What Historical Micro-Spatial Data Can Teach Us about Schools as Vectors for Epidemiological Events like Covid-19

Don Lafreniere, Michigan Technological University
Tim Stone, Michigan Technological University
Rose Hildebrandt, University of Western Ontario

The recent developments of COVID-19 have sharply brought into focus the importance of individual-level disease information in slowing or stopping outbreaks of infectious disease. However, studying contemporary outbreaks in this way can be difficult due to insufficient or altogether incorrect information, lack of understanding of the disease vector or index case, and constantly changing case count and geographic spread- all while needing to maintain the privacy of individuals. Further, despite the access to ‘big data’ we do not have micro-level understandings of infected individuals families, households, or neighbourhoods. The study of historical outbreaks, utilizing geographical high-resolution micro-data can provide remarkable insight not only into the effects of those historic outbreaks, but also into how we should approach contemporary outbreaks and the importance of having availability to built, social, and medical data. In this paper, we utilize the Copper Country Historical Spatial Data Infrastructure (CCHSDI) which includes high precision spatio-temporal models of the built and social environments of Michigan, America’s former copper mining region from 1880-1950. With the CCHSDI we have geocoded and record-linked demographic data from the IPUMS 100% count microdata census to city directories, school records, and local health data with to specific residential and school buildings. In this paper we examine the school-as-disease-vector, and the impacts of classrooms on spreading influenza, pneumonia, and Scarlett Fever in 1918. These findings will assist in strengthening our understanding of the diffusion of secondary infections among populations in moderately dense communities.

No extended abstract or paper available

 Presented in Session 66. Health and Hazards I : Pandemic Geographies