---
# System prepended metadata

title: MSTP COVID Dashboard

---

# MSTP COVID Dashboard

This is just to expound on an intro-to-R / programming idea I had. The basic idea is that we give a "hands-on" tutorial/introduction to R/Python by helping people to answer either pre-selected questions **and/or** provide an introduction to making a custom dashboard for Milwaukee County COVID data

## Motivation
At the beginning of the pandemic, there was a nice COVID dashboard specific for Milwaukee County that I used to keep track of the numbers. However, while this dashboard is still referenced in many official links, the page take *ages* to load (I suggest people try it). Since at least two months ago, I consider the link no longer functional.

[Link](https://mcoem.maps.arcgis.com/apps/dashboards/018eedbe075046779b8062b5fe1055bf)
![](https://i.imgur.com/b4TNI27.png)

For Milwaukee, there are two places to get official numbers. There is a functioning dashboard (below) by the city's health department, but in my opinion it leaves a lot to be desired. For example, there is no way to stratify current hospitalizations by age (a relevant metric with schools re-opening) or look at ventilator availability

[Link](https://city.milwaukee.gov/coronavirus)
![](https://i.imgur.com/4Joghtx.png)

At present, the best resource is from the Wisconsin DHS which has a lot of information, but the maps only occasionally work, and while some metrics are calculated, there are still some missing indicators.

[Wisconsin DHS Data](https://www.dhs.wisconsin.gov/covid-19/data.htm)

Critically, Wisconsin **does** make available a lot of data to download, and it is this data that I think would be a great way to introduce people to data analysis.

![](https://i.imgur.com/ZvD1OSY.png)

## Approach

Roughly, I thought people might be interested in learning how to manipulate this data to generate some plots they might be interested in. If the goal is to make it more structured, we could generate specific questions we think these data could answer. These could be either specific metrics (e.g. hospitalization rates by age over time) or more open ended questions:

* What is the average lag between case-number and hospitalization rate? What about between hospitalization rate and deaths?
* How much more infectious does this new variant appear compared to the variant from last Fall?
* Does this new variant have a differential effect across age groups?
* How well does an SIR model fit the data from previous peaks?
* Can we quantify the effect of vaccination rate on $R_0$

We could then help people answer these or other questions people come up with. A follow-up to this introduction could be showing people how to make Shiny apps utilizing this data.

Thoughts?



