Tick bite data tracker explained

What is syndromic surveillance? Syndromic surveillance tracks the number of patients seeking care in emergency departments with specific symptoms or concerns—before a diagnosis is confirmed. These data help health officials quickly monitor health events and detect unusual levels of illness. Data are used by public health officials to determine if a response may be needed. Syndromic surveillance is used for a variety of diseases and conditions. The National Syndromic Surveillance Program (NSSP) is a collaboration between CDC, federal partners, local and state health departments, and academic and private sector partners.

Where do these data come from? Currently, most non-federal emergency department visits are reported to NSSP, but there are some differences in coverage by regions.  Details about NSSP coverage can be found here.

How are emergency department visits for tick bites detected? Combinations of specific words and ICD diagnostic codes are typically used to identify emergency department visits by patients with specific concerns. To detect visits related to tick bites, records containing the various spellings of the word “tick” or the combination of “tick” and “bite” are located and counted. Since there is not an ICD code for “tick bite”, we were not able to use ICD codes to detect these visits.

What are the advantages of these data? These data can indicate when people in different parts of the country might be at highest risk for tick bites. Unlike some tickborne disease surveillance data, the data shown in the charts below are updated weekly, rather than annually.

What are the limitations of these data? These data are subject to several limitations. Results might not be generalizable to emergency departments that are not contributing data to the BioSense Platform. The key words used to identify tick bite visits may under- or overestimate emergency department visits related to tick bites because of differences in coding, reporting, and availability of chief complaint text data between jurisdictions or over time. Finally, aggregated data by region might be less useful than state or local data.