control
+team_abbr: ECDC
+model_name: Historical simplex pattern
+model_abbr: soca_simplex
+model_contributors:
+  - name: ECDC Mathematical Modelling Team
+    affiliation: European Centre for Disease Prevention and Control
+    email: [email protected]
+website_url: https://www.ecdc.europa.eu/en
+team_model_designation: secondary
+methods: "Using historical data patterns with highest similarity to current data to foreast the future values"
+methods_long: "Model consists of 1) taking 'm' latest data points, 2) find 'n' closest neighbours from all historical data using L2-norm, 3) use the next data time point from each historical data points, 4) use data from point 3 to fit a log-normal distribution , 5) use the log-normal distirbution to estimate the quantiles/distribution, 6) return to step 3 but use two data points ahead for estimations of horizon 2, etc for horizon 3 and 4, 7) find optimal values of 'n' and 'm for a given country, using past 4 weeks of forecasts."
+data_inputs: ECDC ERVISS