Embrace the Space

The Geospatial Centroid at CSU is launching a new blog – Embrace the Space. The intention is to provide a geographic interpretation of current events and timely issues. We begin by writing a series of posts addressing the geographic and multi-faceted aspects of the COVID-19 pandemic, including the use of maps and location-based data, the role of spatial science, and the impact place has on society. This first post focuses on COVID-19 maps and data and provides some initial thoughts on how the spatial perspective can shape our understanding and perception of this remarkable event.  

Part 1:  The Geography of COVID-19 – Maps and Data

Submitted by the Geospatial Centroid Rapid Response Team* 

The current pandemic is a spatial story that crosses boundaries, scales, and cultures and can be told through maps – the language of geographyMaps define space, describe place, and display phenomena that are otherwise invisible on the landscape. They enable us to see patterns, correlate seemingly unrelated data, and observe the world in novel ways. 

What do the maps of COVID-19 tell us about this global event?   

  • First, geography and questions of where are central to this story. Where is it present? Where is it spreading? Where is it most pronounced? Where am I in relation to it?  
  • Second, the geographic concept of scale is important in how the story is depicted –a global, generalized picture tells a significantly different story than the story in my hometown. 
  • Third, place matters – where we live defines access to resources and essential services revealing racial, social, and economic disparities.  

In response to the pandemic, many organizations, individuals, and international communities created websites to share data and information about what was happening, and where. Maps often accompany these sites, helping us “see” the invisible pandemic by tracking and exposing its transmission patterns and spread. Where is the data coming from? At what scale is it being collected and how often? Are the sites interpreting the global extent of the crisis or are they more localized and limited in extent?  

Included below is a selection of map-based COVID-19 sites with commentary on their characteristics, including strengths and caveats to consider. When exploring these sites, we must be cognizant of their limitations and be careful how we interpret their messages and the data they present. 

Same data, different visualizations 

Data dashboards provide a means for sharing multiple data products at a glance. Using maps and charts in tandem provides complementary views of data related to COVID-19 cases and deaths. Although the data sources may be the same, each visualization enables users to see the information differently—some anchored to location in maps or not using charts (WHO COVID-19 DashboardJohns Hopkins Coronavirus Resource Center).  

Time Series 

Animation and time series maps provide a dynamic view of the viral spread across the world (HealthMap-Covid-19).  These are an effective way to quickly see networks, emerging patterns, and regional dissemination. 

Enhancing value of data 

Data from multiple sources that are considered authoritative (China Centers for Disease Control (CCDC), European CDC (ECDC), US CDC Africa CDCand the World Health OrganizationsWHO) are generally updated daily or, in some cases, in realtimeCommon to all of these sites is the one-dimensional emphasis focusing on known quantifiable aspects of the outbreak in the form of numbers of cases and/or deaths. Contextualizing maps and normalizing demographic data can enhance our understanding of local and regional impacts of the virus. An absolute count can be misleading because it is directly related to the total number of people in an area. Normalizing the data (i.e. dividing the number of cases by population) paints quite a different picture.  

Most medical related statistics on disease report in total cases per 100,000 people or provide graphs using logarithmic scales to visualize growth of the COVID-19 virus around the world. This allows for a comparable assessment across different locations and placesFor example, Italy has experienced slightly over half the number of deaths due to the virus compared to the US, but Italy has a considerably smaller population than the US, the proportion of the infected individuals dying from the disease is approximately three times as high. Further exploring other aspects of the data reveals that Italy has the oldest population in Europe, with 23% of the population being 65 or older – an age bracket highly susceptible to the virus. Understanding the demographic make-up of different countries provide a more nuanced understanding of viral spread and transmission.  

Data availability 

Many countries have created interactive maps with graphs and lists tracking the coronavirus by state or province (NigeriaMyanmarEcuador). However, there are fewer maps that provide data and information at the sub-state level. The United States and European countries have extensive datasets at subcountry levels to track infection rates, hospitalization, and virus testing (France – COVID 19)In the US, most states, counties and some cities have maps tracking COVID-19. For example, the Colorado Department of Public Health and Environment has an interactive map that provides information on  number of positive tests and rates of infection.   

The proliferation of interactive maps related to the pandemic provides an important contribution towards better understanding the ongoing threat. Using a geographic lens to interpret the data, while trying to better understand the nature of places behind the statistics, help us find ways to see local and global relationships. This story demonstrates how the geography of COVID-19 is central to examining these intertwined dynamics to identify strategies and solutions. 

*The Geospatial Centroid Rapid Response Team is committed to: 

  • Helping to identify and examine emergent issues  
  • Illustrating the spatial nature of the most current challenges 
  • Elevating spatial thinking in science-based decision making  

Geospatial Centroid Rapid Response Team: 

Staff: Melinda Laituri, Sophia Linn, Dan Carver 

Interns: Arian Brazenwood, Luke Chamberlain, Sam Gudmestad, Caroline Norris