Using pre-diagnostic data fom veterinary laboratories to detect disease outbreaks in companion animals
Emerging infectious diseases and the threat of bioterrorism have fostered a desire
for improved timeliness of outbreak detection. Traditional disease reporting is reliant on
confirmed diagnoses, often involving laboratory analysis that may require days to
complete. Most emerging infectious and bioweapon pathogens are zoonotic organisms.
Detection of zoonotic outbreaks has often relied on the identification of human cases. We
investigated how data from veterinary diagnostic laboratories (VDLs) might contribute to
earlier outbreak detection efforts in Ohio.
We began by determining the representation of animal species in the data and
evaluating the representation of human households. Companion animals comprised
98.1% of the total number of specimens submitted to a commercial, nation-wide VDL
from clinics in Ohio in one year. Using estimates derived from a survey of pet owners,
we determined that these data represented approximately 6.6% of Ohio households.
The value of microbiology test orders was determined by quantifying the
representation and potential gain in timeliness from two VDL datasets. We also
investigated the potential to determine estimated count values from historical records and
detect significant increases in these values using statistical-based detection methods. The
data represented specimens from mostly companion animals (85.0% and 74.3%) followed
by horses (8.2% and 17.2%). We determined a potential gain of timeliness in outbreak
detection of three to five days. We developed baselines of microorganism incidence and
total microbiology orders from the datasets and detected some of the clusters of
pathogen-specific isolates by analyzing the weekly totals of all microbiology orders.
We demonstrated how someone might use these data in a prospective system to
detect outbreaks of disease earlier than traditional methods. Case reviews from a pilot
system indicated the potential benefit to public health as well as veterinary community.
We concluded from these investigations that: 1) data from VDLs do possess certain
qualities that validate their value for syndromic surveillance, 2) these data may be
especially useful for surveillance in companion animals, and 3) earlier detection of
certain disease outbreaks may be possible from a prospective system using VDL data.
School:The Ohio State University
School Location:USA - Ohio
Source Type:Master's Thesis
Keywords:veterinary epidemiology zoonoses public health surveillance
Date of Publication: