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Serologically analyzing blood samples from Mongolian livestock for zoonotic pathogens

IMPACT SIGNAL77/100
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Information from the abstract

Mongolia faces a significant risk from zoonotic diseases including tick-borne encephalitis virus (TBEV), Crimean-Congo hemorrhagic fever virus (CCHFV), Hantaan virus (HTNV), and Yersinia pestis due to its large livestock and pastoralist populations. Given the potential exposure risk from infected livestock for Mongolian herders and military personnel transiting on operation, we sought to characterize seroprevalence rates among livestock animals against these high-consequence vector-borne and rodent-borne diseases. Whole blood samples were collected from cattle, goat, horse, sheep, and camel from 2014 to 2015 in three aimags (provinces): Tuv, Selenge, and Dornogovi. Samples were tested for reactive antibodies against these pathogens using the MAGPIX ® system and an in-house multiplex assay. Based on an optimized 20-fold signal-to-noise threshold cutoff, the following positivity rates were detected: in Tuv- 0% (HTNV), 1.4% (TBEV), 0.5% ( Y. pestis ) and 0% (CCHFV); in Selenge- 0.6% (HTNV), 3.2% (TBEV), 0% ( Y. pestis ), and 0.3% (CCHFV); and in Dornogovi- 0.2% (HTNV), 0.7% (TBEV), 1.3% ( Y. pestis ), and 1.7% (CCHFV). The highest positivity by pathogen and animal group was observed for TBEV in horses from Selenge (9.4%) and CCHFV in camels from Dornogovi (11.4%). These findings highlight the value of livestock surveillance for identifying circulating zoonotic pathogens and assessing public and veterinary health risk in Mongolia.

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Why this record is monitored

This record has an Impact Signal of 77/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.

Related topics: Viral Infections and Vectors · Zoonotic diseases and public health · Vector-borne infectious diseases

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Thai researcher and institutional participation

Ratree Takhampunya · Aekarin Lamalee · Asma Longkunan · Alyssa N. Mann · Armed Forces Research Institute of Medical Science

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Data limitations

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