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Resources

The science behind earlier detection.

Explore the research and validation behind DARO's herd-level approach to pathogen surveillance.

CASE STUDY

How Pipestone Used DARO to Stop a PRRS-Positive Gilt Movement Before It Reached Other Farms

DARO helped Pipestone stop a PRRS-positive gilt movement before it put other farms at risk.


After oral fluid testing returned a negative result, DARO detected PRRSV at the herd level. Pipestone stopped the scheduled movement and confirmed the infection before the gilts were shipped.

VALIDATION DATA

Detecting ASFV at the Herd Level Through Environmental Surveillance

DARO’s environmental surveillance method accurately detected ASFV under real-world field conditions.


Results matched the confirmed ASFV status of all six barns, achieving 100% concordance. ASFV also remained detectable at simulated pooling ratios as large as 1:800, supporting further research into scalable surveillance approaches.

VALIDATION DATA

Engineered for Early & Accurate Detection

Explore DARO's analytical and field performance data, including sensitivity, specificity and extreme pooling capabilities.


The data slides report 151/151 correct for both analytical sensitivity and specificity; field-diagnostic results of 70/70 positive barns and 213/213 negative barns; and 90% observed detection at 1:1,000 pooling with 94.9% probit-predicted performance.

RESEARCH

Comparison of Three Herd-Level Surveillance Methods

DARO detected PRRSV 1 day before serum and 2 days before oral fluids.


A controlled study compared DARO, serum and oral fluids during the early spread of PRRSV. DARO was the first method to detect the virus, providing an earlier window for disease mitigation planning.

RESEARCH

Comparative surveillance testing of PRRSV

PRRSV detected an average of 3.91 days earlier than oral fluids.


Across two high-risk commercial nurseries, DARO consistently identified PRRSV earlier than oral fluid surveillance. The study also found a statistically significant difference in time to detection across the combined datasets.

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