Piloting a Novel Approach for Collecting and Analyzing Travel History Data - Results and Next Steps

Travel history data are often missing or incomplete on infectious disease case investigation records. Poor data quality could be attributable in part to case investigation forms that elicit travel history using general, free-text comment boxes that provide little guidance on what travel history information to collect and are difficult to analyze. A Council of State and Territorial Epidemiologists (CSTE) workgroup developed a standardized, simple, and query-able set of case investigation questions to collect travel history data, which were pilot tested in 30 local and state public health agencies.

Over a 6-month period, an applied research team collected pilot data using this set of standardized travel history case investigation questions, as well as subjective feedback from investigators regarding baseline attitudes toward travel history questions and the efficiency and usefulness of these questions.  Diseases for which the travel history questions were asked included seven zoonotic/vectorborne diseases (Lyme disease—erythema migrans cases only, anaplasmosis, ehrlichiosis, babesiosis, tickborne relapsing fever, tularemia, West Nile virus) and two primarily waterborne diseases (cryptosporidiosis, giardiasis).

Efforts are now beginning to examine all of the data and determine the most useful and appropriate analysis questions. During this roundtable we propose that we review the evaluation responses and data completion rates for each of the nine pilot diseases and discuss potential analysis implications and possible dissemination plans for results and recommendations.  In addition, this roundtable will discuss potential next steps and recommendations for how to move forward with the findings from this pilot project.  While the existing evaluation plan includes general analysis plans and direction, the novelty of the data and data collection process leans itself to an open and intriguing dialogue about the best uses of this type of data as well as potential challenges and pitfalls for the analysis and interpretation.