TickBiteData is an independent, data-driven initiative focused on collecting and analyzing patient-reported experiences related to tick bites and tick-borne conditions.

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Our primary objective is to identify patterns that are not fully captured by traditional surveillance systems—particularly in areas such as delayed diagnosis, misdiagnosis, long-term symptom progression, and real-world patient outcomes.

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While current research often categorizes conditions like Alpha-gal syndrome primarily as allergic responses, emerging patient-reported data suggests a broader and more complex clinical picture. TickBiteData aims to support a more comprehensive understanding by aggregating large-scale, structured survey data directly from affected individuals.

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The platform is designed to:

• Capture detailed exposure and symptom data across diverse populations and geographies

• Highlight trends in healthcare interactions, including physician awareness and diagnostic timelines

• Provide insights into systemic and long-term effects reported by patients

• Support researchers, clinicians, and public health stakeholders with real-world data

 

All survey responses are voluntary and anonymized. The data is not intended to replace established reporting systems (e.g., CDC or regional health authorities), but rather to complement them by amplifying patient-reported experiences at scale.

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TickBiteData is committed to transparency, data integrity, and collaboration with the broader medical and research community to improve understanding, awareness, and outcomes related to tick-borne illness.

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Our Data & Methodology

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TickBiteData.com collects patient-reported survey data to better understand the real-world experience of tick bites and Alpha-gal Syndrome.

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While traditional datasets (such as CDC surveillance and laboratory testing data) provide critical insight into confirmed cases and geographic trends, they often do not capture:

• Time to diagnosis

• Misdiagnosis patterns

• Physician awareness

• Long-term and non-classical symptoms

 

Our dataset is designed to complement existing research by focusing on patient experience, diagnostic timelines, and symptom variability. It currently includes 2,000+ patient-reported survey submissions, making it one of the more comprehensive collections of structured patient experience data in Alpha-gal research.

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