A One Health-Based Framework for Zoonotic Disease Surveillance Using Veterinary Clinical Data: A 9-Year Retrospective Study and Real-Time System Implementation
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A One Health-Based Framework for Zoonotic Disease Surveillance Using Veterinary Clinical Data: A 9-Year Retrospective Study and Real-Time System Implementation

12/07/2026 Compuscript Ltd

https://www.scienceopen.com/hosted-document?doi=10.15212/ZOONOSES-2026-0046
Announcing a new article publication for Zoonoses journal. Zoonotic diseases account for approximately 60% of all known human infectious diseases and nearly 75% of emerging infectious diseases. This article reports two linked components addressing this gap.
This retrospective observational study analyzed 10,934 veterinary vaccination records from a single clinic (Nara Animal Hospital, Dongducheon, Republic of Korea) across three phases: pre-pandemic (2017–2019), pandemic (2020–2021), and post-pandemic (2022–2025). Poisson regression for temporal trend analysis and Pearson’s chi-squared test with Yates for species-level comparisons (α=0.05) were used. All analyses were performed in Python 3.x. Concurrently, One Health Zoonotic Disease Intelligence System (OHZDIS) v2.1, a 43-module surveillance platform integrating five official data streams (CDC, WHO, EPA, USDA, and disease.sh) across 171 zoonotic diseases, was designed and implemented.
Poisson regression revealed a significant increase in total vaccination counts (IRR=1.103 per year, 95% CI: 1.094–1.111, p<0.001), and two-sample t-test indicated a significant difference between pre-pandemic (2017–2019) and post-pandemic (2022–2025) annual means (t=−3.55, p=0.016, mean difference: 664 vaccinations/year, 95% CI: 92–1,235). Post-pandemic vaccination rates increased 76.4% over pre-pandemic levels (1,533 vs. 869 cases/year), a temporal association coinciding with the COVID-19 pandemic period. However, the single-clinic design cannot rule out secular trends, such as regional pet ownership growth, clinic expansion, or regression toward the mean after 2020 supply disruptions, as equally plausible explanations (Section 4.4). Statistically significant species-level differences in rabies vaccination rates between dogs (11.4%) and cats (6.7%) (χ2=39.56, p<0.001) highlighted the effects of regulatory frameworks on zoonotic disease prevention. OHZDIS integrates five authoritative data streams (CDC EID, WHO Disease Outbreak News, EPA ATTAINS, USDA Data.gov, and disease.sh) across 171 zoonotic diseases and all 50 U.S. states and five territories, and is publicly accessible at https://guardian-watch.onrender.com/.
The system offers a publicly accessible proof-of-concept surveillance prototype integrating human, animal, and environmental One Health domains in a unified near-real-time analytical pipeline. Formal prospective performance validation against existing surveillance systems is the next immediate research priority before any operational claims can be made.
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Zoonoses is fully open access journal for research scientists, physicians, veterinarians, and public health professionals working on diverse disciplinaries of zoonotic diseases. Please visit https://zoonoses-journal.org/ to learn more about the journal.

Zoonoses is now open for submissions; articles can be submitted online at https://mc04.manuscriptcentral.com/zoonoses
There are no author submission or article processing fees.

Editorial Board: https://zoonoses-journal.org/index.php/editorial-board/

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eISSN 2737-7474
ISSN 2737-7466
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Jae Seok Bae. A One Health-Based Framework for Zoonotic Disease Surveillance Using Veterinary Clinical Data: A 9-Year Retrospective Study and Real-Time System Implementation. Zoonoses. 2026. Vol. 6(1). DOI: 10.15212/ZOONOSES-2026-0046
Jae Seok Bae. A One Health-Based Framework for Zoonotic Disease Surveillance Using Veterinary Clinical Data: A 9-Year Retrospective Study and Real-Time System Implementation. Zoonoses. 2026. Vol. 6(1). DOI: 10.15212/ZOONOSES-2026-0046
12/07/2026 Compuscript Ltd
Regions: Europe, Ireland
Keywords: Health, Medical

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