{"paper_id":"443bf640-9269-47dc-a2c9-e9f4746139d1","body_text":"Long-term ecological surveillance of hard ticks (Acari: Ixodidae) and SFTSV in Dangjin, central Korea (2018-2024) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Long-term ecological surveillance of hard ticks (Acari: Ixodidae) and SFTSV in Dangjin, central Korea (2018-2024) Hyeon Jun Shin, Jun Yang Jeong, Chan Eui Hong, Hyeok Lee, Kyoung Won Lee, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8379339/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Mar, 2026 Read the published version in Parasites & Vectors → Version 1 posted 7 You are reading this latest preprint version Abstract Background: Hard ticks (Ixodidae) are the primary vectors of severe fever with thrombocytopenia syndrome virus (SFTSV), a tick-borne pathogen of increasing public health concern in East Asia. Understanding local vector ecology requires long-term monitoring, particularly in regions where human cases occur but viral prevalence in ticks remains unclear. This study conducted a multi-year ecological and molecular surveillance of hard ticks and SFTSV in Dangjin-si, Chungcheongnam-do, a representative region of central Korea. Methods: From 2018 to 2024, ticks were collected monthly from April to November across four habitat types (grasslands, mountain road, mixed forest, and cemetery) using standardized 24-hour CO 2 -baited traps. Specimens were morphologically identified and pooled by species, developmental stage, sex, and habitat. A total of 36,478 ticks were grouped into 3,106 pools. Total RNA was extracted and screened for SFTSV using nested RT-PCR, and amplification results were confirmed by agarose gel electrophoresis. Results: A total of 72,956 ticks belonging to Haemaphysalis longicornis , H. flava , and Ixodes nipponensis were collected. Haemaphysalis longicornis dominated the collection, representing 63.42% of all adult and nymphal ticks. Tick abundance peaked during 2018–2019 and was highest in grassland habitats. None of the 3,106 pools tested positive for SFTSV. Conclusions Although SFTSV was not detected, the persistently high abundance and broad ecological distribution of Haemaphysalis species suggest that Dangjin-si maintains environmental conditions that could support pathogen introduction or amplification. These long-term data provide a valuable baseline for early-warning systems and highlight the need for targeted surveillance in nearby high-incidence regions. Integrating ecological, climatic, and epidemiological data including multi-pathogen screening will be essential for strengthening One Health-based risk assessment frameworks in low-prevalence areas. Tick surveillance Ixodidae SFTS virus Vector-borne diseases Seasonal dynamics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Background Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral disease caused by Dabie bandavirus (family Phenuiviridae, genus Bandavirus ) [ 1 ]. In the Republic of Korea, the primary vectors belong to the family Ixodidae, particularly Haemaphysalis longicornis and H. flava , which are widely distributed and frequently collected across diverse habitat types [ 2 , 3 ]. Although tick bites and tick-borne diseases had been recognized for decades, the association between Haemaphysalis ticks and severe viral infection was not established until the first confirmed human SFTS case in 2012, with nationwide reporting beginning in 2013. Since then, SFTS has remained a significant public-health concern due to its severe clinical manifestations, including high fever, thrombocytopenia, leukopenia, and multi-organ dysfunction [ 4 , 5 ]. Climate variability is a major ecological driver influencing both the distribution and seasonal activity of hard ticks. Recent predictive models suggest that the geographic expansion and phenology of Haemaphysalis species may shift under various climate scenarios [ 6 , 7 , 8 , 9 , 10 , 11 ]. In particular, H. longicornis , the dominant species in Korea, reaches high densities in grasslands, mountain road, mixed forests, and cemetery landscapes microhabitats that commonly overlap with human activity [ 11 , 12 , 13 ]. However, the direct pathway through which environmental change translates into increased human infection risk remains uncertain because tick-host-environment interactions depend on multiple factors, including wildlife host density, land-use patterns, vegetation structure, and human behavioral exposure. Despite advances in SFTS epidemiology, long-term ecological observations in Korea remain limited. Many previous tick surveys have been short-term, geographically restricted, or focused primarily on quantifying abundance rather than examining habitat-specific or interannual variation. Moreover, national surveillance has placed a strong emphasis on viral detection, whereas the ecological context, especially in regions with low human incidence has been comparatively underexplored. This gap hampers the development of accurate risk assessments and early warning frameworks, particularly in areas where pathogen circulation may be sporadic or microfocal. Dangjin-si, a coastal agricultural area in central Korea, provides ecologically suitable environments for Haemaphysalis ticks, including extensive grasslands, mixed farmlands, cemetery complexes, and forest margins. Although annual human SFTS incidence in this region is relatively low, the presence of suitable habitats and frequent wildlife–tick–human interface suggests that the area remains relevant for baseline ecological surveillance. Long-term non-detection of SFTSV in such ecologically favorable landscapes can still yield epidemiologically meaningful information by defining upper bounds of local transmission potential and establishing baseline thresholds applicable to low-prevalence settings. Given these knowledge gaps, there is increasing recognition of the need for multidisciplinary and One Health–aligned surveillance frameworks integrating vector ecology, environmental variables, and human incidence patterns [ 14 , 15 , 16 ]. In this context, the present study conducted a seven-year ecological monitoring program in Dangjin-si (2018–2024) to (1) characterize long-term trends in tick abundance, species composition, and habitat-specific distribution; (2) examine seasonal activity patterns of dominant vector species; and (3) assess evidence for or against SFTSV circulation using extensive pooled molecular screening. By integrating vector dynamics with regional human incidence data, this study provides foundational ecological information essential for evaluating local transmission potential and strengthening future One Health-based public health strategies. 2. Methods 2.1 Collection period, location, and environmental characterization From 2018 to 2024, monthly surveillance was conducted from April to November across four representative habitat types grassland, mountain trail, mixed forest, and cemetery in Dangjin-si, Chungcheongnam-do, Republic of Korea. Tick surveillance followed standardized national monitoring procedures previously adopted in Korea [ 2 , 12 , 13 ]. The environmental characteristics of each site were documented, and GPS coordinates were recorded at the centroid of each habitat to ensure spatial reproducibility (grassland: 36°50′40.29″N, 126°40′11.64″E; mountain trail: 36°50′02.20″N, 126°40′29.68″E; mixed forest: 36°50′37.72″N, 126°40′23.51″E; cemetery: 36°50′36.37″N, 126°40′09.55″E). The grassland, mixed forest, and cemetery sites were located adjacent to each other, whereas the mountain trail site was relatively distant. All four habitats exhibited evidence of human residence or activity in the surrounding areas. The close spatial overlap between human land use and tick habitats within a limited area was a major criterion for selecting this region. The study area also supports diverse terrain features and hosts a variety of potential mammalian reservoir species, including rodents (Muridae), deer (Cervidae), and canids (Canidae), which exhibit high mobility and habitat overlap. These characteristics make the site suitable for evaluating host–vector interactions and the local ecology of hard tick distribution [ 17 , 18 , 19 ]. The grassland habitat consisted of a flat area dominated by perennial herbaceous vegetation (approximately 30–100 ㎝ in height), interspersed with occasional shrubs. The presence of water deer ( Hydropotes inermis ) was confirmed during field observations, indicating active vertebrate hosts. The mountain trail consisted of a narrow, shaded path with a mixture of shrubs and herbaceous plants, showing clear signs of frequent human passage. The mixed forest contained decayed logs, leaf litter, and dense understory vegetation, forming a humid microhabitat suitable for a wide range of arthropods and small vertebrates. The cemetery consisted of open grassy areas with scattered gravestones and sparse tall vegetation. Trap locations for each habitat are presented in Fig. 1 and were placed to avoid steep slopes and waterlogged areas. Within each habitat, three traps were positioned within a radius of approximately 40–50 m, maintaining a minimum inter-trap distance of 10 m. Whenever possible, identical trap locations were revisited across years. Prior to trap placement, surrounding vegetation was cleared to ensure that the trap body was in direct contact with the ground. Dry ice-baited traps consisted of insulated plastic beverage dispensers designed for tick capture (white body with red lid and waterproof housing). Each dispenser was filled with 3 ㎏ of dry ice to provide a continuous source of sublimating CO 2 , which served as an attractant. The spout remained open to regulate CO 2 emission, and all traps were deployed for 24 hours. CO 2 -baited dry ice traps are recognized as an effective method for attracting hard ticks [ 20 , 21 ]. After retrieval, each trap was sealed in a plastic bag and transported to the laboratory. Ticks and potential tick specimens attached to the interior and exterior of the trap were collected using an aspirator and fine forceps and placed into individual tubes. For each habitat, collected material was placed on a Petri dish over ice to minimize movement, and examined under a stereomicroscope (Olympus SZ61, Japan). Non-tick arthropods, soil debris, plant fragments, and other particulates were removed, and only ixodid ticks were retained for further analysis. Figure 2. Workflow for hard tick surveillance, species identification, and molecular detection of SFTSV. 2.2 Species identification and developmental stage classification. Species identification and developmental stage classification were conducted using stereomicroscopes provided by the Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources. All isolated ticks were identified to genus and species using standard taxonomic keys [ 22 , 23 ], based on morphological characteristics of the scutum, gnathosoma, and genital structures. Identified specimens were further categorized by developmental stage (adult, nymph, larva) and sex. Larvae of Haemaphysalis longicornis and H. flava exhibit highly similar morphological features, which cannot be reliably differentiated under standard stereomicroscopic observation. Therefore, larvae with indistinguishable gnathosomal traits were grouped as Haemaphysalis cf. spp. to minimize errors in species-level distribution estimates for larval stages [ 24 ]. Here, “cf.” (from the Latin confer, meaning “compare with”) indicates specimens that closely resemble a given species but cannot be identified with certainty. All specimens were cataloged by habitat, developmental stage, and sex. Half of the specimens from each group were used for RNA extraction and nested RT-PCR for pathogen detection, while the remaining half were preserved in 99% ethanol for verification of species occurrence and reproducibility checks. A complete overview of the workflow from field collection to pathogen analysis is shown in Fig. 2. 2.3 RNA Extraction RNA extraction was performed for pooled tick samples that were prepared after each monthly field collection. All ticks collected in a given month were first separated by habitat. Within each habitat group, individuals were classified by species and developmental stage, and adult ticks were further separated by sex. Pools were assembled only after this stratification so that each pool represented a single habitat and a single biological category. This process was repeated independently for every monthly sampling event throughout the seven-year study and resulted in a total of 3,106 pools derived from 36,478 ticks. Monthly stratified pooling prevented unnecessary dilution of viral RNA and avoided mixing across ecologically different categories. Pooling thresholds followed the limits recommended by the manufacturer for efficient homogenization and stable RNA extraction performance. Up to fifty larvae, thirty nymphs, or five adults were placed into each extraction tube [ 25 ]. These limits reflected the maximum tissue load that could be fully lysed during homogenization and helped maintain consistent extraction efficiency while supporting adequate detection sensitivity. Tick homogenization was carried out using the Clear-s Total RNA Extraction Kit (Invirustech, Republic of Korea; Cat. No. IVT3001KS). β-mercaptoethanol was added to the lysis buffer according to the kit protocol. Ticks were homogenized with a Precellys 24 instrument equipped with 2.8 mm zirconium beads. The homogenizer was set to 4.5 m/s for thirty seconds followed by a thirty second pause, and this cycle was performed twice [ 26 ]. All subsequent steps were performed according to the manufacturer’s instructions to obtain total RNA. Extracted RNA was kept on ice during processing, and remaining RNA or homogenate not immediately used was stored at − 80℃. All remaining steps followed the manufacturer’s instructions. RNA was eluted in a final volume of fifty microliters to maintain comparable concentrations across pools. Extracted RNA was kept on ice during preparation and stored at -80℃ when not immediately used. Work surfaces, pipettes, and tools were cleaned with diluted bleach and then with 70% ethanol before and after each extraction to prevent cross contamination. All reagents and equipment were selected to ensure reproducibility of the molecular workflow, and equivalent products from other suppliers can be used without affecting the procedure. The consistent performance of positive and negative controls during nested RT-PCR confirmed that RNA preparation was stable across sampling periods and that technical errors during extraction were unlikely. All procedures were conducted using equipment supported by the Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources. 2.4 PCR for SFTSV Detection SFTSV detection was performed using the Clear-MD® SFTSV Real-time Nested RT-PCR Detection Kit (Invirustech, Republic of Korea, Cat. No. IVT-M1002). All work surfaces, pipettes, and consumables were disinfected with 10% diluted bleach followed by 70% ethanol before and after each step to prevent contamination. Reaction mixtures were prepared following the manufacturer’s recommended formulation, and all reagents used in both the primary and secondary PCR reactions were exclusively those supplied in the Clear-MD® kit. Each reaction had a total volume of 20㎕ and included the appropriate enzyme mix, SFTSV detection reagents, 10㎕ of RNA template, and nuclease-free water as specified in the kit protocol [ 27 , 28 ]. The assay consisted of two amplification rounds. Primary RT-PCR was performed using a Bio-Rad C1000 Touch™ Thermal Cycler (Bio-Rad, Hercules, USA) under the following cycling conditions: reverse transcription at 50°C for 15 minutes, enzyme activation at 95°C for 3 minutes, and 40 amplification cycles of 95°C for 20 seconds, 60°C for 20 seconds, and 72°C for 40 seconds. The secondary nested PCR began with enzyme activation at 95°C for 3 minutes followed by 27 cycles of 95°C for 15 seconds, 58°C for 20 seconds, and 72°C for 30 seconds. For each run, a positive control (template provided with the kit) and a negative control (nuclease-free water) were included. PCR products were analyzed by electrophoresis on a 1.5% agarose gel using a Bioneer AGARO power™ system with 1x TAE buffer. A mixture of 6㎕ PCR product and 1㎕ loading dye (Dyne LoadingSTAR+, DyneBio, Republic of Korea) was loaded alongside a 100 bp DNA ladder. Electrophoresis was performed at 125 V (approximately 7 V/cm) for 50 minutes. A valid run was defined by the appearance of the expected 219 bp band in the positive control and the absence of amplification in the negative control. If a 219 bp band appeared in the negative control or any field sample, the result was interpreted as cross-contamination and the corresponding pool was retested. Field samples were considered positive when a 530 bp band was observed. The analytical sensitivity of the nested RT-PCR assay was evaluated using limit-of-detection (LoD) information provided by the manufacturer. According to these validation data, the assay achieves an LoD 95 % of 1.643 viral copies per microliter and samples containing at least 2 viral copies per microliter are described in the manual as being detected with approximately 99% probability. This information indicates that the analytical sensitivity of the assay is sufficient to detect very low concentrations of viral RNA when present in a sample. Serial dilution experiments combined with digital PCR quantification further support the reported sensitivity. At the 10 − 4 dilution, digital PCR measured 178.55 copies per microliter which corresponds to approximately 535.65 copies in three microliters of template volume. This concentration consistently produced detectable amplification in nested PCR. At the 10 − 5 to 10 − 6 dilutions, detection remained reproducible, whereas at lower concentrations corresponding to approximately 0.5 copies partial detection was observed. These data collectively indicate that the assay maintains reliable detection performance across a wide dynamic range of target concentrations. 3. Results 3.1 Annual and habitat-specific tick collection numbers and proportions From 2018 to 2024, a total of 72,956 hard ticks were collected across the four surveyed habitat types; grassland, mountain trail, mixed forest, and cemetery in Dangjin-si, Chungcheongnam-do. Annual collection numbers were highest in 2018 (n = 16,996) and 2019 (n = 21,668) and showed a gradual decline thereafter: 9,086 in 2020, 8,769 in 2021, 5,168 in 2022, 5,953 in 2023, and 5,316 in 2024. Habitat-specific patterns indicated that the grassland site yielded the highest number of ticks, accounting for 42,186 individuals (56.40%), followed by the mountain trail (13,555 individuals; 18.12%), mixed forest (13,092 individuals; 17.50%), and cemetery (5,965 individuals; 7.97%) (Fig. 3 ). A notable surge in tick abundance was observed in the grassland habitat in 2019, after which a marked decline occurred across most habitats (Figs. 3 and 4 ). 3.2 Monthly occurrence by species (April-November) Monthly and species-specific analyses of ticks collected between 2018 and 2024 revealed distinct seasonal and interannual dynamics (Figs. 5 – 7 ). Haemaphysalis longicornis was the most frequently collected species, with peak activity occurring consistently between April and July in most years. Substantial increases in abundance were observed in 2019 and 2021. Haemaphysalis flava occurred less frequently than H. longicornis and appeared sporadically from April to October, with relatively higher numbers in September and October. Ixodes nipponensis was rare throughout the study period, with annual totals typically below 10 individuals, except for a brief increase recorded in July 2020. Haemaphysalis cf. spp. representing larvae that could not be reliably differentiated morphologically between H. longicornis and H. flava , showed a different seasonal pattern. This larval group peaked strongly in September 2018 (n = 3,660) and September 2019 (n = 3,150) and overall displayed its highest abundance in August and September, which differed from the adult activity periods (Figs. 6 and 7 ). Of all ticks collected (n = 72,956), H. longicornis (adult and nymph) accounted for 46,269 individuals (63.42%), followed by Haemaphysalis cf. spp. (larvae) with 24,889 individuals (34.12%), H. flava with 1,143 individuals (1.57%), and I. nipponensis with 655 individuals (0.90%). 3.3 SFTS pathogen detection results Of the total ticks collected, 36,478 individuals were pooled into 3,106 pools for SFTSV detection using nested RT-PCR targeting SFTS virus RNA. The assay followed the manufacturer’s protocol, including a primary RT-PCR followed by a secondary nested PCR, with final products visualized through 1.5% agarose gel electrophoresis. The positive control consistently produced a distinct 219 bp band, whereas no amplification was observed in the negative control, confirming the absence of contamination. Among the 3,106 pools tested, none yielded the expected 530 bp SFTSV-positive band, indicating that all samples were negative for SFTSV RNA. 4. Discussion 4.1 Ecological interpretation of long-term tick surveillance data This study provides a 7-year ecological dataset characterizing the distribution, seasonal activity, and habitat-specific occurrence of hard ticks in Dangjin-si, Chungcheongnam-do. Three species were identified, and Haemaphysalis longicornis represented the majority of adult and nymphal specimens. This dominance is consistent with nationwide surveillance findings reporting Haemaphysalis species as the prevailing ticks in rural and peri-urban landscapes across the Republic of Korea [ 12 , 13 ]. The persistently high proportion of H. longicornis across all four habitat types suggests broad ecological tolerance and the ability to utilize diverse vertebrate hosts, including rodents, deer, carnivores, livestock, and humans. Seasonal variation of activity patterns observed in this study further reflect well-established biological rhythms of hard ticks in East Asia. Adult and nymphal H. longicornis exhibited peak activity between April and July, whereas H. flava showed distinct activity peaks in September and October. Larval Haemaphysalis cf. spp. peaked primarily during August and September, indicating life-cycle timing that differs from that of adults and nymphs. These seasonal windows overlap with periods of increased agricultural, forestry, and outdoor human activity, increasing opportunities for human-tick encounters [ 3 ]. The temporal heatmap (Fig. 7 ) highlights that agricultural fields, forest edges, and peri-urban interfaces may sustain extended periods of exposure risk throughout the warm season because the activity windows of multiple life stages overlap. This pattern is consistent with reports from other regions in East Asia, where overlapping life stages extend the seasonal window of potential pathogen transmission [ 29 , 30 ]. Interannual variation also revealed meaningful ecological signals. Total tick abundance peaked during 2018–2019 and gradually declined thereafter (Figs. 3 and 4 ). These fluctuations likely reflect changes in climatic conditions, vegetation structure, land-cover transitions, and wildlife host availability across years. Because such interannual dynamics cannot be captured through short-term sampling, the observed trends underscore the importance of long-term datasets for resolving natural population cycles and accurately interpreting local vector ecology. The habitat distribution shown in Figs. 3 and 4 further illustrates that landscapes characterized by forest margins, agricultural fields, and residential zones function as interface environments where ticks, wildlife hosts, domestic animals, and humans interact frequently. Dangjin-si contains a mosaic of such environments, which may support persistent tick populations even under fluctuating environmental conditions. These observations reinforce the relevance of a One Health framework that integrates environmental, veterinary, and human health components when assessing future tick-borne disease risks. 4.2 Interpretation of negative SFTSV detection and factors influencing viral detectability Although 36,478 ticks grouped into 3,106 pools were tested using nested RT-PCR, SFTSV was not detected in any sample. This finding is consistent with several surveillance studies conducted in the Republic of Korea, which reported extremely low or undetectable SFTSV prevalence in questing ticks even in areas with high vector abundance [ 31 , 32 , 33 ]. Given the large number of pools analyzed and the inherent dilution effect associated with pooled testing, these results are most reasonably interpreted as reflecting either very low-level viral circulation or activity below the operational detection threshold of pooled surveillance during the study period in Dangjin-si. The analytical sensitivity of the assay further supports this interpretation. According to the manufacturer, the nested RT-PCR system has a detection limit of LoD95% = 1.643 viral copies per microliter and achieves approximately 99% detection probability at concentrations of two or more copies per microliter. Given this level of sensitivity, the absence of positive detections suggests that any SFTSV present in questing ticks was likely distributed at concentrations below detectable levels when diluted across pooled samples. Thus, the negative results should be interpreted as reflecting methodological and ecological constraints rather than evidence of true viral absence. Broader comparative patterns across East Asia reinforce this view. While China and Japan frequently report SFTSV-positive ticks across diverse ecological settings, Taiwan consistently reports no viral detection in ticks despite ongoing human SFTS surveillance [ 34 , 35 , 36 ]. These contrasting regional patterns indicate that SFTSV circulation is shaped by fine-scale ecological conditions and host-associated transmission networks rather than by vector density alone. The micro-focal and intermittent nature of SFTSV transmission increases the likelihood that environmental sampling may miss viral hotspots that are spatially restricted or temporally transient. Importantly, negative molecular detection does not equate to confirmed viral absence. Non-detection may occur when infection prevalence is extremely low, when viral circulation is confined to micro-focal hotspots outside designated sampling sites, or when RNA degradation occurs prior to laboratory processing. Pooling further reduces the probability of detecting rare infected individuals by diluting viral RNA below detectable concentrations [ 37 , 38 ]. Such limitations are well recognized in tick-borne pathogen surveillance, where transmission is often shaped by wildlife host movements and microclimatic variability operating at spatial scales smaller than those captured by standard environmental sampling frameworks [ 24 , 39 , 40 ]. Data were obtained from the Chungcheongnam-do Infectious Disease Control and Management Center (CNCIDC). Each administrative region is labeled with the City or County name, total number of reported cases, and incidence rate per 100,000 population. Quarterly distributions are shown as Q1 (January to March), Q2 (April to June), Q3 (July to September), and Q4 (October to December). The divergence between environmental tick surveillance and human case occurrence in Dangjin-si illustrates these constraints. Although no SFTSV was detected in ticks collected from this area, approximately twelve human SFTS cases were reported during the study period. A similar discrepancy has been reported in Oita Prefecture, Japan, where one region showed no evidence of SFTSV or antiviral antibodies in ticks, wildlife, livestock, or humans, despite clear viral activity in surrounding areas [ 41 ]. These observations provide further evidence that tick-based environmental surveillance alone may underestimate transmission risk when viral circulation is highly localized or maintained within specific host–vector networks. Consistent with this interpretation, human SFTS incidence in Chungcheongnam-do displays pronounced spatial heterogeneity (Fig. 8 ). Regional comparisons based on incidence rates rather than absolute case counts reveal that Gongju-si, Cheonan-si, and Asan-si exhibit substantially higher incidence rates than Dangjin-si, suggesting uneven distribution of ecological or epidemiological conditions that support viral maintenance. Seasonal patterns further indicate concentration of cases in specific quarters of the year. Together, these findings suggest that aligning future tick collection efforts with both spatial patterns of human incidence and seasonal peaks may increase the likelihood of detecting virus-positive pools and improve the precision of One Health–oriented risk assessments [ 42 ]. Such an integrated approach may also contribute to a more accurate understanding of SFTSV transmission dynamics and support the development of more effective early warning and surveillance strategies. 4.3 Implications for public health and future surveillance directions The ecological patterns identified in this study carry important implications for public health planning and the refinement of national tick-borne disease surveillance strategies. Although no SFTSV was detected in questing ticks from Dangjin-si, the consistently high abundance of Haemaphysalis species across all habitat types indicates that ecological conditions for potential viral introduction or amplification remain present. Similar patterns have been observed in regions where vector densities are high but detectable viral circulation is absent or intermittent, suggesting that transmission risk is shaped not only by tick abundance but also by host community structure and fine-scale environmental variability [ 12 , 14 , 31 ]. Human SFTS cases in Chungcheongnam-do demonstrate strong spatial heterogeneity, with Gongju-si, Cheonan-si, and Asan-si exhibiting markedly higher incidence compared with Dangjin-si (Fig. 8 ). These spatial discrepancies imply that localized environmental or ecological characteristics may foster viral maintenance in some areas but not others [ 11 ]. Aligning surveillance efforts with human case clusters could therefore enhance the probability of detecting SFTSV-positive ticks and enable characterization of viral serotypes or genotypes. Such targeted sampling approaches have been recommended in other vector-borne disease systems to improve detection efficiency and refine One Health-informed risk assessment frameworks [ 43 , 44 , 45 ]. A broader interpretation of these findings underscores the value of integrating ecological, epidemiological, and environmental datasets. Several recent studies have effectively used citizen-science wildlife occurrence records from platforms such as iNaturalist and GBIF to infer potential distributions of reservoir hosts or vector-associated species in vector-borne disease research [ 17 , 19 ]. High-resolution climate data, including temperature, precipitation, humidity indices, and land surface temperature, have been incorporated into species distribution models to predict habitat suitability and seasonal activity patterns at fine spatial scales. Remote-sensing products such as land-use classifications, vegetation indices, and habitat fragmentation metrics can also be processed in GIS environments to identify ecological conditions that support vector persistence [ 46 , 47 , 48 ]. Although these approaches were not used in the present analysis, their potential relevance for SFTSV surveillance in Korea is substantial. Dangjin-si consists of a mosaic of agricultural fields, forest margins, and peri-urban residential areas where wildlife hosts such as rodents, deer, and carnivores move between habitat types and may facilitate micro-scale viral circulation [ 11 ]. Integrating ecological surveillance with citizen-science observations, climate-based risk mapping, and high-resolution environmental variables could therefore help identify environmental configurations associated with SFTSV maintenance. This may also help detect micro-focal viral hotspots in settings where standard tick sampling yields only negative results, as demonstrated in Oita Prefecture, Japan, where one region displayed complete negativity for SFTSV across ticks, domestic animals, wildlife, and humans despite active circulation in adjacent areas [ 41 ]. The mismatch observed in this study between high vector density and absence of viral detection emphasizes the importance of long-term, multi-source surveillance systems. Periodic integration of human case data, wildlife reservoir monitoring, environmental indicators, and vector-based sampling may help identify temporal windows or spatial clusters where viral circulation is more likely [ 2 , 31 , 49 , 50 ]. As climate continues to change and land-use patterns shift, coordinated surveillance across multiple administrative regions will be necessary to detect ecological transitions that precede pathogen emergence. In this context, the dataset generated here contributes a foundational ecological baseline for Dangjin-si while highlighting practical frameworks that could strengthen One Health-oriented surveillance across the Republic of Korea [ 43 , 51 , 52 ]. 4.4 Limitations and future directions Several limitations should be considered when interpreting the findings of this 7-year surveillance study, and these limitations also highlight opportunities for strengthening future research and public-health preparedness. First, Amblyomma testudinarium , a recognized SFTSV vector in southern Korea, was not detected during the study period. However, recent reports from central regions including areas near Daejeon, suggest a possible northward expansion of this species that may be influenced by changing climatic and habitat conditions [ 49 ]. Sustained monitoring across broader latitudinal gradients will be necessary to determine whether this trend reflects a true shift in distribution or localized introductions that may eventually contribute to regional pathogen circulation. Second, surveillance prioritization may benefit from a strategic focus on areas with recurrent human SFTS cases. Regions such as Gongju-si and Cheonan-si consistently report higher case numbers than Dangjin-si, as shown in regional epidemiological data (Fig. 8 ). Concentrating additional sampling in these high-incidence areas could increase the likelihood of detecting SFTSV-positive pools and support downstream analyses such as genotype or serotype characterization. Such targeted approaches would complement the current findings from a low-incidence area and help clarify whether spatial differences in human infections arise from ecological heterogeneity, micro-focal viral persistence, or variation in wildlife host communities. Third, advances in molecular diagnostics provide promising opportunities to enhance sensitivity in future tick-based SFTSV surveillance. Methods such as quantitative RT-PCR, isothermal amplification assays, and metagenomic sequencing may enable detection of viral RNA at lower concentrations or from partially degraded samples. Multi-pathogen screening targeting agents such as Anaplasma , Rickettsia , and Borrelia would expand the ecological value of surveillance datasets and allow more comprehensive assessments of tick-associated pathogen risk. Fourth, integrating long-term ecological datasets with high-resolution environmental and climatic information could substantially improve risk prediction. Coupling tick abundance data with climate variables, land-use change indicators, vegetation indices, and wildlife occurrence records may help identify specific environmental configurations associated with vector persistence or viral maintenance. Species distribution models and landscape epidemiology frameworks have been widely used in vector-borne disease research and can be applied similarly to tick-borne disease systems in Korea to refine spatial risk assessments [ 53 ]. Fifth, because this study relies on a single sampling method, some microhabitat-specific or host-associated ticks may be under-represented. CO 2 -baited traps were intentionally used to minimize operator-dependent variation and maintain consistent trapping conditions across years. However, incorporating additional sampling methods such as drag or flag sampling, or wildlife-associated tick collection, would help capture a broader spectrum of tick species, life stages, and behaviors. This enhancement would be particularly valuable for detecting micro-focal viral circulation that may be linked to host movement patterns or fine-scale habitat structure. Finally, the dataset originates from one city and four habitat types. The findings should therefore be interpreted as region-specific rather than nationally representative. Ecological conditions, wildlife host communities, and viral serotypes may vary across Korea, and additional multi-regional datasets will be needed to determine whether the patterns observed in Dangjin-si generalize to other areas. As climate and land-use changes continue to reshape vector ecology, long-term datasets of this type will be essential for detecting ecological transitions, validating predictive models, and guiding adaptive surveillance strategies. In conclusion, the high abundance, distinct seasonality, and ecological adaptability of Haemaphysalis species suggest that Dangjin-si may continue to support ecological conditions conducive to tick population persistence. Strengthening regional surveillance networks and integrating human, animal, and environmental health data across administrative boundaries will enhance early warning capacity and support more effective responses to future tick-borne disease threats. The dataset presented here provides an important long-term ecological baseline that can facilitate future integration of environmental, climatic, and epidemiological datasets toward more predictive and adaptive One Health surveillance systems in Korea. 5. Conclusions This study provides a seven-year longitudinal assessment of hard tick ecology and One Health–based pathogen risk in Dangjin-si, a representative region of central Korea. Although none of the 3,106 pools tested positive for SFTSV, the persistent dominance of Haemaphysalis longicornis across years and habitats suggests that local environmental conditions remain suitable for the maintenance or potential introduction of tick-borne pathogens. The absence of viral detection should therefore not be interpreted as reduced risk, particularly given the proximity to high-incidence regions. The long-term dataset established here offers a valuable baseline for evaluating future changes in tick species composition, population dynamics, and pathogen circulation. Strengthening surveillance through the integration of ecological factors, climatic trends, and multi-pathogen screening will be essential for advancing regional One Health–based early-warning systems. Declarations Ethics approval and consent to participate This study did not involve human participants or vertebrate animals. Tick collection was conducted as part of routine public health surveillance activities and complied with national guidelines. Therefore, ethical approval and informed consent were not required. Consent for publication Not applicable. Availability of data and materials All data generated or analyzed in this study are included in this published article and its supplementary files. Additional datasets are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was financially supported by the Korea Disease Control and Prevention Agency (KDCA; No. 6332-302); the Korea Basic Science Institute through the National Research Facilities and Equipment Center (NFEC) program funded by the Ministry of Education (No. 2022R1A6C101B794); the National Research Foundation of Korea (NRF; No. 2021R1A6A1A03039503 and No. 2017R1D1A3B06034971); and the Soonchunhyang University Research Fund. Authors' contributions Yong Seok Lee, Wook-Gyo Lee, and Hyeon Jun Shin conceived the study idea and designed the overall research framework. Over the seven-year surveillance period, Hyeon Jun Shin, Jun Yang Jeong, Chan Eui Hong, Hyuk Lee, Kyung Won Lee, Min Gyu Sang 2,3 , Jie Eun Park, Dae Kwon Song, and Yong Seok Lee participated in long-term field tick collection and laboratory analyses. Among them, Jie Eun Park contributed technical guidance for the laboratory workflows, while Dae Kwon Song and Cho-I Moon contributed to data interpretation. Yong Seok Lee and Wook-Gyo Lee made the most substantial contributions to the development of the research methodology and the review of the manuscript structure. The study concept and initial draft were prepared by Hyeon Jun Shin. All authors reviewed and approved the final manuscript. Acknowledgements The authors thank the staff of the Korea Disease Control and Prevention Agency (KDCA), the Chungcheongnam-do Infectious Disease Control and Management Center (CNCIDC), the Dangjin-si Public Health Center, and the Asan-si Public Health Center for their assistance with long-term tick surveillance and field support. We also acknowledge invirustech and GnCbio for providing technical advice and laboratory support. References Liu B, Zhu J, He T, Zhang Z. Genetic variants of Dabie bandavirus: classification and biological/clinical implications. Virol J. 2023;20 1:68; doi: 10.1186/s12985-023-02033-y . https://www.ncbi.nlm.nih.gov/pubmed/37060090 . Kim JY, Jung M, Kho JW, Song H, Moon K, Kim YH, et al. Characterization of overwintering sites of Haemaphysalis longicornis (Acari: Ixodidae) and tick infection rate with severe fever with thrombocytopenia syndrome virus from eight provinces in South Korea. 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McDermott A. Climate change hastens disease spread across the globe. Proceedings of the National Academy of Sciences. 2022;119 7:e2200481119; doi: 10.1073/pnas.2200481119 . https://dx.doi.org/10.1073/pnas.2200481119. Additional Declarations No competing interests reported. Supplementary Files SupplementaryData1.xlsx Cite Share Download PDF Status: Published Journal Publication published 30 Mar, 2026 Read the published version in Parasites & Vectors → Version 1 posted Editorial decision: Revision requested 29 Dec, 2025 Reviews received at journal 27 Dec, 2025 Reviewers agreed at journal 24 Dec, 2025 Reviewers invited by journal 19 Dec, 2025 Editor assigned by journal 19 Dec, 2025 Submission checks completed at journal 19 Dec, 2025 First submitted to journal 16 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":131747,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMonthly distribution of hard ticks collected (2018-2024)\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8379339/v1/da5fd5270a6089cff2b87d4c.png\"},{\"id\":99190103,\"identity\":\"31a052b5-faa6-4a9a-97c9-09e6257e300e\",\"added_by\":\"auto\",\"created_at\":\"2025-12-30 00:49:22\",\"extension\":\"png\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":134591,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eHeatmap of monthly distribution of ticks collected (2018-2024)\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8379339/v1/9b3799be53f9daba00b6b246.png\"},{\"id\":99190112,\"identity\":\"4e5c303f-8e36-4745-b242-4a4769596fe0\",\"added_by\":\"auto\",\"created_at\":\"2025-12-30 00:49:22\",\"extension\":\"png\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":328581,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eSpatial, temporal, and demographic patterns of human SFTS cases in Chungcheongnam-do, Republic of Korea (2015-2024).\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image8.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8379339/v1/8f27f254c9527c4e150da088.png\"},{\"id\":106344976,\"identity\":\"356f1bba-b2b6-446c-bb00-89c9b0e45115\",\"added_by\":\"auto\",\"created_at\":\"2026-04-07 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central Korea (2018-2024)\",\"fulltext\":[{\"header\":\"1. Background\",\"content\":\"\\u003cp\\u003eSevere fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral disease caused by \\u003cem\\u003eDabie bandavirus\\u003c/em\\u003e (family Phenuiviridae, genus \\u003cem\\u003eBandavirus\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. In the Republic of Korea, the primary vectors belong to the family Ixodidae, particularly \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e and \\u003cem\\u003eH. flava\\u003c/em\\u003e, which are widely distributed and frequently collected across diverse habitat types [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Although tick bites and tick-borne diseases had been recognized for decades, the association between \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e ticks and severe viral infection was not established until the first confirmed human SFTS case in 2012, with nationwide reporting beginning in 2013. Since then, SFTS has remained a significant public-health concern due to its severe clinical manifestations, including high fever, thrombocytopenia, leukopenia, and multi-organ dysfunction [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eClimate variability is a major ecological driver influencing both the distribution and seasonal activity of hard ticks. Recent predictive models suggest that the geographic expansion and phenology of \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e species may shift under various climate scenarios [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. In particular, \\u003cem\\u003eH. longicornis\\u003c/em\\u003e, the dominant species in Korea, reaches high densities in grasslands, mountain road, mixed forests, and cemetery landscapes microhabitats that commonly overlap with human activity [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. However, the direct pathway through which environmental change translates into increased human infection risk remains uncertain because tick-host-environment interactions depend on multiple factors, including wildlife host density, land-use patterns, vegetation structure, and human behavioral exposure.\\u003c/p\\u003e \\u003cp\\u003eDespite advances in SFTS epidemiology, long-term ecological observations in Korea remain limited. Many previous tick surveys have been short-term, geographically restricted, or focused primarily on quantifying abundance rather than examining habitat-specific or interannual variation. Moreover, national surveillance has placed a strong emphasis on viral detection, whereas the ecological context, especially in regions with low human incidence has been comparatively underexplored. This gap hampers the development of accurate risk assessments and early warning frameworks, particularly in areas where pathogen circulation may be sporadic or microfocal.\\u003c/p\\u003e \\u003cp\\u003eDangjin-si, a coastal agricultural area in central Korea, provides ecologically suitable environments for \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e ticks, including extensive grasslands, mixed farmlands, cemetery complexes, and forest margins. Although annual human SFTS incidence in this region is relatively low, the presence of suitable habitats and frequent wildlife\\u0026ndash;tick\\u0026ndash;human interface suggests that the area remains relevant for baseline ecological surveillance. Long-term non-detection of SFTSV in such ecologically favorable landscapes can still yield epidemiologically meaningful information by defining upper bounds of local transmission potential and establishing baseline thresholds applicable to low-prevalence settings.\\u003c/p\\u003e \\u003cp\\u003eGiven these knowledge gaps, there is increasing recognition of the need for multidisciplinary and One Health\\u0026ndash;aligned surveillance frameworks integrating vector ecology, environmental variables, and human incidence patterns [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. In this context, the present study conducted a seven-year ecological monitoring program in Dangjin-si (2018\\u0026ndash;2024) to (1) characterize long-term trends in tick abundance, species composition, and habitat-specific distribution; (2) examine seasonal activity patterns of dominant vector species; and (3) assess evidence for or against SFTSV circulation using extensive pooled molecular screening. By integrating vector dynamics with regional human incidence data, this study provides foundational ecological information essential for evaluating local transmission potential and strengthening future One Health-based public health strategies.\\u003c/p\\u003e\"},{\"header\":\"2. Methods\",\"content\":\"\\u003cp\\u003e \\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Collection period, location, and environmental characterization\\u003c/h2\\u003e \\u003cp\\u003eFrom 2018 to 2024, monthly surveillance was conducted from April to November across four representative habitat types grassland, mountain trail, mixed forest, and cemetery in Dangjin-si, Chungcheongnam-do, Republic of Korea. Tick surveillance followed standardized national monitoring procedures previously adopted in Korea [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. The environmental characteristics of each site were documented, and GPS coordinates were recorded at the centroid of each habitat to ensure spatial reproducibility (grassland: 36\\u0026deg;50\\u0026prime;40.29\\u0026Prime;N, 126\\u0026deg;40\\u0026prime;11.64\\u0026Prime;E; mountain trail: 36\\u0026deg;50\\u0026prime;02.20\\u0026Prime;N, 126\\u0026deg;40\\u0026prime;29.68\\u0026Prime;E; mixed forest: 36\\u0026deg;50\\u0026prime;37.72\\u0026Prime;N, 126\\u0026deg;40\\u0026prime;23.51\\u0026Prime;E; cemetery: 36\\u0026deg;50\\u0026prime;36.37\\u0026Prime;N, 126\\u0026deg;40\\u0026prime;09.55\\u0026Prime;E). The grassland, mixed forest, and cemetery sites were located adjacent to each other, whereas the mountain trail site was relatively distant. All four habitats exhibited evidence of human residence or activity in the surrounding areas. The close spatial overlap between human land use and tick habitats within a limited area was a major criterion for selecting this region. The study area also supports diverse terrain features and hosts a variety of potential mammalian reservoir species, including rodents (Muridae), deer (Cervidae), and canids (Canidae), which exhibit high mobility and habitat overlap. These characteristics make the site suitable for evaluating host\\u0026ndash;vector interactions and the local ecology of hard tick distribution [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe grassland habitat consisted of a flat area dominated by perennial herbaceous vegetation (approximately 30\\u0026ndash;100 ㎝ in height), interspersed with occasional shrubs. The presence of water deer (\\u003cem\\u003eHydropotes inermis\\u003c/em\\u003e) was confirmed during field observations, indicating active vertebrate hosts. The mountain trail consisted of a narrow, shaded path with a mixture of shrubs and herbaceous plants, showing clear signs of frequent human passage. The mixed forest contained decayed logs, leaf litter, and dense understory vegetation, forming a humid microhabitat suitable for a wide range of arthropods and small vertebrates. The cemetery consisted of open grassy areas with scattered gravestones and sparse tall vegetation.\\u003c/p\\u003e \\u003cp\\u003eTrap locations for each habitat are presented in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and were placed to avoid steep slopes and waterlogged areas. Within each habitat, three traps were positioned within a radius of approximately 40\\u0026ndash;50 m, maintaining a minimum inter-trap distance of 10 m. Whenever possible, identical trap locations were revisited across years. Prior to trap placement, surrounding vegetation was cleared to ensure that the trap body was in direct contact with the ground.\\u003c/p\\u003e \\u003cp\\u003eDry ice-baited traps consisted of insulated plastic beverage dispensers designed for tick capture (white body with red lid and waterproof housing). Each dispenser was filled with 3 ㎏ of dry ice to provide a continuous source of sublimating CO\\u003csub\\u003e2\\u003c/sub\\u003e, which served as an attractant. The spout remained open to regulate CO\\u003csub\\u003e2\\u003c/sub\\u003e emission, and all traps were deployed for 24 hours. CO\\u003csub\\u003e2\\u003c/sub\\u003e-baited dry ice traps are recognized as an effective method for attracting hard ticks [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAfter retrieval, each trap was sealed in a plastic bag and transported to the laboratory. Ticks and potential tick specimens attached to the interior and exterior of the trap were collected using an aspirator and fine forceps and placed into individual tubes. For each habitat, collected material was placed on a Petri dish over ice to minimize movement, and examined under a stereomicroscope (Olympus SZ61, Japan). Non-tick arthropods, soil debris, plant fragments, and other particulates were removed, and only ixodid ticks were retained for further analysis.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 2. Workflow for hard tick surveillance, species identification, and molecular detection of SFTSV.\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Species identification and developmental stage classification.\\u003c/h2\\u003e \\u003cp\\u003eSpecies identification and developmental stage classification were conducted using stereomicroscopes provided by the Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources.\\u003c/p\\u003e \\u003cp\\u003eAll isolated ticks were identified to genus and species using standard taxonomic keys [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e], based on morphological characteristics of the scutum, gnathosoma, and genital structures. Identified specimens were further categorized by developmental stage (adult, nymph, larva) and sex.\\u003c/p\\u003e \\u003cp\\u003eLarvae of \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e and \\u003cem\\u003eH. flava\\u003c/em\\u003e exhibit highly similar morphological features, which cannot be reliably differentiated under standard stereomicroscopic observation. Therefore, larvae with indistinguishable gnathosomal traits were grouped as \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e cf. spp. to minimize errors in species-level distribution estimates for larval stages [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. Here, \\u0026ldquo;cf.\\u0026rdquo; (from the Latin confer, meaning \\u0026ldquo;compare with\\u0026rdquo;) indicates specimens that closely resemble a given species but cannot be identified with certainty.\\u003c/p\\u003e \\u003cp\\u003eAll specimens were cataloged by habitat, developmental stage, and sex. Half of the specimens from each group were used for RNA extraction and nested RT-PCR for pathogen detection, while the remaining half were preserved in 99% ethanol for verification of species occurrence and reproducibility checks. A complete overview of the workflow from field collection to pathogen analysis is shown in Fig.\\u0026nbsp;2.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 RNA Extraction\\u003c/h2\\u003e \\u003cp\\u003eRNA extraction was performed for pooled tick samples that were prepared after each monthly field collection. All ticks collected in a given month were first separated by habitat. Within each habitat group, individuals were classified by species and developmental stage, and adult ticks were further separated by sex. Pools were assembled only after this stratification so that each pool represented a single habitat and a single biological category. This process was repeated independently for every monthly sampling event throughout the seven-year study and resulted in a total of 3,106 pools derived from 36,478 ticks. Monthly stratified pooling prevented unnecessary dilution of viral RNA and avoided mixing across ecologically different categories.\\u003c/p\\u003e \\u003cp\\u003ePooling thresholds followed the limits recommended by the manufacturer for efficient homogenization and stable RNA extraction performance. Up to fifty larvae, thirty nymphs, or five adults were placed into each extraction tube [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. These limits reflected the maximum tissue load that could be fully lysed during homogenization and helped maintain consistent extraction efficiency while supporting adequate detection sensitivity. Tick homogenization was carried out using the Clear-s Total RNA Extraction Kit (Invirustech, Republic of Korea; Cat. No. IVT3001KS). β-mercaptoethanol was added to the lysis buffer according to the kit protocol. Ticks were homogenized with a Precellys 24 instrument equipped with 2.8 mm zirconium beads. The homogenizer was set to 4.5 m/s for thirty seconds followed by a thirty second pause, and this cycle was performed twice [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. All subsequent steps were performed according to the manufacturer\\u0026rsquo;s instructions to obtain total RNA. Extracted RNA was kept on ice during processing, and remaining RNA or homogenate not immediately used was stored at \\u0026minus;\\u0026thinsp;80℃.\\u003c/p\\u003e \\u003cp\\u003eAll remaining steps followed the manufacturer\\u0026rsquo;s instructions. RNA was eluted in a final volume of fifty microliters to maintain comparable concentrations across pools. Extracted RNA was kept on ice during preparation and stored at -80℃ when not immediately used.\\u003c/p\\u003e \\u003cp\\u003eWork surfaces, pipettes, and tools were cleaned with diluted bleach and then with 70% ethanol before and after each extraction to prevent cross contamination. All reagents and equipment were selected to ensure reproducibility of the molecular workflow, and equivalent products from other suppliers can be used without affecting the procedure. The consistent performance of positive and negative controls during nested RT-PCR confirmed that RNA preparation was stable across sampling periods and that technical errors during extraction were unlikely. All procedures were conducted using equipment supported by the Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 PCR for SFTSV Detection\\u003c/h2\\u003e \\u003cp\\u003eSFTSV detection was performed using the Clear-MD\\u0026reg; SFTSV Real-time Nested RT-PCR Detection Kit (Invirustech, Republic of Korea, Cat. No. IVT-M1002). All work surfaces, pipettes, and consumables were disinfected with 10% diluted bleach followed by 70% ethanol before and after each step to prevent contamination. Reaction mixtures were prepared following the manufacturer\\u0026rsquo;s recommended formulation, and all reagents used in both the primary and secondary PCR reactions were exclusively those supplied in the Clear-MD\\u0026reg; kit. Each reaction had a total volume of 20㎕ and included the appropriate enzyme mix, SFTSV detection reagents, 10㎕ of RNA template, and nuclease-free water as specified in the kit protocol [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe assay consisted of two amplification rounds. Primary RT-PCR was performed using a Bio-Rad C1000 Touch\\u0026trade; Thermal Cycler (Bio-Rad, Hercules, USA) under the following cycling conditions: reverse transcription at 50\\u0026deg;C for 15 minutes, enzyme activation at 95\\u0026deg;C for 3 minutes, and 40 amplification cycles of 95\\u0026deg;C for 20 seconds, 60\\u0026deg;C for 20 seconds, and 72\\u0026deg;C for 40 seconds. The secondary nested PCR began with enzyme activation at 95\\u0026deg;C for 3 minutes followed by 27 cycles of 95\\u0026deg;C for 15 seconds, 58\\u0026deg;C for 20 seconds, and 72\\u0026deg;C for 30 seconds. For each run, a positive control (template provided with the kit) and a negative control (nuclease-free water) were included.\\u003c/p\\u003e \\u003cp\\u003ePCR products were analyzed by electrophoresis on a 1.5% agarose gel using a Bioneer AGARO power\\u0026trade; system with 1x TAE buffer. A mixture of 6㎕ PCR product and 1㎕ loading dye (Dyne LoadingSTAR+, DyneBio, Republic of Korea) was loaded alongside a 100 bp DNA ladder. Electrophoresis was performed at 125 V (approximately 7 V/cm) for 50 minutes. A valid run was defined by the appearance of the expected 219 bp band in the positive control and the absence of amplification in the negative control. If a 219 bp band appeared in the negative control or any field sample, the result was interpreted as cross-contamination and the corresponding pool was retested. Field samples were considered positive when a 530 bp band was observed.\\u003c/p\\u003e \\u003cp\\u003eThe analytical sensitivity of the nested RT-PCR assay was evaluated using limit-of-detection (LoD) information provided by the manufacturer. According to these validation data, the assay achieves an LoD\\u003csub\\u003e95\\u003c/sub\\u003e% of 1.643 viral copies per microliter and samples containing at least 2 viral copies per microliter are described in the manual as being detected with approximately 99% probability. This information indicates that the analytical sensitivity of the assay is sufficient to detect very low concentrations of viral RNA when present in a sample.\\u003c/p\\u003e \\u003cp\\u003eSerial dilution experiments combined with digital PCR quantification further support the reported sensitivity. At the 10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;4\\u003c/sup\\u003e dilution, digital PCR measured 178.55 copies per microliter which corresponds to approximately 535.65 copies in three microliters of template volume. This concentration consistently produced detectable amplification in nested PCR. At the 10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;5\\u003c/sup\\u003e to 10\\u003csup\\u003e\\u0026minus;\\u0026thinsp;6\\u003c/sup\\u003e dilutions, detection remained reproducible, whereas at lower concentrations corresponding to approximately 0.5 copies partial detection was observed. These data collectively indicate that the assay maintains reliable detection performance across a wide dynamic range of target concentrations.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Annual and habitat-specific tick collection numbers and proportions\\u003c/h2\\u003e \\u003cp\\u003eFrom 2018 to 2024, a total of 72,956 hard ticks were collected across the four surveyed habitat types; grassland, mountain trail, mixed forest, and cemetery in Dangjin-si, Chungcheongnam-do. Annual collection numbers were highest in 2018 (n\\u0026thinsp;=\\u0026thinsp;16,996) and 2019 (n\\u0026thinsp;=\\u0026thinsp;21,668) and showed a gradual decline thereafter: 9,086 in 2020, 8,769 in 2021, 5,168 in 2022, 5,953 in 2023, and 5,316 in 2024.\\u003c/p\\u003e \\u003cp\\u003eHabitat-specific patterns indicated that the grassland site yielded the highest number of ticks, accounting for 42,186 individuals (56.40%), followed by the mountain trail (13,555 individuals; 18.12%), mixed forest (13,092 individuals; 17.50%), and cemetery (5,965 individuals; 7.97%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). A notable surge in tick abundance was observed in the grassland habitat in 2019, after which a marked decline occurred across most habitats (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Monthly occurrence by species (April-November)\\u003c/h2\\u003e \\u003cp\\u003eMonthly and species-specific analyses of ticks collected between 2018 and 2024 revealed distinct seasonal and interannual dynamics (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e was the most frequently collected species, with peak activity occurring consistently between April and July in most years. Substantial increases in abundance were observed in 2019 and 2021. \\u003cem\\u003eHaemaphysalis flava\\u003c/em\\u003e occurred less frequently than \\u003cem\\u003eH. longicornis\\u003c/em\\u003e and appeared sporadically from April to October, with relatively higher numbers in September and October. \\u003cem\\u003eIxodes nipponensis\\u003c/em\\u003e was rare throughout the study period, with annual totals typically below 10 individuals, except for a brief increase recorded in July 2020. \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e cf. spp. representing larvae that could not be reliably differentiated morphologically between \\u003cem\\u003eH. longicornis\\u003c/em\\u003e and \\u003cem\\u003eH. flava\\u003c/em\\u003e, showed a different seasonal pattern. This larval group peaked strongly in September 2018 (n\\u0026thinsp;=\\u0026thinsp;3,660) and September 2019 (n\\u0026thinsp;=\\u0026thinsp;3,150) and overall displayed its highest abundance in August and September, which differed from the adult activity periods (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eOf all ticks collected (n\\u0026thinsp;=\\u0026thinsp;72,956), \\u003cem\\u003eH. longicornis\\u003c/em\\u003e (adult and nymph) accounted for 46,269 individuals (63.42%), followed by \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e cf. spp. (larvae) with 24,889 individuals (34.12%), \\u003cem\\u003eH. flava\\u003c/em\\u003e with 1,143 individuals (1.57%), and \\u003cem\\u003eI. nipponensis\\u003c/em\\u003e with 655 individuals (0.90%).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 SFTS pathogen detection results\\u003c/h2\\u003e \\u003cp\\u003eOf the total ticks collected, 36,478 individuals were pooled into 3,106 pools for SFTSV detection using nested RT-PCR targeting SFTS virus RNA. The assay followed the manufacturer\\u0026rsquo;s protocol, including a primary RT-PCR followed by a secondary nested PCR, with final products visualized through 1.5% agarose gel electrophoresis.\\u003c/p\\u003e \\u003cp\\u003eThe positive control consistently produced a distinct 219 bp band, whereas no amplification was observed in the negative control, confirming the absence of contamination. Among the 3,106 pools tested, none yielded the expected 530 bp SFTSV-positive band, indicating that all samples were negative for SFTSV RNA.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1 Ecological interpretation of long-term tick surveillance data\\u003c/h2\\u003e \\u003cp\\u003eThis study provides a 7-year ecological dataset characterizing the distribution, seasonal activity, and habitat-specific occurrence of hard ticks in Dangjin-si, Chungcheongnam-do. Three species were identified, and \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e represented the majority of adult and nymphal specimens. This dominance is consistent with nationwide surveillance findings reporting \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e species as the prevailing ticks in rural and peri-urban landscapes across the Republic of Korea [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. The persistently high proportion of \\u003cem\\u003eH. longicornis\\u003c/em\\u003e across all four habitat types suggests broad ecological tolerance and the ability to utilize diverse vertebrate hosts, including rodents, deer, carnivores, livestock, and humans.\\u003c/p\\u003e \\u003cp\\u003eSeasonal variation of activity patterns observed in this study further reflect well-established biological rhythms of hard ticks in East Asia. Adult and nymphal \\u003cem\\u003eH. longicornis\\u003c/em\\u003e exhibited peak activity between April and July, whereas \\u003cem\\u003eH. flava\\u003c/em\\u003e showed distinct activity peaks in September and October. Larval \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e cf. spp. peaked primarily during August and September, indicating life-cycle timing that differs from that of adults and nymphs. These seasonal windows overlap with periods of increased agricultural, forestry, and outdoor human activity, increasing opportunities for human-tick encounters [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. The temporal heatmap (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e) highlights that agricultural fields, forest edges, and peri-urban interfaces may sustain extended periods of exposure risk throughout the warm season because the activity windows of multiple life stages overlap. This pattern is consistent with reports from other regions in East Asia, where overlapping life stages extend the seasonal window of potential pathogen transmission [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eInterannual variation also revealed meaningful ecological signals. Total tick abundance peaked during 2018\\u0026ndash;2019 and gradually declined thereafter (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). These fluctuations likely reflect changes in climatic conditions, vegetation structure, land-cover transitions, and wildlife host availability across years. Because such interannual dynamics cannot be captured through short-term sampling, the observed trends underscore the importance of long-term datasets for resolving natural population cycles and accurately interpreting local vector ecology.\\u003c/p\\u003e \\u003cp\\u003eThe habitat distribution shown in Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e further illustrates that landscapes characterized by forest margins, agricultural fields, and residential zones function as interface environments where ticks, wildlife hosts, domestic animals, and humans interact frequently. Dangjin-si contains a mosaic of such environments, which may support persistent tick populations even under fluctuating environmental conditions. These observations reinforce the relevance of a One Health framework that integrates environmental, veterinary, and human health components when assessing future tick-borne disease risks.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.2 Interpretation of negative SFTSV detection and factors influencing viral detectability\\u003c/h2\\u003e \\u003cp\\u003eAlthough 36,478 ticks grouped into 3,106 pools were tested using nested RT-PCR, SFTSV was not detected in any sample. This finding is consistent with several surveillance studies conducted in the Republic of Korea, which reported extremely low or undetectable SFTSV prevalence in questing ticks even in areas with high vector abundance [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. Given the large number of pools analyzed and the inherent dilution effect associated with pooled testing, these results are most reasonably interpreted as reflecting either very low-level viral circulation or activity below the operational detection threshold of pooled surveillance during the study period in Dangjin-si.\\u003c/p\\u003e \\u003cp\\u003eThe analytical sensitivity of the assay further supports this interpretation. According to the manufacturer, the nested RT-PCR system has a detection limit of LoD95% = 1.643 viral copies per microliter and achieves approximately 99% detection probability at concentrations of two or more copies per microliter. Given this level of sensitivity, the absence of positive detections suggests that any SFTSV present in questing ticks was likely distributed at concentrations below detectable levels when diluted across pooled samples. Thus, the negative results should be interpreted as reflecting methodological and ecological constraints rather than evidence of true viral absence.\\u003c/p\\u003e \\u003cp\\u003eBroader comparative patterns across East Asia reinforce this view. While China and Japan frequently report SFTSV-positive ticks across diverse ecological settings, Taiwan consistently reports no viral detection in ticks despite ongoing human SFTS surveillance [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. These contrasting regional patterns indicate that SFTSV circulation is shaped by fine-scale ecological conditions and host-associated transmission networks rather than by vector density alone. The micro-focal and intermittent nature of SFTSV transmission increases the likelihood that environmental sampling may miss viral hotspots that are spatially restricted or temporally transient.\\u003c/p\\u003e \\u003cp\\u003eImportantly, negative molecular detection does not equate to confirmed viral absence. Non-detection may occur when infection prevalence is extremely low, when viral circulation is confined to micro-focal hotspots outside designated sampling sites, or when RNA degradation occurs prior to laboratory processing. Pooling further reduces the probability of detecting rare infected individuals by diluting viral RNA below detectable concentrations [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. Such limitations are well recognized in tick-borne pathogen surveillance, where transmission is often shaped by wildlife host movements and microclimatic variability operating at spatial scales smaller than those captured by standard environmental sampling frameworks [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eData were obtained from the Chungcheongnam-do Infectious Disease Control and Management Center (CNCIDC). Each administrative region is labeled with the City or County name, total number of reported cases, and incidence rate per 100,000 population. Quarterly distributions are shown as Q1 (January to March), Q2 (April to June), Q3 (July to September), and Q4 (October to December).\\u003c/p\\u003e \\u003cp\\u003eThe divergence between environmental tick surveillance and human case occurrence in Dangjin-si illustrates these constraints. Although no SFTSV was detected in ticks collected from this area, approximately twelve human SFTS cases were reported during the study period. A similar discrepancy has been reported in Oita Prefecture, Japan, where one region showed no evidence of SFTSV or antiviral antibodies in ticks, wildlife, livestock, or humans, despite clear viral activity in surrounding areas [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. These observations provide further evidence that tick-based environmental surveillance alone may underestimate transmission risk when viral circulation is highly localized or maintained within specific host\\u0026ndash;vector networks.\\u003c/p\\u003e \\u003cp\\u003eConsistent with this interpretation, human SFTS incidence in Chungcheongnam-do displays pronounced spatial heterogeneity (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e). Regional comparisons based on incidence rates rather than absolute case counts reveal that Gongju-si, Cheonan-si, and Asan-si exhibit substantially higher incidence rates than Dangjin-si, suggesting uneven distribution of ecological or epidemiological conditions that support viral maintenance. Seasonal patterns further indicate concentration of cases in specific quarters of the year. Together, these findings suggest that aligning future tick collection efforts with both spatial patterns of human incidence and seasonal peaks may increase the likelihood of detecting virus-positive pools and improve the precision of One Health\\u0026ndash;oriented risk assessments [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. Such an integrated approach may also contribute to a more accurate understanding of SFTSV transmission dynamics and support the development of more effective early warning and surveillance strategies.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.3 Implications for public health and future surveillance directions\\u003c/h2\\u003e \\u003cp\\u003eThe ecological patterns identified in this study carry important implications for public health planning and the refinement of national tick-borne disease surveillance strategies. Although no SFTSV was detected in questing ticks from Dangjin-si, the consistently high abundance of \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e species across all habitat types indicates that ecological conditions for potential viral introduction or amplification remain present. Similar patterns have been observed in regions where vector densities are high but detectable viral circulation is absent or intermittent, suggesting that transmission risk is shaped not only by tick abundance but also by host community structure and fine-scale environmental variability [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eHuman SFTS cases in Chungcheongnam-do demonstrate strong spatial heterogeneity, with Gongju-si, Cheonan-si, and Asan-si exhibiting markedly higher incidence compared with Dangjin-si (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e). These spatial discrepancies imply that localized environmental or ecological characteristics may foster viral maintenance in some areas but not others [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Aligning surveillance efforts with human case clusters could therefore enhance the probability of detecting SFTSV-positive ticks and enable characterization of viral serotypes or genotypes. Such targeted sampling approaches have been recommended in other vector-borne disease systems to improve detection efficiency and refine One Health-informed risk assessment frameworks [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eA broader interpretation of these findings underscores the value of integrating ecological, epidemiological, and environmental datasets. Several recent studies have effectively used citizen-science wildlife occurrence records from platforms such as iNaturalist and GBIF to infer potential distributions of reservoir hosts or vector-associated species in vector-borne disease research [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. High-resolution climate data, including temperature, precipitation, humidity indices, and land surface temperature, have been incorporated into species distribution models to predict habitat suitability and seasonal activity patterns at fine spatial scales. Remote-sensing products such as land-use classifications, vegetation indices, and habitat fragmentation metrics can also be processed in GIS environments to identify ecological conditions that support vector persistence [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAlthough these approaches were not used in the present analysis, their potential relevance for SFTSV surveillance in Korea is substantial. Dangjin-si consists of a mosaic of agricultural fields, forest margins, and peri-urban residential areas where wildlife hosts such as rodents, deer, and carnivores move between habitat types and may facilitate micro-scale viral circulation [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. Integrating ecological surveillance with citizen-science observations, climate-based risk mapping, and high-resolution environmental variables could therefore help identify environmental configurations associated with SFTSV maintenance. This may also help detect micro-focal viral hotspots in settings where standard tick sampling yields only negative results, as demonstrated in Oita Prefecture, Japan, where one region displayed complete negativity for SFTSV across ticks, domestic animals, wildlife, and humans despite active circulation in adjacent areas [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe mismatch observed in this study between high vector density and absence of viral detection emphasizes the importance of long-term, multi-source surveillance systems. Periodic integration of human case data, wildlife reservoir monitoring, environmental indicators, and vector-based sampling may help identify temporal windows or spatial clusters where viral circulation is more likely [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e]. As climate continues to change and land-use patterns shift, coordinated surveillance across multiple administrative regions will be necessary to detect ecological transitions that precede pathogen emergence. In this context, the dataset generated here contributes a foundational ecological baseline for Dangjin-si while highlighting practical frameworks that could strengthen One Health-oriented surveillance across the Republic of Korea [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.4 Limitations and future directions\\u003c/h2\\u003e \\u003cp\\u003eSeveral limitations should be considered when interpreting the findings of this 7-year surveillance study, and these limitations also highlight opportunities for strengthening future research and public-health preparedness.\\u003c/p\\u003e \\u003cp\\u003eFirst, \\u003cem\\u003eAmblyomma testudinarium\\u003c/em\\u003e, a recognized SFTSV vector in southern Korea, was not detected during the study period. However, recent reports from central regions including areas near Daejeon, suggest a possible northward expansion of this species that may be influenced by changing climatic and habitat conditions [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Sustained monitoring across broader latitudinal gradients will be necessary to determine whether this trend reflects a true shift in distribution or localized introductions that may eventually contribute to regional pathogen circulation.\\u003c/p\\u003e \\u003cp\\u003eSecond, surveillance prioritization may benefit from a strategic focus on areas with recurrent human SFTS cases. Regions such as Gongju-si and Cheonan-si consistently report higher case numbers than Dangjin-si, as shown in regional epidemiological data (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e). Concentrating additional sampling in these high-incidence areas could increase the likelihood of detecting SFTSV-positive pools and support downstream analyses such as genotype or serotype characterization. Such targeted approaches would complement the current findings from a low-incidence area and help clarify whether spatial differences in human infections arise from ecological heterogeneity, micro-focal viral persistence, or variation in wildlife host communities.\\u003c/p\\u003e \\u003cp\\u003eThird, advances in molecular diagnostics provide promising opportunities to enhance sensitivity in future tick-based SFTSV surveillance. Methods such as quantitative RT-PCR, isothermal amplification assays, and metagenomic sequencing may enable detection of viral RNA at lower concentrations or from partially degraded samples. Multi-pathogen screening targeting agents such as \\u003cem\\u003eAnaplasma\\u003c/em\\u003e, \\u003cem\\u003eRickettsia\\u003c/em\\u003e, and \\u003cem\\u003eBorrelia\\u003c/em\\u003e would expand the ecological value of surveillance datasets and allow more comprehensive assessments of tick-associated pathogen risk.\\u003c/p\\u003e \\u003cp\\u003eFourth, integrating long-term ecological datasets with high-resolution environmental and climatic information could substantially improve risk prediction. Coupling tick abundance data with climate variables, land-use change indicators, vegetation indices, and wildlife occurrence records may help identify specific environmental configurations associated with vector persistence or viral maintenance. Species distribution models and landscape epidemiology frameworks have been widely used in vector-borne disease research and can be applied similarly to tick-borne disease systems in Korea to refine spatial risk assessments [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eFifth, because this study relies on a single sampling method, some microhabitat-specific or host-associated ticks may be under-represented. CO\\u003csub\\u003e2\\u003c/sub\\u003e-baited traps were intentionally used to minimize operator-dependent variation and maintain consistent trapping conditions across years. However, incorporating additional sampling methods such as drag or flag sampling, or wildlife-associated tick collection, would help capture a broader spectrum of tick species, life stages, and behaviors. This enhancement would be particularly valuable for detecting micro-focal viral circulation that may be linked to host movement patterns or fine-scale habitat structure.\\u003c/p\\u003e \\u003cp\\u003eFinally, the dataset originates from one city and four habitat types. The findings should therefore be interpreted as region-specific rather than nationally representative. Ecological conditions, wildlife host communities, and viral serotypes may vary across Korea, and additional multi-regional datasets will be needed to determine whether the patterns observed in Dangjin-si generalize to other areas. As climate and land-use changes continue to reshape vector ecology, long-term datasets of this type will be essential for detecting ecological transitions, validating predictive models, and guiding adaptive surveillance strategies.\\u003c/p\\u003e \\u003cp\\u003eIn conclusion, the high abundance, distinct seasonality, and ecological adaptability of \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e species suggest that Dangjin-si may continue to support ecological conditions conducive to tick population persistence. Strengthening regional surveillance networks and integrating human, animal, and environmental health data across administrative boundaries will enhance early warning capacity and support more effective responses to future tick-borne disease threats. The dataset presented here provides an important long-term ecological baseline that can facilitate future integration of environmental, climatic, and epidemiological datasets toward more predictive and adaptive One Health surveillance systems in Korea.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"5. Conclusions\",\"content\":\"\\u003cp\\u003eThis study provides a seven-year longitudinal assessment of hard tick ecology and One Health\\u0026ndash;based pathogen risk in Dangjin-si, a representative region of central Korea. Although none of the 3,106 pools tested positive for SFTSV, the persistent dominance of \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e across years and habitats suggests that local environmental conditions remain suitable for the maintenance or potential introduction of tick-borne pathogens. The absence of viral detection should therefore not be interpreted as reduced risk, particularly given the proximity to high-incidence regions. The long-term dataset established here offers a valuable baseline for evaluating future changes in tick species composition, population dynamics, and pathogen circulation. Strengthening surveillance through the integration of ecological factors, climatic trends, and multi-pathogen screening will be essential for advancing regional One Health\\u0026ndash;based early-warning systems.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study did not involve human participants or vertebrate animals. Tick collection was conducted as part of routine public health surveillance activities and complied with national guidelines. Therefore, ethical approval and informed consent were not required.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data generated or analyzed in this study are included in this published article and its supplementary files. Additional datasets are available from the corresponding author upon reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was financially supported by the Korea Disease Control and Prevention Agency (KDCA; No. 6332-302); the Korea Basic Science Institute through the National Research Facilities and Equipment Center (NFEC) program funded by the Ministry of Education (No. 2022R1A6C101B794); the National Research Foundation of Korea (NRF; No. 2021R1A6A1A03039503 and No. 2017R1D1A3B06034971); and the Soonchunhyang University Research Fund.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eYong Seok Lee, Wook-Gyo Lee, and Hyeon Jun Shin conceived the study idea and designed the overall research framework. Over the seven-year surveillance period, Hyeon Jun Shin, Jun Yang Jeong, Chan Eui Hong, Hyuk Lee, Kyung Won Lee, Min Gyu Sang\\u003csup\\u003e2,3\\u003c/sup\\u003e, Jie Eun Park, Dae Kwon Song, and Yong Seok Lee participated in long-term field tick collection and laboratory analyses. Among them, Jie Eun Park contributed technical guidance for the laboratory workflows, while Dae Kwon Song and Cho-I Moon contributed to data interpretation. Yong Seok Lee and Wook-Gyo Lee made the most substantial contributions to the development of the research methodology and the review of the manuscript structure. The study concept and initial draft were prepared by Hyeon Jun Shin. All authors reviewed and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors thank the staff of the Korea Disease Control and Prevention Agency (KDCA), the Chungcheongnam-do Infectious Disease Control and Management Center (CNCIDC), the Dangjin-si Public Health Center, and the Asan-si Public Health Center for their assistance with long-term tick surveillance and field support. We also acknowledge invirustech and GnCbio for providing technical advice and laboratory support.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eLiu B, Zhu J, He T, Zhang Z. Genetic variants of Dabie bandavirus: classification and biological/clinical implications. 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A generalizable one health framework for the control of zoonotic diseases. Scientific reports. 2022;12 1:8588.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee Y, Jeong D-H. Toward a one health-based surveillance strategy for emerging zoonoses: The role of wildlife center. Journal of Preventive Veterinary Medicine. 2025;49 2:91\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHewson R. Understanding Viral Haemorrhagic Fevers: Virus Diversity, Vector Ecology, and Public Health Strategies. 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Proceedings of the National Academy of Sciences. 2022;119 7:e2200481119; doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1073/pnas.2200481119\\u003c/span\\u003e\\u003cspan address=\\\"10.1073/pnas.2200481119\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e. https://dx.doi.org/10.1073/pnas.2200481119.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"parasites-and-vectors\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"parv\",\"sideBox\":\"Learn more about [Parasites \\u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)\",\"snPcode\":\"13071\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13071/3\",\"title\":\"Parasites \\u0026 Vectors\",\"twitterHandle\":\"@bugbittentweets\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Tick surveillance, Ixodidae, SFTS virus, Vector-borne diseases, Seasonal dynamics\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-8379339/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-8379339/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground:\\u003c/h2\\u003e \\u003cp\\u003eHard ticks (Ixodidae) are the primary vectors of severe fever with thrombocytopenia syndrome virus (SFTSV), a tick-borne pathogen of increasing public health concern in East Asia. Understanding local vector ecology requires long-term monitoring, particularly in regions where human cases occur but viral prevalence in ticks remains unclear. This study conducted a multi-year ecological and molecular surveillance of hard ticks and SFTSV in Dangjin-si, Chungcheongnam-do, a representative region of central Korea.\\u003c/p\\u003e\\u003ch2\\u003eMethods:\\u003c/h2\\u003e \\u003cp\\u003eFrom 2018 to 2024, ticks were collected monthly from April to November across four habitat types (grasslands, mountain road, mixed forest, and cemetery) using standardized 24-hour CO\\u003csub\\u003e2\\u003c/sub\\u003e-baited traps. Specimens were morphologically identified and pooled by species, developmental stage, sex, and habitat. A total of 36,478 ticks were grouped into 3,106 pools. Total RNA was extracted and screened for SFTSV using nested RT-PCR, and amplification results were confirmed by agarose gel electrophoresis.\\u003c/p\\u003e\\u003ch2\\u003eResults:\\u003c/h2\\u003e \\u003cp\\u003eA total of 72,956 ticks belonging to \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e, \\u003cem\\u003eH. flava\\u003c/em\\u003e, and \\u003cem\\u003eIxodes nipponensis\\u003c/em\\u003e were collected. \\u003cem\\u003eHaemaphysalis longicornis\\u003c/em\\u003e dominated the collection, representing 63.42% of all adult and nymphal ticks. Tick abundance peaked during 2018\\u0026ndash;2019 and was highest in grassland habitats. None of the 3,106 pools tested positive for SFTSV.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eAlthough SFTSV was not detected, the persistently high abundance and broad ecological distribution of \\u003cem\\u003eHaemaphysalis\\u003c/em\\u003e species suggest that Dangjin-si maintains environmental conditions that could support pathogen introduction or amplification. These long-term data provide a valuable baseline for early-warning systems and highlight the need for targeted surveillance in nearby high-incidence regions. Integrating ecological, climatic, and epidemiological data including multi-pathogen screening will be essential for strengthening One Health-based risk assessment frameworks in low-prevalence areas.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Long-term ecological surveillance of hard ticks (Acari: Ixodidae) and SFTSV in Dangjin, central Korea (2018-2024)\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-12-30 00:49:13\",\"doi\":\"10.21203/rs.3.rs-8379339/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-12-29T21:44:07+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-12-28T04:01:07+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"335872517420808272414936840369053251680\",\"date\":\"2025-12-25T04:19:05+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-12-19T17:35:36+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-12-19T09:26:13+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-12-19T07:06:10+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Parasites \\u0026 Vectors\",\"date\":\"2025-12-16T19:13:14+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"parasites-and-vectors\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"parv\",\"sideBox\":\"Learn more about [Parasites \\u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)\",\"snPcode\":\"13071\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13071/3\",\"title\":\"Parasites \\u0026 Vectors\",\"twitterHandle\":\"@bugbittentweets\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"e271365d-232a-4139-975f-402a73aeb45f\",\"owner\":[],\"postedDate\":\"December 30th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-04-07T16:14:32+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-8379339\",\"link\":\"https://doi.org/10.1186/s13071-026-07338-9\",\"journal\":{\"identity\":\"parasites-and-vectors\",\"isVorOnly\":false,\"title\":\"Parasites \\u0026 Vectors\"},\"publishedOn\":\"2026-03-30 15:59:03\",\"publishedOnDateReadable\":\"March 30th, 2026\"},\"versionCreatedAt\":\"2025-12-30 00:49:13\",\"video\":\"\",\"vorDoi\":\"10.1186/s13071-026-07338-9\",\"vorDoiUrl\":\"https://doi.org/10.1186/s13071-026-07338-9\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-8379339\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-8379339\",\"identity\":\"rs-8379339\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}