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Original Article

Epidemiological trends and regional risk factors for scrub typhus in Busan, Republic of Korea: 2019–2023

Keoungsuk Kim1orcid, Hyeokjin Lee2orcid, Seungah Park1orcid, Gey Ok Lee1orcid, Sang-Eun Lee2orcid

Published online: May 11, 2026

1Division of Infectious Disease Control, Busan Metropolitan City Hall, Busan, Republic of Korea

2Division of Infectious Disease Control & Response, Gyeongnam Regional Center for Disease Control and Prevention, Korea Disease Control and Prevention Agency, Busan, Republic of Korea

Corresponding author: Keoungsuk Kim Division of Infectious Disease Control, Busan Metropolitan City Hall, 1001 Jungang-daero, Yeonje-gu, Busan 47545, Republic of Korea E-mail: lg20130326@gmail.com
Co-Corresponding author: Sang-Eun Lee Division of Infectious Disease Control & Response, Gyeongnam Regional Center for Disease Control and Prevention, Korea Disease Control and Prevention Agency, 1090 Jungang-daero, Yeonje-gu, Busan 47596, Republic of Korea E-mail: ondalgl@korea.kr
• Received: January 24, 2026   • Revised: March 13, 2026   • Accepted: March 19, 2026

© 2026 Korea Disease Control and Prevention Agency.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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  • Objectives
    Scrub typhus, an acute disease caused by Orientia tsutsugamushi and transmitted by larval chigger mites, is a representative autumn febrile illness in the Republic of Korea. We examined epidemiological characteristics underlying spatial heterogeneity in Busan Metropolitan City to inform region-specific prevention and control policies.
  • Methods
    We analyzed 1,645 confirmed and suspected scrub typhus cases reported in Busan from 2019 to 2023. Crude incidence rates and age-standardized incidence rates (ASIRs) per 100,000 population were calculated using the 2021 mid-year population. The chi-square test assessed associations between disease occurrence and exposure activities within the preceding 30 days. Correlation analyses examined the relationships of ASIR with environmental indicators, including per capita urban forest area, and epidemiological indicators, including prior infectious disease education.
  • Results
    The overall mean ASIR in Busan was 8.35 per 100,000 population, below the national average. However, incidence was higher in peri-urban districts, including Gijang-gun (26.12/100,000) and Gangseo-gu (15.02/100,000), than in central urban districts such as Jung-gu (2.20/100,000). Higher incidence was observed among women and older adults (≥60 years). ASIR correlated strongly with per capita urban forest area (r=0.92; 95% confidence interval, 0.79–0.97; p<0.001). Regional differences were significant for agriculture/forestry, gardening, and general outdoor activities (p<0.001). Districts with higher incidence also displayed higher rates of infectious disease education, although this may reflect reverse causation.
  • Conclusion
    In Busan, scrub typhus incidence was concentrated in peri-urban districts. These findings support region-specific prevention strategies, evaluation of infectious disease education, enhanced mite surveillance, and practical protective measures during fieldwork.
  • Keywords: Busan; Epidemiology; Orientia tsutsugamushi; Personal protective equipment; Risk factors; Scrub typhus
Scrub typhus is a vector-borne zoonotic disease caused by infection with Orientia tsutsugamushi following the bite of larval mites (chiggers). It is particularly endemic in the Asia–Pacific region, commonly referred to as the “tsutsugamushi triangle” [1,2]. After an incubation period of 6–21 days, patients typically present with nonspecific symptoms, including fever, headache, myalgia, chills, and vomiting; the presence of a rash and eschar provides key diagnostic clues [1,3]. Because its clinical presentation closely resembles that of other febrile illnesses, delayed diagnosis may lead to rapid progression to severe complications, including multiple organ failure, and case fatality rates as high as 70% have been reported [1].
Recent increases in case reports from newly affected areas have renewed attention to the geographic distribution and evolving global epidemiology of scrub typhus. In particular, changes in climate and human activity patterns are influencing vector habitats and transmission dynamics, suggesting that infection may occur even in previously non-endemic regions [4,5]. Scrub typhus has become a major public health concern in several Asian countries, including India, China, Japan, and Thailand; for example, India has reported recurrent large-scale outbreaks and high mortality over the past several decades [5]. In addition, a recent meta-analysis reported high global average seroprevalence, highlighting both the hidden burden of infection and substantial regional heterogeneity [6]. Collectively, these findings indicate that scrub typhus is not confined to traditionally endemic areas and that its epidemiological patterns continue to evolve in response to climatic and environmental factors.
In the Republic of Korea, the incidence of scrub typhus has increased markedly over the past decade [6], underscoring the need for proactive infectious disease control policies that extend beyond responses to climatic and environmental factors alone. This increase may be partly explained by rapid land-use change and the resulting fragmentation and expansion of chigger habitats. Recent long-term time-series analyses in neighboring China have shown that land-use changes, such as deforestation and agricultural fragmentation, may amplify infection risk by creating an “edge effect” that increases contact between humans and wild vectors [7,8]. Human exposure also increases during agricultural work, grass cutting (e.g., beolcho), and outdoor leisure activities in shrublands and grassy fields near villages and farmlands, which provide abundant food sources for rodents. This mechanism likely contributes to the pronounced seasonal peak observed in autumn [9]. In addition, a recent climate change vulnerability assessment found that coastal areas of Jeolla Province, characterized by extensive farmland and large agricultural populations, were more vulnerable to scrub typhus than other regions [10].
These epidemiological patterns are strongly shaped by climatic and environmental factors. Domestic studies have reported nonlinear associations between scrub typhus incidence and changes in average temperature and rainfall [11]. In addition, socioenvironmental conditions, such as living near forests, engaging in agricultural activities, and residing in traditional houses, have been identified as key risk factors for infection [5]. The effective control of scrub typhus therefore requires a multidimensional strategy that extends beyond patient treatment to incorporate climate and environmental change, demographic characteristics, risk-related behaviors, disease awareness, and relevant educational experience. However, when interpreting the correlation between education and disease incidence, reverse causation cannot be excluded, because public health education efforts may be concentrated preferentially in high-incidence areas. Accordingly, caution is warranted when evaluating the true preventive effectiveness of these educational interventions.
Scrub typhus is one of the major mite-borne infectious diseases that recurs annually in the southern regions of the Republic of Korea, including Busan, and it imposes a substantial disease burden, particularly on older adults and residents of rural and peri-urban areas. Although Busan Metropolitan City is the second-largest city in the Republic of Korea, it also includes urban–rural mixed settings, such as Gijang-gun, resulting in pronounced spatial heterogeneity. Accordingly, this study analyzed scrub typhus cases reported in Busan Metropolitan City from 2019 to 2023. We focused specifically on the associations of incidence with demographic factors (age and sex), regional characteristics, risk-related behaviors, urban forest environments, and prior educational experience. Recognizing the potential ecological fallacy inherent in aggregated data, we also conducted sensitivity analyses to assess the influence of extreme outliers, such as Gijang-gun, and thereby evaluate the statistical robustness of our findings. Ultimately, this study sought to identify the key epidemiological and environmental factors underlying regional disparities in incidence, emphasize the need for targeted prevention strategies for high-risk populations, and provide evidence to inform region-specific vector-borne disease control policies in Busan.
Data Source and Case Definition
To analyze the incidence and epidemiological characteristics of scrub typhus in Busan Metropolitan City, we used data on confirmed and suspected cases reported to the Korea Disease Control and Prevention Agency (KDCA) through the Integrated Disease and Health Management System. The study period extended from January 1, 2019, to December 31, 2023. A total of 1,797 cases were reported, of which 152 were excluded because of missing epidemiological investigation records or incomplete data entries. Therefore, the final analytical dataset included 1,645 cases. The epidemiological data collected included general characteristics (sex, age, and residential district), clinical symptoms, and exposure history during the 30 days before illness onset, specifically participation in forestry-, agriculture-, or livestock-related activities.
Case Definition
Case definitions were based on the KDCA National Notifiable Infectious Diseases Diagnostic and Reporting Standards (2024). A confirmed case was defined as a patient with clinical symptoms in whom pathogen infection was verified by laboratory testing. A suspected case was defined as a patient with compatible clinical symptoms and epidemiological links in whom infection was suspected on the basis of a presumptive diagnosis, such as the detection of specific antibodies in blood specimens.
Data Analysis
Crude incidence rates were calculated per 100,000 population using the mid-year population of each year as the denominator and were stratified by region, sex, and age group. Age-standardized incidence rates (ASIRs) were calculated by the direct standardization method using 5-year age intervals and the 2021 mid-year population as the standard population. As an indicator of vector habitat, per capita urban forest area was obtained from the National Urban Forest Statistics (2021) through the e-Nara Indicator portal. Regional differences in epidemiological characteristics were compared using the chi-square test. Correlations between ASIRs and environmental or epidemiological factors were evaluated using Pearson or Spearman correlation analyses. Statistical analyses were performed using jamovi (ver. 2022) and Microsoft Excel 2016 (Microsoft Corp.), and the results were presented in tables and figures.
Ethics Statement
This study used de-identified public health surveillance data and was deemed exempt from KDCA Institutional Review Board review (Exemption No: KDCA-2025-10-09).
General Characteristics
During 2019–2023, Busan Metropolitan City reported 1,645 cases of scrub typhus (confirmed and suspected), corresponding to an average incidence rate of 9.85 per 100,000 population. Incidence peaked in 2022 at 13.02 per 100,000 and then declined to 8.20 per 100,000 in 2023. Female patients accounted for 56.2% of all cases, and the incidence rate was consistently higher among female residents (10.84 per 100,000) than among male residents (8.80 per 100,000). The age distribution showed a clear concentration among older adults: individuals aged 60–69 years accounted for 35.4% of cases, and those aged ≥70 years accounted for 36.2%, indicating that more than half of cases occurred in persons aged 60 years or older (Table 1).
Regional Incidence
From 2019 to 2023, the national average ASIR was 10.25 per 100,000 population, whereas the overall ASIR in Busan was 8.35 per 100,000. However, substantial variation was observed across Busan’s 16 districts. Gijang-gun had the highest ASIR, at 26.12 per 100,000, over 2 and 3 times the national and city averages, respectively (Figure 1). Other districts with elevated incidence included Gangseo-gu (15.02), Haeundae-gu (13.28), and Geumjeong-gu (11.13). In contrast, central districts such as Dong-gu (3.97), Yeongdo-gu (3.92), and Jung-gu (2.20) had relatively low incidence. Regarding annual trends, Busan’s ASIR peaked in 2022 at 10.77 per 100,000 and then declined markedly to 6.50 per 100,000 in 2023. This pattern paralleled the national trend, which decreased from 11.74 to 10.31 per 100,000 between 2022 and 2023 (Table 2).
Correlation Between Urban Forest Area and ASIR
To evaluate the relationship between scrub typhus incidence and the surrounding green-space environment, we performed a Pearson correlation analysis between per capita total urban forest area (2021) and ASIR in each district of Busan. The analysis showed a very strong positive correlation (r=0.92; 95% confidence interval [CI], 0.79–0.97; p<0.001) (Figure 2). Because the sample size was small (n=16) and certain districts had disproportionately high values, an additional sensitivity analysis was conducted after excluding Gijang-gun as a potential outlier. After this exclusion, the correlation coefficient decreased slightly to r=0.86 (95% CI, 0.63–0.95; p=0.004), but the positive association remained statistically significant. This finding suggests that the observed association between urban forest distribution and scrub typhus incidence was not driven solely by extreme values, supporting the robustness of this association.
In general, districts with larger per capita green space had higher incidence rates. For example, Gijang-gun, which had the highest ASIR (26.1 per 100,000), also had the largest per capita urban forest area (747.9 m2), followed by Gangseo-gu (ASIR, 15.0; 324.8 m2) and Geumjeong-gu (ASIR, 11.1; 215.2 m2). By contrast, densely populated metropolitan cities with smaller green areas, such as Seoul (ASIR, 1.3; 19.7 m2) and Incheon (ASIR, 2.0; 52.6 m2), showed substantially lower incidence rates. A similar pattern was observed across the 8 metropolitan cities nationwide, including Ulsan (ASIR, 22.2; 366.2 m2), Sejong (ASIR, 14.0; 49.9 m2), and Daejeon (ASIR, 10.5; 186.9 m2) (Figure 3). In addition, to address the potential temporal mismatch between the baseline year of the environmental indicator (2021) and the disease incidence analysis period (2019–2023), we conducted supplementary comparative analyses using biennial forest statistics from 2019, 2021, and 2023. These analyses showed that temporal variation in forest coverage and urban forest area in Busan was minimal over the 5-year study period. This supports the use of the single time point of 2021 as representative of environmental characteristics during the entire study period.
Risk-Related Exposure Activities
Based on epidemiological investigation data from the 1,645 scrub typhus cases reported in Busan from 2019 to 2023, exposure activities during the 30 days before illness onset were analyzed to identify potential risk factors. These activities were classified into 5 categories: (1) agriculture and forestry/livestock work, (2) kitchen garden work, (3) weekend farming, (4) one-time agricultural/forestry work, and (5) non-agricultural outdoor activities. Chi-square analyses showed statistically significant regional differences for most activities, including agriculture and forestry/livestock activities (χ2=91, p<0.001), kitchen garden work (χ2=59, p<0.001), one-time agricultural/forestry work (χ2=46, p<0.001), and non-agricultural outdoor activities (χ2=33, p=0.004). Weekend farming was the only activity that did not differ significantly by region (χ2=23, p=0.082).
Regional analysis of these activities showed distinct patterns. Exposure to agriculture and forestry/livestock activities was highest in Gijang-gun (21.74%), followed by Haeundae-gu and Suyeong-gu (15.65% each) and Nam-gu and Gangseo-gu (12.17% each). Kitchen garden work was most prevalent in Gijang-gun (18.96%) and Haeundae-gu (14.81%). One-time agricultural or forestry-related activities were reported most frequently in Buk-gu and Haeundae-gu (16.66% each), followed by Dongnae-gu and Nam-gu (10.00% each). Non-agricultural outdoor activities were reported most often in Haeundae-gu (16.34%), followed by Gijang-gun (13.10%), Geumjeong-gu (9.86%), and Buk-gu (9.15%) (Figure 4).
Kitchen garden work was a notable risk-related exposure, with significant findings regarding both specific tasks and geographic distribution. By activity type, statistically significant regional differences were observed for crop harvesting (χ2=41.8, p<0.001), weeding (χ2=67.7, p<0.001), grass cutting (χ2=25.6, p=0.042), and other related tasks (χ2=59.3, p<0.001) (Table 3). Among these, weeding and crop harvesting were reported relatively frequently in suburban districts with extensive green space and farmland, such as Haeundae-gu, Gijang-gun, and Gangseo-gu. These findings suggest that tasks involving direct contact with vegetation were important contributors to infection risk. In contrast, crop planting (e.g., transplanting seedlings) did not differ significantly by region (χ2=23.4, p=0.075), which may reflect seasonal constraints and the timing of data collection.
Analysis of kitchen garden activities by location further showed statistically significant regional differences for both work in rice paddies (χ2=56.2, p<0.001) and direct contact with grass (χ2=56.3, p<0.001) (Table 4). Collectively, these findings suggest that specific types and settings of agricultural activity, particularly those involving vegetation contact, were key factors associated with scrub typhus infection.
Awareness and Educational Experience
The proportion of patients who reported prior education on scrub typhus was low, at approximately 10%. However, statistically significant regional variation was observed (χ2=58.1, p<0.001). Higher rates of prior educational experience were reported in Geumjeong-gu (23.1%), Haeundae-gu (19.0%), Gijang-gun (16.9%), and Gangseo-gu (14.6%). In contrast, Jung-gu (0%), Buk-gu (4.7%), and Saha-gu (4.3%) had very low levels of such experience (Figure 5).
Correlation analysis between the rate of scrub typhus educational experience (per 100,000 population, based on the 2021 mid-year population) and the ASIR in each district showed a strong positive correlation (r=0.70, p<0.001) (Figure 6). This finding indicates that districts with higher infection burden also tended to report higher levels of educational experience. For example, Gijang-gun (ASIR, 26.1 per 100,000) had a relatively high educational experience rate (16.9%). Similarly, Geumjeong-gu (ASIR, 11.1; educational experience rate, 23.1%) and Haeundae-gu (ASIR, 13.3; educational experience rate, 19.0%) were characterized by both high incidence and high levels of educational outreach.
Analysis of scrub typhus cases (confirmed and suspected) reported in Busan Metropolitan City from 2019 to 2023 identified several key epidemiological features. Although Busan’s average ASIR was lower than the national average, relatively high incidence rates were observed in suburban districts such as Gijang-gun, Gangseo-gu, Haeundae-gu, and Geumjeong-gu. Notably, Gijang-gun recorded 26.1 cases per 100,000 population, over 2 and 3 times the national and city averages, respectively, confirming its status as a major high-risk area. In contrast, central urban districts, including Jung-gu, Dong-gu, and Yeongdo-gu, had very low incidence. With respect to temporal trends, incidence peaked in 2022 and then declined sharply in 2023. Although a nationwide decline was also observed, the decrease was more pronounced in Busan. These temporal variations may reflect the combined effects of fluctuations in vector density related to climatic and environmental conditions, strengthened public vector-control interventions, and improved personal preventive behaviors. However, because this study did not include direct vector-density data or quantitative indicators of vector-control effectiveness, these interpretations should be regarded as plausible hypotheses based on the available epidemiological context rather than as direct evidence.
With respect to sex distribution, female patients accounted for 56.2% of cases, and the incidence rate among female residents exceeded that among male residents in every study year. By age group, individuals aged 60–69 years (35.4%) and those aged ≥70 years (36.2%) collectively accounted for a large proportion of cases, indicating a concentration among older adults. This pattern may reflect more frequent participation by older adults in agricultural and forestry-related outdoor activities, as well as the larger proportion of women in older age groups. These findings are consistent with previous reports showing high incidence rates among individuals in their 60s and 70s.
Differences in incidence across Busan’s districts were closely associated with local ecological and environmental characteristics. Correlation analysis between per capita total urban forest area (2021) and ASIR showed a very strong positive correlation (r=0.92; 95% CI, 0.79–0.97; p<0.001), indicating that districts with more extensive green space tended to have higher incidence. For example, Gijang-gun had both the largest per capita urban forest area (747.9 m2) and the highest incidence. Elevated incidence was also observed in other suburban districts with extensive forest and farmland, including Gangseo-gu, Haeundae-gu, and Geumjeong-gu. In contrast, central urban districts with high population density and limited green space had lower incidence rates. A similar pattern was observed in comparisons across the 8 metropolitan cities nationwide: incidence tended to be higher in areas with larger green space (e.g., Ulsan, Sejong, Daejeon, and Gwangju) and lower in urban centers with less green space (e.g., Seoul and Incheon). Together, these findings suggest that urban green areas may increase opportunities for human contact with mite vectors and thus may be associated with increased infection risk. Consistent with this interpretation, recent studies have reported that forest area, rodent habitat indices, and regional socioeconomic conditions are important predictors of vector-mite distribution and that high-risk populations tend to be concentrated in rural or suburban areas at the urban periphery [11,12]. However, given the limited sample size (n=16 districts) and the presence of extreme values such as Gijang-gun, the correlation coefficient may have been overestimated. Although the sensitivity analysis excluding Gijang-gun still showed a statistically significant positive correlation (r=0.86, p=0.004), future studies should use more sophisticated spatial regression models to account more rigorously for potential spatial autocorrelation among adjacent districts. In addition, because this was an ecological analysis based on aggregated area-level data, caution is required to avoid ecological fallacy; district-level environmental indicators cannot be used to infer individual-level infection risk directly.
The analysis of exposure activities further supported these findings. Participation in agricultural, kitchen garden, and outdoor activities during the preceding 30 days was more common in suburban districts with higher proportions of forest and farmland, such as Gijang-gun, Haeundae-gu, Geumjeong-gu, and Gangseo-gu, than in central urban districts. In particular, kitchen garden activities involving direct contact with vegetation, such as crop harvesting and weeding, were associated with infection. Work in rice paddies and contact with grassy fields also showed significant regional differences. These findings suggest that wet rice paddies and grassy fields may provide favorable habitats for chigger mites and that behaviors such as sitting or squatting during agricultural tasks may increase exposure risk. Collectively, these results support the interpretation that agricultural and kitchen garden activities in suburban areas were important factors associated with scrub typhus transmission.
The analysis of disease awareness and educational experience showed that only about 10% of patients had received prior education on scrub typhus, indicating a low overall level of awareness. However, marked regional differences were observed (χ2=58.1, p<0.001), with relatively high rates of educational experience in high-risk areas such as Geumjeong-gu (23.1%), Haeundae-gu (19.0%) and Gijang-gun (16.9%). The strong positive correlation between educational experience and ASIR (r=0.70, p<0.001) should not be interpreted as evidence that education is ineffective in reducing incidence. Rather, this pattern may reflect reverse causation, whereby public health authorities preferentially direct educational programs toward high-risk communities. The indicator used in this study reflects an ecological correlation at the population level and does not measure the preventive effectiveness of education at the individual level. It is therefore plausible that educational interventions were implemented more intensively in high-incidence areas. To evaluate the infection-reducing effect of health education more rigorously, future prospective studies should control carefully for the timing and intensity of educational interventions. For example, despite multiple educational and promotional activities, Gijang-gun continued to record the highest incidence rate, underscoring the limitations of education alone in reducing community transmission. In addition, some high-risk areas lacked sufficiently tailored educational materials and programs, and residents often relied on family members, neighbors, or mass media for information [13,14]. Therefore, practical prevention strategies are needed in addition to strengthened education for high-risk groups. These strategies should emphasize personal protective equipment (PPE), post-exposure hygiene, recognition of early symptoms, and prompt medical consultation [13,15]. Accordingly, the current educational framework should move beyond a knowledge-centered approach toward more practical, action-oriented guidance. Specifically, during high-risk agricultural activities involving direct vegetation contact, such as weed clearing, practical guidance on PPE use should be emphasized to minimize skin exposure. Such guidance should include wearing long-sleeved shirts, long pants, and boots; securing sleeves and trouser hems inside arm covers or socks; and applying insect repellents containing DEET or picaridin before and during fieldwork [4,5].
The distribution of chigger mites, particularly Leptotrombidium pallidum (the principal vector of scrub typhus), is closely associated with disease incidence [15]. Effective prevention of vector-borne diseases requires proactive surveillance strategies, including monitoring vector distribution and managing vector habitats. The KDCA currently operates the Regional Climate Change Vector Surveillance Centers project, which collects, identifies, and tests mosquitoes, chiggers, and hard ticks across 8 designated regions nationwide. However, the Busan–Gyeongnam region is not included.
In this study, Gijang-gun had an incidence rate 2 to 3 times higher than the national average and represented a substantial disease burden within eastern Busan. Establishment of a dedicated vector-surveillance hub in eastern Busan, including Gijang-gun, should therefore be considered to enable systematic monitoring of chigger density and pathogen carriage. Both domestic and international studies have shown that coastal suburban areas with dense forest cover provide favorable habitats for chigger larvae and may therefore have increased transmission risk [16–19]. In China, ecological modeling has been used to predict high-risk regions, with corresponding recommendations to strengthen mite surveillance and control in those areas [20]. Integrating predictive approaches for high-risk areas that combine land-use change and vegetation-fragmentation modeling, as proposed in recent studies [7,8], into Busan’s vector-control policy could provide a stronger scientific basis for predicting risk zones and for strengthening targeted surveillance and habitat-management strategies.
Future infectious disease control policies should extend beyond education-centered approaches to include multidimensional strategies, such as environmental improvement (e.g., grass cutting and removal of mite habitats around farmland, urban forest management), vector control, and the distribution and promotion of PPE. Further studies are needed to quantify the effectiveness of tailored regional management programs. Although this study was limited by the use of urban forest area data from a single reference year (2021), which introduces a temporal limitation, our supplementary review of biennial statistics indicated that forest coverage in Busan remained relatively stable throughout the study period, thereby minimizing potential bias due to temporal mismatch. Nevertheless, future research should develop multiyear, high-resolution environmental time-series datasets to characterize more precisely the dynamic temporal relationships between exposure and disease outcomes.
Because this study used aggregated area-level data across 16 districts within an ecological study design, it is inherently subject to ecological fallacy. Accordingly, the ecological associations observed between district-level incidence and urban forest area cannot be extrapolated directly to infer individual-level infection risk, and causal interpretations should be made with caution. To examine these associations more rigorously, future analyses should use multivariable spatial regression models that control for potential confounders, such as age structure, the proportion of agricultural workers, and population density. In addition, direct vector-habitat indicators highlighted in the Introduction, including vegetation type, soil moisture, and rodent density, as well as microclimatic variables such as temperature and precipitation, were not incorporated directly into the present analytical model. Future studies should therefore attempt to integrate high-resolution satellite remote-sensing data, localized meteorological data, and field-based vector-surveillance data to develop a more comprehensive environmental risk index. Ultimately, scrub typhus control in Busan Metropolitan City should shift toward a multidimensional strategy that integrates the ecological risks of peri-urban areas with the behavioral patterns of older adults. Targeted distribution of PPE to high-risk groups and establishment of a Regional Climate Change Vector Surveillance Center would represent important policy measures to strengthen the city’s infectious disease response capacity and promote public health equity. Through implementation of such region-specific vector-borne disease management strategies, disease prevention could be improved and health equity strengthened over time.
Scrub typhus incidence in Busan showed marked spatial heterogeneity. Incidence was higher in peri-urban districts. Age-standardized incidence was positively associated with per capita urban forest area. Urban-rural transitional environments and outdoor activities were key risk factors. Region-specific prevention and strengthened vector surveillance are needed.

Ethics Approval

This study was confirmed to be exempt from institutional review board review at its 20th meeting in 2025 (Exemption No: KDCA-2025-10-09).

Conflicts of Interest

The authors have no conflicts of interest to declare.

Funding

None.

Availability of Data

The datasets are not publicly available but are available from the corresponding author upon reasonable request.

Authors’ Contributions

Conceptualization: KK, HL, SEL; Data curation: KK; Formal analysis: KK; Investigation: KK; Methodology: KK, HL; Project administration: SP, GOK; Supervision: SL; Writing–original draft: KK; Writing–review & editing: all authors. All authors read and approved the final manuscript.

Figure 1.
Average age-standardized incidence rate (ASIR) for the Nationwide and 16 Districts/Counties of Busan, 2019–2023. ASIR=age-standardized incidence rate. ASIR=Σ(crude incidence rate by age×standard population ratio by age group)×100,000 people. The standard population by age group (5-year intervals) is calculated based on the national mid-year population of 2021.
Figure 1. Average age-standardized incidence rate (ASIR) for the Nationwide and 16 Districts/Counties of Busan, 2019–2023. ASIR=age-standardized incidence rate. ASIR=Σ(crude incidence rate by age×standard population ratio by age group)×100,000 people. The standard population by age group (5-year intervals) is calculated based on the national mid-year population of 2021.  
Figure 2.
Correlation analysis between age-standardized incidence rates of scrub typhus and per capita total urban forest area (m²/person) across the 16 districts of Busan (2019–2023), showing a strong positive correlation (r=0.92).
Figure 2. Correlation analysis between age-standardized incidence rates of scrub typhus and per capita total urban forest area (m²/person) across the 16 districts of Busan (2019–2023), showing a strong positive correlation (r=0.92).  
Figure 3.
Correlation analysis between age-standardized incidence rates of scrub typhus and per capita total urban forest area (m²/person) across 8 metropolitan cities in Korea (2019–2023), showing a positive correlation (r=0.76).
Figure 3. Correlation analysis between age-standardized incidence rates of scrub typhus and per capita total urban forest area (m²/person) across 8 metropolitan cities in Korea (2019–2023), showing a positive correlation (r=0.76).  
Figure 4.
Regional distribution of risk-related exposure activities among scrub typhus cases in Busan (2019–2023). Labels indicate the primary high-risk districts displayed: Gijang-gun, Haeundae-gu, Buk-gu, and Geumjeong-gu. Statistical results of chi-square (χ2) tests for regional differences in exposure activities: agricultural/forestry/livestock activities: χ2=91, p<0.001; kitchen garden work: χ2=59, p<0.001; weekend farming: χ2=23, p=0.082; one-time agricultural/forestry work: χ2=46, p<0.001; non-agricultural outdoor activities: χ2=33, p=0.004.
Figure 4. Regional distribution of risk-related exposure activities among scrub typhus cases in Busan (2019–2023). Labels indicate the primary high-risk districts displayed: Gijang-gun, Haeundae-gu, Buk-gu, and Geumjeong-gu. Statistical results of chi-square (χ2) tests for regional differences in exposure activities: agricultural/forestry/livestock activities: χ2=91, p<0.001; kitchen garden work: χ2=59, p<0.001; weekend farming: χ2=23, p=0.082; one-time agricultural/forestry work: χ2=46, p<0.001; non-agricultural outdoor activities: χ2=33, p=0.004.  
Figure 5.
Regional distribution of prior education on scrub typhus in Busan (2019–2023).
Figure 5. Regional distribution of prior education on scrub typhus in Busan (2019–2023).  
Figure 6.
Correlation analysis between the age-standardized incidence rate of scrub typhus and the rate of prior scrub typhus education per 100,000 population (2019–2023), showing a strong positive correlation (r=0.70).
Figure 6. Correlation analysis between the age-standardized incidence rate of scrub typhus and the rate of prior scrub typhus education per 100,000 population (2019–2023), showing a strong positive correlation (r=0.70).  
Table 1.
Annual, sex-specific, and age-specific incidence rates of confirmed and suspected scrub typhus cases reported in Busan Metropolitan City (per 100,000 population)
Table 1.
Region/district 2019–2023 (total) 2019 2020 2021 2022 2023
n (%) IR n (%) IR n (%) IR n (%) IR n (%) IR n (%) IR
Korea (total) 26,297 10.26 4,005 7.80 4,479 8.72 5,915 11.52 6,235 12.16 5,663 11.07
Busan (total) 1,645 (100) 9.85 289 (100) 8.52 345 (100) 10.25 309 (100) 9.24 432 (100) 13.02 270 (100) 8.20
Sex
 Male 720 (43.77) 8.80 118 (40.83) 7.09 152 (44.06) 9.21 138 (44.66) 8.43 179 (41.44) 11.05 133 (49.26) 8.29
 Female 925 (56.23) 10.84 171 (59.17) 9.91 193 (55.94) 11.25 171 (55.34) 10.02 253 (58.56) 14.91 137 (50.74) 8.12
Age (y)
 ≤19 34 (2.07) 1.37 4 (1.38) 0.7 9 (2.61) 1.75 10 (3.24) 2.02 7 (1.62) 1.46 4 (1.48) 0.86
 20–29 37 (2.25) 1.78 6 (2.08) 1.4 6 (1.74) 1.39 4 (1.29) 0.95 11 (2.55) 2.72 10 (3.70) 2.59
 30–39 32 (1.95) 1.55 8 (2.77) 1.8 8 (2.32) 1.89 4 (1.29) 0.98 8 (1.85) 2.01 4 (1.48) 1.02
 40–49 84 (5.11) 3.35 20 (6.92) 3.9 22 (6.38) 4.33 18 (5.83) 3.59 14 (3.24) 2.83 10 (3.70) 2.06
 50–59 279 (16.96) 10.02 60 (20.76) 10.4 60 (17.39) 10.57 43 (13.92) 7.75 69 (15.97) 12.67 47 (17.41) 8.72
 60–69 583 (35.44) 22.07 98 (33.91) 20.0 113 (32.75) 22.06 117 (37.86) 21.89 156 (36.11) 28.43 99 (36.67) 17.83
 ≥70 596 (36.23) 21.22 93 (32.18) 18.5 127 (36.81) 23.88 113 (36.57) 20.19 167 (38.66) 28.25 96 (35.56) 15.40

Incidence rates (IRs) per 100,000 population were calculated using the mid-year population for each corresponding year as the denominator. The average incidence rate per 100,000 population for the entire study period (2019–2023) was calculated by pooling the data as follows: average incidence (2019–2023)=[total number of cases (2019–2023)/sum of mid-year populations (2019–2023)]×100,000.

Table 2.
ASIRs of confirmed and suspected scrub typhus cases reported via notifiable disease surveillance in Busan (2019–2023)
Table 2.
Region/district 2019–2023 2019 2020 2021 2022 2023
n ASIR n ASIR n ASIR n ASIR n ASIR n ASIR
Korea 26,297 10.25 4,005 8.33 4,479 9.02 5,915 11.52 6,235 11.74 5,663 10.31
Busan 1,645 8.35 289 7.68 345 8.91 309 7.87 432 10.77 270 6.50
Jung-gu 6 2.20 1 2.42 0 0.00 1 1.57 4 6.79 0 0.00
Seo-gu 40 6.32 10 8.62 5 3.94 12 9.95 6 4.81 7 4.44
Dong-gu 24 3.97 8 6.91 1 0.72 2 1.75 11 9.03 2 1.56
Yeongdo-gu 33 3.92 7 4.17 10 6.50 4 2.99 8 3.98 4 2.06
Busanjin-gu 99 4.84 20 5.16 32 8.04 3 0.71 23 5.20 21 4.85
Dongnae-gu 112 7.35 20 6.44 7 2.15 25 8.23 44 14.54 16 5.03
Nam-gu 90 5.79 19 6.13 14 4.35 23 7.55 21 6.44 13 4.29
Buk-gu 150 8.97 30 9.40 47 14.25 4 1.44 44 12.57 25 7.15
Haeundae-gu 295 13.28 48 11.61 65 15.14 88 19.69 53 11.77 41 8.58
Saha-gu 96 5.21 25 6.84 12 3.48 20 5.40 29 8.00 10 2.60
Geumjeong-gu 155 11.13 28 10.62 29 11.39 15 4.76 48 16.89 35 11.85
Gangseo-gu 86 15.02 11 10.13 22 20.70 22 19.42 15 11.75 16 13.63
Yeonje-gu 57 4.63 12 5.16 0 0.00 6 2.29 27 11.07 12 4.59
Suyeong-gu 68 6.57 3 1.65 17 7.94 20 9.28 11 5.69 17 7.69
Sasang-gu 110 8.42 16 6.11 30 11.74 21 8.47 26 8.89 17 6.66
Gijang-gun 448 26.12 62 21.04 108 32.15 86 24.65 124 34.90 68 17.78

Age-standardized incidence rate (ASIR) calculation: ASIR=∑(age-specific crude incidence rate×proportion of the standard population in each age group)×100,000. The standard population was based on the 2021 national mid-year population, stratified by 5-year age intervals.

Table 3.
Types of kitchen garden activities among confirmed and suspected scrub typhus cases in Busan (2019–2023)
Table 3.
Region/district Crop planting (χ2=23.41, p=0.075) Crop harvesting (χ2=41.8, p<0.001) Weeding (χ2=67.7, p<0.001) Grass cutting (χ2=25.6, p=0.042) Other activities (χ2=59.3, p<0.001)
Yes No Yes No Yes No Yes No Yes No
Total 105 (100) 1,540 (100) 227 (100) 1,418 (100) 160 (100) 1,485 (100) 87 (100) 1,558 (100) 55 (100) 1,590 (100)
Jung-gu 0 (0.00) 6 (0.39) 0 (0.00) 6 (0.42) 0 (0.00) 6 (0.40) 0 (0.00) 6 (0.39) 0 (0.00) 6 (0.38)
Seo-gu 4 (3.81) 36 (2.34) 6 (2.64) 34 (2.40) 2 (1.25) 38 (2.56) 1 (1.15) 39 (2.50) 5 (9.09) 35 (2.20)
Dong-gu 1 (0.95) 23 (1.49) 3 (1.32) 21 (1.48) 3 (1.88) 21 (1.41) 2 (2.30) 22 (1.41) 1 (1.82) 23 (1.45)
Yeongdo-gu 5 (4.76) 28 (1.82) 6 (2.64) 27 (1.90) 5 (3.13) 28 (1.89) 3 (3.45) 30 (1.93) 1 (1.82) 32 (2.01)
Busanjin-gu 7 (6.67) 92 (5.97) 20 (8.81) 79 (5.57) 1 (0.63) 98 (6.60) 4 (4.60) 95 (6.10) 5 (9.09) 94 (5.91)
Dongnae-gu 4 (3.81) 108 (7.01) 17 (7.49) 95 (6.70) 3 (1.88) 109 (7.34) 2 (2.30) 110 (7.06) 1 (1.82) 111 (6.98)
Nam-gu 4 (3.81) 86 (5.58) 5 (2.20) 85 (5.99) 5 (3.13) 85 (5.72) 4 (4.60) 86 (5.52) 12 (21.82) 78 (4.91)
Buk-gu 8 (7.62) 142 (9.22) 16 (7.05) 134 (9.45) 15 (9.38) 135 (9.09) 10 (11.49) 140 (8.99) 7 (12.73) 143 (8.99)
Haeundae-gu 20 (19.05) 275 (17.86) 46 (20.26) 249 (17.56) 37 (23.13) 258 (17.37) 21 (24.14) 274 (17.59) 2 (3.64) 293 (18.43)
Saha-gu 8 (7.62) 88 (5.71) 12 (5.29) 84 (5.92) 6 (3.75) 90 (6.06) 4 (4.60) 92 (5.91) 0 (0.00) 96 (6.04)
Geumjeong-gu 6 (5.71) 149 (9.68) 11 (4.85) 144 (10.16) 9 (5.63) 146 (9.83) 1 (1.15) 154 (9.88) 6 (10.91) 149 (9.37)
Gangseo-gu 13 (12.38) 73 (4.74) 25 (11.01) 61 (4.30) 22 (13.75) 64 (4.31) 9 (10.34) 77 (4.94) 1 (1.82) 85 (5.35)
Yeonje-gu 4 (3.81) 53 (3.44) 5 (2.20) 52 (3.67) 1 (0.63) 56 (3.77) 1 (1.15) 56 (3.59) 3 (5.45) 54 (3.40)
Suyeong-gu 2 (1.90) 66 (4.29) 12 (5.29) 56 (3.95) 6 (3.75) 62 (4.18) 1 (1.15) 67 (4.30) 0 (0.00) 68 (4.28)
Sasang-gu 5 (4.76) 105 (6.82) 8 (3.52) 102 (7.19) 8 (5.00) 102 (6.87) 7 (8.05) 103 (6.61) 1 (1.82) 109 (6.86)
Gijang-gun 14 (13.33) 210 (13.64) 35 (15.42) 189 (13.33) 37 (23.13) 187 (12.59) 17 (19.54) 207 (13.29) 10 (18.18) 214 (13.46)

Data are presented as n (%).

Table 4.
Kitchen garden activity locations and grass contact exposure among confirmed and suspected scrub typhus cases in Busan (2019–2023)
Table 4.
District Rice paddies (χ²=56.2, p<0.001) Fields (χ²=16.6, p=0.343) Orchards (χ²=15.8, p=0.396) Mountains (χ²=17.9, p=0.27) Grass contact (χ²=56.3, p<0.001)
Yes No Yes No Yes No Yes No Yes No
Total 338 (100) 1,307 (100) 7 (100) 1,638 (100) 15 (100) 1,630 (100) 35 (100) 1,610 (100) 366 (100) 1,279 (100)
Jung-gu 0 (0.00) 6 (0.46) 0 (0.00) 6 (0.37) 0 (0.00) 6 (0.37) 0 (0.00) 6 (0.37) 0 (0.00) 6 (0.47)
Seo-gu 12 (3.55) 28 (2.14) 0 (0.00) 40 (2.44) 1 (6.67) 39 (2.39) 1 (2.86) 39 (2.42) 14 (3.83) 26 (2.03)
Dong-gu 5 (1.48) 19 (1.45) 0 (0.00) 24 (1.47) 0 (0.00) 24 (1.47) 1 (2.86) 23 (1.43) 5 (1.37) 19 (1.49)
Yeongdo-gu 9 (2.66) 24 (1.84) 0 (0.00) 33 (2.01) 0 (0.00) 33 (2.02) 0 (0.00) 33 (2.05) 9 (2.46) 24 (1.88)
Busanjin-gu 22 (6.51) 77 (5.89) 1 (14.29) 98 (5.98) 0 (0.00) 99 (6.07) 4 (11.43) 95 (5.90) 22 (6.01) 77 (6.02)
Dongnae-gu 19 (5.62) 93 (7.12) 0 (0.00) 112 (6.84) 1 (6.67) 111 (6.81) 2 (5.71) 110 (6.83) 21 (5.74) 91 (7.11)
Nam-gu 16 (4.73) 74 (5.66) 0 (0.00) 90 (5.49) 2 (13.33) 88 (5.40) 3 (8.57) 87 (5.40) 19 (5.19) 71 (5.55)
Buk-gu 31 (9.17) 119 (9.10) 3 (42.86) 147 (8.97) 4 (26.67) 146 (8.96) 1 (2.86) 149 (9.25) 34 (9.29) 116 (9.07)
Haeundae-gu 55 (16.27) 240 (18.36) 1 (14.29) 294 (17.95) 2 (13.33) 293 (17.98) 1 (2.86) 294 (18.26) 55 (15.03) 240 (18.76)
Saha-gu 17 (5.03) 79 (6.04) 0 (0.00) 96 (5.86) 1 (6.67) 95 (5.83) 3 (8.57) 93 (5.78) 19 (5.19) 77 (6.02)
Geumjeong-gu 17 (5.03) 138 (10.56) 0 (0.00) 155 (9.46) 1 (6.67) 154 (9.45) 4 (11.43) 151 (9.38) 22 (6.01) 133 (10.40)
Gangseo-gu 35 (10.36) 51 (3.90) 0 (0.00) 86 (5.25) 2 (13.33) 84 (5.15) 3 (8.57) 83 (5.16) 37 (10.11) 49 (3.83)
Yeonje-gu 6 (1.78) 51 (3.90) 1 (14.29) 56 (3.42) 1 (6.67) 56 (3.44) 2 (5.71) 55 (3.42) 8 (2.19) 49 (3.83)
Suyeong-gu 16 (4.73) 52 (3.98) 0 (0.00) 68 (4.15) 0 (0.00) 68 (4.17) 0 (0.00) 68 (4.22) 16 (4.37) 52 (4.07)
Sasang-gu 13 (3.85) 97 (7.42) 1 (14.29) 109 (6.65) 0 (0.00) 110 (6.75) 1 (2.86) 109 (6.77) 14 (3.83) 96 (7.51)
Gijang-gun 65 (19.23) 159 (12.17) 0 (0.00) 224 (13.68) 0 (0.00) 224 (13.74) 9 (25.71) 215 (13.35) 71 (19.40) 153 (11.96)

Data are presented as n (%).

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