This repository is under construction.
This repository is designed as an example modeling Hub that follows the infrastructure guidelines laid out by the Consortium of Infectious Disease Modeling Hubs. The example is documented in more detail here.
The example model outputs that are provided here are adapted from forecasts submitted to the US COVID-19 Forecast Hub, but have been modified to provide examples of nowcasts. They should be viewed only as illustrations of the data formats, not as realistic examples of nowcasts and forecasts. In particular, scores calculated by comparing the model outputs to the target data will not give a meaningul measure of predictive skill.
To work with the data in R, you can use code like the following:
library(hubUtils)
library(dplyr)
model_outputs <- hubUtils::connect_hub(hub_path = ".") %>%
dplyr::collect()
head(model_outputs)
#> # A tibble: 6 × 8
#> origin_date horizon location target output_type output_type_id value model_id
#> <date> <int> <chr> <chr> <chr> <dbl> <int> <chr>
#> 1 2022-12-05 -6 20 inc co… quantile 0.01 22 UMass-ar
#> 2 2022-12-05 -6 20 inc co… quantile 0.025 24 UMass-ar
#> 3 2022-12-05 -6 20 inc co… quantile 0.05 26 UMass-ar
#> 4 2022-12-05 -6 20 inc co… quantile 0.1 28 UMass-ar
#> 5 2022-12-05 -6 20 inc co… quantile 0.15 30 UMass-ar
#> 6 2022-12-05 -6 20 inc co… quantile 0.2 32 UMass-ar
target_data <- read.csv("target-data/covid-hospitalizations.csv")
head(target_data)
#> time_idx location value target
#> 1 2021-03-21 46 12 inc covid hosp
#> 2 2021-03-04 45 82 inc covid hosp
#> 3 2021-02-26 46 7 inc covid hosp
#> 4 2021-02-20 44 21 inc covid hosp
#> 5 2021-02-09 44 19 inc covid hosp
#> 6 2021-01-25 25 224 inc covid hosp