Mass Gathering Surveillance: New ESSENCE Report and Collaboration Win Gold in OR
AbstractObjectiveTo streamline production of a daily epidemiology report includingsyndromic surveillance, notifiable disease, and outbreak data duringa mass gatheringIntroductionThe 2016 U.S. Olympic Track and Field Team Trials were heldJuly 1-10 in Eugene, OR. This mass gathering included over 1,000athletes, 1,500 volunteers, and 175,000 spectators. The Oregon PublicHealth Division (PHD) and Lane County Public Health (LCPH)participated in pre-event planning and collaborated to produce adaily epidemiology report for the Incident Management Team (IMT)during the event. The state and county public health agencies hadcollaborated on surveillance for prior mass gatherings, including the2012 Trials. However, 2016 was the first opportunity to use completestate and county syndromic surveillance data.MethodsPHD staff developed an ESSENCE report, highlighting sevenpriority health outcomes: total emergency department visits; injury,gastrointestinal, respiratory, and fever syndromes; and asthma-like and heat-related illness queries. The report included side-by-side comparisons of county and state time series graphs, a tablesummarizing reportable diseases, and space to narratively describeoutbreaks. PHD staff did a virtual demonstration and in-persontutorial for LCPH staff on how to run the report. ESSENCE accesspermissions had to be modified so that county users could see andproduce state time-series graphs but not data details for non-LaneCounty visits. Emphasis was placed on interpretation of likelyscenarios, i.e., one or two days with a warning that was not indicativeof an incident of public health importance.ResultsDuring the event, LCPH staff were able to run the reportsuccessfully, i.e., there were no technical glitches. For the first fewdays, LCPH staff consulted with PHD staff about epidemiologicalinterpretation. State data were of specific interest since data detailswere suppressed. Additionally, increases were seen in the injurysyndrome in the days preceding the July 4 holiday. Stratification bykey demographic factors and looking at subsyndrome breakdownson warning and alert days provided the needed information withoutrequiring the use of the detail details.ConclusionsAfter the event, there were three main recommendations forimproving the process.LCPH suggested that the side-by-side visualization of countyand state time series graphs was useful to see trends but the relativescale of the number of visits was unclear due to size and placement(see figure 1). Solutions for future reports include additionalexplanatory text, limiting the report to only county data, and alternativevisualizations that highlight the differences in visit magnitude.As part of the IMT process, the LCPH lead felt that her efforts tophysically go to the Emergency Operations Center to run the reporthelped facilitate communication with partners. However, it is notclear if this effort directly translated into IMT use of the report, whichwas posted to the online event management system and not includedin the daily situation status reports. While LCPH leadership and staffreported anecdotally that they found the report to be very useful,no formal evaluation of use was done with either public health orIMT staff. In advance of the next event, state and county staff shouldprepare evaluation metrics.The report feature in ESSENCE is a bit cumbersome to set up, butit allows for easy production of appealing and customizable reports.This template can be modified for future mass gatherings, includingathletic competitions and county fairs. PHD staff will continueto collaborate with LCPH to repurpose and improve the report foruse in Lane and other counties. Fostering local user comfort withinterpreting ESSENCE data and generating summaries for local useis a priority of the OR ESSENCE team.
How to Cite
Jagger, M. A., Jaramillo, S., Boyd, L., Johnson, B., Reed, K. R., & Powell, M. (2017). Mass Gathering Surveillance: New ESSENCE Report and Collaboration Win Gold in OR. Online Journal of Public Health Informatics, 9(1). https://doi.org/10.5210/ojphi.v9i1.7719
Non-Infectious Disease Surveillance Use Cases