Hantavirus RNA Detection in Small Mammals and Spatial Association with Human Hemorrhagic Fever with Renal Syndrome in the West Kazakhstan Region, 2025

1. Introduction

Hemorrhagic fever with renal syndrome (HFRS) is a viral zoonotic natural focal disease characterized by pronounced intoxication, fever, specific vasculitis with hemorrhagic syndrome, and the development of tubulointerstitial nephritis. HFRS incidence is registered in many countries of Europe, Asia, Africa, and North America, indicating the high epidemiological significance of this infection [1]. In recent years, a steady trend toward an increase in incidence and a rise in the proportion of severe clinical forms of the disease has been observed.

In the Republic of Kazakhstan, official registration of HFRS has been conducted since 2000. From 2000 to 2025, 329 cases of the disease were registered [2]. The incidence occurs both sporadically and in the form of outbreaks. The most pronounced increases in incidence were recorded in 2005 and 2008, with 85 and 30 cases, respectively, corresponding to rates of 14.0 and 4.9 per 100,000 population.

HFRS is characterized by marked seasonality, repeatedly described in the works of various authors. The maximum number of hospitalized patients occurs from November to January (up to 87.6%), with a peak in November, while in some years the disease is registered only as isolated cases from February to August [3]. The seasonal nature of the incidence is explained by the active colonization of residential and farm buildings by rodents during the cold season, which leads to increased contact between the population and infected animals and their waste products [4].

Among the patients, residents of rural areas predominate (84.7%), with a mean age of 33.7 years [5]. A close epidemiological link has been established between the occurrence of HFRS cases and rodents, which serve as the natural reservoir of the pathogen. An increase in the abundance of small mammals contributes to greater human contact with the virus and elevates the risk of infection via aerosol (airborne-dust) and alimentary routes. The highest density of rodents is observed in river floodplains and gullies of above-floodplain terraces, due to the presence of shelters, abundant food resources, and lesser impact of floods.

In the natural foci of HFRS in the West Kazakhstan Region, various species of small mammals are present, including Microtus arvalis, Myodes glareolus, Apodemus uralensis, Mus musculus, Dryomys nitedula, Sorex araneus, Sorex minutus, and Crocidura suaveolens [5]. Previous studies have shown that the highest infection rate with the hantavirus is observed in the wood mouse Apodemus uralensis, although infection levels vary significantly depending on the species and year of observation [6]. However, the available data on the infection rate of small mammals in the West Kazakhstan Region are fragmentary and cover different time periods.

In this context, obtaining up-to-date epizootiological data using molecular methods is important for documenting current hantavirus circulation and its spatial distribution in the West Kazakhstan Region. The aim of the present study was to characterize hantavirus RNA detection among small mammals using RT-PCR and to compare rodent sampling locations with reported human HFRS occurrence in 2025.

2. Materials and Methods

2.1. Study Design

The study was observational and descriptive-analytical in nature and aimed to characterize hantavirus RNA detection among small mammals in natural focal areas of the West Kazakhstan Region in 2025.

2.2. Study Material

The study material consisted of lung tissue samples from small mammals captured in various natural focal zones of the West Kazakhstan Region. All captured rodent individuals were included in the study.

2.3. Capture and Species Identification

Small mammals were captured using “Hero” traps of various modifications with standard bread bait. Traps were set at 2-meter intervals, taking into account the landscape features of the territories and signs of rodent activity [7].

Species identification of the captured animals was performed based on morphological characteristics using generally accepted keys for mammals [8,9,10].

2.4. Sample Preparation and RNA Extraction

Prior to laboratory testing, lung tissue samples were pooled by host species and capture location. A total of 123 pooled testing units were formed from 329 animals. Pool size ranged from 1 to 6 animals, depending on the host species and the number of animals available at each sampling location. Most Apodemus uralensis pools contained five animals, whereas Myodes glareolus and Microtus arvalis were predominantly tested individually. Fourteen specimens from the same 2025 surveillance campaign were tested individually by PCR rather than in pools; these specimens were treated as testing units with a pool size of one in the revised statistical analysis. Thus, the complete molecular testing dataset comprised 137 testing units representing 343 individual animals. Rodent lungs were homogenized using a “TissueLyser II” homogenizer (QIAGEN, Germany) with the addition of 1 mL of physiological saline and 3 mm diameter metal beads (2 beads per sample) [11]. Ribonucleic acid was extracted from the resulting suspensions using a commercial kit “QIAamp Viral RNA Mini Kit” (QIAGEN, Germany) according to the manufacturer’s instructions.

Detection of Hantavirus RNA by RT-PCR

Real-time RT-qPCR. For the detection of hantavirus RNA, real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed using the Qiagen OneStep RT-PCR Mix (Cat. No. 210212, Qiagen, Germany). Amplification was carried out on a Rotor-Gene 6000 thermocycler. The assay targeted a partial sequence of the L segment with an expected amplicon size of 230 bp [12]. The primer mix contained each primer at a concentration of 0.125 µM and was supplemented with EvaGreen (VWR International, Vienna, Austria). Samples with a Ct value ≤40 were considered positive by real-time RT-qPCR. All samples were subsequently subjected to conventional RT-PCR, regardless of their Ct value, and the PCR products were analyzed by agarose gel electrophoresis. Samples showing the expected 380-bp amplicon were considered confirmed positive.

Table 1. Oligonucleotide primers used for real-time RT-qPCR in this study.

Primer Name	Sequence (5′–3′)	Direction
Pan-Hanta 1a-fw	TgATgCATATTgTgTgCAgAC	Forward
Pan-Hanta 1b-fw	TgATgCATACTgTgTgCAAAC	Forward
Pan-Hanta 1c-fw	CAgTATgATgCATACTgTgTCCAA	Forward
Pan-Hanta 1d-fw	TgATgCCTATTgTgTTCAgAC	Forward
Pan-Hanta 1a-rev	CTTgCTCTgTTTTgAATCTCA	Reverse
Pan-Hanta 1b-rev	CTTgCTCggTgTTgAATCgCA	Reverse
Pan-Hanta 1c-rev	CCTgTTCTgTATTAAATCTCA	Reverse
Pan-Hanta 1d-rev	CTTgTTCAgTCTTgAATCTCA	Reverse

Table 1. Oligonucleotide primers used for real-time RT-qPCR in this study.

Primer Name	Sequence (5′–3′)	Direction
Pan-Hanta 1a-fw	TgATgCATATTgTgTgCAgAC	Forward
Pan-Hanta 1b-fw	TgATgCATACTgTgTgCAAAC	Forward
Pan-Hanta 1c-fw	CAgTATgATgCATACTgTgTCCAA	Forward
Pan-Hanta 1d-fw	TgATgCCTATTgTgTTCAgAC	Forward
Pan-Hanta 1a-rev	CTTgCTCTgTTTTgAATCTCA	Reverse
Pan-Hanta 1b-rev	CTTgCTCggTgTTgAATCgCA	Reverse
Pan-Hanta 1c-rev	CCTgTTCTgTATTAAATCTCA	Reverse
Pan-Hanta 1d-rev	CTTgTTCAgTCTTgAATCTCA	Reverse

Conventional RT-PCR. For additional molecular confirmation, conventional RT-PCR was performed to amplify a fragment of the S segment using broadly reactive primers targeting orthohantaviruses. RNA was reverse-transcribed and amplified using the SuperScript III One-Step RT-PCR System with Platinum Taq High Fidelity Polymerase (Invitrogen, Langenselbold, Germany) and the primers DOBV-M6 (5′-AGYCCWGTNATGRGWGTRATTGG-3′) and DOBV-M8 (5′-GAKGCCATRATNGTRTTYCKCATRTCCTG-3′), as described previously [13,14]. Amplification was performed on a Rotor-Gene 6000 thermocycler using the following program: reverse transcription at 50 °C for 30 min; initial denaturation at 94 °C for 2 min; followed by 50 cycles of 94 °C for 25 s, 54 °C for 50 s, and 68 °C for 60 s; and a final extension at 68 °C for 10 min. Amplification products were analyzed by electrophoresis in a 1.5% agarose gel. The expected amplicon size was approximately 380 bp [15,16].

No sequencing of the PCR products was performed. Therefore, the detected hantavirus RNA could not be assigned to a specific orthohantavirus species, serotype, or genetic lineage.

2.5. Statistical Analysis

The minimum infection rate (MIR) was calculated as the number of hantavirus RNA-positive testing units divided by the total number of individual animals tested and expressed as a percentage. Individually tested specimens were treated as testing units with a pool size of one. MIR was calculated overall, by host species, and by district and was interpreted as a descriptive minimum estimate because a positive pooled testing unit indicates that at least one animal in that unit was positive. Because testing units varied in size, individual-level infection probability was additionally estimated using a pooled-testing likelihood model. For a testing unit containing nᵢ animals, the probability of a positive result was modeled as 1 − (1 − p)ⁿᵢ, and the probability of a negative result as (1 − p)ⁿᵢ, where p is the underlying individual-level infection probability. The likelihood was constructed across all testing units using the observed molecular result and actual testing-unit size. The maximum-likelihood estimate (MLE) was obtained numerically, and 95% confidence intervals were calculated using the profile-likelihood method [25,26]. The model assumes independent infection status within testing units and negligible false-positive and false-negative classification error. Species-specific estimates were interpreted descriptively because species differed in sample size and pooling structure. No inference regarding reservoir competence or relative reservoir importance was made solely from the observed positive testing units.

2.6. Ethical Aspects

All stages of the study were conducted in compliance with generally accepted ethical principles for handling laboratory and wild animals, in accordance with national and international recommendations for the humane treatment of animals in scientific research. Capture and euthanasia of animals were performed using methods that minimize stress and suffering.

3. Results

3.1. Capture of Small Mammals in Study Areas

Capture of small rodents was carried out in the Burlinsky, Baytereksky, Chingirlauisky, and Terektiinsky districts of the West Kazakhstan Region. Rodent trapping was conducted from late August to September 2025. During the field studies, 343 individuals of small mammals were captured. Information on species diversity and capture locations is presented in Table 2.

In the species composition, the wood mouse (Apodemus uralensis) dominated, accounting for 74.3% of the total captured animals. The bank vole (Myodes glareolus) comprised 17.2%. Significantly smaller proportions were represented by the common vole (Microtus arvalis) - 4.4%, field mouse (Apodemus agrarius) - 1.5%, and common shrew (Sorex araneus) - 1.7%. The remaining species (water vole, house mouse, pygmy shrew) occurred singly and collectively accounted for less than 1%.

3.2. Molecular Detection Results

Molecular testing identified hantavirus RNA in 47 of 137 testing units representing 343 small mammals. Forty-five positive results were obtained from pooled testing units and two from individually tested specimens. Positive testing units were observed among Apodemus uralensis, Myodes glareolus, and Microtus arvalis (Table 3).

MIR, minimum infection rate, calculated as the number of positive testing units divided by the total number of individual animals tested. MIR is a descriptive minimum estimate because each positive testing unit may contain more than one infected animal. The model-based estimate represents the maximum-likelihood estimate of individual-level infection probability under the pooled-testing model; 95% CIs are profile-likelihood intervals that account for testing-unit size [25,26].

Hantavirus RNA was detected in 47 of 137 testing units representing 343 small mammals, corresponding to a descriptive MIR of 13.7%. Positive results comprised 45/123 pooled testing units and 2/14 individually tested specimens. The pooled-testing likelihood model estimated an individual-level infection probability of 18.0% (95% profile-likelihood CI: 13.5–23.1%). Among the principal host species, Apodemus uralensis accounted for 36 positive testing units among 255 animals, with a descriptive MIR of 14.1% and a model-based estimate of 21.0% (95% CI: 15.2–28.0%). Myodes glareolus had 9 positive testing units among 59 individually tested animals, corresponding to a MIR and model-based estimate of 15.3% (95% CI: 7.6–25.8%). Microtus arvalis had 2 positive testing units among 15 animals, with a MIR and model-based estimate of 13.3% (95% CI: 2.3–35.8%). No positive testing units were detected among the remaining species. Because pooling intensity differed among host species, these estimates are interpreted descriptively and do not establish differences in individual-level infection prevalence or reservoir importance among host species.

3.3. Spatial Relationship Between Rodent Sampling Sites and Human HFRS Cases

To provide epidemiological context, the locations of rodent sampling sites in the present study were compared with the distribution of human HFRS cases reported in the West Kazakhstan Region in 2025. The comparison was performed at the settlement level whenever the sampling location corresponded to a named settlement.

In 2025, small mammals were collected at 17 sampling sites located in four districts of the West Kazakhstan Region: Burlinsky, Chingirlauisky, Terektiinsky, and Baytereksky districts. A total of 343 animals were collected. Several sampling sites corresponded to settlements in which human HFRS cases were reported during the same year (Table 4).

Note: “—“ indicates that no corresponding record was available in the respective dataset. Human HFRS case data were derived from the detailed epidemiological dataset [24]; official regional surveillance data reported 47 cases in 2025 [2].

Among the sampling sites, Utvinka in Burlinsky District was associated with two reported human HFRS cases, while Daryinsk and Rubezhinskoye in Baytereksky District were associated with eight and two cases, respectively [24]. In Daryinsk, 48 small mammals were collected, whereas 15 small mammals were collected in Rubezhinskoye. In Utvinka, one Apodemus uralensis was collected.

At the district level, hantavirus RNA-positive testing units were detected in all four investigated districts. The descriptive MIR was 19.0% in Chingirlauisky District, 12.6% in Terektiinsky District, 12.7% in Baytereksky District, and 11.6% in Burlinsky District. These values are descriptive minimum estimates and should not be interpreted as directly comparable individual-level prevalence estimates because the number and size of testing units differed among districts. The spatial distribution of human HFRS cases therefore partially overlapped with areas in which hantavirus RNA was detected in small mammals, but this spatial coincidence does not establish a direct transmission link.

4. Discussion

The present study provides current molecular surveillance data on hantavirus RNA among small mammals in the West Kazakhstan Region in 2025. Positive testing units were detected in three host species and in all four investigated districts, demonstrating that hantavirus RNA was detectable across multiple host taxa and locations during the study period. Because no sequencing was performed, the detected RNA could not be assigned to a specific orthohantavirus species or genetic lineage.

The descriptive overall MIR was 13.7%. MIR is appropriate as a minimum estimate in pooled surveillance because a positive testing unit establishes that at least one animal in that unit was positive, but does not determine how many animals were infected. To account for the variable testing-unit size, we additionally applied a pooled-testing likelihood model. The resulting model-based estimate of individual-level infection probability was 18.0% (95% profile-likelihood CI: 13.5–23.1%). The difference between MIR and the model-based estimate illustrates why positive pooled results should not be interpreted as direct individual-level prevalence.

The host-species results should also be interpreted cautiously. Apodemus uralensis contributed the largest number of positive testing units and represented the majority of animals examined, while Myodes glareolus showed a higher descriptive MIR than Apodemus uralensis in the original pooled dataset. After accounting for testing-unit size and the 14 individually tested specimens, the model-based estimates were 21.0% for Apodemus uralensis, 15.3% for Myodes glareolus, and 13.3% for Microtus arvalis, with wide and overlapping confidence intervals. These results do not establish differences in reservoir competence, reservoir importance, or the relative contribution of these species to virus maintenance. Such conclusions would require standardized sampling, adequate individual-level testing or appropriately designed pooled analyses, repeated temporal observations, and molecular characterization.

No hantavirus RNA was detected in Apodemus agrarius, Sorex araneus, Sorex minutus, Arvicola amphibius, or Mus musculus in the present sample. Because several of these taxa were represented by very few animals, absence of a positive result should not be interpreted as evidence that these species cannot participate in hantavirus circulation.

Spatially, positive testing units were detected in all four investigated districts, with the highest descriptive MIR in Chingirlauisky District (19.0%). The district-level differences should be considered descriptive because sample sizes and testing-unit structures were not uniform. The observed heterogeneity may reflect differences in host composition, sampling intensity, local environmental conditions, or other unmeasured factors, but the present study was not designed to identify the determinants of spatial variation.

The human surveillance comparison provides complementary epidemiological context. Several rodent sampling sites were located in settlements where human HFRS cases were reported in 2025, including Utvinka, Daryinsk, and Rubezhinskoye. However, the settlement-level dataset contained 42 cases, whereas the official regional surveillance report recorded 47 cases. The detailed dataset was therefore used only for spatial comparison and should not be interpreted as a complete regional case count.

The present findings are also consistent with previous evidence of hantavirus exposure among residents of West Kazakhstan. In a 2023 seroepidemiological study of 921 adults from 14 rural settlements in the Bayterek and Boryly districts, hantavirus antibody seroprevalence was 3.1% (95% CI: 2.1–4.3%). Among 28 seropositive participants, 14 showed a serological pattern consistent with PUUV, while other samples demonstrated cross-reactivity with PUUV, HTNV, and DOBV antigens [23]. The geographic overlap between human serological evidence and hantavirus RNA-positive small mammals provides complementary evidence of ongoing hantavirus circulation in the region, but it does not identify the viral genotype or establish a direct animal-to-human transmission chain.

Taken together, the rodent and human data support continued integrated surveillance of hantavirus in Western Kazakhstan. Future studies should incorporate standardized individual-level or modelled pooled testing, repeated seasonal and multi-year sampling, and sequencing of PCR-positive specimens. These additions would allow more robust assessment of host associations, viral diversity, and the relationship between animal surveillance findings and human HFRS.

The comparison of small-mammal detections with human HFRS occurrence should therefore be regarded as a spatial descriptive analysis rather than evidence of direct transmission. Point-level epidemiological linkage would require more detailed information on human exposure history, timing, location, and molecular characteristics of viruses detected in humans and animals.

The present study provides evidence of hantavirus RNA circulation among small mammals in multiple locations of the West Kazakhstan Region in 2025. Hantavirus RNA-positive testing units were detected among Apodemus uralensis, Myodes glareolus, and Microtus arvalis. The overall descriptive MIR was 13.7%, while the pooled-testing likelihood model estimated an individual-level infection probability of 18.0% (95% profile-likelihood CI: 13.5–23.1%). Because testing-unit size and pooling intensity differed among host species and districts, these estimates should be interpreted as descriptive/model-based measures rather than direct evidence of individual-level prevalence or differences in reservoir importance. The spatial overlap between rodent sampling sites and settlements reporting human HFRS cases provides epidemiological context but does not establish a direct transmission link. Continued integrated animal–human surveillance, standardized sampling, and molecular characterization of positive specimens are warranted to clarify hantavirus diversity, host associations, and epidemiological risk in the region.

5. Conclusions

The present study documented hantavirus RNA circulation among small mammals in the West Kazakhstan Region in 2025. Hantavirus RNA-positive testing units were detected among Apodemus uralensis, Myodes glareolus, and Microtus arvalis and in all four investigated districts. The overall descriptive minimum infection rate was 13.7%, while the pooled-testing likelihood model estimated an individual-level infection probability of 18.0% (95% profile-likelihood CI: 13.5–23.1%). Because testing-unit size and pooling intensity differed among host species and districts, these estimates should be interpreted as descriptive/model-based measures rather than direct evidence of individual-level prevalence or differences in reservoir importance. The spatial overlap between rodent sampling sites and settlements reporting human HFRS cases provides epidemiological context but does not establish a direct transmission link. Continued integrated animal–human surveillance, standardized sampling, and molecular characterization of positive specimens are warranted to clarify hantavirus diversity, host associations, and epidemiological risk in the region.