Estimating contact rates at a mass gathering by using video analysis: a proof-of-concept project.

Jeanette J Rainey,Richard J Radke,Daniel B Koch,Julie Suzuki Crumly,Anil Cheriyadat

doi:10.1186/1471-2458-14-1101

Abstract

BackgroundCurrent approaches for estimating social mixing patterns and infectious disease transmission at mass gatherings have been limited by various constraints, including low participation rates for volunteer-based research projects and challenges in quantifying spatially and temporally accurate person-to-person interactions. We developed a proof-of-concept project to assess the use of automated video analysis for estimating contact rates of attendees of the GameFest 2013 event at Rensselaer Polytechnic Institute (RPI) in Troy, New York.MethodsVideo tracking and analysis algorithms were used to estimate the number and duration of contacts for 5 attendees during a 3-minute clip from the RPI video. Attendees were considered to have a contact event if the distance between them and another person was ≤1 meter. Contact duration was estimated in seconds. We also simulated 50 attendees assuming random mixing using a geo-spatially accurate representation of the same GameFest location.ResultsThe 5 attendees had an overall median of 2 contact events during the 3-minute video clip (range: 0–6). Contact events varied from less than 5 seconds to the full duration of the 3-minute clip. The random mixing simulation was visualized and presented as a contrasting example.ConclusionWe were able to estimate the number and duration of contacts for 5 GameFest attendees from a 3-minute video clip that can be compared to a random mixing simulation model at the same location. The next phase will involve scaling the system for simultaneous analysis of mixing patterns from hours-long videos and comparing our results with other approaches for collecting contact data from mass gathering attendees.

Highlights

Current approaches for estimating social mixing patterns and infectious disease transmission at mass gatherings have been limited by various constraints, including low participation rates for volunteer-based research projects and challenges in quantifying spatially and temporally accurate person-to-person interactions
We describe our proof-ofconcept project on the use of video analysis techniques to estimate contact rates of attendees of the 2013 GameFest event at Rensselaer Polytechnic Institute (RPI) in Troy, New York
An attendee was considered to have a contact event if the distance between the attendee and another person was ≤1 meter. In this proof-of-concept project, we explored the use of IMPACT, an existing Oak Ridge National Laboratory (ORNL) platform, for conducting random mixing simulations [15], including the use of the application’s drawing tools to outline the boundaries of Studio 1 in a geospatially-accurate way

Summary

Introduction

Current approaches for estimating social mixing patterns and infectious disease transmission at mass gatherings have been limited by various constraints, including low participation rates for volunteer-based research projects and challenges in quantifying spatially and temporally accurate person-to-person interactions. Better quantification of individual contact rates and mixing patterns will become increasingly important as public health officials require more accurate infectious disease models for refining or validating pandemic mitigation strategies, including. A number of approaches have been used to estimate mixing patterns at mass gatherings with variable levels of success, primarily due to the need for high participation among attendees and challenges associated with recording face-to-face interactions in a spatially and temporally accurate way [5,6,7,8]

Methods

Results

Discussion

Conclusion