Why does mindful data use matter?
Data is constantly changing, especially during turbulent times like a pandemic. Being mindful about how you are reading each news story and new set of numbers that’s presented will help you to understand the full story and impact on current events.
Our Guide to Data Consumption
Our COVID-19 Response
To help our community better visualize the impact of the COVID-19 pandemic and identify the populations that need the most help.
Check out our data map resources below:
Read more about our data-driven response to the pandemic in our series of blogs, which detail the impact COVID-19 has had on our community.
What do we know we don’t know?
The Infection Rate
Estimates of infection rate are impacted by the way that data is collected, and the consistency of the methods used both in each geography and across multiple geographies (e.g.: in a city vs. on a global scale). It’s difficult to begin to understand the rate of infection without having an accurate count of cases, which is impossible due to early testing limitations.
Even if testing is very accurate, transmission of COVID-19 is extremely variable, depending on social behaviors and environmental factors.
Social distancing—or lack thereof—can have a huge impact on the rate of contact, or how many other people an infected person interacts with in a given span of time. Environmental factors, such as climate, population density, and landscape, also play a role in the likelihood of transmission.
The rate of transmission per contact is another variable, and can be affected by how long the virus can survive on any given surface that an infected person comes in contact with, and how far the virus travels in the air. Additionally, how long an individual is considered contagious is unknown and may vary by individual case.
The ratio of people who are infected and show symptoms versus those who do not show symptoms is largely guesswork at this point. People who are symptomatic are much more likely to seek testing and treatment, or to simply self-isolate, than people who are not. However, the unknown quantity of people who are infected but asymptomatic are still potentially transmitting COVID-19 to others.
The Fatality Rate
The uncertainties detailed in the other factors play a huge role in the accuracy of reported cases and by extension, fatalities.
It’s difficult to determine fatality rate by dividing the number of people who have died by the number of people who have been infected when there isn’t an accurate count of infected individuals or individual fatalities.
Additionally, pre-existing conditions need to be taken into consideration, as rates of infection and death are going to differ in areas where chronic health problems are more prevalent. Hospital capacity also has an impact on fatality rates, as the ability to prevent death from COVID-19 or other illness depends on it.
Navigating the ever-changing landscape of pandemic data can be challenging. We’ve rounded up some of our favorite reliable resources to help.
Why It’s So Freaking Hard To Make A Good COVID-19 Model
By Maggie Koerth, Laura Bronner and Jasmine Mithani
Here we are, in the middle of a pandemic, staring out our living room windows like aquarium fish. The question on everybody’s minds: How bad will this really get? Followed quickly by: Seriously, how long am I going to have to live cooped up like this? READ MORE
Here are some other great sources of pandemic data and consumption guides:
Five Powerful Charts | Coronavirus Case Counts are Meaningless* | Michigan.gov Coronavirus Resources | Michigan.gov COVID-19 Data | Healthdata.org COVID-19 Death Projections | Best-Case and Worst-Case Forecasts | Unemployment Impact | Employment Impact by Industry | Michigan Employment Snapshot | Impact on the US Census | US Coronavirus Pandemic Data in Numbers