diff --git a/.gitignore b/.gitignore
index f32bdb0..be49f51 100644
--- a/.gitignore
+++ b/.gitignore
@@ -170,3 +170,7 @@ cython_debug/
 ################################################################################
 
 poetry.lock
+
+*.csv
+
+*.tsv
diff --git a/forecasttools_py/data.py b/forecasttools_py/data.py
new file mode 100644
index 0000000..26e702c
--- /dev/null
+++ b/forecasttools_py/data.py
@@ -0,0 +1,38 @@
+"""
+Retrieves US 2020 Census data,
+hospitalization count data, and
+example forecast data.
+"""
+
+import os
+
+import polars as pl
+
+
+def get_census_data(
+    save_path: str = os.getcwd(),
+    save_as_csv: bool = False,
+    url: str = "https://www2.census.gov/geo/docs/reference/state.txt",
+):
+    """
+    Retrieves US 2020 Census data in a
+    three column polars dataframe.
+    """
+    nation = pl.DataFrame(
+        {
+            "location_code": ["US"],
+            "short_name": ["US"],
+            "long_name": ["United States"],
+        }
+    )
+    jurisdictions = pl.read_csv(url, separator="|").select(
+        [
+            pl.col("STATE").alias("location_code").cast(pl.Utf8),
+            pl.col("STUSAB").alias("short_name"),
+            pl.col("STATE_NAME").alias("long_name"),
+        ]
+    )
+    flusight_location_table = nation.vstack(jurisdictions)
+    if save_as_csv:
+        flusight_location_table.write_csv("flusight_location_table.csv")
+    return flusight_location_table
diff --git a/vignettes/example-infectious-disease-forecast.qmd b/vignettes/example-infectious-disease-forecast.qmd
new file mode 100644
index 0000000..0efd44f
--- /dev/null
+++ b/vignettes/example-infectious-disease-forecast.qmd
@@ -0,0 +1,10 @@
+---
+title: "Example Infectious Disease Forecast"
+format: gfm
+engine: jupyter
+---
+
+
+# Background
+
+The fitting data for this example came from HHS's HealthData website, which hosted the National Health Safety Network's (NHSN) [dataset](https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh/about_data), which the author located off of the FluSight Hub's [data GitHub repository](https://github.com/cdcepi/Flusight-forecast-data/tree/master/data-truth).
diff --git a/vignettes/format-flusight-output.qmd b/vignettes/format-flusight-output.qmd
new file mode 100644
index 0000000..42cb205
--- /dev/null
+++ b/vignettes/format-flusight-output.qmd
@@ -0,0 +1,41 @@
+---
+title: "Formatting Output For FluSight Submission"
+
+format: gfm
+engine: jupyter
+---
+
+_This document details the process of using `forecasttools-py` to turn an infectious disease forecast produced in Python and stored as an `InferenceData` object into a correctly formatted FluSight submission._
+
+---
+
+# Background
+
+> The FluSight Challenge[^historical_flusight] uses the [`hubverse`](https://hubverse.io/) framework to accept forecast submissions from contributing teams via [GitHub pull requests](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-pull-requests). The submitted `model-output` files need to follow a [specified formatting schema](https://github.com/cdcepi/FluSight-forecast-hub/blob/main/model-output/README.md). `forecasttools-py` provides functions to automate production of FluSight submissions.
+
+[^historical_flusight]: For FluSight data, please refer to [this repository](https://github.com/cdcepi/Flusight-forecast-data). For the FluSight Hub repository, please refer [here](https://github.com/cdcepi/FluSight-forecast-hub), and for historical FluSight forecasts, please refer [here](https://github.com/cdcepi/FluSight-forecasts).
+
+Below is an example[^example_forecast] of model output submitted to the FluSight Hub:
+
+[^example_forecast]: [This forecast](https://github.com/cdcepi/FluSight-forecast-hub/blob/main/model-output/cfarenewal-cfaepimlight/2023-12-02-cfarenewal-cfaepimlight.csv) was made for `2023-12-02` by the model `cfarenewal-cfaepimlight`.
+
+```
+reference_date,target,horizon,target_end_date,location,output_type,output_type_id,value
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.01,48
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.025,52
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.05,57
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.1,61
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.15,64
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.2,67
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.25,70
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.3,72
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.35,74
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.4,75
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.45,77
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.5,79
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.55,81
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.6,83
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.65,85
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.7,87
+2023-12-02,wk inc flu hosp,-1,2023-11-25,01,quantile,0.75,89
+```