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Internal MedicineCohort / Prospective2 min read · distilled by Vetree AI

Canine parvovirus cases (2010-2023): a retrospective study of 78,977 cases demonstrates declining incidence, but mortality risk remains.

Morrison J, George CM, Kollasch TM, Pattee JC, Ryan WG, Moore GE · Journal of the American Veterinary Medical Association · 31 August 2026

Clinical bottom line

CPV incidence is declining, but mortality remains high; hypoproteinemia and underweight status are key mortality predictors.

Summary

This retrospective cohort study analyzed 78,977 canine parvovirus (CPV) cases diagnosed across more than 1,000 primary care veterinary hospitals in the United States from January 2010 through June 2023. CPV incidence declined significantly from 45.2 cases per 10,000 dogs per year in 2010 to 6.5 cases per 10,000 dogs per year in 2022, with diagnoses peaking seasonally in April through June. The most commonly affected age group was 8–16 weeks (46.3% of cases), and median age at diagnosis decreased from 17 to 14 weeks over the study period. The most frequently affected breeds included pit bull-type dogs, Chihuahuas, Labrador Retrievers, German Shepherd Dogs, and mixed breeds, collectively representing 54.3% of cases. Among 37,707 dogs with 14-day survival data, 43.6% died or were euthanized. Stepwise logistic regression identified hypoproteinemia (OR 4.44), underweight body condition (OR 2.99), lymphopenia, leukopenia, and elevated ALT as significant predictors of mortality. Conversely, neutered/spayed status (OR 0.04), higher body weight, and concurrent intestinal parasitism were associated with reduced mortality odds. Despite the overall decline in case numbers and mortality over time, CPV continues to cause thousands of deaths annually. These findings highlight the persistent clinical burden of CPV and identify key prognostic indicators that can guide triage, treatment prioritization, and client communication in clinical practice.

Internal MedicineSmall AnimalEmergency

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.