Abstract
Introduction: Geospatial temporal data derived from smartphones traditionally used for purposes of navigation may offer valuable information for public health surveillance and locational hot spotting. Our objective was to develop a web-based application, called Covidseeker, that captures continuous fine-grained geospatial temporal data from smartphones and leverages these data to study transmission patterns of COVID-19. Methods: This report describes the development of Covidseeker and the process by which it utilizes geospatial temporal data from smartphones and processes it into a usable format to study geospatial temporal patterns of COVID-19. We provide an overview of the design process, the principles, the software architecture, and the dashboard of the Covidseeker application and consider key challenges and strategic uses of capturing geospatial temporal data and the potential for future applications in outbreak surveillance. Results: A resource such as Covidseeker can support situational awareness by providing information about the location and timing of transmission of diseases such as COVID-19. Geospatial temporal data housed in smartphones hold tremendous potential to capture more depth about where and when transmission occurs and the patterns of human mobility that lead to increases in risk of COVID-19. Conclusion: An enormous and highly rich source of geospatial temporal information about human mobility can be used to provide highly localized discrete information that is difficult to capture by traditional sources. The architecture of Covidseeker can be applied to help track COVID-19 and should be integrated with traditional disease surveillance practices.
Highlights
Understanding human mobility is one of the first steps to preventing the spread of infectious diseases transmitted from person to person such as COVID-19
We can begin to compare human mobility patterns between those who test positive vs. those who test negative, which can help develop further public health recommendations on public safety and social behaviors that are associated with transmission of COVID-19
The duration that someone spent at each location is captured, enabling researchers to uncover if the length of time at a location poses a certain level of risk of COVID-19
Summary
Understanding human mobility is one of the first steps to preventing the spread of infectious diseases transmitted from person to person such as COVID-19. Models using human mobility data offer the potential to identify hot spots of transmission and likely locations of exposure to the pathogen [1]. Understanding human mobility enables us to identify the hierarchy and timing of the progression, as well as the social and environmental contextual risks of infectious disease pandemics such as COVID-19 [1]. Capturing these human patterns of mobility can help us understand how to develop more effective and timely strategies to prevent the spread of COVID-19.
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