# Human Hantavirus Infections in Hungary (2018–2025): Epidemiology, Molecular Detection Across Clinical Sample Types, and Phylogenetic Analysis

## TL;DR

This study analyzed hantavirus infections in Hungary from 2018 to 2025, focusing on detection methods and genetic similarities.

## Contribution

The study provides new insights into the molecular detection and phylogenetic analysis of hantaviruses in Hungary.

## Key findings

- Most hantavirus RNA was detected in serum and whole blood, with limited success in urine.
- Phylogenetic analysis showed high similarity between Hungarian hantavirus sequences and regional samples.
- Whole blood was more effective than serum for detecting DOBV in some cases.

## Abstract

Hantaviruses are globally distributed, rodent-borne zoonotic pathogens. In Hungary, Dobrava-Belgrade virus (DOBV) and Puumala virus (PUUV) are circulating, causing hemorrhagic fever with renal syndrome and nephropathia epidemica, respectively. Due to the short viremic period, hantaviruses are primarily diagnosed by serological methods. Detection of viral nucleic acid by real-time or nested reverse transcription polymerase chain reaction (RT-PCR) is limited to samples collected in the early phase of disease. Between 2018 and 2025, 51 laboratory-confirmed hantavirus infections were identified in Hungary; 30 cases were assigned to DOBV, 20 to PUUV, and one remained undetermined. Most patients were male (82%), suggesting increased exposure-related risk. Viral RNA was detected in 21 cases, mainly from serum and whole blood samples, and sporadically from urine. In three DOBV cases, viral RNA was detectable exclusively in whole blood but not in paired serum samples. Phylogenetic analysis included four PUUV and six DOBV partial S segment sequences showing high similarity to other human- and rodent-derived samples from the region. Hantavirus infections remain infrequently diagnosed in Hungary. Our findings suggest that serum and whole blood may be useful specimen types for molecular detection, whereas urine had limited diagnostic value in our dataset.