Clinical and Epidemiological Information Required for Lyme Disease Surveillance in a Low-Incidence State, California 2011–2017. Brummitt et al. 2024. Vector-Borne and Zoonotic Diseases [ahead of print]. https://doi.org/10.1089/vbz.2024.0043
Abstract [shortened]: 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.
Objective: This study identified whether a minimum number of variables was sufficient to reliably classify LD cases in California and potentially reduce workload. 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 showed that automatically reported data were not sufficient, additional information such as a patient’s clinical presentation and travel history were necessary to improve the sensitivity of the models. Conclusion: This study demonstrated that both clinical and travel information were required to accurately classify a case of LD in California.
Note: These results were critical to interpret data from a passive case surveillance system to identify areas of high risk endemic transmission.