Clinical and Epidemiological Information Required for Lyme Disease Surveillance in a Low-Incidence State, California 2011-2017.

Abstract

Background: Between January 1, 2011, and December 31, 2017, over 12,000 case reports of Lyme disease (LD) were submitted to the California Reportable Disease Information Exchange for further investigation. The number of case reports has tripled compared to previous years, emphasizing the need for efficient estimation and classification methods. We evaluated whether estimation procedures can be implemented in a low-incidence state such as California to correctly classify a case of LD, similar to those procedures used in high-incidence states. Objective: The purpose of this study was to identify whether a minimum number of variables was sufficient to reliably classify cases in California and potentially reduce workload while maintaining the ability to track LD trends in California. Methods: To determine the relative value of diagnostic information, we compared five candidate logistic regression models that were used to classify cases based on information that varied in its degree of difficulty for collection. Results: Our results using California's surveillance data showed that automatically reported data were not sufficient, additional information such as, a patient's clinical presentation and travel history were necessary in a low-incidence state to improve the overall sensitivity of the models. Conclusion: This study may help inform public health surveillance efforts by demonstrating that both clinical and travel information are required to accurately classify a case of LD in a low-incidence state.