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ISSN : 1225-0171(Print)
ISSN : 2287-545X(Online)
Korean Journal of Applied Entomology Vol.65 No.3 pp.241-250
DOI : https://doi.org/10.5656/KSAE.2026.04.1.071

Year-Round Surveillance of Ticks and SFTSV in Andong, South Korea (2019–2022)

Ye Eun Park1, Young Ho Kim1,2*
1Department of Ecological Science, Kyungpook National University, Sangju 37224, Korea
2Research Institute of Invertebrate Vector, Kyungpook National University, Sangju 37224, Korea
*Corresponding author:yhkim05@knu.ac.kr
December 29, 2025 April 15, 2026 July 2, 2026

Abstract


We conducted long-term field monitoring of hard ticks collected in Andong, South Korea, from 2019 to 2022, in four environments (grassland, mountain trail, graveyard, and copse) with CO2-baited trap. The collected ticks were identified morphologically and molecularly, and pooled RNA samples were tested for severe fever with thrombocytopenia syndrome virus (SFTSV) (Dabie bandavirus, Phenuiviridae, Bunyavirales). A total of 2,491 ticks were collected, with Haemaphysalis longicornis comprising 88.4% of specimens, followed by H. flava (10.4%), Ixodes nipponensis (0.6%), Haemaphysalis larvae (0.5%), and Ixodes spp. (0.1%). Population peaks of nymphs, adults, and larvae were observed in April, June, and August, respectively, indicating univoltine life cycle of H. longicornis. Among the 287 RNA pools tested, 18 were positive for SFTSV, yielding a minimum infection rate (MIR) of 1.43%. The MIR was highest in October (16.67%) and highest by species in H. flava (10.0%). All viral sequences belonged to genotype B-2. The integration of quantitative species identification with pathogen detection enhances tick surveillance strategies and facilitates early identification of emerging tick-borne diseases in endemic regions.


Haemaphysalis longicornis , Haemaphysalis flava , Molecular tick identification , Tick surveillance , Severe fever with thrombocytopenia syndrome virus

2019–2022년 경북 안동 지역에서의 참진드기 연중 발생 양상 및 SFTSV 감염 실태

박예은1, 김영호1,2*
1경북대학교 생태과학과
2경북대학교 질병매개무척추동물연구소

초록


본 연구는 경상북도 안동에서 참진드기의 계절별 발생 양상과 중증열성혈소판감소증후군 바이러스(severe fever with thrombocytopenia syndrome virus, SFTSV) (Dabie bandavirus, Phenuiviridae, Bunyavirales)의 감염률을 조사하기 위해 2019년부터 2022년까지 초지, 산길, 무덤, 잡목림 환경에서 CO2-baited trap을 이용하여 참진드기를 채집하였다. 특히, 형태적 구분이 어려운 Haemaphysalis 속 유충에 대해서는 PCR 기반 분자 동정 기법을 적용하여 밀도 조사를 수행하였다. 조사 기간 동안 총 2,491개체의 참진드기가 채집되었으며, 형태 및 분자 생물학적 동정을 통해 작은소피참진드기(H. longicornis)가 전체의 88.4%로 가장 높은 비율을 차지하였다. 작은소피참진드기의 약충, 성충, 유충이 각각 4월, 6월, 8월에 개체 수 정점을 보여 1년 생활사가 확인되었다. 채집된 참진드기를 채집일, 환경, 종, 발달 단계에 따라 풀링한 RNA 샘플을 대상으로 SFTSV를 검사한 결과, 총 287개 풀 중 18개 풀에서 SFTSV 양성이 확인되었으며, 최소감염률(minimum infection rate, MIR)은 1.43%로 나타났다. 월별 MIR은 10월에 16.67%로 가장 높았으며, 종별로는 개피참진드기(H. flava)에서 10.00%로 가장 높은 감염률을 보였다. 검출된 SFTSV는 모두 유전자형 B-2로 확인되었다. 본 연구의 결과는 진드기 종별·계절별 발생 특성과 SFTSV 감염 실태에 대한 기초 생태학적 정보를 제공하며, 향후 진드기 매개 감염병의 방제 전략 및 역학 조사에 유용한 자료로 활용될 수 있을 것으로 기대된다.


작은소피참진드기 , 개피참진드기 , 분자동정 , 참진드기 모니터링 , 중증열성혈소판감소증후군 바이러스

    Introduction

    Ticks (family Ixodidae) undergo four developmental stages in their life cycle: egg, larva (six-legged), nymph (eight-legged), and adult (Barker and Walker, 2014;Nava et al., 2017). They are obligate blood-feeding ectoparasites, requiring a blood meal from a wide range of hosts—including amphibians, reptiles, birds, mammals, and humans—to progress through each life stage. Due to this hematophagous behavior, ticks can transmit various pathogens such as bacteria, parasites, and viruses to humans (Hajdušek et al., 2013;Jongejan and Uilenberg, 2004;Lu et al., 2015).

    Critical tick-borne diseases reported in Europe and the United States include Rocky Mountain spotted fever, Helvetica spotted fever, Colorado tick fever, cytauxzoonosis, tularemia, relapsing fever, ehrlichiosis, babesiosis, and Lyme disease (Bratton and Corey, 2005;Portillo et al., 2015;Wikander and Reif, 2023). Among these, severe fever with thrombocytopenia syndrome (SFTS) was first reported in China in 2009 and later in Japan and South Korea in 2012 and 2013, respectively (Ding et al., 2013;Kim et al., 2013;Takahashi et al., 2014). Typical clinical symptoms of SFTS include vomiting, multiple organ dysfunction syndrome, fever, and severe cases lead to fatal (Ding et al., 2013;Kim and Oh, 2014). In South Korea, a total of 2,065 SFTS cases were reported between 2013 and 2024, with a case fatality rate of 18.5%, underscoring the disease’s public health significance (Korea Disease Control and Prevention Agency, 2025).

    Given the role of ticks as vectors of emerging infectious diseases, monitoring seasonal dynamics and pathogen infection rates is critical for effective disease prevention and control. However, accurate species identification of Haemaphysalis larvae remains challenging due to morphological similarity between species. To address this limitation, our previous study (Lee et al., 2021) developed a PCR-based molecular identification method using species-specific primers for H. longicornis and H. flava. In the present study, we applied both morphological and molecular identification methods to investigate the seasonal and habitat-specific distribution of hard ticks, with a particular focus on Haemaphysalis larvae. In addition, we screened pooled RNA samples from the collected ticks for SFTS virus (SFTSV) (Dabie bandavirus, Phenuiviridae, Bunyavirales) infection. As part of a tick-borne disease surveillance program supported by the Korea Disease Control and Prevention Agency (KDCA), ticks were collected monthly from April to November between 2019 and 2022 in four distinct environments—grassland, mountain trails, graveyards, and copses—in Andong, Gyeongsangbuk-do, as one of the designed sites in the national monitoring program.

    Materials and Methods

    Tick monitoring

    Tick surveillance was conducted monthly from April to November between 2019 and 2022 in four distinct habitats in Andong, Gyeongsangbuk-do, South Korea: Grassland (36°37′44.76″N 128°36′45.36″E), Mountain trail (36°37′46.55″N 128°36′42.65″E), graveyard (36°37′46.13″N 128°36′41.98″E), and copse (36°37′46.81″N 128°36′41.4″E) (Lee et al., 2021). The grassland consisted of grasses and mixed herbaceous vegetation less than 1 m in height and was located adjacent to a reservoir. The mountain trail was covered with leaf litter and featured short grasses and herbaceous vegetation on the ground, with various shrubs along the trail margins. The graveyard was surrounded by mixed coniferous and broadleaf forests and was covered with short grasses and herbaceous vegetation, which were less than 1 m in height during spring and summer and less than 30 cm in autumn and winter due to mowing. The copse consisted of coniferous and broadleaf trees, with a ground layer covered by grasses and herbaceous vegetation and shrubs in the understory. Ticks were collected using CO2-baited traps (Shin-Young Commerce System, Gyeonggi-do, South Korea) filled with dry ice. After 24 hours of trap deployment, the ticks were retrieved and transported to the laboratory.

    In the lab, the collected ticks were anesthetized on ice to minimize movement and examined under a stereoscopic microscope (Olympus, Tokyo, Japan). Morphological identification was performed using standard taxonomic keys (Guglielmone et al., 2020;Yamaguti et al., 1971). Adult and nymphal ticks were identified to the species level, whereas larvae were identified to the genus level. Due to the morphological similarity of Haemaphysalis larvae, molecular identification was performed using a previously established method targeting the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene with species-specific primers for H. longicornis and H. flava (Lee et al., 2021) (Table S1). Because SFTSV detection required RNA extraction, only RNA samples were available for subsequent analyses. In many cases, the amount of field-collected tick material was limited, making additional DNA extraction impractical and potentially insufficient for parallel analyses. Moreover, performing separate DNA extraction would require additional experimental steps, increasing both time and resource demands. Therefore, in our previous study (Lee et al., 2021), we developed a molecular identification method that enables species-level identification using RNA extracts by targeting the housekeeping gene GAPDH. In the present study, we applied this method to allow simultaneous SFTSV detection and species identification from the same RNA samples.

    Following morphological identification, approximately half of the collected specimens were pooled for SFTSV detection and species-level molecular identification. Tick samples were pooled according to collection date, location, species, and developmental stage, with a maximum of 5 adults, 30 nymphs, or 50 larvae per pool.

    RNA extraction

    Ticks were homogenized in 400 µL of NucleoZOL (Macherey-Nagel, Düren, Germany) using 2.8 mm stainless steel beads (Innogenetech, Gyeonggi-do, South Korea) at 6,600 rpm for 30 seconds, repeated three times. Total RNA was extracted using the Direct-zol RNA extraction kit (Zymo Research, Irvine, CA, USA) for samples collected in 2019–2020, and the Clear-S total RNA extraction kit (Cat. No. IVT3001; Invirustech, Gwangju, South Korea) for those collected in 2021–2022, according to the manufacturers’ protocols. To assess potential methodological variation between sampling periods, a comparison of the RNA extraction methods was conducted and is provided in the Supplementary Materials (Table S2). The extracted RNA was used for SFTSV detection and molecular identification of Haemaphysalis larvae.

    SFTSV detection and sequencing

    SFTSV detection in ticks collected in 2019 and 2020 was performed as previously described (Lee et al., 2021) (Table S1). For ticks collected in 2021 and 2022, detection was carried out using the Clear-MD SFTSV Real-time Nested RT-PCR Detection Kit (Cat. No. IVT-M1002; Invirustech, Gwangju, South Korea). To evaluate the potential impact of methodological differences on detection performance, a comparative analysis of the detection methods was performed and is summarized in the Supplementary Materials (Table S2 and Fig. S1).

    The primary RT-PCR was conducted using a T100 Thermal Cycler (Bio-Rad, Hercules, CA, USA) with a 20 µL reaction mixture containing 10 µL of RNase-free water, 5 µL of tick RNA, 4 µL of 5× RT-PCR mix, and 1 µL of 1st Detection Primer (provided by the manufacturer). The cycling conditions were as follows: 50°C for 10 minutes, 95°C for 3 minutes, followed by 30 cycles of 95°C for 20 seconds, 60°C for 20 seconds, and 72°C for 40 seconds, with a final extension at 60°C for 20 seconds.

    Nested PCR was then performed in a 20 µL reaction mixture consisting of 7 µL of distilled water, 1 µL of 2nd Detection Primer (provided by the manufacturer), 1 µL of 20× loading dye, 10 µL of 2× qPCR mix, and 1 µL of the primary PCR product. The thermal cycling conditions were: 95°C for 3 minutes, followed by 27 cycles of 95°C for 20 seconds and 58°C for 40 seconds.

    Amplicons were visualized using agarose gel electrophoresis. Samples suspected to be SFTSV-positive were purified using the QIAquick PCR Purification Kit (Qiagen, Hilden, Germany) and sequenced (Macrogen, Seoul, South Korea). Sequence identity was confirmed using BLAST analysis against the NCBI nucleotide database. All SFTSV sequences generated in this study are available in GenBank (accession no. PZ241881–PZ241895). The minimum infection rate (MIR) was calculated as the number of positive pools divided by the total number of tested ticks, multiplied by 100.

    Phylogenetic analysis

    Among the 18 SFTSV-positive samples, sequence analysis was performed on the 15 samples that yielded high-quality reads. The 15 sequences obtained in this study were analyzed alongside 47 reference sequences from South Korea, China, and Japan retrieved from GenBank. The SFTSV sequences, including those derived from clinically reported SFTS cases, were included where available for the same genomic region. A 219-bp region of the M segment was aligned using the ClustalW algorithm implemented in MEGA software (version 10.2) (Kumar et al., 2018). Phylogenetic analysis was conducted using the maximum likelihood (ML) method with 1,000 bootstrap replicates to assess branch support.

    Results

    Monitoring of hard ticks

    A total of 22 larval pools were collected between 2019 and 2022 and analyzed by PCR using species-specific primers targeting the GAPDH gene, following a previously developed method (Lee et al., 2021). This GAPDH-based molecular identification method has been previously validated for both individual and mixed-species samples, and Lee et al. (2021) demonstrated reliable species discrimination in pooled larval samples. H. longicornis and H. flava amplicons were detected in 12 and 1 pools, respectively, indicating that most larval pools consisted of a single species (Fig. 1). One pool collected in August 2020 yielded amplicons for both H. longicornis and H. flava, suggesting a mixed population. No amplification was observed in eight pools (September 2019; June 2020-1, -2; May 2021; June 2021; July 2021; August 2021-1; and July 2022) (Fig. 1). Both the mixed-species pool and the non-amplified pools were classified as Haemaphysalis spp.

    Based on molecular identification of larvae and morphological identification of nymphs and adults, a total of 2,491 ticks were collected over the four-year surveillance period from four distinct habitats: grassland, mountain trail, graveyard, and copse (Table S3). Notably, H. longicornis was the most prevalent species, accounting for 88.4% of all ticks collected, followed by H. flava (10.4%) and I. nipponensis (0.6%) (Fig. 2A). H. longicornis was consistently dominant across all habitats, with detection rates of 93.3% in grassland, 88.6% on mountain trails, 85.5% in graveyards, and 63.4% in copses (Fig. 2B–E).

    Monthly collection trends revealed that total tick abundance peaked in April, June, and August (Fig. 3A & Table S4). Seasonal dynamics of H. longicornis showed distinct peaks corresponding to developmental stages: nymphs in April, adults in June, and larvae in August (Fig. 3B & Table S4). In contrast, H. flava nymphs and adults peaked in April, followed by a decline and a secondary increase that extended into November (Fig. 3C & Table S4).

    SFTSV detection and phylogenetic analysis

    To detect SFTSV, 287 pools comprising 1,257 ticks (approximately half of the total collected specimens) were prepared and stratified by collection date, environment, tick species, and developmental stage. Among these, 18 pools tested positive for SFTSV during the four-year study period (Table S5).

    Monthly minimum infection rate (MIR) analysis revealed the highest rate in October (16.67%), followed by September (7.69%), April (3.16%), August (0.78%), and June (0.38%) (Table 1). MIR also varied by species, with the highest rate observed in H. flava (10.0%), followed by H. longicornis (0.88%) (Table 2). SFTSV infection was detected across multiple species, developmental stages, and environments, as detailed in Table S5.

    Phylogenetic analysis of the SFTSV sequences, conducted alongside reference strains from South Korea, China, and Japan, revealed that all sequences obtained in this study clustered within genotype B-2. This genotype is a sublineage of the broader genotype B clade, which includes B-1, B-2, and B-3 (Fig. 4).

    Discussion

    Our four-year tick surveillance in Andong confirmed H. longicornis as the dominant species, comprising 88.4% of all ticks collected (Fig. 2A). This result aligns with previous national and regional studies consistently identifying H. longicornis as the most prevalent tick species in South Korea (Jin et al., 2021;Johnson et al., 2017;Jung et al., 2019;Lee et al., 2021). H. longicornis was dominant across all surveyed environments (Fig. 2B–E), whereas H. flava was least abundant in grassland (5.0%) but more frequently detected in other habitats, supporting earlier observations that grasslands are unfavorable habitats for H. flava (Kakuda et al., 1990).

    The observed seasonal peaks of H. longicornis—nymphs in April, adults in June, and larvae in August (Fig. 3B & Table S4)—support a one-year life cycle, consistent with developmental and field-based studies (Kakuda et al., 1990;Zheng et al., 2011). In South Korea, previous studies also reported univoltine life cycle in developmental stages of H. longicornis from spring to autumn in Gyeonggi-do and Ganghwa Island (Jung et al., 2019;Kim-Jeon et al., 2019;Jin et al., 2021;Jung and Lee, 2023). In contrast, H. flava nymphs and adults were most frequently collected in spring and autumn (Fig. 3C & Table S4), consistent with previous findings from Chungcheongbuk-do, Chungcheongnam-do, Jeollabuk-do, and Jeollanam-do (Coburn et al., 2016). However, the absence of a clear larval peak precluded confirmation of a one-year life cycle for H. flava in this study. These seasonal patterns are likely shaped by ecological factors such as temperature, precipitation, humidity, vegetation conditions, and host availability. Consistent with this, we observed distinct developmental stage-specific peaks in this study, which align with patterns reported in previous tick surveillance studies in South Korea (Jung et al., 2019;Kim-Jeon et al., 2019;Jin et al., 2021;Jung and Lee, 2023). These life cycle patterns are crucial for predicting seasonal risk of tick-borne pathogen transmission.

    In this study, PCR was used to identify Haemaphysalis larvae (Fig. 1). Although effective, limitations arose in cases with insufficient nucleic acid—especially in pools with low tick counts—or when both species were amplified simultaneously, resulting in ambiguous identification. These findings underscore the need for more sensitive and quantitative tools to improve pooled tick sample analysis.

    A key strength of this study was the integration of molecular identification with SFTSV screening using the same RNA extracts. SFTSV was detected in nymphs and adults of H. longicornis and H. flava, but not in larvae or I. nipponensis (Table S4). However, previous studies have reported SFTSV detection in larval Haemaphysalis spp. and I. nipponensis (Suh et al., 2016;Oh et al., 2016;Lee et al., 2021), suggesting that various tick species and life stages may contribute to virus transmission and emphasizing the need for broader surveillance.

    The overall MIR was 1.43% over four years (Table 1), which exceeds MIR values reported in most other Korean regions (0.08–1.13%) (Park et al., 2014). The relatively high MIR observed in Andong may reflect more intense local circulation of SFTSV, which is consistent with KDCA surveillance indicating that Gyeongsangbuk-do has reported relatively high numbers of SFTS cases in multiple years. Although H. flava was less abundant than H. longicornis, it showed a higher MIR (10.0% vs. 0.88%), consistent with previous reports (Chae et al., 2017;Kang et al., 2022). Notably, MIR peaked in October (16.67%) (Table 1), corresponding with previous studies reporting elevated SFTSV infection rates in autumn (Park et al., 2014;Lee et al., 2021;Kang et al., 2022). According to KDCA data, the number of human SFTS cases also peaks in October (Korea Disease Control and Prevention Agency, 2025), likely due to ecological and behavioral factors. During this period, H. flava nymph and adult populations increase (Fig. 3C & Table S4), and previous studies have consistently reported high MIR in this species (Kim-Jeon et al., 2019;Lee et al., 2021;Jung and Lee, 2023). Both our study and previous studies have reported relatively high MIR in H. flava (Table 2). Moreover, traditional outdoor activities, such as cemetery visits during Chuseok, may elevate human–tick contact (Coburn et al., 2016). These combined factors likely contribute to the seasonal spike in SFTS incidence. The observed autumn peak in MIR and tick activity suggests an increased risk of SFTS transmission to humans in the Andong region, highlighting the need for targeted public health interventions and risk communication during this period.

    Phylogenetic analysis of partial M-segment sequences revealed that all SFTSV isolates from this study belonged to genotype B-2 (Fig. 4), and the clustering of Andong strains suggests the existence of regional sublineages. Although this study does not confirm local endemicity, it lays the groundwork for further research into regional virus evolution and transmission dynamics. Genotype B-2 is the most prevalent in South Korea, where genotypes A through F have been reported (Yun et al., 2020;Lee et al., 2022;Moon et al., 2023).

    Genotype B is also dominant in Japan, where mortality rates are comparable to South Korea, whereas genotypes A and F are more prevalent in China, where mortality rates tend to be lower (Zhan et al., 2017;Gokuden et al., 2018;Korea Disease Control and Prevention Agency, 2025;Robles et al., 2018;Lee et al., 2022). These trends suggest a possible correlation between genotype prevalence and SFTS fatality rates across countries. Furthermore, ongoing recombination and evolution of SFTSV strains continue to generate new genotypes (Yun et al., 2020;Li et al., 2021;Lee et al., 2022), emphasizing the need for nationwide surveillance incorporating both infection rates and genetic diversity.

    In summary, 2,491 ticks were collected from four different environments in Andong, South Korea, from 2019 to 2022. Based on morphological and molecular identification, H. longicornis was the dominant species across all habitats, with seasonal peaks by developmental stage in April (nymphs), June (adults), and August (larvae). SFTSV MIR was highest in October, and by species, highest in H. flava. Given the increased MIR and H. flava activity during autumn, intensified tick surveillance and public health interventions are warranted during this period. These findings highlight the importance of ongoing seasonal tick monitoring, species identification, and genotype-specific pathogen screening to reduce the risk of human infections in endemic areas.

    Supplementary Information

    Supplementary data are available at Korean Journal of Applied Entomology online (http://www.entomology2.or.kr).

    Acknowledgments

    This work was supported by the Research Program funded by the Korea Disease Control and Prevention Agency (6332-305-320). Y. E. P. was supported by an R&D Program for Forest Science Technology (RS-2024-00404388) provided by Korea Forest Service (Korea Forestry Promotion Institute). We would like to thank Ki Beom Park (Invirustech, Gwangju, South Korea) for verifying the detection efficiency of the two SFTSV detection methods through comparative analysis.

    Statements for Authorship Position & Contribution

    • Park, Y.E.: Kyungpook National University, Ph.D candidate; Investigated the ticks, conducted the experiment and wrote the manuscript

    • Kim, Y.H.: Kyungpook National University, Associate Professor; Designed the research, supervision, writing-review, and editing

    All authors read and approved the manuscript.

    Figure

    KJAE-65-3-241_F1.jpg

    Molecular identification of pooled Haemaphysalis larvae collected from the field between 2019 and 2022

    KJAE-65-3-241_F2.jpg

    Species composition of ticks collected in Andong, South Korea (2019–2022). Overall species distribution (A). Species distribution by habitat type: grassland (B), mountain trail (C), graveyard (D), and copse (E)

    KJAE-65-3-241_F3.jpg

    Seasonal dynamics of tick populations by species and developmental stage. Monthly total number of ticks collected (A). Monthly distribution of H. longicornis by developmental stage (B). Monthly distribution of H. flava by developmental stage (C)

    KJAE-65-3-241_F4.jpg

    Phylogenetic analysis of severe fever with thrombocytopenia syndrome virus (SFTSV) based on partial M-segment sequences (219 bp). A maximum likelihood tree was constructed using MEGA version 10.2 with 1,000 bootstrap replicates. Sequences obtained in this study are indicated with closed blue circles. GenBank accession numbers, host species, country, and year are shown for each reference sequence

    Table

    Monthly infection rates of SFTSV in ticks based on collection date (2019–2020)

    aMIR: minimum infection rate (number of positive pools/total number of tested ticks × 100)

    SFTSV infection rates in ticks by species (2019–2020)

    MIR: minimum infection rate (number of positive pools/total number of tested ticks × 100)

    Reference

    1. Barker, S.C.,Walker, A.R., 2014. Ticks of Australia. The species that infest domestic animals and humans . Zootaxa3816, 1-144.
    2. Bratton, R.L.,Corey, G.R., 2005. Tick-borne disease . Am. Fam. Physician.71, 2323-2330.
    3. Chae, J.-B.,Kang, J.-G.,Kim, H.-C.,Chong, S.-T.,Lee, I.-Y.,Shin, N.-S.,Chae, J.-S., 2017. Identification of tick species collected from wild boars and habitats of wild boars and domestic pigs in the Republic of Korea . Korean J. Parasitol.55, 185.
    4. Coburn, J.M.,Chong, S.-T.,Kim, H.-C.,Chang, N.W.,Calix, L.C.,Resto, K.,Lee, D.-J.,Johnson, J.L.,Robbins, R.G.,Klein, T.A., 2016. Tick surveillance in four southwestern provinces of the Republic of Korea during 2013 . Syst. Appl. Acarol.21, 147-165.
    5. Ding, F.,Zhang, W.,Wang, L.,Hu, W.,Soares Magalhaes, R.J.,Sun, H.,Zhou, H.,Sha, S.,Li, S.,Liu, Q., 2013. Epidemiologic features of severe fever with thrombocytopenia syndrome in China, 2011–2012 . Clin. Infect. Dis.56, 1682-1683.
    6. Gokuden, M.,Fukushi, S.,Saijo, M.,Nakadouzono, F.,Iwamoto, Y.,Yamamoto, M.,Hozumi, N.,Nakayama, K.,Ishitani, K.,Nishi, N., 2018. Low seroprevalence of severe fever with thrombocytopenia syndrome virus antibodies in individuals living in an endemic area in Japan . Jpn. J. Infect. Dis.71, 225-228.
    7. Guglielmone, A.A.,Petney, T.N.,Robbins, R.G., 2020. Ixodidae (Acari: Ixodoidea): descriptions and redescriptions of all known species from 1758 to December 31, 2019 . Zootaxa4871, 1–322.
    8. Hajdušek, O.,Šíma, R.,Ayllón, N.,Jalovecká, M.,Perner, J.,De La Fuente, J.,Kopáček, P., 2013. Interaction of the tick immune system with transmitted pathogens . Front. Cell. Infect. Microbiol.3, 26.
    9. Jin, K.,Koh, Y.-J.,Ahn, S.K.,Cho, J.,Lim, J.,Song, J.,Lee, J.,Gong, Y.W.,Kwon, M.J.,Kwon, H.W., 2021. Hard ticks as vectors tested negative for severe fever with thrombocytopenia syndrome in Ganghwa-do, Korea during 2019–2020 . Korean J. Parasitol.59, 281-289.
    10. Johnson, J.L.,Kim, H.-C.,Coburn, J.M.,Chong, S.-T.,Chang, N.W.,Robbins, R.G.,Klein, T.A., 2017. Tick surveillance in two southeastern provinces, including three metropolitan areas, of the Republic of Korea during 2014 . Syst. Apple. Acarol.22, 271-288.
    11. Jongejan, F.,Uilenberg, G., 2004. The global importance of ticks . Parasitol.129, S3-S14.
    12. Jung, M.,Kho, J.-W.,Lee, W.-G.,Roh, J.Y.,Lee, D.-H., 2019. Seasonal occurrence of Haemaphysalis longicornis (Acari: Ixodidae) and Haemaphysalis flava, vectors of severe fever with thrombocytopenia syndrome (SFTS) in South Korea . J. Med. Entomol.56, 1139-1144.
    13. Jung, M.,Lee, D.-H., 2023. Population dynamics of hard ticks (Acari: Ixodidae) and their harboring rates of Severe Fever with Thrombocytopenia Syndrome (SFTS) virus in four landscapes of Gyeonggi Province, South Korea . Exp. Appl. Acarol.91, 359-368.
    14. Kakuda, H.,Shiraishi, S.,Uchida, T., 1990. Seasonal fluctuations of populations and effects of temperatures on development and growth in the tick, Haemaphysalis flava . J. Fac. Agr. Kyushu Univ.35, 17-26.
    15. Kang, J.-G.,Cho, Y.-K.,Jo, Y.-S.,Han, S.-W.,Chae, J.-B.,Park, J.-E.,Jeong, H.,Jheong, W.-H.,Chae, J.-S., 2022. Severe fever with thrombocytopenia syndrome virus in ticks in the Republic of Korea . Korean J. Parasitol.60, 65.
    16. Kim, K.-H.,Oh, M.-D., 2014. Severe fever with thrombocytopenia syndrome . Korean J. Med.86, 271-276.
    17. Kim, K.-H.,Yi, J.,Kim, G.,Choi, S.J.,Jun, K.I.,Kim, N.-H.,Choe, P.G.,Kim, N.-J.,Lee, J.-K.,Oh, M.-D., 2013. Severe fever with thrombocytopenia syndrome, South Korea, 2012 . Emerg. Infect. Dis.19, 1892.
    18. Kim-Jeon, M.-D.,Jegal, S.,Jun, H.,Jung, H.,Park, S.H.,Ahn, S.K.,Lee, J.,Gong, Y.W.,Joo, K.,Kwon, M.J., 2019. Four year surveillance of the vector hard ticks for SFTS, Ganghwa-do, Republic of Korea . Korean J. Parasitol.57, 691-698.
    19. Korea Disease Control and Prevention Agency, 2025. Infectious disease portal. https://dportal.kdca.go.kr/pot/index.do (accessed on 17 Decmber, 2025).
    20. Kumar, S.,Stecher, G.,Li, M.,Knyaz, C.,Tamura, K., 2018. MEGA X: molecular evolutionary genetics analysis across computing platforms . Mol. Biol. Evol.35, 1547-1549.
    21. Lee, J.,Moon, K.,Kim, M.,Lee, W.-G.,Lee, H.-I.,Park, J.K.,Kim, Y. H., 2021. Seasonal distribution of Haemaphysalis longicornis (Acari: Ixodidae) and detection of SFTS virus in Gyeongbuk Province, Republic of Korea, 2018 . Acta. Trop.221, 106012.
    22. Lee, J.,Park, K.,Kim, J.,Lee, S.-H.,Lee, G.-Y.,Cho, S.,Kim, H.-C.,Klein, T.A.,Kim, J.-A.,Choi, J., 2022. Whole-genome sequencing and genetic diversity of severe fever with thrombocytopenia syndrome virus using multiplex PCR-based nanopore sequencing, Republic of Korea . PLoS Negl. Trop. Dis.16, e0010763.
    23. Li, A.,Liu, L.,Wu, W.,Liu, Y.,Huang, X.,Li, C.,Liu, D.,Li, J.,Wang, S.,Li, D., 2021. Molecular evolution and genetic diversity analysis of SFTS virus based on next-generation sequencing . Biosaf. Health.3, 105-115.
    24. Lu, H.,Ren, Q.,Li, Y.,Liu, J.,Niu, Q.,Yin, H.,Meng, Q.,Guan, G.,Luo, J., 2015. The efficacies of 5 insecticides against hard ticks Hyalomma asiaticum, Haemaphysalis longicornis and Rhipicephalus sanguineus . Exp. Parasitol.157, 44-47.
    25. Moon, M.-Y.,Kim, H.K.,Chung, S.-J.,Byun, J.H.,Kim, H.-N.,Lee, W.,Lee, S.-W.,Monoldorova, S.,Lee, S.,Jeon, B.-Y., 2023. Genetic diversity, regional distribution, and clinical characteristics of severe fever with thrombocytopenia syndrome virus in Gangwon Province, Korea, a highly prevalent region, 2019–2021 . Microorganisms11, 2288.
    26. Nava, S.,Venzal, J. M.,González-Acuña, D.,Martins, T.F.,Guglielmone, A.A., 2017. Ticks of the Southern Cone of America: diagnosis, distribution, and hosts with taxonomy, ecology and sanitary importance. Academic Press, London.
    27. Oh, S.-S.,Chae, J.-B.,Kang, J.-G.,Kim, H.-C.,Chong, S.-T.,Shin, J.-H.,Hur, M.-S.,Suh, J.-H.,Oh, M.-D.,Jeong, S.-M., 2016. Detection of severe fever with thrombocytopenia syndrome virus from wild animals and Ixodidae ticks in the Republic of Korea . Vector Borne Zoonotic Dis.16, 408-414.
    28. Park, S.-W.,Song, B. G.,Shin, E.-H.,Yun, S.-M.,Han, M.-G.,Park, M.Y.,Park, C.,Ryou, J., 2014. Prevalence of severe fever with thrombocytopenia syndrome virus in Haemaphysalis longicornis ticks in South Korea . Ticks Tick Borne Dis.5, 975-977.
    29. Portillo, A.,Santibáñez, S.,García-Álvarez, L.,Palomar, A.M.,Oteo, J.A., 2015. Rickettsioses in europe . Microbes Infect.17, 834-838.
    30. Robles, N.J.C.,Han, H.J.,Park, S.J.,Choi, Y.K., 2018. Epidemiology of severe fever and thrombocytopenia syndrome virus infection and the need for therapeutics for the prevention . Clin. Exp. Vaccine Res.7, 43-50.
    31. Suh, J.-H.,Kim, H.-C.,Yun, S.-M.,Lim, J.-W.,Kim, J.-H.,Chong, S.-T.,Kim, D.-H.,Kim, H.-T.,Kim, H.,Klein, T.A., 2016. Detection of SFTS virus in Ixodes nipponensis and Amblyomma testudinarium (Ixodida: Ixodidae) collected from reptiles in the Republic of Korea . J. Med. Entomol.53, 584-590.
    32. Takahashi, T.,Maeda, K.,Suzuki, T.,Ishido, A.,Shigeoka, T.,Tominaga, T.,Kamei, T.,Honda, M.,Ninomiya, D.,Sakai, T., 2014. The first identification and retrospective study of severe fever with thrombocytopenia syndrome in Japan . J. Infect. Dis.209, 816-827.
    33. Wikander, Y.M.,Reif, K.E., 2023. Cytauxzoon felis: an overview . Pathogens12, 133.
    34. Yamaguti, N.,Tipton, V.J.,Keegan, H.L.,Toshioka, S., 1971. Ticks of Japan, Korea, and the Ryukyu islands . Brigham Young Univ. Sci. Bull. Biol. Ser.15, 1.
    35. Yun, S.-M.,Lee, W.-G.,Ryou, J.,Yang, S.-C.,Park, S.-W.,Roh, J.Y.,Lee, Y.-J.,Park, C.,Han, M.G., 2014. Severe fever with thrombocytopenia syndrome virus in ticks collected from humans, South Korea, 2013 . Emerg. Infect. Dis.20, 1358.
    36. Yun, S.-M.,Park, S.-J.,Kim, Y.-I.,Park, S.-W.,Yu, M.-A.,Kwon, H.-I.,Kim, E.-H.,Yu, K.-M.,Jeong, H.W.,Ryou, J., 2020. Genetic and pathogenic diversity of severe fever with thrombocytopenia syndrome virus (SFTSV) in South Korea . JCI Insight5, e129531.
    37. Zhan, J.,Wang, Q.,Cheng, J.,Hu, B.,Li, J.,Zhan, F.,Song, Y.,Guo, D., 2017. Current status of severe fever with thrombocytopenia syndrome in China . Virol. Sin.32, 51-62.
    38. Zheng, H.,Yu, Z.,Chen, Z.,Zhou, L.,Zheng, B.,Ma, H.,Liu, J., 2011. Development and biological characteristics of Haemaphysalis longicornis (Acari: Ixodidae) under field conditions . Exp. Appl. Acarol.53, 377-388.

    Vol. 40 No. 4 (2022.12)

    Journal Abbreviation Korean J. Appl. Entomol.
    Frequency Quarterly
    Doi Prefix 10.5656/KSAE
    Year of Launching 1962
    Publisher Korean Society of Applied Entomology
    Indexed/Tracked/Covered By