Authors: Coco Plasencia and Kristianny Ruelas-Vargas
This article was authored by participants of ITGH's summer program in "Health, Technology, & Society," in collaboration with the Data-Smart City Solutions Program at the Harvard Kennedy School
Abstract:
The COVID-19 pandemic changed not only the lives of millions across the globe, but also how policymakers use spatial tools for decision-making. Health officials at the federal, state, and local level used geographic information systems (GIS) to track infection patterns, predict outbreaks, and optimize public health responses, providing a compelling case study for the utility of localized spatial data for both real-time decisions and long-term planning.
Localized spatial data are geographically tagged and can include information on physical features, demographic details, land use patterns, infrastructure, and environmental conditions. The data are often collected through GIS, remote sensing technologies, Global Positioning System (GPS) devices, and, increasingly, Internet of Things (IoT) sensors.
As environmental and public health efforts become more intersectional and justice-oriented, the importance of using technologies and designing data-driven solutions has grown in equal measure. This modernized approach requires more sophisticated data to address the complex nature of systemic environmental health inequities. Spatial data provides the necessary precision to track and address health disparities and environmental burdens in real time across sectors. It also enables governments to visualize environmental conditions, health outcomes, and access to resources, which can be used to develop more targeted interventions, promote equity in policy decisions, monitor progress, and identify areas for improvement.
This article highlights successful applications of localized spatial data to accomplish goals within environmental work of preservation, adaptation, mitigation, and prediction.
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